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0d7cef02-7f34-44b4-982b-062478f66273 | http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2008:199:0001:0136:EN:PDF | 2,008 | [
"Transport",
"Light-duty vehicles",
"Energy efficiency"
] | eur-lex.europa.eu | 2.3.1.5. Effective reference temperature on the SBC. The effective reference temperature of the standard bench cycle SBC
shall be determined for the actual catalyst system design and actual ageing bench which will be used using the fol-
lowing procedures
a Measure time-at-temperature data in the catalyst system on the catalyst ageing bench following the SBC. Cata-
lyst temperature shall be measured at the highest temperature location of the hottest catalyst in the system. Alternatively, the temperature may be measured at another location providing that it is adjusted to represent
the temperature measured at the hottest location. Catalyst temperature shall be measured at a minimum rate of one hertz one measurement per second dur-
ing at least 20 minutes of bench ageing. The measured catalyst temperature results shall be tabulated into a
histogram with temperature groups of no larger than 10 C. b The BAT equation shall be used to calculate the effective reference temperature by iterative changes to the
reference temperature Tr until the calculated ageing time equals or exceeds the actual time represented in
the catalyst temperature histogram. The resulting temperature is the effective reference temperature on the
SBC for that catalyst system and ageing bench. 2.3.1.6. Catalyst Ageing Bench. The catalyst ageing bench shall follow the SBC and deliver the appropriate exhaust flow,
exhaust constituents, and exhaust temperature at the face of the catalyst. All bench ageing equipment and procedures shall record appropriate information such as measured AF ratios and
time-at-temperature in the catalyst to assure that sufficient ageing has actually occurred. L 19978
EN
Official Journal of the European Union
28.7.2008
2.3.1.7. | d3fc6859-41cb-4ee2-997b-90ebc4f9b481 | 287 |
0d855c4f-36e7-4ed5-8958-cca30b3858d2 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_e2ed2f6c199088dc30a95fddf6e84c72.pdf | 2,023 | [
"emissions",
"data",
"inventory",
"energy",
"emission"
] | cdn.climatepolicyradar.org | Uncertainties and Time Series Consistency Estimates for this sector are uncertain because of the use of a Tier 1 methodology. The time series consistency of the activity data are good, as they are part of a long -running routine energy data compilation and reporting system, by the UK energy statistics team in BEIS, and also for the EFs as a Tier 1 default is used in all years. Source Specific QA/QC and Verification This source category is covered by the general QA/QC of the inventory in Section 1.6. Industrial Processes (CRF Sector 2) 4 UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 287 Source Specific Recalculations No major recalculations have been made to this sector. For further information on recalculations, see Section 10. Source Specific Planned Improvements Emission factors and activity data will be kept under review. Emissions of CO2 are estimated from consumption of urea by road vehicles with relevant types of catalytic converters for control of pollutant emissions and are reported under 2D3. Urea has the chemical formula (NH 2)2CO and is injected into the exhaust stream of certain ty pes of diesel vehicles (currently Euro IV, V and VI HGVs and buses) as a 32.5% (by weight) aqueous solution. The catalytic process of converting NOx to nitrogen in the exhaust leads to the release of CO2 from the urea in the tailpipe. Petroleum coke is known to be used by various sectors either as a fuel (e.g. at power stations and in cement kilns), or in various processes (e.g. in brickmaking, titanium dioxide manufacture, aluminium smelting, or electric arc steelmaking). The consumption of petroleum coke for each sector is either available directly from DUKES or estimated, based on ETS and other data. For most years, there is more petroleum coke listed in the UK energy statistics than can be accounted for by these known users . In other years, the known use rs require more petroleum coke than is available in the energy statistics. But since there is excess petroleum coke for most years (20 out of 32) between 1990 and 2021, it is assumed that there are additional, unknown uses of the fuel in those years. The e xcess petroleum coke in the energy statistics is reported as being for non-energy uses but this will include both fuel grade and anode grade coke, so it is possible that the coke could be used as a fuel, or in processes, or both. In the absence of any data, and because the coke appears in DUKES as ‘non-energy use’, it has been assumed that it is used for an unknown process. Such uses could be non - emissive with the carbon stored, but in the UK inventory it is assumed that all carbon in this petroleum coke is emitted and reported in 2D3. The 2006 IPCC Guidelines specify two approaches for estimating CO 2 emissions from urea consumption. This is either from statistics on total urea sales or by estimating urea consumption as a proportion of the amount of fuel consumed. There are no statistics on urea sales in the UK, so the approach based on fuel consumption is used. Not all diesel vehicles use urea, so it is necessary to know the amount of fuel consumed specifically from those vehicles with the relevant exhaust after treatment technology that require urea injection. Urea is used by HGVs and buses in the UK manufactured to Euro IV , V and VI standards. These came into effect from 2006. The EMEP/EEA Emissions Inventory Guidebook (2016) provides the means for estimating urea consumption as a proportion of fuel consumed by these specific types of vehicles. Fuel consumption by Euro IV, V and VI HGVs and buses was estimated using a bottom-up method described in Chapter 3. The estimations involve the use of vehicle km activity and fleet composition data from DfT and g/km fuel consumption factors, with total fuel consumption calculated for road transport by this method normalised to national
Industrial Processes (CRF Sector 2) 4 UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 288 Following figures given in the EMEP/EEA Guidebook for estimating other pollutant emissions, an assumption was made that 75% of Euro V HGVs and buses are equipped with SCR – the catalyst system that uses urea. The same assumption was also applied to Euro IV vehicles, and it is assumed that 100% of Euro VI vehicles are equipped with SCR. Fuel consumption was calculated for these types of vehicles using SCR technology. Following the EMEP/EEA Guidebook, urea consumption is assumed to be 4% of fuel consumption for a Euro IV HGV or bus, 6% for Euro V and 3.5% for Euro VI. Independent assessment in the UK from suppliers of urea and vehicle manufacturers supports these assumptions. These assumptions allowed the time-series for consumption of urea by UK road transport to be estimated. No urea was A constant emission factor of 0.238 kgCO 2/kg urea solution was used, from the EMEP/EEA Guidebook. This is consistent with the factor and emission equation given in the 2006 IPCC Guidelines, assuming urea is used as a 32.5% aqueous solution which is the norm in the UK. The emissive non-energy use of petroleum coke is assumed to result in 100% of the carbon in this fuel being emitted. The 2006 IPCC default factor for petroleum coke has been used in conjunction with calorific values for petroleum coke used in sectors other than electricity generation, taken from UK energy statistics. The relatively high calorific value given for this type of petroleum coke means that the IPCC default factor implies that this petroleum coke is over 90% carbon, which is higher than the carbon content of coke oven coke or anthracite. Uncertainties and Time Series Consistency The main uncertainty on estim ates of emissions from urea consumption comes from the uncertainty in the amount of urea consumed by the categories of vehicles equipped with SCR exhaust after treatment technologies in the UK fleet. | 70afacf8-8641-4466-819d-f4db8cad9d69 | 330 |
0d85e3ea-bf1f-4932-a0e9-183131d461c0 | https://cdn.climatepolicyradar.org/navigator/GBR/2024/english-devolution-white-paper_1b39c256f452248a3c086f368c081dd9.pdf | 2,024 | [
"Other",
"Institutions / Administrative Arrangements",
"Energy",
"Housing",
"Renewables",
"Adaptation",
"local",
"authorities",
"strategic",
"government",
"devolution"
] | cdn.climatepolicyradar.org | This will include enhanced powers over strategic planning, local transport networks, skills and employment support, enabling them to create jobs and improve living
4/10/25, 5:12 PM English Devolution White Paper - GOV.UK 94/101 Moving to systematic devolution, by making it easier to grant new powers. The government will be able to add functions to the statutory framework by statutory instrument following consultation with Mayoral Strategic Authorities. Established Mayoral Strategic Authorities will also be able to make formal proposals on an annual basis for functions to be added to which the government is required to respond. Providing devolved powers more easily and quickly through establishing a simpler process for creating new Combined and Combined County Authorities to ensure that every part of England can rapidly Improving and unlocking local decision-making through more effective governance arrangements, ensuring Mayors and Combined Authorities can deliver for their areas. Empowering communities to revamp high streets and end the blight of empty premises with a strong new ‘Right to Buy’ for valued community 6.4 Engaging with the sector on detail of our reforms We will work with key stakeholders on next steps. 1. Identify a set of jointly agreed shared priorities, which will guide action and collaboration in delivering their statutory requirement to 2. Establish the Mayoral Data Council, bringing together data leads from across central and local government, to review and implement the data 3. Set up a new working group with the Greater London Authority to compare the powers and policy approaches of other global city authorities We will target engagement with Mayors and Strategic Authorities to shape how we deliver our reforms 1. New freedoms for local and strategic authorities, on removing the requirements for Secretary of State consent they are required to seek on use of their powers and byelaws. 2. The areas of competence for Strategic Authorities and how these are supported by the powers to deliver against them. 3. How best to reflect devolution into our policymaking, where these are appropriate for local delivery and in their areas of competency. This
4/10/25, 5:12 PM English Devolution White Paper - GOV.UK 95/101 includes feeding back proposals, developing our ambition for public sector boundary realignment, and how we can ensure Non-Departmental Public Bodies and Arm’s Length Bodies build in Local Growth Plans and Spatial Development Strategies to their work. 4. The future of the Scrutiny Protocol to continue to improve the standards of scrutiny locally. 5. How to deliver external scrutiny of value for money of local public spending, particularly where freedoms and flexibilities of the Integrated Settlement are being utilised. The wider reform of audit will include consideration of how to support and provide external assurance on this. 6. Considering a single point of accountability for value for money, exploring Local Accounting Officers and Local Public Accounts Committees models to enhance the accountability of Strategic Authorities. 7. Considering how to ensure transparency and oversight of decision- making and activity conducted by the bodies that Strategic 8. Boosting capacity support for institutions, looking at what would best 9. Delivering data reform, developing a comprehensive vision for local 10. Effective voting arrangements for strategic planning. Work with local authorities and the wider local government sector 1. Identify where we can provide more freedoms for local authorities to use powers without central approval. 2. Develop proposals to improve support and development for councillors, as well as addressing barriers to attracting and retaining 3. Consult on local government standards. 4. Set out our vision for radically simplifying the local audit system, including our intention to establish a new body for local audit. We will engage with key stakeholders on a separate document, which will set out 5. Establish a local government workforce development group, run in partnership with the sector, to identify practical solutions to workforce 6. Work with individual areas on local government reorganisation, inviting proposals from all remaining two-tier areas and those unitary councils where there is evidence of failure or their size or boundaries may be hindering their ability to deliver sustainable and high-quality services to their residents. We will facilitate delivery of an ambitious first wave of reorganisation in this Parliament. | 969ae9d8-79fb-416b-8702-ba47c750f97a | 34 |
0d8ce33c-9759-4429-921b-f38c8f7b00af | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_e2ed2f6c199088dc30a95fddf6e84c72.pdf | 2,023 | [
"emissions",
"data",
"inventory",
"energy",
"emission"
] | cdn.climatepolicyradar.org | The sum of the “household intakes” and “eating out intakes” then provides the total protein consumption per year per person. UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 477 Nitrous oxide emissions are calculated by 2. annual total protein consumption per person; 3. the fraction of nitrogen in protein (0.16kg N/kg protein); 4. the fraction of municipal nitrogen load from unconsumed protein (1.16; Henze and 5. the fraction of municipal nitrogen load from commercial and industrial sources, as per the 2006 IPCC guidelines (1.25); and, 6. The default emission factor (EFEFFLUENT) for N2O-N (0.005 kg N2O-N/kg –N) 7. The conversion factor 44/28, from kg N2O-N into kg N2O. This derives a total for the UK nitrous oxide emissions from sewage sludge, but not all of those emissions are allocated to 5D1. The nitrous oxide emissions from sludge spread on agricultural land are reported under IPCC source category 3D Agricultural Soils , emissions from waste incineration are included in 5C , and some sewage sludge is disposed to landfill sites, where N2O emissions do not generally occur due to the anaerobic conditions. Therefore, to avoid a double-count in the UK GHG inventory, the estimated nitrogen content of sewage sludge disposed via these other routes is removed from the total N estimated to be in 7.5.2.3.1 Use of UK-Specific Protein Consumption Data instead of FAO Data The FAO estimate of per capita protein consumption is based on supply balance sheets for all commodity items. For each commodity supply balance sheet, factors are applied to the estimate of supply for human consumption to derive total protein consumption and a per capita balance sheets to derive a total protein consumption estimate for a country. The FAO estimate is therefore an aggregate calculation based on aggregate commodity supply data. It uses common conversion factors (not specific to an y country) to derive food, protein and fat per capita consumption estimates. It also relates to quantities available for consumption and does not account for losses (e.g. fat trimmed from meat) beyond the farm - gate through to retail. These methodological l imitations of the FAO estimates are more significant for developed countries such as the UK where a greater proportion of consumption is in the form of processed products. The UK GHGI estimate of protein consumption is derived from the Expenditure and Food Survey (Defra, 20 20). This is a sample household survey in which households record the actual purchases of food they make. UK-specific conversion factors are then applied to these individual food items to estimate consumption of protein and other nutrients. The UK-specific conversion factors are based on a detailed analysis of the individual types of food purchased and contrasts to the more broad -brush factors used by the FAO. The Expenditure and Food Survey estimate is also net of any losses through the food chain through to retail as it is based on actual purchases. The only limitation to the Expenditure and Food Survey is that it may have an element of under-recording due to purchases of some food items not being included in the diary of survey participa nts, but the Inventory Agency considers that it is more representative of UK protein consumption per capita than the FAO estimate. UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 478 7.5.2.4 5D2: Industrial Waste-water Treatment In the UK, a high proportion of industry trade wastewater is disposed to the municipal sewer system and treated by water operators together with the sewage and effluent from domestic In the data reported by the water operators and used to generate methane emission estimates in 5D1 (see above), some of the annual reporting to water regulators includes explicit data on the COD from “trade waste” and the total COD treated (i.e. including domestic and commercial effluent) in the municipal systems. The share of total BOD that is attributable to the industry sector (i.e. “tr ade waste”, managed via contracts between water operators and industry operators) is variable across the UK and across years. This is removed from estimates of COD generated by industrial activity, to mitigate double -counting and leave only the COD treated through on-site treatment systems within the industrial sector. It is this source of emissions considered under IPCC category 5D2. In addition to the above, where large industrial sites that have on -site waste-water treatment plant are regulated under IPPC/EPR, the annual IPPC/EPR reporting to regulator inventories (PI/SPRI/NIPI) includes the requirement to report any methane emissi ons from the waste - water effluent plant. The PI/SPRI/NIPI data on methane emissions are used within the UK GHGI, and included within many IPCC source categories, but the lack of source-specific detail in the PI/SPRI/NIPI reporting does not enable the waste -water treatment emission estimates from these industrial facilities to be split out and reported separately in the CRF. In practice it is not straightforward to ascertain the extent to which emissions from waste-water treatment are consistently included in operator estimates across different industry sectors, as the IPPC/EPR data are not presented ‘by source’, but rather ‘by installation’. Within sector - specific guidance to plant operators on pollution inventory data preparation, emissions of methane from wastewater treatment are not highlighted as a common source to be considered, whilst in guidance for several industrial sectors, wastewater treatment is singled out as a potentially significant source of ammonia and nitrous oxide emissions. Therefore, some industrial waste-water treatment methane emissions are already reported within a range of IPCC source categories, but cannot be quantified explicitly due to the lack of transparency of available source data from UK environmental regulatory reporting systems. In 2020, Ricardo Energy & Environment developed a new tier 1 estimate and timeseries for both methane and nitrous oxide emissions from industrial waste-water treatment, with regard to previous review comments (Section 10.4) and in preparation for the 2019 Refinement to the 2006 IPCC Guidelines yet to be formally adopted. | 70afacf8-8641-4466-819d-f4db8cad9d69 | 403 |
0d91e2b3-a7d9-482f-b71b-575dadc033c8 | https://cdn.climatepolicyradar.org/navigator/GBR/2025/united-kingdom-national-inventory-report-nir-2025_3d22864cf237013c86452d4c6455250a.pdf | 2,025 | [
"emissions",
"data",
"inventory",
"emission",
"used"
] | cdn.climatepolicyradar.org | For England, the inventory areas were revised downwards based on improved on-site information primarily The peat extraction site activity dataset has also been partially verified by comparing the measured areas with reported areas of planning permission, which were available for some extraction sites in England and Scotland. The measured areas either matched or were smaller than the planning permission areas, which is to be expected as it is known that not all areas with planning permission are undergoing active extraction. The locations and previous land -use of new reservoirs were verified using the geographic information portal. 6.5.7 Category-Specific Recalculations The Category 4D net source has reduced by between 0.0 and 0.1 Mt CO2e (-4.7%) across the time series compared to the previous inventory. This is mainly due to updates in the activity The changes and their justification • Updates to organic soil areas. New activity data on existing and rewetted organic soils have been included and consistency improvements have been implemented. The rewetted fen areas between grassland and wetland have been separated in the methodology to ensure that these areas end up in the right LULUCF categories after 20 • Updates to forest rewetting activity data. Newly available activity data for deforestation to wetland in Scotland(from 2013) and Northern Ireland (from 2020) has now been included. This is the first year that Forest to Wetland data for NI has been available. Land-Use, Land Use Change and Forestry (CRT Sector 4) 6 UK NID 2025 (Issue 1) Ricardo Page 434 value Units Comment / Justification 4.D1.a Net carbon stock change in soils 652.00 527.07 651.97 527.55 Gg C 4.D.1.c Net carbon stock change in soils -495.98 -494.99 -495.98 -495.09 Gg C 4.D.2.a/4(IV) Biomass burning - controlled burning 0.00 29.08 0.00 17.60 Gg C Updates to forest rewetting activity data 4.D.2.c.i Carbon stock change in living biomass - losses 0.00 37.84 0.00 23.39 Gg C 4.D.2.c.i Net carbon stock change in dead organic matter 0.00 13.12 0.00 7.46 Gg C 4.D.2.c.i Net carbon stock change in soils 0.00 1.05 0.00 0.86 Gg C 82.47 85.52 82.47 85.06 Gg CH4 Updates to organic soil areas 4.D.2.a/4(IV) Biomass burning - controlled burning 0.00 0.32 0.00 0.19 Gg CH4 Updates to forest rewetting activity data 4.D.2.a/4(IV) Biomass burning - controlled burning 0.000 0.018 0.000 0.011 Gg
Land-Use, Land Use Change and Forestry (CRT Sector 4) 6 UK NID 2025 (Issue 1) Ricardo Page 435 6.5.8 Category-specific planned improvements There are ongoing discussions with policy experts and peatland managers to improve the register of peat restoration activities across all nations of the UK and update the rewetting activity data as appropriate. A Defra -funded project to assess the status o f former domestic peat extraction for fuel in England is due to be completed in March 2025. This project will assess whether the current assigned peat condition category and associated EFs, which are similar to that of industrial peat extraction (for horticultural use) are appropriate for these areas. BEIS (now DESNZ) commissioned a review of current knowledge and gaps of GHG emissions and removals from UK coastal wetlands, which provided recommendations for moving towards inclusion of saltmarshes in the UK GHGI (Burden and Clilverd, 2022). Evidence gaps identified in this report were addressed in a Defra -funded project to provide a roadmap for inclusion of saltmarsh in the UK GHGI by defining terminology, and mapping implications of different terminologies on saltmarsh areal extent (Burden at al. 2024). Subsequent government-funded projects are underway - 1) compile a database of carbon stocks and GHG fluxes, 2) develop Tier 2 emission factors for saltmarsh, and 3) develop a baseline map of UK saltmarsh extent. Emissions sources 4.E Carbon stock change 4(II).E Emissions and removals from drainage and rewetting and other management of organic and mineral soils 4(III).E Direct and indirect nitrous oxide (N2O) emissions from nitrogen (N) mineralization/immobilization associated with loss/gain of soil organic matter resulting from change of land use or management of mineral soils Methods T3 for carbon stock changes, T2 for organic soils, T1 for other Emission Factors Country-specific for T3 methods, T2 for direct CO2 and CH4 emissions from organic soils, T1 for other emissions Key Categories 4E: Settlements – CO2 (L1, T1, L2, T2) Completeness No known omissions- areas are reported for land uses with no This section describes LULUCF emissions and removals from Settlement in the UK. A description of LULUCF emissions and removals from the OTs and CDs is given in Section Net emissions from the Settlements category include carbon stock gains and losses due to land-use change (LUC) and associated GHG emissions. It is the second largest net source in
Land-Use, Land Use Change and Forestry (CRT Sector 4) 6 UK NID 2025 (Issue 1) Ricardo Page 436 Ongoing carbon stock changes in soils arising from LUC to Settlements are reported under both 4.E.1 Settlements remaining Settlements (for historic LUC >20 years before the inventory reporting year) and 4.E.2 Land converted to Settlements (for LUC in the past 20 years). Direct and indirect N2O emissions from N mineralization from these land use changes are reported in 4(III).E. These non-organic soil net carbon stock changes are the largest component of the category total emissions and are calculated using a Tier 3 dynamic soil carbon model. Other contributors to the Settlements net total emissions • Carbon, CH4 and N 2O emissions resulting from drainage of organic soils (4.E and • biomass carbon stock changes due to LUC (4.E.2); • N2O emissions from soil disturbance associated with LUC (4(III).E); and • biomass burning emissions of GHGs from controlled burning following forest land conversion to Settlements (4(IV).E.2.a). Full details of the methods and activity data are given in Annex 5.1.4. 6.6.2 Information on approaches used for representing land areas and on land use databases used for the inventory preparation The UK uses Approach 2 (IPCC 2006) for the representation of land use areas in the inventory and compiles several different data sources into a non -spatially-explicit land use conversion matrix (Annex 5.1.4.3.1 for details). | 95866fde-5b53-4214-b279-97a1078c466c | 369 |
0d92362f-3541-4665-be16-34d11b18c78d | http://arxiv.org/pdf/2107.06174v1 | 2,021 | [
"models",
"model",
"load",
"peak",
"forecasting"
] | arxiv.org | The KSLF model consists of a panel macroeconomic model and auxiliary time series models; the model calibrates predictions for the peak load of the following day by continuously reflecting the temperature volatility of the current peak load [80,81]. A comparison between the predicted and actual values of the KSLF model is displayed in Figure 12. As shown, the KSLF model's predicted values were typically less than the actual values. Furthermore, as indicated in the last row in Table 2, the actual highest peak load in 2019 was 91300 MW; however, the KSLF model predicted a value of 83440 MW, which is less than the predictions made by LSTM and all the hybrid models of this study. The RMSE of the KSLF model was 3531.0519, and the MAPE was 4.37%; thus, the LSTM, SARIMAX-SVR, and SARIMAX-LSTM models outperformed the KSLF model in both the overall performance and greatest peak load prediction. Therefore, the performance of the current peak load-forecasting model used in Korea, which consists of panel and time series models, can be improved by including machine learning or hybrid models. This study comprehensively compared the performances of peak load-forecasting models, including the traditional time series model and most recent hybrid models. The seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model, artificial neural network (ANN), support vector regression (SVR), and long short-term memory (LSTM) for the single models, and SARIMAX-ANN, SARIMAX-SVR, and SARIMAX-LSTM for the hybrid models were chosen. This study successfully fits the daily electricity peak load to all models, considering weekends, holidays, and meteorological variables such as temperature, cooling and heating degree days, and The main findings based on the forecasting results are summarized below:
(1) All single (ANN, SVR, LSTM) and hybrid (SARIMAX-ANN, SARIMAX-SVR, SARIMAX-LSTM) machine learning models exhibited significantly superior predictive power compared to the time series model (SARIMAX). (2) LSTM and SARIMAX-LSTM exhibited the best performance among single models and hybrid models, respectively; thus, the LSTM-based models were, comparatively, the most accurate for electricity peak load forecasting in Korea. (3) LSTM and SARIMAX-LSTM indicated no significant performance difference; however, LSTM demonstrated a superior predictive power for a sharp increase and decrease of the peak load. (4) LSTM and SARIMAX-LSTM, which are the most predictive among the models used in this study, outperformed the current peak load-forecasting model of Korea. Therefore, Korea's current forecasting models could be significantly improved by including LSTM-based models. Despite the achievements of this study, there are limitations. First, this study conducted electricity peak load forecasting for Korea only. As mentioned above, Korea has four distinct seasons, where peak loads increase significantly in summer and winter. Although this study observed that the single LSTM model outperformed the other models, it is not proven that the LSTM model would demonstrate the best predictive power in countries that have relatively small temperature or meteorological variations over the course of a year. Thus, it is inappropriate to apply the results of this study to all countries; an additional comparative analysis using the data from each country would be necessary. Secondly, this study fit the learning data using tree models, Gaussian process regression and ensemble (boosted trees and bagged trees), and SVR. However, the RMSE values of these models were significantly less than that of SVR; therefore, this study did not apply them to the peak load forecasting. In the case of the hyperparameter optimization techniques, there are studies concluding that metaheuristic techniques such as the grasshopper optimization technique, whale optimization technique, ant lion optimization, and spider monkey optimization are superior to the grid search [82][83][84]. However, they have not been sufficiently verified through comprehensive comparative studies, and other studies have indicated that the optimization performance of grid search is superior to that of the other optimization techniques [85,86]. The optimization techniques are primarily used for classification or clustering methodologies (such as support vector machine), rather than SVR. Comprehensive and comparative studies considering different newly proposed models and techniques could be conducted in future research. However, one must preemptively analyze whether new models are applicable to peak load forecasting, have no fatal disadvantages, and can reflect the distinct seasonal and holiday characteristics of the targeted countries. Despite these limitations, this study is academically and socially meaningful because, to the best of our knowledge, it is the first attempt to successfully consider time series, machine learning, deep learning, and hybrid forecasting models for the nationwide electricity peak load. Based on the conclusions and limitations of this study, there are meaningful future study suggestions. First, because the hybrid models combine the nonlinear residuals of a time series model by fitting them with machine learning models, the predictive power of the hybrid models is highly dependent on how well the time series model fits the linearity of the peak load data. Thus, it is important to choose a well-fitting time series model, or machine learning or other nonlinear fitting models, to develop hybrid models that can produce accurate predictions. Recently, several extended and modified SARIMAX models such as two-way SARIMAX [87] and interaction SARIMAX [88],
have been proposed; they could be considered for the improvement of the predictive power of hybrid models in future studies. Second, the highest peak load in Korea in 2019 did not exceed the supply reserve margin, and Korea could avoid a national crisis, such as a blackout. However, as abnormal weather caused by climate change is becoming more frequent, Korea's current forecasting models must be improved. Moreover, further studies to derive an optimal supply reserve margin for the supply and demand balance could be conducted based on accurate peak load forecasting. Third, this study selected the forecasting models that were the most widely used in previous studies; hence, it did not consider the latest extended models. As mentioned earlier, LSTM is one of the extended models used to overcome the shortcomings of RNN models. However, ANN- [89][90][91] and SVM-extended models [92][93][94] have also been proposed and utilized, with a variety of derivative models complementing the disadvantages of basic models. | 00936587-b3ab-441d-9333-0ffa8899d874 | 4 |
0d93cf02-db86-4181-b7bf-1d84db81b4e2 | http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32006L0040 | 2,006 | [
"Transport",
"Non-energy use"
] | eur-lex.europa.eu | Regulation as last amended by Commission Regulation (EC) No 29/2006 (OJ L 6, 11.1.2006, p. 27). (11) IPCC Third Assessment Climate Change 2001. A Report of the Intergovernmental Panel on Climate Change (http://www.ipcc.ch/pub/reports.htm). (12) For the calculation of the GWP of non-fluorinated greenhouse gases in preparations, the values published in the First IPCC Assessment shall apply, see: Climate Change, The IPCC Scientific Assessment, J.T. Houghton, G.J. Jenkins, J.J. Ephraums (ed.), Cambridge University Press, Cambridge (UK) 1990. (13)
OJ L 204, 21.7.1998, p. 37. Directive as last amended by the 2003 Act of Accession. ANNEX
PART 1
Directive 70/156/EEC is amended as follows:
1. In Annex IV, part I, a new item numbered 61, and footnote, is inserted as follows:
Subject
Directive No
Official Journal reference
Applicability
M1
M2
M3
N1
N2
N3
O1
O2
O3
O4
61. | d8fef834-b7ca-4a3a-a38f-4da679dc0fb3 | 6 |
0d9d6f4e-ff97-4863-84f4-6b5d2cd8eadc | 2,025 | [
"pfc emissions",
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"unfccc coverage",
"projection period",
"sector"
] | HF-national-climate-targets-dataset | SF, emissions remain at low levels over the projection period. Table 4.19: PFC emissions by sector, MtCO, (WEM scenario, UNFCCC coverage) Table 4.20: SF6 emissions by sector, MtCO, (WEM scenario, UNFCCC coverage) | ff6903ed-b7f3-400a-9a3f-95deb3008b5a | 0 | |
0da1d2ea-2e61-4402-b7a1-ac2285abcd95 | http://arxiv.org/pdf/2108.03722v2 | 2,021 | [
"adaptation",
"technologies",
"patents",
"mitigation",
"climate"
] | arxiv.org | Water-related adaptation also relies on engineering but also basic research in chemistry, which is relevant for water conservation, filtration, recovery, and desalination that make use of chemical processes. The scientific knowledge base of infrastructure adaptation consists of material science, thermodynamics, construction, and electrical engineering, among other fields. | e7c5ec21-08e6-4ef3-84cf-6a259e7f7c53 | 47 |
0da2dcc7-1adf-4580-92ef-c1519eb721ce | http://arxiv.org/pdf/2503.10644v1 | 2,025 | [
"firms",
"losses",
"carbon",
"emissions",
"banks"
] | arxiv.org | Figure 1(b) shows the aggregate sales of firms within Hungary (y-axis) for each NACE 1-digit sector (x-axis). The sales of firms with known emissions (ETS I) account for only 17 bn (7%) of sales (blue bars), whereas the 185, 783 firms with newly estimated positive emission (dark yellow) cover 179 bn (70%) of sales -this amount of sales will be directly affected by carbon prices (if firms do not adapt). Firms for which our estimate yields zero emissions from oil and gas purchases (white bars) are responsible for 58 bn (23%) of sales. For assessing the transition risks of carbon pricing we need to relate the costs of CO 2 emissions of individual firms to their profits. Figure 1(c) shows the cumulative probability distribution of CO 2 emissions in tons; the yaxis is the probability of a firm having more emissions than the value indicated on the x-axis. Note the log-log scale; firms with 0 emissions are not shown. The distribution is heavy tailed -few firms have very large emissions, most firms have small emissions. For a reference, the dash-dotted line shows a power-law with exponent -1.05. Only 0.09% of the firms have more than 10 4 t of emissions, and 0.009% of firms have emissions larger than 10 5 t. The distribution of firms' emissions across NACE 1 sectors is shown in SI Section S1 Fig. S2. To analyze the sensitivity of individual firms to carbon pricing, we calculate their Carbon-to-Profit Ratio (CPR), as a firm's emissions in tons (E i ) divided by its net profits (P i ), i.e., CPR i = Ei Pi . A CPR of 0.1 (0.02) means that a firm becomes unprofitable at a carbon price, π, of 10 EUR/t (50 EUR/t), and hence, goes out of business. Knowing the CPR of firms before introducing car-bon pricing highlights, which firms need to adapt the most to avoid bankruptcy. Figure 1(d) plots the CPR of firms (x-axis) against the probability (y-axis) of firms having a CPR higher than the x-axis value. 2,328 firms (2% of all firms with non-negative profits and estimated emissions) will become unprofitable at the ETS II price cap of 45 EUR/t (dashed vertical line) -given their cur-rent business model and assuming they can not pass on the costs 5 . Assessing transition risks at specific carbon price levels (EUR/t) requires estimates of their effects on the real economy (measured in gross output) and financial system losses (measured in bank loan write-offs). To estimate direct real economy losses for a given carbon price, π, in EUR/t, we estimate which firms become unprofitable due to additional costs from carbon pricing, and, hence should shut down. 6 Given the emission estimate, E i , of firm, i, (see Fig. 1(c)) and the carbon price, π, firm i faces costs of π • E i . Hence, i becomes unprofitable if its current profits, P i , are smaller than the additional carbon costs π • E i . To arrive at the economy-wide direct production (gross output) losses for a given price, π, we sum the sales, s out i , of all firms i becoming unprofitable and divide by the total sales of all firms; for details, see Section Methods, Step 2. Figure 2(a) shows the economy-wide direct production losses (y-axis) for carbon price scenarios of 10, 20, . . . , to 1,000 EUR/t (x-axis) for all firms as a purple, dashed line. 7 The total sales losses are 0.2%, 2.0%, 3.3%, and 9.5% at 10, 100, 200 and 1,000 EUR/t, respectively. At the ETS II price cap of 45 EUR/t, losses are estimated to affect around 1% of economy-wide sales. Within the carbon price range compatible with 2 degree warming (estimated at 5-220 USD/t in 2030, [5]) losses could increase up to 3.3% at 200 EUR/t. The purple solid line shows corresponding production losses when only firms with bank loans (relevant for loan write offs) are considered. Firms would likely attempt to pass on additional carbon costs to their customers. To capture this, we use a simple cost pass-through mechanism that yields updated costs for each firm. The model assumes that firms can pass on a fraction of their additional carbon costs proportional to their market share (within their NACE 4digit sector), for details, see Section Methods, Step 2. Figure 2(a) shows the economy-wide direct production losses, given the cost pass-through-based carbon costs of firms as red dashed line. Interestingly, the production 5 Note, that the profit variable is not available for all the firms in the supply chain network, therefore, the CPR ratio can be quantified for a subset of firms. The number of firms with positive profits and estimated emissions is 93,215. 6 If for a given carbon price, π, a firm becomes unprofitable, continuing its operations would result in losses for its owners and they should decide to close the firm and take out the remaining equity. In accounting, the contribution margin becoming negative is called shut down point. 7 Production here is measured in terms of value of products sold to other firms, i.e., sales. losses are slightly higher when allowing for carbon costs being passed on downstream along supply chains, 0.2%, 1.3%, 2.3%, and 3.8% for 10, 45, 100 and 200 EUR/t, respectively. The difference in losses increases to about 1.5 percentage points for prices above 300 EUR/t. When considering the output losses from only firms with loans (solid lines), the difference is negligible for prices below 300 EUR/t and small for prices above. The subsequent results are obtained using carbon costs including passthrough. Note here we consider sales losses due to firms shutting down, but ignore that firms might sell less due to higher prices. Direct and in-direct output and bank equity losses and the corresponding amplification factors are summarized in SI Section S2 Table S2. Estimating direct financial system losses from carbon pricing
Next, we assess the exposure of the banking system to transition risks from carbon pricing. | 54018bb6-b4ca-4daf-a2af-62348528342b | 1 |
0da3e166-f601-4b9f-8026-2c3021f4b34e | https://cdn.climatepolicyradar.org/navigator/GBR/1900/united-kingdom-biennial-report-br-br-4_3ed9930a9ceb3d956a389f73b35d0ba4.pdf | 2,021 | [
"climate",
"energy",
"committed",
"emissions",
"grant"
] | cdn.climatepolicyradar.org | Regulatory Implemented The EU Ecodesign Directive by setting minimum performance (respectively) for energy-using products. They aim to take the least efficient products off the market and to give consumers clear energy use-related information to guide their purchasing decisions. | 025a518f-ffd4-4f95-b5a2-b6052b167c0d | 56 |
0dae9a6c-a7e6-44e7-957f-9ed6d902b4f3 | http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=uriserv%3AOJ.L_.2014.103.01.0015.01.ENG | 2,014 | [
"Transport",
"Energy efficiency"
] | eur-lex.europa.eu | The Commission, when preparing and drawing up delegated acts, should ensure a simultaneous, timely and appropriate transmission of relevant documents to the European Parliament and to the Council. (17)
It is appropriate to retain the approach of setting the target based on a linear relationship between the utility of the car and its target CO2 emissions as expressed by the formulae set out in Annex I to Regulation (EC) No 443/2009, since this allows the diversity of the passenger car market and the ability of manufacturers to address different consumer needs to be maintained, thus avoiding any unjustified distortion of competition. (18)
In its impact assessment, the Commission assessed the availability of footprint data and the use of footprint as the utility parameter in the formulae set out in Annex I to Regulation (EC) No 443/2009. On the basis of that assessment, the Commission has concluded that the utility parameter used in the formula for 2020 should be mass. Nevertheless, the lower cost and merits of a change to footprint as the utility parameter should be considered in the future review. (19)
Greenhouse gas emissions related to energy supply and vehicle manufacturing and disposal are significant components of the current overall road transport carbon footprint and are likely to significantly increase in importance in the future. Policy action should therefore be taken to guide manufacturers towards optimal solutions taking account of, in particular, greenhouse gas emissions associated with the generation of energy supplied to vehicles such as electricity and alternative fuels, and to ensure that those upstream emissions do not erode the benefits related to the improved operational energy use of vehicles aimed for under Regulation (EC) No 443/2009. (20)
Since the objective of this Regulation, namely to define the modalities for reaching the 2020 target to reduce CO2 emissions from new passenger cars, cannot be sufficiently achieved by the Member States but can rather, by reason of its scale and effects, be better achieved at Union level, the Union may adopt measures, in accordance with the principle of subsidiarity as set out in Article 5 of the Treaty on European Union. In accordance with the principle of proportionality, as set out in that Article, this Regulation does not go beyond what is necessary in order to achieve that objective. (21)
Regulation (EC) No 443/2009 should therefore be amended accordingly,
HAVE ADOPTED THIS REGULATION:
Article 1
Regulation (EC) No 443/2009 is amended as follows:
(1)
in Article 1, the second paragraph is replaced by the following:
From 2020 onwards, this Regulation sets a target of 95Â g CO2/km for the average emissions of the new car fleet as measured in accordance with Regulation (EC) No 715/2007 and Annex XII to Regulation (EC) No 692/2008 and its implementing measures and innovative technologies. ;
(2)
in Article 2, the following paragraph is added:
4. With effect from 1 January 2012, Article 4, Article 8(4)(b) and (c), Article 9 and Article 10(1)(a) and (c) shall not apply to a manufacturer which, together with all of its connected undertakings, is responsible for fewer than 1Â 000 new passenger cars registered in the Union in the previous calendar year. ;
(3)
in point (a) of Article 3(2), the first indent is replaced by the following:
the power to exercise more than half the voting rights, or ;
(4)
in Article 4, the second paragraph is replaced by the following:
For the purposes of determining each manufacturer s average specific emissions of CO2, the following percentages of each manufacturer s new passenger cars registered in the relevant year shall be taken into account:
65Â % in 2012,
75Â % in 2013,
80Â % in 2014,
100Â % from 2015 to 2019,
95Â % in 2020,
100Â % by the end of 2020 onwards. ;
(5)
the following Article is inserted:
Article 5a
Super-credits for 95Â g CO2/km target
In calculating the average specific emissions of CO2, each new passenger car with specific emissions of CO2 of less than 50Â g CO2/km shall be counted as:
2 passenger cars in 2020,
1,67 passenger cars in 2021,
1,33 passenger cars in 2022,
1 passenger car from 2023,
for the year in which it is registered in the period from 2020 to 2022, subject to a cap of 7,5Â g CO2/km over that period for each manufacturer. | a421885f-773e-412c-92bd-4a3766f5ae66 | 4 |
0dbcba92-18e7-4000-a519-81a3de2ab76b | https://www.gov.uk//guidance/post-combustion-carbon-dioxide-capture-best-available-techniques-bat | 2,021 | [
"Solvent selection",
"CO2 capture efficiency",
"CO2 compression",
"Cooling water options",
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"Hazard and mitigation assessment",
"Capture level",
"Flexible operation",
"Start-up/shutdown",
"Potassium carbonate capture",
"Discharge to water",
"Regulatory advice"
] | gov.uk | Where you plan to install CO2 capture onto a CHP plant, you must design the plant so that it can operate efficiently during periods of power only mode. The primary purpose of an EfW plant is to treat waste. Therefore, they need to operate continuously. The PCC plant design and operation must be compatible with this. 2.3 Supplying heat and power for PCC operation
You will need to use low grade for example 130C heat and electrical power to operate the PCC plant. You should work out the amounts needed based on factors that include the
You should supply this heat and electricity from the main plant. Where not possible, this will need to be by fuel combustion in ancillary plants with CO2 capture that are then also treated as a power or CHP plant system for performance calculations. The ratio between heat supplied as steam or otherwise and electricity output lost will depend on the
You should consider using a back-pressure turbine if it is not possible to supply enough steam to the PCC plant by extracting steam from a condensing turbine. If the plant needs to supply heat for district heating, and extracting steam to supply the PCC plant will mean there is insufficient steam to do this, you should consider using heat pumps or other plant to reduce the amount of steam required to meet that heat demand. | 5ac30264-cadd-4c49-b296-790a073ee776 | 2 |
0dbd642b-74c7-44c2-a29f-5c026a0bdc1f | https://assets.publishing.service.gov.uk/media/643583fb877741001368d815/mobilising-green-investment-2023-green-finance-strategy.pdf | 2,023 | [
"strategy",
"green",
"finance",
"published"
] | www.gov.uk | The British Industry Supercharger, with targeted measures to bring the energy costs for key U K i ndustries in line with other major economies, benefitting 300 b. The Energy Intensive Industries (E I I ) Compensation Scheme, extended until March 2025, helps high energy usage businesses such as steel and paper manufacturers with their electricity costs; c. A commitment to outline a clear approach to gas vs electricity ‘rebalancing’ by the end of 2023/4, aiming to make significant progress affecting relative prices by the end of 2024. Rebalancing will generate the clear short-term price signal necessary to shift businesses to lower carbon, more energy efficient technologies like heat pumps. This is vital to meet Government’s existing decarbonisation commitments, including our goal of 600,000 heat pumps installed per year by 60. Investment in the circular economy and resource efficiency can also contribute to energy demand reduction targets, whilst increasing the resilience of U K i ndustrial supply chains. This requires the adoption of new, sustainable business models and growth in the U K ’s capacity to reuse, remanufacture and recycle products and materials. In the Resources and Waste Strategy (2018) and Net Zero Strategy (2021), the U K g overnment has set out plans to support the development of the circular economy. The U K i s well placed to capture the opportunity from this transformation. To support the transition and to help drive investment, U K R I h as initiated programmes including the National Interdisciplinary Circular Economy Research (N I C E R ), which is bringing together researchers, businesses, policymakers, and wider society to identify, develop and embed circular economy approaches and technologies across key 61. We are working with the oil and gas industry and regulators to decarbonise oil and gas production in the North Sea, primarily through electrification of infrastructure and cessation of routine flaring (see Fuel Supply and Hydrogen chapter in the Net Zero Growth Plan). Through the North Sea Transition Deal, the industry is committed to reducing its emissions by 10% by 2025, 25% by 2027 and 50% by 2030 (against 159 The North Sea Transition Deal will support workers, businesses, and the supply chain through this transition by harnessing the industry’s existing capabilities, infrastructure and private investment potential to exploit new and emerging technologies such as hydrogen production, C C U S a nd floating offshore wind. 62. Government wants to encourage oil and gas companies to reinvest their profits in oil and gas extraction from the U K t o support the economy, jobs and the U K ’s energy security. The Energy Profits Levy on extraordinary oil and gas profits was increased to 35% in the Autumn Statement, but in recognition of the need to continue investing in U K e nergy security and decarbonisation, it comes with an investment allowance for the reinvestment of profits in ring-fenced activities and a separate investment allowance for investment in carbon emissions reducing technology, such as installing bespoke wind turbines to power upstream production assets. 63. The Energy Profits Levy is accompanied by the temporary Electricity Generator Levy, introduced by Government on extraordinary returns in the market due to electricity prices far exceeding historical levels, as a result of Putin’s illegal invasion of Ukraine and weaponisation of gas supplies. This will ensure that energy companies contribute to the U K ’s collective efforts to strengthen public finances, and fund cost of living support and public services. We will keep the investment landscape for renewables under review to ensure we can deliver the capacity needed to decarbonise the sector. 64. We are also committed to ensuring that efforts to shift U K i ndustry towards greener practices are not undermined by carbon leakage; that is, the movement of production and associated emissions from one country to another due to different levels of decarbonisation effort through carbon pricing and climate regulation. Alongside this Strategy, the government has published a consultation on a range of domestic policies to protect against carbon leakage and ensure U K i ndustry has the optimal policy environment to decarbonise. These include a carbon border adjustment mechanism (C B A M) and mandatory product standards (M P S ) and the embodied emissions data required to introduce those policies. (See Industry chapter of Net Zero Growth Plan.) Across the maturity enabling and stimulating investment into climate resilience 65. The Climate Change Committee published its ‘Investment for a well-adapted U K ’ report in February 2023 highlighting the need to mobilise a range of funding sources to support adaptation investment 160. The report highlights a range of market barriers holding back new investment, limitations on climate risk information; lack of bankability of climate adaptation projects; and policy, regulatory and behavioural barriers. One of the biggest barriers to adaptation finance is being able to monetise
the benefits of adaptation action to repay private investment. We are running two projects seeking to address this a. Monetising insurance benefits from flood Insurance is a major part of the financial response to climate risk, but its viability and affordability is threatened where risks become very high. We will explore opportunities for new financing mechanisms for facilitating insurance markets to build flood resilience, where that b. Coastal Loss Innovative Funding and Financing (C L I F F ): A study exploring the development of innovative financing mechanisms to support residents in properties impacted by sea level rise, either through incentives to relocate from high-risk areas or by providing financial protection. 3.2.3 Supporting local areas to unlock green investment opportunities 66. Local authorities play an essential role to unlock the investment opportunities that support the U K ’s net zero, resilience and nature objectives, whilst also supporting local economic around 80% of all the U K ’s G H G e missions are potentially within scope or influence of local authorities and they have key responsibilities around planning, transport and waste management 67. | 56ee4d88-2ab4-4059-810e-e3d833392a95 | 37 |
0dc53735-3ec0-4895-b98a-08c315c358e9 | http://arxiv.org/pdf/2503.08761v1 | 2,025 | [
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] | arxiv.org | The results are shown in tables C2 and C3. In contrast, I do not find any significant robust effects of temperature on the probability of having suffered from extreme/severe anxiety in the last 30 days. While the point estimates for two top bins are positive, they are not statistically significant and also some of the lower bins pointin a positive
direction, rejecting a clear relationship between high wet bulb temperaturesand anxiety levels. There is also no significant effect when the continuous anxiety score is used as outcome variable. For this reason, I focus in the remainder solely on depression. Table 2 presents the results for depression using alternative heatindicators. Column uses only the number of days above 27°C as explanatory variable (without any other temperature bins)
and confirms the main results. One more heat day above 27° in the last 30 days increases the likelihood of having suffered from extreme or severe depression by 0.3 percentage points. In Column, I focus on the number of consecutive days above 27°C. The results show that consecutive heat days indeed are worse for mental health than the same number of heat days which are not necessarily consecutive; if the number of consecutive days above 27° increases by one day, itincreases the likelihood of having suffered from extreme or severe depression by 0.64 percentage points. Column presents the main results for the binary heatwave indicator; individuals that were exposed to two or more consecutive days with a mean wet bulb temperature above 27°C were two percentage points more likely to have
5 The results for anxiety using alternative heatindicators are shown in Table C4 in Appendix C. 10 suffered from severe/extreme depression in the last 30 days. If instead three or more days are used as the cut-off point, this effectincreases to 2.3 percentage points. In relative terms, these numbers corre spond to an increase of 24% and 27% relative to the mean prevalence of severe/extreme depression. When a heatwave is defined as 2 or more consecutive days above 28°C, the effect becomes as large as
5.8 percentage points. However, such extreme heat events are very rare. Only 2.1% of the individuals in the sample experienced such a heatwave in the last 30 days. Figure 3: Heat effects on depression and anxiety (wet bulb temperature) - The figure displays the effect of the number of days in a given wet bulb temperature range relative to the number of days with a wet bulb temperature in the reference category in the last 30 days on self-reported symptoms of depression and anxiety. Outcomes are binary variables; severe/extreme anxiety). Coefficients are multiplied by 100. 11 Table 2: Alternative heatindicators - Wet bulb
Sev./Extr. Sev./Extr. Sev./Extr. Sev./Extr. | c256096c-e04e-46dd-a140-03cce0061121 | 13 |
0dca5eab-ba8c-4a30-8a6b-f729de252ad9 | https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=OJ%3AL_202401781 | 2,024 | [
"General",
"Energy efficiency",
"Energy service demand reduction and resource efficiency",
"Non-energy use",
"Other low-carbon technologies and fuel switch",
"Renewables"
] | eur-lex.europa.eu | It is therefore necessary that Member States lay down rules on penalties
applicable to infringements of this Regulation and ensure that those rules are implemented. The penalties provided
54 OJ L 123, 12.5.2016, p. 1. 55
Regulation EU No 1822011 of the European Parliament and of the Council of 16 February 2011 laying down the rules and
general principles concerning mechanisms for control by Member States of the Commissions exercise of implementing powers OJ
L 55, 28.2.2011, p. 13. ELI httpdata.europa.euelireg20241781oj
2389
EN
OJ L, 28.6.2024
for should be effective, proportionate and dissuasive and should at least include fines and time-limited exclusion
from public procurement procedures. Without prejudice to Member States procedural autonomy and to the
discretion of competent authorities and judges to impose appropriate penalties in the individual cases, common
non-exhaustive criteria should be established for determining the types and levels of penalties to be imposed in the
event of infringements of this Regulation, to facilitate more consistent application of penalties. Those criteria should
include, inter alia, the nature, gravity and duration of the infringement, the financial situation of the natural or legal
person held responsible, as indicated for example by the total turnover or the annual income, and the economic
benefits derived from and generated by the infringement, insofar as those benefits can be determined. 115 The Commission should carry out an evaluation of this Regulation. Pursuant to paragraph 22 of the
Interinstitutional Agreement on Better Law-Making, that evaluation should be based on the five criteria of
efficiency, effectiveness, relevance, coherence and value added and should provide the basis for impact assessments
of possible further measures. The Commission should submit to the European Parliament, to the Council, to the
European Economic and Social Committee, and to the Committee of the Regions a report on the implementation of
this Regulation and its impact on the environmental sustainability of products and the functioning of the internal
market. Where appropriate, the report should be accompanied by a proposal to amend this Regulation. 116
It is appropriate that the Commission assess the potential benefits of setting requirements also in relation to social
aspects of products. As part of that assessment, the Commission should consider to what extent those requirements
could complement Union law, thereby addressing adverse impacts on human and social rights arising from
companies operations and from products. The Commission should therefore carry out an evaluation within four
years of the date of entry into force of this Regulation on the potential benefits of inclusion of social sustainability
requirements within the scope of this Regulation. The Commission should submit to the European Parliament, to the
Council, the European Economic and Social Committee, and to the Committee of the Regions a report on the
evaluation. | a753c674-997e-439a-b7e9-1f2dc3546402 | 39 |
0dcc97f8-93bc-4dfe-840f-98c5ca86ec94 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_e2ed2f6c199088dc30a95fddf6e84c72.pdf | 2,023 | [
"emissions",
"data",
"inventory",
"energy",
"emission"
] | cdn.climatepolicyradar.org | 2. Knowledge sharing with the Vietnam inventory team. | 70afacf8-8641-4466-819d-f4db8cad9d69 | 146 |
0dd45444-22b8-4858-a131-cedc46322d9d | https://cdn.climatepolicyradar.org/navigator/GBR/2021/decarbonising-transport-a-better-greener-britain_0e5fa97fb3d78e19b69ccf8f78fdd0cc.pdf | 2,021 | [
"Transport",
"Co-benefits",
"Cycling",
"Climate Finance",
"Public Transport",
"Freight",
"EVs",
"Shipping",
"Aviation",
"Walking",
"transport",
"zero",
"emissions",
"emission",
"carbon"
] | cdn.climatepolicyradar.org | The UK’s existing strengths and expertise along its value chain makes us well placed to generate significant quantities of green hydrogen from renewable electricity. Through bold initiatives such as our world first ‘hydrogen transport hub’ 14 we can now expand our innovation and infrastructure to create critical mass in its production and use. | b1244f11-6485-47b2-ba2a-c8a54f51cd77 | 38 |
0dda48a6-249f-4ea5-a430-7e753cf2887d | https://cdn.climatepolicyradar.org/navigator/GBR/2020/agriculture-act-2020_89bf740371b886d403c833463a2d589f.pdf | 2,020 | [
"regulations",
"section",
"provision",
"made",
"regulation"
] | climate-laws.org | This exclusion is referred to in this paragraph as the “RIBO exclusion”. (2) The condition in this sub-paragraph is that the organisation has notified the agreement to the CMA and provided all further details required by (a) the CMA has decided that it is appropriate for the RIBO (b) within two months of the CMA receiving all the details it requires, the CMA has not decided that it is inappropriate for (3) In deciding whether it is appropriate for the RIBO exclusion to apply, the CMA must consider whether the benefit of the agreement to the specified activities of the recognised interbranch organisation outweighs any prevention, restriction or distortion of competition within the United Kingdom as a result of the agreement. (4) The CMA may at any time give a direction to the effect that the RIBO exclusion no longer applies to a particular agreement. (5) Sub-paragraphs (4) to (8) of paragraph 9 apply to a direction under this paragraph as they apply to a direction under paragraph 9. “recognised interbranch organisation” means an organisation of agricultural businesses recognised under section 30 of the “specified activities” means the activities specified in regulations under section 30(6)(e) of that Act.” 1 The Agricultural Holdings Act 1986 is amended as follows. Notices relating to third party determination of rent 2 (1) Section 12 (arbitration or third party determination of rent) is amended as follows. (2) In subsection (1) for “referred to arbitration under this Act” substitute “determined in accordance with this section”. SCHEDULE 3 – Agricultural tenancies Document 2023-04-25 This is the original version (as it was originally enacted). (3) For subsection (1A) substitute— “(1A) Where a notice under subsection (1) is served, the question of how much rent is to be payable in respect of the holding as from the next termination date— (a) may be required by the landlord or tenant to be determined by arbitration under this Act (see section 84), or (b) may be referred by the landlord and tenant for third party determination under this Act (see section 84A).” (4) In subsection (2), for the words from “demand” to “third party determination” substitute “notice under subsection (1)”. (a) for “demand for arbitration under this section” substitute “notice under (b) for “the demand” substitute “the notice”; (c) in paragraph (a), after “arbitrator” insert “or third party”. (a) omit the words from “in relation to” to “third party determination”; (b) for the first “the demand or reference” substitute “a notice under (c) for the second “the demand or reference” substitute “the notice”; (d) for the third “the demand or reference” substitute “the notice under 3 (1) Schedule 2 (arbitration or third party determination of provisions supplementary to section 12) is amended as follows. (2) In the italic heading before paragraph 4, for “arbitrations” substitute (3) In paragraph 4, in sub-paragraph (1)— (a) for “demand for arbitration” substitute “notice under section 12(1) of this (b) for “the demand” substitute “the notice”. Appointment of arbitrators etc 4 In section 12 (arbitration or third party determination of rent), in subsection (3)(b), for the words from “to the” to “by him” substitute “under section 84 for the appointment 5 (1) Section 22 (rights to require certain records to be made) is amended as follows. (2) In subsection (2), for the words from “in default” to “so appointed” substitute “by the landlord and tenant (“the parties”) or, in default of agreement between the parties, by a person appointed by a professional authority on the application of either of them; and any person appointed by a professional authority”. (3) After subsection (2) insert—
54 Agriculture Act 2020 (c. 21) SCHEDULE 3 – Agricultural tenancies Document 2023-04-25 This is the original version (as it was originally enacted). “(2A) A party may not make an application to a professional authority under subsection (2) in any case if the other party has already made an application to a professional authority under that subsection in that case.” (a) for “the President” substitute “a professional authority”; (b) for “him” substitute “that authority”. (a) for the first “the President” substitute “a professional authority”; (b) for the second “the President” substitute “that authority”. (6) After subsection (5) insert— “(6) In this section “professional authority” has the same meaning as in 6 (1) Section 84 (arbitrations) is amended as follows. (2) In subsection (2), for “the President of the RICS” substitute “a professional (3) After subsection (2) insert— “(2A) A party may not make an application to a professional authority under subsection (2) in relation to a matter if the other party has already made an application to a professional authority under that subsection in relation to (a) for “the President of the RICS” substitute “a professional authority”; (b) for “him”, in both places, substitute “that authority”. (5) For subsection (6) substitute— “(6) In this section “professional authority” means— (a) the President of the Royal Institution of Chartered Surveyors, (b) the President of the Central Association of Agricultural Valuers, or (c) the Chair of the Agricultural Law Association. (7) The appropriate authority may by regulations amend this section so as to— (a) include a person in, or remove a person from, the definition of (b) reflect changes in the name or internal organisation of any body (8) In subsection (7) “appropriate authority” means— (a) the Secretary of State, in relation to England, and (b) the Welsh Ministers, in relation to Wales.” Requests for landlord’s consent or variation of terms
SCHEDULE 3 – Agricultural tenancies Document 2023-04-25 This is the original version (as it was originally enacted). “19A Disputes relating to requests for landlord’s consent or variation of terms (1) The appropriate authority may by regulations make provision for the tenant of an agricultural holding to refer for arbitration under this Act a request made by the tenant to the landlord where— (a) the request falls within subsection (3), and (b) no agreement has been reached with the landlord on the request. | 78f8c6bc-c906-4ba1-b960-a996ce3f3a28 | 21 |
0ddc6890-f9e1-47ab-b91d-7e3aa21c7bbe | https://cdn.climatepolicyradar.org/navigator/GBR/1900/united-kingdom-biennial-reports-br-br-3-national-communication-nc-nc-7_dabcc5bcde8c5a69cb06295558ac6b22.pdf | 2,017 | [
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] | cdn.climatepolicyradar.org | The policy statement recognises the need to make woodland planting more attractive to landowners and attract private investment to fund it, particularly through the development of payments for ecosystem services as set out by the Ecosystems Market Task Force. In England, the Environmental Impact Assessment (Forestry) Regulations were revised in May 2017 , requiring more information be provided by proposers of afforestation projects, while increasing the EIA threshold in areas mapped as low risk if a UKFS woodland creation plan is submitted. The objective of raising the threshold was to encourage the planting of larger woodlands, in part, to contribute to emissions reduction. The design of larger scale productive woodlands is supported through the Woodland Creation Planning Grant (from 2015), while their establishment is financed through the Woodland Carbon Fund (from 2016). A policy on when to convert woods and forests to open habitats in England is in place, which includes as assessment of implications for carbon balance in the process of prioritising sites for restoration. The development of a thriving forestry sector, through an industry-led action plan (Grown in Britain), is highlighted as an essential element to achieve woodland planting aspirations and deliver emissions savings in other sectors through the sustainable use of woodfuel as a source of renewable energy and harvested wood products substituting for other materials. The Clean Growth Strategy (CGS) was published in October 2017 and sets out broad aspirations to enhance the rate of afforestation and use of timber in construction in an illustrative pathway to meet the fifth carbon budget (2028-32) and longer term emissions reduction. The CGS also committed to ‘set up a stronger and more attractive domestic carbon offset market that will encourage more businesses to support cost effective emissions reductions, such as through planting trees’ and to ‘We will unlock private finance to invest in forestry by establishing forestry investment zones to offer investors streamlined decision making and more certainty, In Scotland, forestry is recognised as having an important role in contributing to emissions reduction targets through carbon sequestration which is a specific objective of woodland creation. The Scottish Government is committed to expand this important carbon sink and the Programme for Government spells out the support to a growing forestry industry to contribute to climate change targets. The draft Climate Change Plan (third report on policies and proposals) sets out how the Scottish Government will meet its greenhouse gas emission reduction targets
Chapter 3 – Policies and Measures 145 2017-2032 and includes a policy on increasing the long term annual woodland creation target from the current 10,000 hectares of new woodland per year to 15,000 hectares per year from 2024/25. To complement woodland creation, a framework to better control woodland removal is also in place with a proposed policy to further increase emissions abatement through greater use of Scottish timber in building construction and refurbishment. These targets will be taken forward in a sustainable way and require the creation of a range of different woodland types, on different sites, with different objectives. The Scottish Government is committed to supporting the creation of at least 3,000 hectares of new native woodland a year (Scottish Biodiversity Route Map 2020). To support the delivery of the draft Climate Change Plan, the Forestry Grant Scheme offers financial support for the creation of new woodland and the sustainable management of existing woodland. All applications are assessed against the UK Forestry Standard and associated The Scottish Government has recently introduced the Forestry and Land Management (Scotland) Bill to replace the 1967 Forestry Act in Scotland. The Bill includes duties on Ministers to promote sustainable forest management and to publish a forestry strategy which will set out the Government’s priorities in relation to the economic, environmental and social benefits of The Forestry (Environmental Impact Assessment) (Scotland) Regulations 2017 came into force in May 2017 , driven by EU EIA Directive 2014 that aims to streamline aspects of the EIA process and improve transparency and consistency in EIA practice across a number of regimes. The main changes include an increase of the threshold for afforestation projects outside sensitive areas from 5 to 20 hectares to secure a more effective way in assessing woodland creation applications to contribute to emission reductions. The 2017 Regulations have been reflected in England, Scotland and Wales also have established Woodfuel Strategies that aim to maximise the contribution of both existing and new woodlands to renewable energy production. For example, the supply of small to medium scale heat in off gas grid areas is the focus of Forestry Commission England’s Woodfuel Implementation Plan, which is supported by renewable energy policies including the Renewable Heat Incentive. To promote sustainable land use, “Woodlands for Wales” is the Welsh Government’s fifty-year Strategy. The Welsh Government has set a new short term target over the life of the current action plan of 10,000 hectares of new woodland by 2020. This will require an average of 2,000 hectares of tree planting per annum. In 2015 GHG emissions from waste contributed to 4% of total UK emissions; representing a decrease of 73% since 1990. Approximately 67% of emissions from this sector are attributable Consistent with the EU Waste Framework Directive, the government and the devolved administrations have published waste management and prevention plans aiming to reduce the quantity of waste produced and to increasingly recover value from it. In addition to these, the UK government has recently published its Clean Growth Strategy, where it set its long- term ambition to move towards zero avoidable waste by 2050 and a commitment to publish a renewed Resources and Waste Strategy in 2018. 146 7th National Communication In 2015 households in the UK produced 26.7 million tonnes of waste. This has remained relatively flat since 2010. The latest commercial and industrial arisings show a significant decrease in arisings, with 27 .7 million tonnes in 2014 compared to 33.9 million tonnes in 2010. That is a decrease of 18%. The industrial sector accounts for 12.6 million tonnes and the commercial sector 15.1 million tonnes. | c6207828-d0f1-4adb-9ed1-c6b8e81a528f | 55 |
0de3563b-8d22-4a1c-8849-4a95c8223e10 | https://www.gov.uk//guidance/smart-meters-how-they-work | 2,013 | [
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] | gov.uk | What are smart meters? Unlike traditional meters, which simply register a running total of energy used, smart gas and electricity meters can record half-hourly price and consumption data and provide automatic meter readings to your energy supplier. Most homes have two meters, one for gas and one for electricity both will be replaced with smart meters. You will also be offered an In-Home Display sometimes referred to as an IHD, an easy-to-use handheld device that sits within your home. This will show you the cost and amount of energy you are using, updating every 30 minutes for gas and in near real-time for electricity. The installation will also include a communications hub, which allows the smart meters and IHD to communicate with each other, and links your smart metering system to the secure national smart meter network. How do I get a smart meter? The government has required energy suppliers in England, Scotland and Wales to provide smart meters to their customers. Get in touch with your energy supplier, which can arrange for smart meters to be installed at a time and date that suits you. | 1e45c54c-01c0-43ce-9c2a-4e9c8f067f8a | 0 |
0de8d5a8-2380-4d07-8dfc-7dcc2317c9dd | https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:52021PC0554&from=EN | -1 | [
"Agriculture and forestry",
"Non-energy use"
] | eur-lex.europa.eu | The 2030 target is in line with the Paris Agreement objective to keep the global temperature increase to well below 2°C and pursue efforts to keep it to 1.5°C. The Communication proposes to move towards a more stringent contribution from the LULUCF sector and, as a further step, to combine the agriculture non-CO2 greenhouse gas emissions with the land use, land use change and forestry sector, thereby creating a newly regulated land sector (covering emissions and removals from agriculture, forestry and other land use). This can promote synergies between land-based mitigation actions and enable more integrated policymaking and policy implementation at the national and EU level. The analysis underpinning the Communication shows that the land sector would have the potential to become climate-neutral by around 2035 in a cost-effective manner, and subsequently generate more CO2 removals than greenhouse gas emissions. The European Council endorsed the new EU binding target for 2030 at its meeting of December 2020
4
. It also called on the Commission to assess how all economic sectors can best contribute to the 2030 target and to make the necessary proposals, accompanied by an in-depth examination of the environmental, economic and social impact at Member State level, taking into account national energy and climate plans and reviewing existing flexibilities . To this end, the European Climate Law makes the EU s climate neutrality target legally binding, and raises the 2030 ambition by setting the target of at least 55% net emission reduction by 2030 compared to 1990. In order to follow the pathway proposed in the European Climate Law, and deliver this increased level of ambition for 2030, the Commission has reviewed the climate and energy legislation currently in place that is expected to reduce greenhouse gas emissions by 40% by 2030 and by 60% by 2050. This Fit for 55 legislative package, as announced in the Commission's Climate Target Plan, is the most comprehensive building block in the efforts to implement the ambitious new 2030 climate target, and all economic sectors and policies will need to make their contribution. The initial regulatory framework for the land use, land use change and forestry (LULUCF) sector, as laid down in Regulation (EU) 2018/841, was adopted in 2018 and covers CO2 emissions and removals and greenhouse gas emissions of CH4 and N2O resulting from the management of land, forests and biomass during the period from 2021 to 2030. It contributes to the previous Union s emission reduction target of at least 40% by 2030 compared to 1990, by ensuring that the sum of total emissions does not exceed the sum of total removals generated by the sector after the application of the accounting rules and of the flexibility with the effort sharing (or ESR) sector set out by Regulation (EU) 2018/842. The proposal to amend Regulation (EU) 2018/841 as part of the Fit for 55 package aims to strengthen the contribution of the LULUCF sector to the increased overall climate ambition for 2030. To this end, the proposal: sets out the overall Union target of net greenhouse gas removals in the LULUCF sector to 310 million tonnes of CO2 equivalent in 2030; reinforces the obligation for Member States to submit integrated mitigation plans for the land sector and enhances monitoring requirements using digital technologies; aligns the objectives with related policy initiatives of biodiversity and bioenergy; determines the Union target of climate neutrality for 2035 in the land sector (which combines the LULUCF sector and the non-CO2 agricultural sector); and commits the Commission to make proposals for national contributions to the 2035 target by 2025. The proposed amendment introduces only minor, non-substantive, changes in the LULUCF regulatory framework for the first compliance period, i.e. from 2021 to 2025. In contrast, significant change takes place with the beginning of the second compliance period from 2026 to 2030. In order to simplify implementation and compliance, the Kyoto-inspired land accounting rules will no longer be applied post 2025, and the flexibility between LULUCF and with the effort sharing sectors will be adjusted, in line with the European Climate Law. The overall Union target of net greenhouse gas removals of 310 million tonnes of CO2 equivalent will be distributed between Member States as annual national targets for the period from 2026 to 2030, and be based on the emissions and removals reported in the greenhouse gas inventories and the areas of managed land. A new system of governance of the target compliance will be introduced and the land use flexibility mechanism addressing risk of non-compliance by Member States will be adjusted. | 6305f6c7-4e72-4dc0-a09c-8e54d845c295 | 1 |
0dee7ed6-fa76-4049-a9da-fb933931fb61 | https://cdn.climatepolicyradar.org/navigator/GBR/2025/united-kingdom-national-inventory-report-nir-2025_3d22864cf237013c86452d4c6455250a.pdf | 2,025 | [
"emissions",
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] | cdn.climatepolicyradar.org | Consistent with decision 7/CP.2715, the UK uses AR5 Global Warming Potentials (GWPs) for reporting under the UNFCCC, and the Paris Agreement (PA). The other elements of this submission include the reporting of GHG emissions by sources and removals by sinks in the Common Reporting Format (CRT) tables, and any other additional information in support of this submission. | 95866fde-5b53-4214-b279-97a1078c466c | 49 |
0df5aca0-4291-49fd-8bb5-a0d6bb4b5033 | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:31998L0069 | 1,998 | [
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] | eur-lex.europa.eu | 5.3. Soak
5.3.1. Within five minutes of completing the preconditioning operation specified in 5.2.1 the engine bonnet must be completely closed and the vehicle driven off the chassis dynamometer and parked in the soak area. The vehicle is parked for a minimum of 12 hours and a maximum of 36 hours. The engine oil and coolant temperatures must have reached the temperature of the area or within ± 3 oK of it at the end of the period. 5.4. Dynamometer test
5.4.1. After conclusion of the soak period the vehicle is driven through a complete Type I test drive as described in Annex III (cold start urban and extra urban test). Then the engine is shut off. Exhaust emissions may be sampled during this operation but the results must not be used for the purpose of exhaust emission type-approval. | 282d51c7-9418-4d78-8dce-aec1567a8b80 | 39 |
0e010e3e-0091-48a6-a943-13ccc2669ffa | https://cdn.climatepolicyradar.org/navigator/GBR/1900/united-kingdom-national-communication-nc-nc-8-biennial-reports-br-br-5_288d5f885869447df3e9910829b567a3.pdf | 2,022 | [
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] | cdn.climatepolicyradar.org | More broadly we continue supporting and engaging with organisations like the NDC Partnership, whose mission is to ensure effective support for the implementation of developing countries’ NDCs and enable us to coordinate our support with that of other countries and organisations. The UK will also work closely with partner countries to plan and evaluate our programmes and identify ways to achieve greater impacts. Over the period 2021 – 2025, UK ICF will focus on driving transformation and systemic shifts required to achieve the Paris Agreement goals and deliver on the Glasgow Climate Pact Clean A major focus of our ICF programming will be on accelerating the clean energy transition in developing countries so that they can provide access to affordable, reliable and clean energy for all and reduce or avoid high emissions pathways, making use of innovation, technology and carbon pricing and addressing social and gender barriers to clean Nature for Climate and Through our ICF and in line with the recommendations from the Dasgupta Review, we will protect, restore and sustainably manage nature including through protection and restoration of critical ecosystems on land and in the ocean, reversing forest loss, and supporting sustainable food and water systems. We will also seek to ensure our global financial and economic systems support nature through sustainable production and consumption and management of risks, while supporting communities and livelihoods. Adaptation and UK ICF will ensure that countries and communities are supported to adapt to, prepare for and cope with the damaging effects of climate change and climate-linked disasters. Without action, hard won gains in areas such as health, nutrition and livelihoods risk being reversed. Those living in poverty, women and girls, Indigenous Peoples and Local Communities, people with disabilities and marginalised and crisis-affected groups are already being hit hardest by the impacts of a changing climate and they stand to suffer most unless action is taken. Sustainable Cities, Infrastructure and In the context of rapid changes in urban development, UK ICF will focus on supporting the low-carbon, green and resilient urbanisation needed to promote sustainable cities, along with wider infrastructure across the transport, building, water and waste sectors. With 68% of the world population projected to live in urban areas by 2050 and cities accounting for 75% of global CO2 emissions, investment in sustainable cities is key for meeting both our development and climate goals. 6.4.2 Support for cross cutting multilateral climate funds The UK is one of the largest contributors to the major multilateral climate funds, with £724m provided over 2019 and 2020. The UK’s contribution to the GCF will double to £1.44bn between 2020 and 2023, making the UK the largest contributor. £450m of this commitment was provided in 2020. The other main multilateral funds that that benefitted from UK support are the Climate Investment Funds (£200 million UK finance), and the Global Environment Facility with £50m climate specific support provided over 2019 and 2020. 346 8th National Communication Global Environment Facility 150.5 general ICF ODA Grant Cross-cutting Support is new contributions. Green Climate Fund 595.46 climate UNDP Climate Promise 3 climate Relevant CTF tables submitted for UNFCCC reporting including those with NC8 6.4.2.1 G lobal Environment Facility The Global Environment Facility (GEF) is the principal multilateral agency supporting developing countries in tackling major environmental problems and supporting implementation of the international agreements covering biodiversity (including wildlife loss), land degradation, deforestation, chemical pollution, marine and freshwater degradation – including marine plastic – and climate change. The GEF budget is replenished on 4-yearly cycles and a total of 28 countries contribute. It is currently in the seventh replenishment period (GEF7) from July 2018 until June 2022 which has a total budget of $4.1 billion (the GEF 8 replenishment negotiations will be finalised in June 2022). Of the GEF7 total, the UK is contributing up to £250 million in total (10.07% burden share of the total). The UK contribution makes the UK the third largest donor to GEF7 after Japan and Germany. Of this, 60% of programmes under GEF7 have clear climate benefits and so £150 million of our contribution is scored as ICF. Since its inception in 1991 GEF has invested in improving the management of 3,300 protected areas covering an area of about 860m hectares, an area larger than Brazil. GEF has been instrumental in supporting national policy reform and planning frameworks that promote biodiversity considerations across sectors and geographies with globally significant biodiversity. This has resulted in legal, environmental, regulatory, governance and socio- economic additionalities beyond incremental cost benefits. GEF Sustainable Forestry Management interventions were estimated to have avoided 4,875km2 of deforestation, sequestering 1.33 tonnes of carbon per hectare per year and increasing household assets by USD$163-353. It has also supported management of 790 climate change mitigation projects contributing to 2.7 billion tonnes of greenhouse gas emission reductions and sustainable management of 34 of the world’s major river basins and provided $131m to the Global Wildlife Programme to tackle the illegal wildlife trade. Since becoming operational in 2015, the Green Climate Fund (GCF) has become the key multilateral climate fund, with a mandate to make ‘an ambitious contribution to the global efforts towards attaining the goals set by the international community to combat climate change’. The UK is a strong supporter of the GCF having committed £720 million
Chapter 6 Financial Assistance and Support for Technologies 347 for the initial resource mobilisation period (2015-2019), and doubling this commitment to £1.44 billion for the first replenishment period (2020-2023). The UK is committed to ensuring that the GCF delivers maximum impacts in the developing countries it supports. The GCF funds transformational projects with a strong focus on leveraging private finance, with a commitment to provide 50% of its resources for mitigation and 50% for adaptation. At least 50% of its adaptation support will be provided to particularly vulnerable countries including Least Developed Countries (LDCs), Small Island Developing States (SIDS) and African States. | e6994b55-18ee-49c8-92db-2261135aea96 | 148 |
0e045604-9a0f-4476-8728-13d8f4c047a7 | http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52012XC0419(02) | 2,012 | [
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] | eur-lex.europa.eu | Therefore an estimate of the lifetime of the building as a whole (and not of single building elements) is required. This may depend on the type of construction on the one hand (e.g. prefabricated house versus solid construction) and on the type of use on the other (e.g. retail properties usually have shorter lifetimes than residential buildings). Member States are free to choose building lifetimes, but the lifetimes used should show plausible relationships when comparing different building categories. Secondly, disposal costs may be introduced in connection with replacement costs, since the dismantling or demolition of an old building element creates some cost. This cost is usually not included when fixing the replacement cost at the same level as the initial investment (no cost increase/decrease in real terms). Therefore, the addition of some extra disposal costs related to replacement activities may be included in the global cost calculation. The major challenge with respect to the consideration of disposal costs is the acquisition of reliable and market-based cost data. Usually disposal costs in the construction sector are only taken into account through an approximation based on the volume of the building, differentiated (in some cases) by construction type. 7. DERIVATION OF A COST-OPTIMAL LEVEL OF ENERGY PERFORMANCE FOR EACH REFERENCE BUILDING
7.1. Identification of the cost-optimal range
Based on the calculations of primary energy use (step 3) and global costs (step 4) associated with the different measures/packages/variants (step 2) assessed for the defined reference buildings (step 1), graphs can be drawn per reference building that describe primary energy use (x-axis: kWh primary energy/(m2 useful floor area and year)) and global costs (y-axis: EURO/m2 useful floor area) of the different solutions. From the number of measures/ packages/variants assessed, a specific cost curve (= lower border of the area marked by the data points of the different variants) can be developed
Figure 5
Different variants within the graph and position of the cost-optimal range
 (13)
The combination of packages with the lowest cost is the lowest point of the curve (in the illustration above, package 3 ). Its position on the x-axis automatically gives the cost-optimal level of minimum energy performance requirements. As stipulated in paragraph 2 of Annex I(6) to the Regulation, if packages have the same or very similar costs, the package with the lower primary energy use (= left border of the cost-optimal range) should if possible guide the definition of the cost-optimum level. For building elements, cost-optimal levels are assessed by fixing all parameters (option 1: starting from the variant that has been identified as cost-optimal; option 2: starting from different variants and using an average of the resulting values) and varying the performance of a specific building element. Graphs can then be developed to show the performance (x-axis, e.g. in W/(m2K) for building elements like the roof of a building) and global costs (y-axis, in EURO/m2 useful floor area). The building element properties with the lowest cost will provide the cost-optimal level. If different building element properties have the same or very similar costs, the building element property with the lower primary energy use (= left border of the cost-optimal range) should guide the definition of the cost-optimum level (the fact that higher upfront investment needs occur should be taken into account). It is important to note that minimum performance requirements for boilers and other installed appliances and equipment are being set under the framework of the Ecodesign Directive (14). 7.2. Comparison with current requirements at Member State level
The current requirements at Member State level need to be compared to the calculated cost-optimal level. Therefore, the current regulations need to be applied to the reference building, leading to a calculation of the primary energy consumption of the building according to the rules set out in step 3. In a second step, the difference between the current level and the identified cost-optimal level is calculated according to equation in the box below. Identification of the gap
Gap % (reference building level) = (cost-optimal level [kWh/m2a] current minimum performance requirements [kWh/m2a]) / cost-optimal level [kWh/m2a]) x 100 %
For building elements, the gap is calculated according to the following equation:
Gap % (for building elements) = (cost-optimal level [unit of performance indicator (15)] current minimum performance requirements [unit of performance indicator]) / cost-optimal level [unit of performance indicator]) x 100 %
The difference between the calculated cost-optimal levels of minimum performance requirements and those in force should be calculated as the difference between the average of all the minimum energy performance requirements in force and the average of all the calculated cost optimal levels resulting from the variants applied to all the comparable reference buildings and building types used. It is up to the Member State to introduce a weighing factor representing the relative importance of one reference building (and its requirement) in a MS over another. However, such approach should be made transparent in the reporting to the Commission. In line with recital 14 of Directive 2010/31/EU, a significant discrepancy between the outcome of the cost optimal cost calculation and the minimum requirements currently in force in a Member State exist if the latter are 15Â % lower than the cost-optimum. | 72b1b0d7-9201-431b-9c48-a9d73c828514 | 30 |
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] | cdn.climatepolicyradar.org | The Arbed programme contributes to the eradication of fuel poverty, cutting GHG emissions and to improving the energy performance of homes in Wales. Arbed 2 ERDF takes a ‘whole-house’ approach when assessing potential energy efficiency measures for a property; this approach considers the nature of the property, the occupancy, the potential impact of different measures and value for money. Potential measures within Arbed can include external wall insulation, heating system upgrade, solar hot water, heating controls The introduction of the Welsh Housing Quality Standard (WHQS) in May 2002 provides a common target standard for the physical condition of all existing social housing within Wales to be originally achieved by 2012 (now 2020). The WHQS provides for the annual energy consumption for space and water heating to be estimated using the SAP (Standard Assessment Procedure) method and specifies the minimum WHQS specifies a single SAP score of 65 out of a possible 100 and the energy efficiency targets within WHQS are challenging in relation to the difficulties faced in improving the older The latest published statistics on achievement of the WHQS shows that (at 31 March 2012) over 159,000 dwellings (nearly 72%) are fully compliant in achieving an EPC rating of 65 or above, and over 170,000 dwellings (nearly 77%) are fully compliant in having a central heating system. For new social housing energy efficiency is defined by Planning Policy Wales and is required to meet Code for Sustainable Homes 3+. From December 2013, Part L of the Building Regulations Wales will apply to new social housing. 3.6.14 Fuel poverty and domestic energy efficiency in Scotland The Scottish Government is currently developing a long term Fuel Poverty Strategy, including setting new statutory targets and putting in place a revised definition of fuel poverty that will help inform where action is most needed across the country. Further details on this are provided in Whilst work to develop the new strategy is ongoing, the Scottish Government will continue to deliver support to householders through the Home Energy Efficiency Programmes for Scotland (HEEPS). HEEPS is designed to tackle fuel poverty, reduce carbon emissions and support jobs
118 7th National Communication • H Area Based Schemes will deliver provide a range of insulation measures helping to reduce heat loss and save households money. They are delivered by local authorities and prioritise fuel poor areas. Warmer Homes Scotland, offered to vulnerable households in receipt of certain benefits. Those receiving assistance must either be homeowners or tenants of private sector landlords. Warmer Homes Scotland (WHS) has a strong focus on fabric measures, such as heating and insulation, but also includes micro-generation to offer a wider range of heating options to off-gas households. Loans, available to all private sector households in Scotland (both owner occupiers and private sector landlords) who wish to install energy efficiency measures. The scheme offers an interest-free loan of up to £15,000 per household. The loans can be combined with ECO, and ABS. The Scottish Government has designated energy efficiency as a National Infrastructure Priority, which in future will be delivered through Scotland’s Energy Efficiency Programme (SEEP), a transformational and integrated approach to improving the energy efficiency and provision of heat to all types of buildings across Scotland. The Scottish Government is committed to ensuring that fuel poverty is prioritised and supported throughout SEEP. Heating our homes, businesses and industry accounts for nearly half of all energy use in the UK and a third of our carbon emissions. Nearly 70% of our heat is produced from natural gas. Meeting our target of reducing emissions by at least 80% by 2050 implies decarbonising nearly all heat in buildings and most industrial processes. Reducing the demand for heat through improved energy efficiency will have an important role to play but will not by itself suffice to meet There are a variety of fuels, technologies and distribution systems with potential to deliver the transformation necessary to meet 2050 targets – including heat networks, heat pumps, hydrogen and biogas, which can be used separately or in combination. But it is not yet clear which approach will work best at scale and offer the most cost-effective, long-term answer. Officials at The Department for Business, Energy and Industrial Strategy are currently conducting work to better understand the options and to lay the groundwork to support decisions in the first half of the 2020s on the long-term future of heat. There are active measures in place to reduce our emissions from heat and are developing policies to address issues that aren’t affected by complex decisions about decarbonisation of the gas network. The heating and cooling proposals set out in the Clean Growth Strategy to achieve the ambitious 5th carbon budget include action to phase out all oil-based heating systems off the gas grid, a sustainable market for heat networks, and strong action on new build and in the business and industrial sectors. 3.6.16 Domestic Renewable Heat Incentive The Domestic RHI policy is set out along with the non-domestic policy on page 103 of this 3.6.17 Renewable Heat Premium Payment scheme The Renewable Heat Premium Payment (RHPP) scheme opened in August 2011 and closed in March 2014. The scheme provided cash back vouchers for householders (mainly those not connected to the gas grid) in England, Scotland and Wales in order to incentivise the purchase of eligible renewable heat generating installations. Chapter 3 – Policies and Measures 119 Registered social landlords could also bid for money to support the installation of cost- effective renewable heating systems in social housing stock. Again, the focus was on areas not The scheme’s purpose was to support the take-up of renewable heating technologies in the domestic sector prior to the introduction of the Domestic Renewable Heat Incentive in April 2014. The technologies supported by the RHPP were ground-, water- or air-source pumps, biomass boilers and solar thermal. The RHPP scheme supported over 15,000 installations across England, Scotland and Wales and generated an estimated 232,959MWh of heat annually. | c6207828-d0f1-4adb-9ed1-c6b8e81a528f | 41 |
0e070580-12ea-4510-8c04-370a3c601ce5 | http://arxiv.org/abs/2104.05506v2 | 2,021 | [
"non - carbon dioxide greenhouse gas emission rate",
"global warming potential values",
"year time horizons",
"government agencies",
"scenario database"
] | ArXiv | Emission metrics, a crucial tool in setting effective equivalences between greenhouse gases, currently require a subjective, arbitrary choice of time horizon. Here, we propose a novel framework that uses a specific temperature goal to calculate the time horizon that aligns with scenarios achieving that temperature goal. We analyze the Intergovernmental Panel on on Global Warming of 1.5 deg C Scenario Database to find that time horizons that align with the 1.5 and 2 deg C global warming goals of the Paris Agreement are 24 [90% prediction interval: 7, 41] and 58 [90% PI: 41, 74] years respectively. We then use these time horizons to quantify time-dependent emission metrics with methane as our main example. We find that the Global Warming Potential values that align with the 1.5 and 2 deg C goals are GWP1.5 deg C = 75 [90% PI: 54, 107] and GWP2 deg C = 42 [90% PI: 35, 54]; for the Global Temperature change Potential they are GTP1.5 deg C = 41 [90% PI: 16, 102] and GTP2 deg C = 9 [90% PI: 7, 16]. The most commonly used time horizon, 100 years, underestimates methane emission 2 metrics by 34-38% relative to the values we calculate that align with the 2 deg C goal and 63-87% relative to the 1.5 deg C goal. To best align emission metrics with the 1.5 deg C goal of the Paris Agreement, we recommend a 24-year time horizon, using 2045 as the endpoint time, with its associated GWP1.5 deg C = 75 and GTP1.5 deg C = 41. Emission metrics, the "exchange rates" between greenhouse gases, are necessary for policymakers and decision-makers to compare the relative effects of different gases to carbon dioxide, the generally accepted baseline [1][2][3][4][5][6][7][8][9][10] . Emission metrics underpin the Nationally Determined Contributions (NDCs) of the Paris Agreement and form the basis of so-called "carbon dioxide equivalent" emissions by allowing greenhouse gases to be compared on the same scale. Here, we develop a framework to quantify emission metrics that align with the Paris Agreement goal to keep global warming well below 2 deg C and ideally to 1.5 deg C, compared to preindustrial levels. Currently, the Intergovernmental Panel on Climate Change (IPCC) uses 20-and 100-year time horizons for emission metrics 1 while simultaneously acknowledging that these arbitrary values "should not be considered as having any special significance" 11 . Our framework derives time horizons of special significance that align with specific temperature goals. Time horizons are required for most emission metrics because greenhouse gases with shorter atmospheric lifetimes impact the climate much more over the short-term compared to the more constant effects of carbon dioxide over centuries 12 . We focus on methane because it is the second-most important greenhouse gas after carbon dioxide and its atmospheric lifetime of only 11.8 years means that its emission metrics depend strongly on the time horizon 1,13 . The extension of our method to other short-lived climate forcers would be straightforward. The IPCC's use of two reference time horizons, 20 and 100 years, has been criticized for being arbitrary and unjustified 14 , with the choice between the two often based on political perspectives or vested interests 15 . Quantitative justifications for specific time horizons are surprisingly lacking in the literature. One rare example comes from Sarofim and Giordano, who argued that time horizons could be justified based on their equivalent economic discount rate, and showed that the 100-year time horizon aligned implicitly with a 3.3% discount rate (consistent with many climate and economic impact analyses) 15 . Here, we instead define "justified time horizons" as those that align with the predicted timing of peak warming for the specific temperature goals of the Paris Agreement. We then use these justified time horizons to quantify time-dependent emission metrics. What is the justification for aligning emission metrics with temperature goals? We believe that greenhouse gases should be weighted based on their contribution to achieving a given climate goal. We acknowledge that emission metrics are used in a wide range of applications, not all of which relate to temperature stabilization goals, meaning that the criteria for selecting time horizons is not universal. Potential policy goals, beyond temperature stabilization, include intergenerational equity 8,9,16 , air quality 17 , and cost-effectiveness 18,19 . However, since the main goal of the Paris Agreement is to limit the temperature peak well below 2 deg C, the impact of emissions on achieving this specific temperature goal should dictate the relative importance of different greenhouse gases. We use 1.5 deg C and 2 deg C as representative examples of the temperature goals of the Paris Agreement since they are the two values explicitly mentioned. Throughout this work we use "justified" as short-hand for "justified in its alignment with the Paris Agreement temperature goals," while noting that other justifications could and should be developed for different applications. Our framework is primarily designed for times before peak temperature; we make no claim about optimal emission metrics after the time of peak temperature, but simply aim to align emission metrics with the current goal of avoiding the exceedance of a given temperature limit. We hypothesize that as a temperature peak is approached, new climate goals will be developed (likely regarding stabilization at a certain temperature) and argue that future time horizons should be calculated that align with those goals. We recognize the value in having an agreed upon emission metric to standardize the weighting of different greenhouse gases and support the narrowing of the broad range of possible emission metrics. The use of the Global Warming Potential with a 100-year time horizon (GWP100) as the common metric in the implementation of the Paris Agreement, as agreed upon in the 24th Conference of the Parties (COP24) in 2019, is a step in the right direction towards standardization 19 . However, it has been shown that pathways with identical carbon dioxide equivalent emissions calculated using GWP100 can vary in temperature by as much as 0.17 deg C20 . | 67348e5b-cc8e-46c0-b5a9-1e347d6eb701 | 0 |
0e1360a0-6e8e-46e5-8015-acaf271615a7 | https://cdn.climatepolicyradar.org/navigator/GBR/2025/united-kingdom-national-inventory-report-nir-2025_3d22864cf237013c86452d4c6455250a.pdf | 2,025 | [
"emissions",
"data",
"inventory",
"emission",
"used"
] | cdn.climatepolicyradar.org | UK NID 2025 (Issue 1) Ricardo Page 574 Petersen, S.O., Dorno, N., Lindholst, S. et al. Emissions of CH4, N2O, NH3 and odorants from pig slurry during winter and summer storage. | 95866fde-5b53-4214-b279-97a1078c466c | 426 |
0e163b11-78cf-4bdf-92d9-69cfd4358aa8 | http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52006DC0105 | 2,006 | [
"General",
"Energy service demand reduction and resource efficiency",
"Energy efficiency",
"Renewables",
"Other low-carbon technologies and fuel switch"
] | eur-lex.europa.eu | Encouraging innovation: a strategic European energy technology plan
The development and deployment of new energy technologies is essential to deliver security of supply, sustainability and industrial competitiveness. Energy related research has contributed strongly to energy efficiency (e.g. in car engines) and to energy diversity through renewable energy sources. However the magnitude of the challenges ahead requires increased efforts. This necessitates a long term commitment. As an example research has allowed efficiency of coal power stations to be improved by 30% in the last thirty years. The Research Fund for Coal and Steel has contributed to funding this at EU level. Further technological developments would see significant reductions in CO2 emissions. Research can also bring commercial opportunities. Energy efficient and low carbon technologies constitute a rapidly growing international market that will be worth billions of Euros in the coming years. Europe must ensure that its industries are world leaders in these new generations of technologies and processes. | 50b4a4ac-f6e9-4dda-86b6-697f6447e2ab | 36 |
0e1718ac-3212-440b-b7f7-c4d717f2b9b7 | http://arxiv.org/pdf/2111.00987v1 | 2,021 | [
"electricity",
"model",
"market",
"energy",
"learning"
] | arxiv.org | I hereby declare that except where specific reference is made to the work of others, the contents of this dissertation are original and have not been submitted in whole or in part for consideration for any other degree or qualification in this, or any other university. This dissertation is my own work and contains nothing which is the outcome of work done in collaboration with others, except as specified in the text and Acknowledgements. This dissertation contains fewer than 65,000 words including appendices, bibliography, footnotes, tables and equations and has fewer than 150 figures. November 2021
The impacts of global warming on the earth may have profound effects on land and ocean ecosystems [120]. The release of carbon emissions into the atmosphere increases the likelihood of the most severe impacts and increases the likelihood that tipping points are reached, where runaway carbon emissions and average temperature rises are likely. Therefore a transition to a low-carbon energy supply is required to prevent the impacts of climate change. A low-carbon electricity supply is one which releases a lower amount of carbon dioxide over its lifetime than the current, fossil-fuel based system. However, such a transition is complex and contains multiple uncertainties. For instance, what carbon tax should the UK government set over the next 30 years? Are poor short-term electricity demand forecasts locking us in to higher emissions over the long-term? Can we limit the market power of generator companies? And can we rely on these models to make decisions of such importance? Whilst much work has been carried out investigating energy models in different electricity and energy markets, these models are not often fully validated against real-world data. This thesis seeks to validate a novel agent-based model, ElecSim, by calibrating with real-world data. Through this calibration, confidence can be gained in the underlying dynamics of the model and provide policy makers with the opportunity to better understand the system with which they are dealing with. Secondly, much work has been undertaken to understand certain aspects of electricity markets using agent-based models and machine learning. However, this work, often, does not place these findings into a wider context. For instance, whilst a high degree of focus is placed on the ability of reinforcement learning to bid strategically within an agent-based setting, how to limit this behaviour has not been investigated to the same extent. Similarly, machine learning has been used to predict electricity demand at various time intervals. However, the effect that different prediction methods have on the long-term electricity market has not been explored. Finally, machine learning and simulation has the ability to optimise an entire system. However, this ability received much research attention, instead the focus has been on smaller scale changes to models. In this thesis we aim to fill this research gap by first calibrating our model, and secondly reducing electricity price and carbon emissions from the United Kingdom's electricity mix by optimising carbon tax strategies. The central question of this thesis is: how can artificial intelligence (AI) and machine learning (ML) answer fundamental questions of the energy transition using an agent-based model of the electricity system? This thesis aims to go beyond small-scale improvements to agent-based models and answering scope-limited questions by understanding first: what challenges can AI and ML tackle, and secondly: how do these methods relate back to the wider energy system? By taking this approach, we answer multiple subquestions, which are explored below:
1. Can a simulation model an electrcity market over the long-term? Traditional electricity market models mimic the behaviour of centralised actors with perfect foresight and information. Other models which model actors as having imperfect foresight and information lack the ability to model multiple time-steps over a long time horizon. In Chapter 3, a novel open-source agent-based model called ElecSim is presented which challenges these issues. We show that it is possible to create an electricity model which can simulate multiple time-steps over a long-time horizon and generate realistic electricity mixes as model outputs. 2. Is it possible to model the variability of an electricity system? Intermittent renewable energy can produce electricity at both maximum capacity and at zero capacity in short time intervals. It, therefore, becomes important to model these variations in power output over a long-term horizon. Otherwise, the model may overestimate the production of energy from renewables and underestimate the variability of such technologies. This is achieved in Chapter 3 by showing that with representative days, we are able to accurately model an entire year with a reduced computational burden. Without this additional feature, an overestimation of intermittent renewable energy and underestimation of dispatchable generation is observed. markets occurs prior to the time in which the demand must be supplied. However, the long-term effect on the markets of poor forecasts has not been investigated. In Chapter 4 we investigate the long-term impact of poor short-term predictions. We find that poor short-term demand forecasts leads to increased investments in coal, gas and nuclear power, with a reduction in both onshore and offshore wind. 5. Is it possible to use an algorithm to set carbon policy? Setting carbon taxes has been proposed as a solution to reduce our reliance on fossil fuels. However, the impact of such carbon taxes are unknown, as are the optimal strategies from different perspectives. Such a problem can be solved using optimisation based techniques. Here, a solution to finding optimal strategies from the perspective of a benevolent government is presented in Chapter 5. We find that it is possible to find a variety of different carbon tax strategies to minimise both electricity price and carbon emissions, as long as a high carbon price is set (around £200). 6. Is it possible to limit the power of large generator companies? It is known that oligopolies have a negative effect on markets for consumers. However, what has been explored to a lesser degree, is the proportion of capacity that generation company must own before they have market power. | d602c796-019d-4603-b326-d7f62c6a33dd | 0 |
0e1a603a-fd41-402a-83c0-3dbc64c98f61 | https://ec.europa.eu/clima/eu-action/european-green-deal/delivering-european-green-deal/co2-emission-performance-standards-cars-and-vans_en | 2,019 | [
"Transport",
"Light-duty vehicles",
"Low-emissions mobility",
"Other low-carbon technologies and fuel switch",
"Renewables"
] | ec.europa.eu | Passenger cars and light commercial vehicles (vans) are respectively responsible for around 16% and 3% of total EU emissions of carbon dioxide (CO2), the main greenhouse gas driving climate change. To help reduce emissions, the EU has a Regulation that sets CO2 emission performance standards for new passenger cars and vans (Regulation (EU) 2019/631). With stricter CO2 emission targets in place since 2020, the average CO2 emissions from all new passenger cars registered in Europe fell by 27% between 2019 and 2022, while the average emissions from new vans dropped by 10%. The main driver of this decrease in emissions is the surge in zero-emission vehicles, which respectively amounted to 13.4% and 6% of the 2022 EU (and Norway and Iceland) new car and van fleet. On 19 April 2023, the European Parliament and the Council amended the Regulation to strengthen the CO2 emission performance standards for new passenger cars and vans, and bring them in line with the EU s ambition to reach climate neutrality by 2050. This amendment strengthened the emission targets applying from 2030 and set a 100% emission reduction target for both cars and vans from 2035 onwards. Benefits
The amended Regulation (EU) 2019/631 will:
Target levels
Below are the EU fleet-wide CO2 emission targets set in the Regulation:
2020 to 2024
These target levels refer to the NEDC emission test procedure. 2025 to 2034
The targets that will apply from 2025 onwards are based on the WLTP (Worldwide harmonized Light vehicles Test Procedure) and were set out in Commission Implementing Decision (EU) 2023/1623:
From 2035 onwards, the EU fleet-wide CO2 emission target for both cars and vans is 0 g CO2/km, corresponding to a 100% reduction. The annual specific emission targets of each manufacturer are based on these EU fleet-wide targets, taking into account the average mass of its registered new vehicles. Since 2021, those specific emission targets are based on the WLTP. The manufacturer targets for the years 2021-2024 are calculated in accordance with point 4 of Annex I (parts A and B) to Regulation (EU) 2019/631, using the values set out in Annex II to Commission Implementing Decision (EU) 2022/2087. The manufacturer targets from 2025 onwards are calculated in accordance with point 6 of Annex I (parts A and B) to Regulation (EU) 2019/631, using the values set out in Annex II to Commission Implementing Decision (EU) 2023/1623. On 1st of April 2025, the European Commission proposed a one-time flexibility measure allowing car and van manufacturers to meet 2025 2027 CO targets over a three-year average rather than annually. Part of the Industrial Action Plan for the automotive sector, this aims to support investment in the clean transition while preserving overall climate ambition. | 0d017378-52f1-4172-8482-01e1c3d0b103 | 0 |
0e1b62a8-b51d-4ec4-babd-68f5643e16ae | https://committees.parliament.uk/publications/3215/documents/29785/default/ | 2,020 | [
"government",
"register",
"companies",
"information",
"response"
] | parliament.uk | Minister for Climate Change and Corporate Department for Business, Energy & I am writing to you in your capacity as Chair of the Treasury Select Committee. I am pleased to inform you that the Government will publish its response to the consultation on Corporate Transparency and Register Reform today. In 2019, the Government consulted on a range of options to enhance the role of Companies House and increase the transparency of companies and other legal entities. The consultation received over 1300 responses and feedback was overwhelmingly positive. The reforms set out in the Government response support our ambition of making the UK the best place to work and grow a business and will ensure that our regulatory framework for setting up and reporting company information is fit for the 21st century. Register data informs many business-to-business transactions and underpins credit scores and lending decisions. The transformation of Companies House will see processes streamlined and the user experience improved. Users of the register, including sectors that fall under anti-money laundering regulations, will be able to take greater assurance from this The key policy proposals outlined in the Government response Identity introducing compulsory identity verification for all directors, People with Significant Control and those filing information on behalf of a company. Reforms to Companies House providing the Registrar of Companies with stronger powers to query, seek evidence for, amend or remove information and to share it with law enforcement partners when certain conditions are met. Protecting Personal simplifying and speeding up the process for removing personal information from the public register. Company the response proposes further consultation on how to introduce full digital tagging of accounts to ensure consistency, easier identification and comparability of information on the register. The Government’s vision is for a register built upon relevant and accurate information that supports the UK’s global reputation as a great place to work and grow a business, and as a leading exponent of corporate transparency. Companies House will play an even stronger role as an enabler of economic growth, whilst strengthening the UK’s ability to combat We plan further consultation on some detailed aspects of these plans later this year, and I will keep you informed as we do so. Following further consultation on certain detailed aspects of the reforms, the Government intends to bring forward legislation when I will be placing a copy of the Government response in the Libraries of the House, along Minister for Climate Change and Corporate Responsibility | 956b0344-8c79-4bed-b99f-cf43f8d6fe96 | 0 |
0e1b6e49-9410-42e5-9f88-e3838ded0ecf | http://arxiv.org/pdf/1707.04870v3 | 2,017 | [
"model",
"technology",
"policy",
"costs",
"prices"
] | arxiv.org | The consequences are profound. For example, without full knowledge by every economic agent of supply-and demand-price elasticities, there is no guarantee that prices will move to market-clearing rates, where resources would be used in the most efficient manner. The level of output is no longer determined by supply-side constraints (e.g. the number of factories), as the available resources will not necessarily be used (there may be too many factories for the demand). Alternatively, given fundamental uncertainty in the knowledge of the demand function by agents, agents may decide to build spare capacity in preparation for possible demand fluctuations. Without optimizing behavior, it is not possible to design optimal policy. Probst and Bassi [2] recognize the shortcomings of attempting to optimize public policy. The authors advocate an approach that is based on identifying policy that is found to be effective in the real world, rather than aiming for optimal outcomes. Learning-by-doing in policy-making reduces fundamental uncertainty. To be effective, the policies must first address the issue they are designed for, but ideally, also avoid negative consequences in other policy areas (for example, large economic costs or negative impacts on social cohesion). Due to the complex nature of contemporary economies and the heterogeneous nature of agents that interact within these economies [8], it is not sufficient to monetise these impacts and sum them together using a cost-benefit analysis approach; each must be considered in its own right. Importantly, policies must also be considered in the context of political and legal feasibility (ibid). Policy-making does not take place in a political and legal vacuum. The enactment of some policies (e.g. a top-down global carbon price or a standardized income tax rate across countries) may be highly unrealistic and even counterproductive. In some cases, such policies may fall foul of fundamental tenets of social organization enshrined in constitutions or treaties (e.g. human rights provisions) or, due to the limited political space left for their adoption, they may have to be legally structured in a manner that makes them less resilient (e.g. local content requirements in green industrial policy or the use of regulations under scattered statutes [31]). These findings suggest, for example, that policies based on estimates of the social cost of carbon could be misguided. The assessment approach adopted by the European Commission [3], which follows a method of multi-criteria analysis with extensive stakeholder interaction is much more viable. Under this approach, a limited set of feasible policy options are identified and these are tested across a range of key assessment indicators. This method is applied to all policy proposals, not just those relating to sustainability. This is likely a valid blueprint for successful evidence-based policy-making elsewhere in the world. Perhaps the key aspect that must be properly accounted for in sustainability transition scenarios, and in macroeconomics in general, is technological and productivity change. Economists here fall into two schools of thought: some consider that technology cannot be influenced by policy and therefore that the economy must adapt to existing 'exogenous' technological change (e.g. robotisation), whereas others think that technology is 'endogenous' and can be influenced by targeted policy. There is extensive empirical evidence that supports the latter position by showing how public policy plays a key role in promoting and guiding technological change [20,32]. The work of Grubb provides a review of the process of technological development and diffusion in the context of decarbonisation and low-carbon transition [32]. He finds that the rate and direction of technological change can undoubtedly be influenced by policy, and that different types of policy instruments are suitable for different stages of technology development and diffusion. Therefore, a modelling tool that aims to match reality as closely as possible must account for this finding. On the other hand, it is far from demonstrated empirically that the economy can indeed 'internalise' externalities using only pricing incentives, as suggested by standard welfare economics. Yet, this finding is not new. The work of Arthur showed, using simple models, that relatively minor changes to policy could lead to qualitatively different outcomes for technology diffusion in the long run due to 'social influence', 'path dependency' and technology 'lock-in' [33,34]. These processes describe how a single technology can come to dominate a particular sector, with highly non-linear outcomes. This is also a key finding in the study of the diffusion of innovations [35]. Policy-makers can steer users towards a particular technology but the rates of technology adoption are, again, highly complex, with considerable uncertainty about the outcomes. Modelling path-dependent systems requires simulation models, since the behaviour of such systems, by definition, depends on relationships between present and past conditions. Optimisation methodologies are not suitable to model path-dependence, since they do not make a clear connection between points in time. The E3ME-FTT-GENIE12 model is a simulation-based integrated assessment model that is fully descriptive, in which dynamical (time-dependent) human or natural behaviour is driven by empirically-determined dynamical relationships. At its core is the macroeconomic model E3ME, which represents aggregate human behaviour through a chosen set of econometric relationships that are regressed on the past 45 years of data and are projected 35 years into the future. The macroeconomics in the model determine total demand for manufactured products, services and energy carriers. Meanwhile, technology diffusion in the FTT family of technology modules determines changes in the environmental intensity of economic processes, including changes in amounts of energy required for transport, electricity generation and household heating. Since the development and diffusion of new technologies cannot be well modelled using time-series econometrics, cross-sectional datasets are used to parameterise choice models in FTT. Finally, greenhouse gas emissions are produced by the combustion of fuels and by other industrial processes, which interfere with the climate system. Natural non-renewable energy resources are modelled in detail with a dynamical depletion algorithm. And finally, to determine the climate impacts of chosen policies, E3ME-FTT global emissions are fed to the GENIE1 carbon cycleclimate system model of intermediate complexity. This enables, for instance, policy-makers to determine probabilistically whether or not climate targets are met. | 47c8f063-8804-4f59-9a25-04d0e255bba5 | 1 |
0e1ded4e-5d21-4cc4-8cba-bbb52f819d4f | https://www.legislation.gov.uk/ukpga/2008/27/part/1 | 2,008 | [
"s.i. 2023/118",
"net uk carbon account u.k.",
"greenhouse gas emissions",
"statutory instrument",
"next budgetary period"
] | legislation.gov.uk | (6) It must state the amount of the carbon budget for the period. That is the amount originally set, subject to any exercise of the powers conferred by section 17 (powers to carry amounts from one budgetary period to another) and any alteration of the budget under section 21. (7) Whether the carbon budget for a period has been met shall be determined by reference to the figures given in the statement laid before Parliament under this section in respect of that period. (8) If the carbon budget for the period has not been met, the statement must explain why it has not been met. (9) The statement required by this section must be laid before Parliament not later than 31st May in the second year following the end of the period to which it relates. (10) The Secretary of State must send a copy of the statement to the other national authorities. 19 Duty to report on proposals and policies for compensating for budget excess U.K. (1) As soon as is reasonably practicable after laying a statement before Parliament under section 18 in respect of a period for which the net UK carbon account exceeds the carbon budget, the Secretary of State must lay before Parliament a report setting out proposals and policies to compensate in future periods for the excess emissions. (2) So far as the report relates to proposals and policies of the Scottish Ministers, the Welsh Ministers or a Northern Ireland department, it must be prepared in consultation with that authority. (3) The Secretary of State must send a copy of the report to those authorities. 20 Final statement for 2050 U.K. (1) It is the duty of the Secretary of State to lay before Parliament in respect of the year 2050 a statement containing the following information. (2) In respect of each targeted greenhouse gas, it must state the amount for that year of UK emissions, UK removals and net UK emissions of that gas. That is the amount stated for that year in respect of that gas under section 16 (annual statement of UK emissions). (3) It must- (a) state the amount of carbon units that have been credited to or debited from the net UK carbon account for the year, and (b) give details of the number and type of those carbon units. (4) It must state the amount of the net UK carbon account for that year. (5) Whether the target in section 1 (the target for 2050) has been met shall be determined by reference to the figures given in the statement laid before Parliament under this section. (6) If the target has not been met, the statement must explain why it has not been met. (7) The statement required by this section must be laid before Parliament not later than 31st May 2052. (8) The Secretary of State must send a copy of the statement to the other national authorities. Alteration of budgets or budgetary periods U.K. 21 Alteration of carbon budgets U.K. (1) An order setting the carbon budget for a period may not be revoked after the date by which a budget for the period was required to be set. (2) An order setting the carbon budget for a period may be amended after the date by which a budget for the period was required to be set only if it appears to the Secretary of State that, since the budget was originally set (or previously altered), there have been significant changes affecting the basis on which the previous decision was made. (3) An order setting the carbon budget for a period may be amended after the period has begun only if it appears to the Secretary of State that there have been such changes since the period began. (4) An order setting the carbon budget for a period may not be amended after the period has ended. (5) An order revoking or amending an order setting a carbon budget is subject to affirmative resolution procedure. 22 Consultation on alteration of carbon budgets U.K. (1) Before laying before Parliament a draft of a statutory instrument containing an order under section 21 (alteration of carbon budgets), the Secretary of State must- (a) obtain, and take into account, the advice of the Committee on Climate Change, and (b) take into account any representations made by the other national authorities. (2) The Committee must, at the time it gives its advice to the Secretary of State, send a copy to the other national authorities. (3) As soon as is reasonably practicable after giving its advice to the Secretary of State, the Committee must publish that advice in such manner as it considers appropriate. (4) The Secretary of State may proceed to lay such a draft statutory instrument before Parliament without having ) by Energy Act 2013 (c. 32) , ss. 1(8)(a) , 156(3) Targeted greenhouse gases U.K. 24 Targeted greenhouse gases U.K. (1) In this Part a " targeted greenhouse gas " means- (a) carbon dioxide, (b) methane, (c) nitrous oxide, (d) hydrofluorocarbons, (e) perfluorocarbons, (f) , and (g) any other greenhouse gas designated as a targeted greenhouse gas by order made by the Secretary of State. (2) The order may make such consequential amendments of the provisions of this Act as appear to the Secretary of State to be necessary or expedient. (3) Before making an order under this section, the Secretary of State must- (a) consult the other national authorities, and (b) obtain, and take into account, the advice of the Committee on Climate Change. (4) As soon as is reasonably practicable after giving its advice to the Secretary of State, the Committee must publish that advice in such manner as it considers appropriate. (5) If the order makes provision different from that recommended by the Committee, the Secretary of State must publish a statement setting out the reasons for that decision. | 5f6e0789-61b6-4280-9f82-c3a8e25857fa | 3 |
0e24616c-8d37-4b5e-8f8f-2814efe5f9f3 | https://www.gov.uk//guidance/clean-heat-market-mechanism-who-it-applies-to-annual-tasks | 2,025 | [
"CHMM",
"heat pumps",
"fossil fuel boilers",
"UK market",
"regulations",
"Enviro Agency",
"Energy Act 2023",
"scheme participants",
"near-threshold suppliers",
"credit holders",
"carbon reduction",
"installation targets",
"reporting requirements",
"compliance",
"enforcement",
"penalties",
"credit transfer",
"scheme year",
"quarterly reporting",
"annual report",
"verification",
"registration",
"obligation",
"credit shortfall",
"accreditation",
"Clean Heat Market Mechanism",
"carbon emissions",
"heat pump subsidies",
"boiler sales",
"energy efficiency."
] | gov.uk | The CHMM supports the development of low-carbon electric heat pumps. It places an obligation on manufacturers supplying gas and oil boilers in the UK market. Manufacturers must meet targets for the installation of heat pumps in existing properties in proportion to their sales of fossil fuel boilers. Manufacturers can do this by supplying heat pumps themselves or by getting credits from other manufacturers. The scheme runs from 1 April 2025 until at least 2029 and applies to the whole of the UK. The Environment Agency is the scheme administrator. The Clean Heat Market Mechanism Regulations 2025 the CHMM Regulations give the obligations of the scheme. The Energy Act 2023, Part 4, Chapter 1 is the primary legislation underpinning the scheme. Who the scheme applies to
The CHMM applies to your business if you both
If the CHMM applies to you and you do not follow the regulations, you may face enforcement action. This could be a civil penalty or criminal prosecution. The CHMM has 3 categories of undertakings. How these apply to you will depend on the activities your business carries out and the extent of these activities. | ef2d4e60-f69e-4060-87e9-f0536933c8f4 | 0 |
0e313914-99d1-42bb-b0cb-a9201d5322c3 | https://cdn.climatepolicyradar.org/navigator/GBR/1900/united-kingdom-national-communication-nc-nc-8-biennial-reports-br-br-5_288d5f885869447df3e9910829b567a3.pdf | 2,022 | [
"climate",
"energy",
"support",
"emissions",
"carbon"
] | cdn.climatepolicyradar.org | The objectives of the proposed Northern Ireland Peatland Strategy 2021-2040 By 2030, degraded peatland habitats prioritised for restoration to favourable • By 2040, all high priority degraded peatlands ar • By 2040, that high priority degraded peatlands in Norther
218 8th National Communication • By 2040, all peatlands supporting semi-natural vegetation being managed for their peatland biodiversity and ecosystem function; – It is also proposed that the Farming for Carbon Measures be supported by existing complementary DAERA policy measures, notably in relation to woodland creation. The Forests for Our Future Programme, launched in 2020, has the objective of planting 9,000 ha of new woodland by 2030. The Small Woodland Grant Scheme provides grant aid for woodland planting area between 0.2 and 5.0 ha; with an establishment grant and annual premia. The Woodland Carbon Code (WCC) is the quality assurance standard for woodland creation projects in the UK, generating independently verified carbon storage data. Soil carbon – work to establish and refresh baseline data on carbon stored in agricultural soils and above ground biomass will be progressed through the Soil Testing and LiDAR measure. As the baseline levels of soil carbon and research supporting further soil carbon sequestration are validated to enable carbon accumulations to be credited in the GHG Inventory, DAERA will engage with stakeholders on the design of possible schemes to incentivise the farming of carbon as a business enterprise. The Soil Nutrient Health Scheme is a new initiative aimed at verifiably baselining soil nutrient levels and estimating farm carbon stocks, right across Northern Ireland (NI). The scheme will run from 2022 to 2025. Farmers will have all their fields soil sampled and analysed Results will be provided along with training, enabling farmers to match nutrient applications to crop need, thereby increasing efficiency, reducing excess nutrient run-off to watercourses and improving farm economic and environmental sustainability. In March 2016, the Northern Ireland Department for Regional Development launched Sustainable Water – A Long Term Water Strategy for Northern Ireland (2015-2040). This cross-Departmental strategy contains a long-term vision to manage flood risk and drainage in a sustainable manner, which will help to address the future risks from climate change. In March 2022, the Department for Infrastructure launched a consultation on Water, Flooding and Sustainable Drainage. Responses to the consultation will help to inform future policy on the introduction of more sustainable, environmentally friendly and green solutions to During the 2021/22-year Northern Ireland’s recycling performance remained at over 50% thereby meeting the Waste Strategy target for recycling. This was in spite of the recycling pressures experienced by Councils due to the Coronavirus (Covid-19) pandemic. A programme of work commenced to normalise recycling behaviours once again, and ensure good progress is made towards meeting future EU Circular Economy package During this period DAERA operated a continuous cycle of behaviour change campaigns aimed at preventing waste and moving our resources further up the waste hierarchy. In addition, we funded the setup of the Northern Ireland Resources Network which aims to grow the reuse and repair sector in NI by providing targeted support. The recently agreed Climate Change (Northern Ireland) Act requires that at least 70% of
Chapter 3 Policies and Measures 219 The primary method of achieving net zero is to take ambitious decarbonisation measures across society. However, we must also acknowledge that sectors such as industry, agriculture and aviation will be difficult to decarbonise completely by 2050. Greenhouse gas removals (GGR) are therefore essential to compensate for the residual emissions arising from the most difficult activities to reduce or eliminate from within polluting sectors. This approach is supported by the Climate Change Committee 104, the Energy Systems Catapult105, the National Infrastructure Commission and the National Grid ESO (the GB electricity GGR is the name given to a group of methods that actively remove greenhouse gases, 2, from the atmosphere, also commonly referred to as Carbon Dioxide Removal (CDR) methods and Negative Emission Technologies (NETs). The range of GGR approaches fall broadly into two Nature-based such as afforestation, and soil carbon sequestration. Engineering-based such as Direct Air Carbon Capture and Storage (DACCS), Bioenergy with Carbon Capture and Storage (BECCS), wood in construction, biochar, and The 2017 Clean Growth Strategy was the first time the UK government formally addressed the need to deploy GGR methods. Since then, we Committed up to £100 million funding to r esearch and develop nascent GGR; • Published a call for evidence on GGR in December 2020; and • Commissioned 4 studies to further our evidence base on the potential for GGR deployment in the UK and understanding of possible policy incentives. Set out our ambition for deployment of engineer ed GGRs in the Net Zero Strategy, including an ambition for 5MtCO2 per year by 2030. • Working in partnership with the devolved administrations, launched a call for evidence in the coming months exploring the r ole of the UK ETS as a potential long- term market for GGRs, as part of our consultation on the UK ETS. • Set the ambition of deploying at least 5 MtCO2/year of engineered removals by 2030, in line with CCC107 and National Infrastructure Commission assessments108. 104 CCC (2020), ‘The Sixth Carbon Greenhouse gas removals’, uploads/2020/12/Sector-summary-GHG-removals.pdf 105 Energy Systems Catapult (2020), ‘Innovating to Net UK Net Zero Report’, reports/innovating-to-net-zero/ 106 National Grid (2020), ‘Future Energy Scenarios’, 107 CCC (2021), 2021 Progress Report to Parliament’, Progress-in-reducing-emissions-2021-Report-to-Parliament.pdf 108 National Infrastructure Commission (2021), ‘Engineered greenhouse gas removals’, uploads/NIC-July-2021-Engineered-Greenhouse-Gas-Removals-UPDATED.pdf
220 8th National Communication • Deliver £100 million innovation funding for Dir ect Air Carbon Capture and Storage (DACCS) and other GGRs. The £100m is made up of £70m allocated and delivered from the BEIS Energy Innovation Programme and a further £31.5m spent through the UKRI Strategic Priorities Fund. | e6994b55-18ee-49c8-92db-2261135aea96 | 89 |
0e3ce635-774b-4acd-82b1-c72d2f873d10 | https://www.gov.uk/government/consultations/regulating-co2-emission-standards-for-new-cars-and-vans-after-transition/co2-emission-performance-standards-for-new-passenger-cars-and-light-commercial-vehicles#mainchanges | 2,019 | [
"vehicles",
"regulation",
"vehicle",
"manufacturers",
"emissions"
] | www.gov.uk | The specific target that each manufacturer is set is determined by formulae listed within annexes in the regulation. These formulae will be discussed in this document. EU
countries are required to record information about new vehicle registrations within their territories and report it to the European Environment Agency by 28 February each year. In 2018 (the most recent year for which data is available), according to provisional data from the
EU
, the
UK
had 2,355,962 new passenger vehicle registrations. This compares to a community-wide figure of 15,272,915 meaning that
UK
passenger car registrations account for roughly 15.43% of the
EU
’s new passenger car market. (EU28 plus Iceland)
. For vans, in 2018 (the most recent year for which data is available), according to provisional data from the
EU
, the
UK
had 334,502 new van registrations. This compares to a community-wide figure of 1,747,296 meaning that
UK
van registrations account for roughly 19.14% of the
EU
’s new van market. (EU28 plus Iceland)
. By 30 June each year, the European Commission publishes provisional data on the previous year’s
EU
-wide registrations for each manufacturer, who then have 3 months to report any errors to the commission. By 31 October, the European Commission publishes the final data and fines are issued to any manufacturer that exceeds their emissions target by way of an ‘excess emissions premium.’ This premium is €95 per gram of exceedance per vehicle registered by that manufacturer. The fines are collected by the commission and paid into the central
EU
fund. Manufacturers currently liaise directly with the European Commission on matters concerning the administration of regulations. This includes working with European Commission officials when:
finalising annual data
applying for flexibility mechanisms within the regulations, such as the pooling of registrations, applying for derogations from the
EU
-wide CO
2
target, or applying for eco-innovation credits
‘excess emissions premiums’ have been levied
In order to protect small business interests a number of derogations exist, providing different sized manufacturers with different types of carbon reduction target. Manufacturers registering between 10,000 and 300,000 vehicles per calendar year are not set a target in line with the formula, but must instead meet a set reduction. Currently this is a 25% reduction from their 2007 average emissions until 2019, rising to a 45% reduction from 2020. If 2007 data does not exist, then a manufacturer must meet a reduction based on the average reduction of a similar manufacturer over the same period. This derogation option exists until the end of 2028. Manufacturers registering 1,000-9,999 vehicles per calendar year must agree a reduction target with the commission. Both parties should take into account a number of criteria, including the type of vehicle being sold, the type of market that the vehicle is being marketed towards, and the economic ability of the manufacturer to employ reduction technologies. Any manufacturer registering fewer than 1,000 vehicles in a calendar year is out of scope of the legislation. As multiple manufacturers may fall under the same overall umbrella group, manufacturers may also ‘pool’ resources and combine their registrations. Upon agreement with all parties involved, manufacturers may submit a request to the commission to pool their registrations. If accepted, for the purposes of these regulations the ‘pool’ will be considered as one manufacturer, and the pool will receive one CO
2
target based on the average weight of all of the applicable vehicles under all included manufacturers. Manufacturers (or pools) may also apply for credits for any eco-innovations that would result in a carbon reduction but which would not be captured through traditional CO
2
testing for example energy efficient LED lightbulbs. Upon application to the commission (the application itself is the subject of a separate regulation) the Commission will grant emission credits up to a maximum of 7g/km per year. ‘Super-credits’ also apply for the registration of ultra-low emission vehicles (ULEVs) through to 2022. In 2020, any vehicle emitting less than 50g CO
2
/km will be counted as 2 vehicles; 1.67 vehicles in 2021; 1.33 vehicles in 2022 before the end of super-credits in 2023. Following the
UK
’s exit from the European Union on 31 January 2020 the above provisions of
EU
2019/631 continue to apply during the transition period. However, after 31 December 2020, subject to the terms of the future trade agreement between the
UK
and the
EU
, new vehicle registrations in the
UK
will cease to fall under the scope of this regulation. The Department for Transport (
DfT
) is therefore laying a
SI
to correct for ‘deficiencies/inoperabilities’ within a revised text of the regulation. This includes, for example, formulae that set specific CO
2
targets in order to account for
UK
only regulations and derogation thresholds to account for the size of the
UK
market rather than the
EU
. Full
. Irrespective of the scenario that will apply between the
UK
and
EU
at the end of the transition period, the Northern Ireland Protocol will continue to apply from 2021 onwards. It is for the elected institutions in Northern Ireland to decide what happens to the Protocol alignment provisions in a consent vote that can take place every four years, with the first vote taking place in 2024. Regulation 2019/631 is listed in Annex II to the Northern Ireland Protocol. This therefore means that
EU
Regulation 2019/631 will continue to have effect in Northern Ireland from 1 January 2021 onwards. For clarity, this therefore means that newly registered vehicles in Northern Ireland from 1 January 2021 will continue to be the subject of the
EU
regulation. The retained version of the regulation, and the subject of this consultation, will apply in Great Britain only. Further information can be found in the Northern Ireland sections of this document. | 8832b0c2-d44a-4894-8252-51deda84c6e2 | 1 |
0e3e1b02-082e-46f1-9f44-6b8c157c270f | https://cdn.climatepolicyradar.org/navigator/GBR/2023/2023-green-finance-strategy_0895a38af9ea8d89570e1f7f4d06113a.pdf | 2,023 | [
"Finance",
"investment",
"finance",
"financial",
"green",
"climate"
] | cdn.climatepolicyradar.org | Ahead of this review, we will begin to engage with stakeholders and seek evidence. Depending on the evidence we receive and the outcome of the review, further action to ensure the effectiveness of the stewardship regulatory framework may be necessary. 101. The UK government recognises the key role of pension scheme trustees especially, as there are over £3 trillion[footnote 62] in UK pension investments, but also that climate change impacts, and actions that governments globally take to tackle it, present a financial risk/opportunity for pensions. The regulations we’ve already introduced require relevant trustees to measure and report on their investment portfolio’s alignment with the Paris Agreement, together with existing climate governance and disclosure requirements. This will help inform trustees’ investment decisions, 102. The Law Commission’s 2014 report suggested that fiduciary duty means that non-financial factors can be taken into account if the 2-stage test trustees should have good reason to think the scheme members would the decision should not involve a risk of significant financial detriment to 103. We recognise trustees would like to know what latitude they have and in DWP’s Stewardship Guidance, introduced in 2022, the UK government stated that trustees may want to consider both financial and non-financial matters in their stewardship activities. We acknowledge decisions around investing and systemic risks are complicated and that trustees would like
further information and clarity on their fiduciary duty in the context of the transition to net zero. To address this, we are taking the following a. DWP will examine the extent to which their Guidance is being b. This will be complemented by a working group of the Financial Markets and Law Committee (FMLC) where participants, including DWP, will consider the issues around fiduciary duty and what further action is c. We will be holding a series of roundtables later this year to engage with interested stakeholders on how we can continue to clarify fiduciary 104. UK regulators have an important role to play, including as active members of standard setting organisations and partnerships, to support the financial system shift necessary to achieve climate and sustainability goals. Key regulatory bodies we consider in this space are the Bank of England, the Environment Agency, the Financial Conduct Authority, the Financial Reporting Council and The Pensions Regulator (‘the regulators’). 105. Box 12 below sets out the commitment made by regulators in the context of this Strategy. The regulators will also share insights and seek opportunities more widely, supporting the priorities of the Green Finance Strategy and helping to drive clear and consistent disclosure and reporting regulators’ remit, current work and future actions related to climate and Box 12: Commitment from green finance regulators Green finance regulators will identify shared priorities for environmental and financial regulators and explore options for closer working ties to deliver shared objectives, establishing a working group within the existing Sustainable Finance Regulators group to explore opportunities. Areas to be considered by the group may include, but not be limited to, a review of regulatory priorities on environmental finance and how support can be leveraged across the group, intelligence gathering on greenwashing and other ESG risks bringing together financial and real- economy regulators, and coordination of collective views and responses to international consultations. The group will share insights and seek opportunities more widely, supporting the priorities of the Green Finance
Strategy and helping to drive clear and consistent disclosure and reporting of financially material non-financial risks. The Bank of England’s mission is to promote the good of the people of the UK by maintaining monetary and financial stability. Climate change is relevant to the Bank’s mission as the physical effects of climate change and the transition to net-zero create financial risks and economic consequences. These risks and consequences can affect the safety and soundness of the firms that the Bank regulates, the stability of the wider financial system, and the economic outlook. Non-exhaustive examples of recent activity and future Supported the UK government, regulators, and international authorities to develop a transition finance infrastructure and the broader green finance strategy, including a direct role in the Transition Set supervisory expectations for banks and insurers on the management of climate-related financial risks. These expectations became part of core supervisory processes in 2022. Set up the Climate Financial Risk Forum (CFRF) with the FCA to build capacity and share best practice to help the financial sector address climate-related financial risks. Advanced international thinking on the relationship between climate risks and regulatory capital, setting out its thinking in a climate change adaptation report (CCAR)[footnote 63], and a subsequent report on climate-related risks and regulatory capital frameworks[footnote 64]. Delivered a bottom-up climate scenario exercise (the Climate Biennial Exploratory Scenario (CBES)) the results[footnote 65] explored risks in banks, insurers and the UK system. Undertook domestic and international work to advance the understanding of financial stability risks from climate change, including tools to monitor risks and the use of transition plans and Explored possible macroeconomic implications of climate Taken action to understand its own climate exposures – as set out in its climate disclosure report[footnote 67] and seen in its commitment to achieve net zero across its operations. Engaged with external stakeholders (including Defra) to further explore the degree that nature loss and degradation can give rise to Been an active member of international climate groups focusing on the financial risks from climate change and an orderly transition to net The Environment Agency is the largest environmental regulator in the UK and plays a critical role in ensuring environmental standards are met and maintained. The EA works with businesses, communities and others to reduce, mitigate and adapt to the impacts of climate change, and to manage their use of resources to protect and improve water, air, land and biodiversity for all, and encourage sustainable development. | 6eb9d039-1897-4987-bfa9-ac3e1bf22f61 | 21 |
0e41f234-513f-47ae-8416-baa73a7230ef | https://cdn.climatepolicyradar.org/navigator/GBR/1900/uk-net-zero-strategy-build-back-greener_807a7bbb4df0326606e1552618bffc6f.pdf | 2,021 | [
"zero",
"carbon",
"emissions",
"energy",
"government"
] | cdn.climatepolicyradar.org | There has already been significant work by the Bank of England and the Financial The Bank’s approach to climate change is to play a leading role, through its policies and operations, in ensuring the financial system, the macroeconomy, and the Bank of England itself, are resilient to the risks from climate change and supportive of the transition to a Recent actions to deliver this • In April 2019, the Bank published a comprehensive set of supervisory expectations for how banks and insurers should enhance their approaches to managing the financial risks from climate change. This was followed up in July 2020 with a Dear CEO letter, which included additional guidance and set a deadline for firms to embed fully these expectations by • In June 2021 the Bank launched its Climate Biennial Exploratory Scenario (CBES) exercise to assess the resilience of individual banks, insurers, and the wider UK financial system to three different climate scenarios. These scenarios are based on those published by the international central banks and supervisors Network for Greening the Financial System (NGFS), of which the Bank is a founding member and where it chairs the workstream developing the NGFS • In November 2020, the UK joint regulator and government TCFD Taskforce, of which the Bank is a member, published an interim report and roadmap for mandatory TCFD-aligned disclosure requirements • The Bank has also sought to lead by example and in 2021 became the first central bank to publish a climate-related financial disclosure which included analysis of financial asset portfolios held for monetary policy purposes. The Bank also committed to reduce the emissions from its physical operations to net-zero by The FCA’s work on climate change and sustainable finance aims to make sure market participants can manage the risks, impacts and opportunities from moving to a more sustainable economy and can capture opportunities from the net zero transition. Key • Introducing a TCFD-aligned Listing Rule for premium-listed commercial companies, and consulting on new proposals to extend the application of the rule to issuers of standard listed equity shares, and to implement new disclosure rules for asset managers, life insurers, and FCA-regulated pension providers with a focus on the information needs of • Co-chairing work on climate-related and sustainability disclosures at the International Organisation of Securities
• Issuing a supervisory letter to the chairs of Authorised Fund Managers, including a set of guiding principles to help clarify the FCA’s expectations for the design, delivery and disclosure of retail responsible and sustainable funds – both as applications are submitted for authorisation and on • Launching a comprehensive innovation work programme on sustainability, including the announcement that the next cohort of the Digital Sandbox Pilot will focus on sustainability and climate change; the FCA has begun work with the City of London Corporation and industry to support the development of solutions to ESG data and disclosures issues via a digital testing environment, and is aiming for this environment to go live • Alongside the other financial regulators, publishing an inaugural Climate Adaptation Report (CAR) setting out the actions the FCA and financial services industry are taking to adapt to the challenges of climate change; the CAR will include a chapter on net zero which will explore net zero commitments, targets, tools Net Zero Build Back Greener
Creating the skilled workforce to deliver net zero and putting UK supply chains at the forefront of global markets • Publish sector and supply chain development plans for key low carbon sectors and work with business to encourage investment in green skills and industries in the UK. • Publish a UK Critical Minerals strategy, setting out our approach to securing technology-critical minerals and metals. • Support the development of a skilled, competitive supply chain for key green • Reform the skills system so that training providers, employers and learners are incentivised and equipped to play their part in delivering the transition to net zero – including by legislating for skills required for jobs that support action on climate change and other environmental goals to be considered in the development of new local skills improvement plans. • Deliver a Lifetime Skills Guarantee and grow key post-16 training programmes (such as apprenticeships, Skills Bootcamps and T levels) in line with the needs of employers in the green economy, helping individuals get the training they need for a job in the green economy, either at the start of their careers or when retraining or upskilling once already in the workforce. • Introduce a sustainability and climate change strategy for education and children’s services which will include a focus on equipping children and young people with the knowledge and skills they need to contribute to the green economy. 1. The national and global shift towards net zero provides a once in a generation opportunity to level up the country, create new green jobs, and put the UK at the forefront of growing global markets in green technologies. Delivering on this promise, whilst meeting our ambitious climate and environmental targets, will be in a large part dependent on having a sufficiently skilled workforce and robust, competitive supply chains in the UK. 2. Recent developments have thrown into sharp relief the inherent vulnerabilities associated with complex global supply chains and shocks to the global economic system. The transition to net zero will change the nature of the UK’s critical supply chains. Our aim is to help ensure that supply chains critical for the transition to net zero are secure, ensuring that we have access to the materials, minerals, and chemicals that our growing green economy will need. Our approach is that there is no “one size fits all” model for building resilience in individual supply often a combination of levers may be the best solution 3. | 23d06bea-fd9c-4b53-9b9a-c35258d49ad9 | 69 |
0e490b67-21a9-4141-ab89-fb581a65127e | http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32006L0040 | 2,006 | [
"Transport",
"Non-energy use"
] | eur-lex.europa.eu | In accordance with the principle of proportionality as set out in that Article, this Directive does not go beyond what is necessary in order to achieve those objectives. (11)
In accordance with paragraph 34 of the Interinstitutional Agreement on better law-making (7), Member States are encouraged to draw up, for themselves and in the interests of the Community, their own tables which will, as far as possible, illustrate the correlation between this Directive and the transposition measures, and to make them public,
HAVE ADOPTED THIS DIRECTIVE:
Article 1
Subject matter
This Directive lays down the requirements for the EC type-approval or national type-approval of vehicles as regards emissions from, and the safe functioning of, air-conditioning systems fitted to vehicles. It also lays down provisions on retrofitting and refilling of such systems. Article 2
Scope
The Directive shall apply to motor vehicles of categories M1 and N1 as defined in Annex II of Directive 70/156/EEC. For the purpose of this Directive, vehicles of category N1 are limited to those of class I as described in the first table in point 5.3.1.4 of Annex I to Council Directive 70/220/EEC of 20 March 1970 on the approximation of the laws of the Member States on measures to be taken against air pollution by emissions from motor vehicles (8), as inserted by Directive 98/69/EC of the European Parliament and of the Council (9). Article 3
Definitions
For the purposes of this Directive the following definitions shall apply:
1. vehicle means any motor vehicle falling within the scope of this Directive;
2. vehicle type means a type as defined in section B of Annex II of Directive 70/156/EEC;
3. air-conditioning system means any system whose main purpose is to decrease the air temperature and humidity of the passenger compartment of a vehicle;
4. dual evaporator system means a system where one evaporator is mounted in the engine compartment and the other in a different compartment of the vehicle; all other systems shall be considered single evaporator systems ;
5. fluorinated greenhouse gases means hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and sulphur hexafluoride (SF6) as referred to in Annex A of the Kyoto Protocol and preparations containing these substances, but excludes substances controlled under Regulation (EC) No 2037/2000 of the European Parliament and of the Council of 29 June 2000 on substances that deplete the ozone layer (10);
6. hydrofluorocarbon means an organic compound consisting of carbon, hydrogen and fluorine, and where no more than six carbon atoms are contained in the molecule;
7. perfluorocarbon means an organic compound consisting of carbon and fluorine only, and where no more than six carbon atoms are contained in the molecule;
8. global warming potential means the climatic warming potential of a fluorinated greenhouse gas relative to that of carbon dioxide. The global warming potential (GWP) is calculated in terms of the 100 year warming potential of one kilogram of a gas relative to one kilogram of CO2. | d8fef834-b7ca-4a3a-a38f-4da679dc0fb3 | 2 |
0e4c02d0-da52-4536-ab31-f8b5d5de399a | http://arxiv.org/pdf/2409.17378v1 | 2,024 | [
"climate",
"change",
"activism",
"treatment",
"information"
] | arxiv.org | Climate change has irreversible negative effects on all sectors of life, from biodiversity to infrastructure to health to individual livelihoods. More than 75% of individuals find climate change to be a major threat to their society (Poushter et al., 2022). For United States voters, climate change is a top ten issue when voting for a candidate (Leiserowitz et al., 2021). Addressing climate change is a collective action problem. Climate activism has been shown to be a solution to this problem through changing and strengthening political and public will on climate change action (Swim et al., 2019). Yet, how much people value the effect of climate activism is highly dependent on their beliefs, concerns, and literacy on climate change and activism. There is a lack of climate literacy among the United States population, including among university students (Bedford, 2015). Low climate literacy can be attributed to a lack of comprehensive environmental education on the issue of anthropogenic climate change, especially the lack of information on the sociological implications of and political, legal, and economic solutions for climate change (Stevenson, 2007). However, even among those who do have a more comprehensive understanding of climate change and the importance of climate activism, direct action efforts to mitigate the effects of climate change are still limited. While climate activism can range from actions such as contacting a representative and attending a protest to donating money and volunteering for an activity that is focused on combatting climate change, only 24% of United States adults reported performing any of these actions in the last year as of 2021 (Tyson et al., 2021). Not all climate activism efforts are viewed equally either. Whether it be notions on the effect of an individual participating in a collective action movement (Kutlaca et al., 2020) or perceptions of different modes of activism, many people may have strong feelings for or against certain kinds of climate activism, especially the very traditional forms of protest like marches or civil disobedience (Bugden, 2020). In fact, among all United States adults who reported making efforts to support climate action, sending donations was the most common method of support while protesting was the least common method of support for climate action (Tyson et al., 2021). To determine people's propensity towards climate activism, specifically, their donation habits, we use a modified dictator game (generally following Shreedhar and Mourato (2019)). In our experiment, participants are evaluated on their climate literacy and general climate attitudes before they are randomly assigned to one of four informational infographic treatments. The treatments are either an infographic, informational treatment with neutral climate change information (1) with or (2) without additional information on a climate activism organization and (3) with or (4) without an image of protest. After the treatment, participants' climate attitudes are reassessed, and they participate in a modified dictator game in which they choose whether to donate to a climate activism organization from an allocation of $30. Based on this, we assess how treatments change participants' propensity to donate to climate activism groups and examine how these materials affect their climate change attitudes. From our experiment, we find that the average donation is around half of the endowment ($14.28). This exceeds regular dictator game donations two-fold and is at the upper-bound for charitable giving experiments. Moreover, we find that people were twice as likely to donate their entire endowment than to keep the entire endowment; this is the opposite of what is found in other dictator games (Engel, 2011) and charitable giving experiments (Shreedhar & Mourato, 2019). Additionally, we find that information treatments have a significant negative effect on donation amount, while identifying with a gender other than cisgender male, what we refer to as a non-male person for simplicity, and having climate concern have a significant positive effect. Finally, we discover that the protest only treatment had a significant positive effect on climate concern. The driving factor behind the overall high donation results is the equally high concern for the issue of climate change, motivating a positive valuation of climate activism as a problem-solving tool by our participants. We also believe that our negative information treatment effect may be a result of the free-riding effect as seen amongst political campaign supporters who exerted less effort upon learning that peer supporters planned to exert more effort than expected for a campaign in Hager et al. (2020). Upon learning that a large, organized group is combating climate change, people become less concerned about the need to contribute to the cause of climate activism. Yet, conversely, images of grass-root protest dampen this effect by increasing climate concern once seeing people perform activism. There are numerous studies on the willingness to pay for climate change adaptation measures. Yet, there is little information on social valuation measures beyond willingness to pay and how much people will fund the sociopolitical mechanisms needed to bring about these often-technical solutions, such as through the mechanism of climate activism. Moreover, there is little information on how these funding preferences for climate activism may be affected by knowledge and opinions on climate change, climate activism, and protests in climate activism. In this study, we investigate a new aspect of funding sociopolitical climate change solutions by eliciting donation preferences for climate activism rather than willingness to pay (WTP) for climate adaptation (Mayer & Smith, 2018;O'Garra & Mourato, 2015;Vilela et al., 2022). We examine donation preferences to assess We begin with our motivation and a review of previous literature. We first delve into different non-market valuation methods and experiments followed by a discussion of the value of collective action and activism as well as people's perception of forms of activism. We then move on to our experimental method where we discuss how we determine the differences in climate knowledge, climate attitudes, and individual donation behavior using a climate literacy test, pre-treatment and post-treatment attitudes tests, and a dictator game. | aeaac3d9-de1d-4d03-acc5-21808f2be1ea | 0 |
0e4edbee-059b-4d79-ab29-cbacc9f9c70f | https://committees.parliament.uk/publications/41129/documents/200843/default/ | 2,023 | [
"defence",
"climate",
"emissions",
"change",
"ministry"
] | parliament.uk | The Arctic will also be used increasingly as a route for international trade, but Russia has declared its intent to treat the region as its own internal sea, potentially restricting access. There is also concern that the current ban on exploiting the resources of the Antarctic could be under threat, driving future competition and potential conflict. Lieutenant-General Nugee (retd) Antarctic and melting at a speed that is being accelerated by hot water coming in under the glaciers and undermining the ice shelfs. Antarctica is, if you like, governed by the 1960s treaty,25 which does not allow any military capability on the Antarctic. There is some evidence that some countries are showing some interest in the raw minerals in Antarctica.26 21. In the Arctic, between the frozen winter seas and the open water in the summer there is a period when the ice is not thick enough to require an icebreaker but is too thick for the very thin hulls of warships. Lieutenant-General Nugee (retd) told us that he understood the Russians, Chinese and the Canadians were hardening some of their ships’ hulls to operate in this ‘disruptive ice’.27 22. Retrofitting existing ships to operate in disruptive ice would be expensive, and it is probably too late to fit strengthened bows to the much-delayed—but yet to be built— Batch 2, Type 26 City-class frigates. Design of the future Type 83 destroyers—planned replacements in the late 2030s for the existing Type 45s—is still at a very early stage and it would be possible to scope in that requirement. The challenge will be to ensure the UK retains a fleet that is truly global—able to operate in the polar regions but also in the increasingly hot waters nearer the Equator—without a repeat of the propulsion difficulties that have dogged the Type 45 fleet to date.28 22 International Energy Agency The Role of Critical Minerals in Clean Energy Transitions May 2021. 23 The United Nations Economic Commission for Europe (UNECE) Future-proofing Supply of Critical Minerals for 24 In fact, 87% of the Antarctic glaciers are receding. Glaciers and climate change - Antarctic Glaciers accessed 25 The treaty was signed in 1959. 26 Oral Defence & Climate Change, HC 179, Tuesday 22 November 2022, Q50. 27 Oral Defence & Climate Change, HC 179, Tuesday 22 November 2022, Q49. 28 Navy Lookout The Power Improvement Project for the Royal Navy’s Type 45 destroyers 10 October 2022. 23. Closer cooperation with regional allies and partners will also be beneficial. The UK’s leadership of the Joint Expeditionary Force (JEF) provides an excellent example in the so- called ‘High North’ region.29 The JEF might have wider applicability for security outside of the High North, or other partner groupings might be appropriate to enhance operational effectiveness across other demanding climatic conditions, such as in Africa. 24. The increasing exploitation of the Arctic for international trade and exploration for critical minerals gives greater importance to the role of the Joint Expeditionary Force (JEF) as a security alliance in the ‘High North’. The Ministry of Defence should assess how the JEF might need to be adapted in the face of climate-change induced developments in the Arctic and beyond. Future low-carbon technologies for military advantage 25. Over the next decade or so, innovation largely from the commercial sector is expected to make available in greater quantities other low carbon technologies, such as modular nuclear reactors and electric and hybrid-drive vehicles. Defence could exploit these technologies, particularly on deployed operations and within overseas bases. For example, it has been estimated that between 2,000 and 3,000 US personnel were killed or injured protecting resupply missions in Iraq and Afghanistan between 2003–200730— convoys that could be dramatically reduced if deployed forces were able to use a range of solar, electric-drive and micro-nuclear technologies to generate and/or reduce their own hydrocarbon-fuelled power requirements. 26. The view of the Ministry of Defence to these technologies is one of ‘fast follower’ — leaving industry to innovate and then adopting the best technical solutions as they mature.31 The Ministry of Defence told us it is intending to electrify its 15,000 strong ‘white fleet’ (non-military vehicles) by 2027,32and the RAF is looking at alternative fuels for its ‘yellow fleet’ refuelling vehicles.33 By 2025, the Army expects to complete hybrid electric drive experiments with technology retrofitted to a Support Vehicle truck, Foxhound and Jackal vehicles following a £9 million investment.34 27. These technologies also offer military benefits, including silent surveillance without a noisy engine running, a degree of silent mobility, and increased on-board power for more complex electrical systems and to support dismounted operations. And future plans involve robotics, artificial intelligence and hybrid-power technology as part of an acquisition process dubbed Mercury.35 28. However, it will take a long time for the Armed Forces to fully re-quip with adapted technology. Over the next few years, the Army is expecting to receive more than 1,000 Challenger 3, Ajax and Boxer armoured vehicles, all equipped with conventional diesel engines — many of which are still expected to be in service after the 2050 net zero target, along with some equipment already in service such as the aircraft carriers. Rear Admiral 29 The JEF consists Denmark; Estonia; Finland; Iceland; Lithuania; Latvia; Norway; Sweden; The Netherlands, and the United Kingdom. Ready to What is the JEF? - Strategic Command 11 May 2021. 30 Oral Defence & Climate Change, HC 179, Tuesday 22 November 2022, Q31. 31 Oral Defence & Climate Change, HC 179, Tuesday 21 March 2023, Q193. 32 Oral Defence & Climate Change, HC 179, Tuesday 21 March 2023, Q175. 33 Oral Defence & Climate Change, HC 179, Tuesday 22 November 2022, Q38. 34 Royal United Services Institute, Greening The British Army’s Bet on Electrification 22 March 2022. 35 Defense News, UK’s future force to lean heavily into robotics, AI and hybrid power 16 September 2021. | 0fc9c68c-8883-4acd-af80-4635600b0f6f | 3 |
0e55a8ce-794b-4cef-bc1a-0c025c095242 | http://arxiv.org/pdf/2505.05508v1 | 2,025 | [
"agricultural",
"competitiveness",
"climate",
"change",
"gaci"
] | arxiv.org | Consequently, this study incorporates climate change into the index utilized to evaluate the competitiveness of agricultural markets. This approach facilitates the formulation of climate-friendly policies that are conducive to the growth and sustainability of the industry by leveraging the full potential of agricultural markets. The Global Agricultural Competitiveness Index (GACI) is a new study that measures the competitive position of countries in the agricultural sector while accounting for climate change factors. The GACI incorporates twelve pillars from the Global Competitiveness Index (GCI) and introduces two new pillars on agriculture and climate change. On the basis of their GACI values, 78 countries were analyzed and ranked. The top performers in the GACI are the United States, Switzerland, Sweden, Germany, the Netherlands, the United Kingdom, Denmark, Norway, France, and Austria. In contrast, the leading developing countries on the GACI are China, the Russian Federation, Chile, Poland, Malaysia, Romania, Bulgaria, Kazakhstan, Saudi Arabia, and Thailand. The study reveals that only six developed countries experienced a decline of over 4 points in their competitiveness scores, whereas the scores for other developed countries decreased by 4 points or less. On the other hand, 37 developing countries faced a decline of over 4 points in their competitiveness scores. These findings indicate that agricultural vulnerability and climate change impacts are greater in the developing world than in developed countries. workshops that teach conservation tillage or integrated pest management will empower farmers to increase both resilience and competitiveness. ⮚ Sustainability Metrics: It will lay foundations for integrating sustainability metrics into a competitiveness framework (GACI), that reflect climate change impacts. This can involve tracking carbon sequestration, biodiversity, and soil health as part of the competitiveness assessment, encouraging countries to adopt practices that enhance both productivity and environmental health. ⮚ A study can be conducted on specific crops and regions to analyze the agricultural commodities in which countries/regions have specialization and a larger global market share. ⮚ The twelve pillars of the global competitiveness index (GCI) can be redesigned to focus solely on agriculture-specific measures. However, the current study could not do so because of a lack of data and the high costs associated with data collection. Moreover, the experts surveyed in the study reported that the current pillars are equally applicable to the agricultural sector. The Global Competitiveness Index (GCI) is an already developed index with its scores and rankings already calculated. However, for the purpose of the present study, those countries were picked for which the GACI scores are calculated. The selected countries are then re ranked within the 78 countries on the basis of their GCI scores and then compared with the GACI scores. * Shows significance at p<.05
Source: Author's reranking of global competitiveness index (GCI) scores within the selected countries. | 7df694a5-2669-4d3d-ab09-8ee9c3f56e23 | 5 |
0e5f64bd-c4a2-450d-9cc5-148e04831f83 | https://cdn.climatepolicyradar.org/navigator/GBR/1900/the-clean-growth-strategy_af15f03cfcd3b9529c696ef513762900.pdf | 2,018 | [
"energy",
"carbon",
"emissions",
"government",
"million"
] | cdn.climatepolicyradar.org | Out to 2030, this will require industry to make progress in switching from fossil fuel use to low carbon fuels such as sustainable biomass, in line with broader Government priorities on delivering clean air, and clean electricity. Beyond 2030, this switching will need to substantially increase in scale and be coupled with the deployment of new technologies, for example carbon capture, usage and storage (CCUS). Over the course of this Parliament, we will therefore also develop a framework to support the decarbonisation of heavy industry. Overall, one possible pathway to 2032 could involve emissions from business and industry falling by around 30 per cent on today’s levels to as low as 83 Mt by 2032. Emissions from the business and industry sectors have decreased by 47% since 1990 account the clean growth pathway, 1990-2050
The UK energy efficiency sector already turns over £20.3 billion, employs 144,000 people and sells exports worth over £1 billion 166. We know the potential for further energy efficiency in businesses and industry is significant - up to £6 billion could be saved by 2030 through investment in cost-effective energy efficiency technologies in buildings and industrial processes. As well as reducing bills across the UK, building the energy efficiency market would place UK businesses and industry in a prime position to further increase the export of knowledge, skills and products to other countries. It would also involve greater flows of external finance, a sector where the UK is already a market leader. For example, the UK energy services market is estimated to have a potential annual size of €1 billion per year and would require significantly more third party finance than we see currently167. 165 BIS, DECC (2017) Industrial Decarbonisation and Energy Efficiency Roadmaps to 2050 and-energy-efficiency-roadmaps-to-2050 ‘Fuel switching’ includes a small amount of bioenergy used for feedstock 166 ONS (2017) Low Carbon and Renewable Energy Economy Survey, final 2015 167 EC (2014) The European ESCO Market Report 2013 european-esco-market-report-2013 2050 Roadmaps Cross-Sector Summary report (2015). This illustrates the technical potential for emissions savings in the report’s ‘MAX TECH’ pathway. Carbon reduction opportunity (Mt)
Department for Business, Energy and Industrial Strategy Unlocking Business Energy Efficiency 1. The Government will develop a package of measures to support businesses to improve how productively they use energy and will consult on this in 2018, with the aim of improving energy efficiency by at least 20 2. The Government will ensure incentives for investment in energy efficiency are regularly reviewed, for instance the list of products that qualify for enhanced capital allowances 3. We will continue with plans to close the CRC Energy Efficiency Scheme following the 2018-19 compliance year. We will drive energy efficiency by implementing the previously announced increase to the main rates of the Climate Change Levy 4. We will undertake an evaluation of the Climate Change Agreements to inform any 5. The Government will build on existing schemes such as the Energy Savings Opportunity Scheme (ESOS), undertaking a comprehensive assessment of its effectiveness and consider any future 6. The Government will work with stakeholders to improve the market for energy services, building confidence across commercial and 7. Alongside this Strategy, we are consulting on a new and streamlined energy and carbon reporting framework to replace some existing schemes, such as the reporting element of the CRC Energy Efficiency Scheme, and align with mandatory annual greenhouse gas reporting by UK quoted companies. This will improve the way in which businesses report their energy use, and provide businesses with the information needed to identify how they can reduce 8. The Government will establish an Industrial Energy Efficiency scheme to help large companies install measures to cut their 9. We are consulting on the design of a new industrial heat recovery programme. This £18 million fund will encourage investment by manufacturers to recover and reuse heat from industrial processes that would 10. The Government will explore with stakeholders how we can improve the provision of information and advice to SMEs to encourage the uptake of energy efficiency
More Energy Efficient Commercial and 11. The Government has commissioned an independent review of Building Regulations and fire safety, being led by Dame Judith Hackitt. The review will report in spring 2018. Subject to the conclusions of that review, the Government intends to consult on making improvements to Building Regulations requirements for new and existing commercial buildings where there are cost- effective and affordable opportunities, and it is safe and practical to do so. This will look to promote low carbon and higher energy efficiency heating, ventilation and air conditioning systems in new commercial 12. 42 per cent of business buildings’ energy use is in the private rented sector 168. We will consult in 2018 on how best to improve the energy performance of these buildings through tighter minimum energy standards. 13. The Government will explore how voluntary building standards can support future improvements in business building 14. As we work to understand different options for the long term decarbonisation of heat, we will need to tackle the challenge of those business properties off the gas grid, particularly those heated by oil boilers and facing volatile costs. Beyond support through the Renewable Heat Incentive (RHI), our ambition is to phase out the installation of high carbon fossil fuel heating in new and existing business buildings off the gas grid during the 2020s, starting with new buildings as these lend themselves more readily to other forms of low carbon heating. We will involve businesses and industry in developing our new policy, in line with broader Government priorities on delivering Anglian Water’s ‘Love Every Drop’ campaign aims to significantly reduce carbon emissions, including in their supply chain, and encourage customers to be more resource efficient and cut down their carbon emissions. Their manifesto, published in 2015, aims to raise awareness about how essential water is to life, to people and the environment, and to a vibrant and growing economy too. This helped to save £2.5 million in energy costs in 2016. | fa606d5e-1f24-4c2d-a92a-646f5ee9e9b7 | 22 |
0e66e749-33f7-42ed-a47c-81594ec6a758 | https://unfccc.int/sites/default/files/resource/UK%20Net%20Zero%20Strategy%20-%20Build%20Back%20Greener.pdf | 2,021 | [
"zero",
"carbon",
"emissions",
"energy",
"government"
] | unfccc.int | We know that people want to play their part in achieving net zero. Our approach for how government will empower everyone to make green choices is underpinned by six 50 Although they were developed with the public in mind, many of them equally apply to green choices taken by businesses, particularly medium or small enterprises. The principles reflects wider public engagement from across the country and Parliament. 6. Public engagement, including through communications campaigns such as Together for Our Planet, plays a significant role in driving green choices. We will deliver public a. Communicate a vision of a net zero 2050, build a sense of collective action, improve understanding of the role different actors play in reaching net zero, and how and b. Ensure there is trusted advice and support for people and businesses to c. Mobilise a range of actors and stakeholders to increase and amplify their communication and action on net zero and d. Give people opportunities to participate in and shape our plans for reaching net zero, thereby improving policy design, buy-in Net Zero Build Back Greener
Principles underpinning green public and business choices Principle 1: Minimise the ‘ask’ by sending clear regulatory signals 7. By targeting measures at an industry level, rather than at the individual consumer, we can make green choices much simpler for the consumer. This will also help grow a stronger market for low carbon goods and give businesses clear, early signals. For example, the 2030 phase out date for petrol and diesel cars and vans sends a signal to industry and will improve the availability and quality of zero emission vehicles on the market. Similarly, as set out in the Heat and Buildings Strategy there are a range of policies we will introduce that will bolster the low carbon heating market, creating new opportunities for business, and better choice for the consumer. 8. We are taking action to ensure that products are more sustainable, both in relation to their energy efficiency during use and use of materials over their lifetime (resource efficiency) through developing proposals for new regulatory product standards and better consumer information. We are exploring updating and expanding ‘Ecodesign’ product regulation which sets minimum requirements to phase out the least energy and resource efficient products from the market. Principle 2: Make the green choice 9. By addressing all the major, practical barriers to individual behaviours we can make it easier for people to make green choices. We will ensure that we take a consumer- centred approach to net zero policy design, removing frictions and minimising disruptions to 10. In our Transport Decarbonisation Plan, we have committed to better integrating transport modes, with more bus routes serving railway stations and improved integration of cycling and walking networks, so that opting to make a green travel choice is easier. This is in addition to delivering interventions to enable more people to walk and cycle for short journeys such as a national e-cycle support programme. Our vision is that half of all journeys in towns and cities will be cycled or walked by 2030. We are also committed to increasing road vehicle occupancy. This will help decarbonise and decongest our roads. We will publish guidance for local authorities on support for shared car ownership and shared occupancy schemes and services and are continuing to build our evidence base to understand the barriers and potential policies to increase the uptake of shared mobility. 11. We are committed to removing inconvenience and increasing availability of green choices. Following the commitments made in our Resources and Waste Strategy, the Environment Bill will introduce powers that will allow us to require separate food waste collections in all local authorities in England, which will help people to reduce emissions Chapter 4 – Supporting the Transition across the Economy
Principle 3: Make the green choice 12. We are already seeing the upfront cost of green choices, such as electric vehicles, drop. We are looking across all sectors to see how we can continue this trend and make green 13. Through the Smart Export Guarantee (SEG) energy suppliers are moving to increasingly innovative tariffs which support electric vehicle deployment while continuing to enable households to access a market-led route for exporting and receiving payment for their unused electricity. As committed to in our Heat and Buildings Strategy, the Boiler Upgrade Scheme will provide grants to help households transition to low carbon heating. We are also supporting motorists through plug-in vehicle grants, which provide support towards the upfront purchase of eligible cars, vans, motorcycles, and trucks. 14. We are supporting the public to both save and contribute towards public spending that helps the UK reduce its emissions through the NS&I Green Savings Bond. The Green Finance Institute and Abundance Investment, supported by UK100, Local Partnerships and Innovate UK, have also launched a national campaign to help local authorities issue a type of municipal finance investment – Local Climate Bonds. For citizens, the Local Climate Bond provides a low-risk and fixed return investment, and a way to mobilise their savings to help tackle the climate 15. Consumer preference can shape producers’ decisions, but sometimes consumers and businesses lack clear information to make informed choices. As announced by the chancellor in his Mansion House speech in July 2021, we will work with the Financial Conduct Authority to introduce a sustainable investment label - a quality stamp - so that consumers and retail investors can clearly compare the impacts and sustainability of their investments for the first time. We plan to help empower people to make informed choices about the goods and products they buy and services they use by exploring how we better label these with their emission intensity and environmental impact. We are also exploring the use of product labelling to show the durability, repairability and recyclability of products, as well as their environmental footprint with a view to stimulating demand for better quality items. | 44870195-36a9-4258-b046-ac522bc94ef6 | 94 |
0e68c1a1-46ae-40a3-bd6b-3911f3e512fa | http://arxiv.org/pdf/2507.12994v1 | 2,025 | [
"Aerosols",
"Brown Carbon",
"SOA",
"Light Absorption",
"Climate",
"Human Health",
"Aging",
"Photochemistry",
"Optical Trap",
"Vortex LG beams",
"Gaussian beams",
"Spatial Light Modulator",
"Photochemistry",
"Aqueous Droplets",
"Fulvic Acid",
"Orbital Angular Momentum",
"Holography",
"Spectroscopy",
"Fluorescence",
"Raman Scattering",
"Particle Confinement",
"Trapping",
"Universal Trap."
] | arxiv.org | 3. Scheme of the experimental setup showing all lenses (L x ), mirrors (M), polarization beamsplitter cubes (PBS), half-wave plates, microscope objectives (MO x ) and cameras (CAM x ), the spatial light modulator (SLM), pinhole (PH), long-pass filter (LPF), trapping cell (TC), neutral-density (ND) filter, dichroic mirror (DM) and HeNe laser for holography. The black arrows along each trapping beam indicates the direction of rotation of the LG beams. For absorbing particles, Gaussian beams were used to provide an initial momentum transfer to the particles which pushed them into the trapping region. Gaussian beams were then changed to LG mode with comparatively high OAM to capture a single particle in the formed Steinmetz solid. The spatial confinement of the trap was then increased by smoothly decreasing the l order of the beam. Aligning the 4-beam trap using LG beams with non-zero l order would be challenging, but because no realignment is necessary between the different operation modes, the trap can be aligned using Gaussian beams and non-absorbing particles. Making alignment straightforward. 2.2 Characterization techniques
The properties of the trapped droplets were characterized using digital in-line holography, Raman scattering / fluorescence spectroscopy (for fluorescing droplets) and broadband light scattering (BLS). The components for digital holography and Raman scattering are sketched in Fig. 3, while the BLS components are omitted to avoid over-crowding of the figure. More details can be found in previous publications of our group [X]. The digital in-line holography allows recording of the particle 3D position and quantifying its size and shape. We used a HeNe laser = 0.42) to focus the beam in front of the trapped particle. A second microscope objective of the same type is used to collect the hologram created by the interference of the particle scattering and the reference incident laser. A lens L 9 is used to fill out the sensor of the CMOS camera 1. The spatial resolution of the holographic imaging is ~0.9 μm. To avoid possible interference coming from the scattering of the trapping beams by the particle, a 532 nm notch filter is placed in front of the holography camera. The numerical reconstruction of in-line holograms was done using a two Fourier transform approach. The confinement study of salt was done with 852 holograms. For the probability distribution maps of fulvic acid/K 2 CO 3 9002 holograms were taken for each LG mode. The nigrosin/K 2 CO 3 confinement study was done with 480 and 900 holograms for | l| = 5, | l| = 6 respectively. For Raman scattering and fluorescence spectroscopy, the trapping laser was used as excitation source. The elastic and inelastic light emitted by the trapped particle were collected with a microscope objective. A dichroic mirror and two 532 nm notch filters were used to detect only the inelastic light (Raman scattering and fluorescence, if there is any). The scattered/fluoresced light was detected with a spectrometer and coupled to a high sensitivity camera. More can be found in. The BLS measurements provide accurate information on the droplet size for non-absorbing following the procedure described in. To excite BLS, we used the light of a broadband Xenon lamp, focused on the droplet with a microscope objective. The elastic light scattered by the droplet in the wavelength range between 370 and 700 nm was collected with another objective and detected with a spectrometer. The intensity pattern of the scattered light was fitted with Mie theory to retrieve the droplet radius and wavelength-dependent refractive index. | 42e4f242-d7bd-4f93-a58a-fac080933372 | 5 |
0e713d3a-e4e3-447b-ab4e-14d4263cd9c6 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_e2ed2f6c199088dc30a95fddf6e84c72.pdf | 2,023 | [
"emissions",
"data",
"inventory",
"energy",
"emission"
] | cdn.climatepolicyradar.org | The DUKES commodity balance tables are regarded as high quality and complete for most fuels and sectors, where the fuel allocations are based on fuel sale s data (from tax records, from annual and periodic surveys), surveys of fuel suppliers and producers, import and export data. However, for the upstream oil and gas sector a high proportion of fuel use (and hence combustion emissions) arise from operators’ own use of fuels (mainly fuel gas, a mixture of methane and other hydrocarbons) that are generated and used on site and are therefore not ‘bought and sold’ (unlike most fuel use across the UK economy), nor are they metered or 53 EU Emissions Trading Scheme, Approved Phase I National Allocation Plan 2005-2007, Defra (2005) phase_1/phasei_nap/phasei_nap.aspx
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 147 delivered through a system (e. g. pipeline network) where inputs and outputs are routinely monitored to track fuel use / sales to recharge the suppliers. The DUKES long-term trends in producers’ own fuel gas use by the upstream sector54 exhibit a ~20% single year step -change from the year 2000 to 2001 that the UK Government (then DECC) energy statistics team confirmed was due to the more complete data capture after the Petroleum Production Reporting System (PPRS) was implemented (DECC, 2012. Personal communication) and was not a ‘real’ change in fuel use. Prior to PPRS the data capture mechanisms in place under -reported the sector fuel use, with data gaps indicated by UK Government energy statisticians for fuel gas use at gas terminals and at oil terminals. This has informed our method choice to deviate from UK energy statistics and to use the industry reported data for emission estimates in the 1990s (i.e. the UKOOA 2005 dataset) in preference as they are the more accurate, complete dataset. Further, the UK energy statistics are still in complete in recent years for fuel gas use, as confirmed during the oil and gas improvement project through analysis of the own gas use reported by UK terminals and consultation with the BEIS energy statistics team. Consultation with BEIS energy statistics (BEIS, 2021. Personal communication) has confirmed that the fuel gas use reported within PPRS and UK ETS from oil terminals is not included in the DUKES data for ‘oil and gas extraction’ use of ‘natural gas’. Hence the UK GHGI method deviates from DUKES, using the operator-reported (and Third Party verified) UK ETS data on fuel gas use as it is regarded as the most complete and accurate dataset for the oil and gas sector. This is a continuation of the method from the 2021 submission. DUKES (BEIS, 2022a) reports gas oil use for the upstream oil and gas sector since 2005 but not for earlier years in the time series; the operator data from EEMS (1998 -2004) and from UKOOA (1990-1997) shows that gas oil has been used by the sector throughout the time series. Therefore, the UK GHGI uses the operator -reported estimates directly for 1990-2004 and the DUKES data for 2005 onwards, which are based on operator returns to EEMS. We note that when the operators’ own fuel gas is the primary fuel for generating heat and power in upstream facilities , it is formed predominantly of methane and has a similar composition to natural gas processed at gas terminals and provided to downstream users in the UK via the National Transmission System (NTS) . However, fuel gas frequently ha s a greater proportion of higher-chain hydrocarbons (e.g. ethane, propane, butane, C5 and above) than natural gas, as well as higher levels of CO 2 and sulphur compounds. Tables in Annex 3.1.6 set out the fuel compositional data for the fuel gas, illustrati ng the variability of CEFs, densities and NCVs of the fuel gas across the UK upstream oil and gas sector. All of the emissions are reported under ‘natural gas’ use in 1A1cii, reflecting the allocation of the fuel gas to the natural gas commodity balance in DUKES. Emissions from OTs and CDs are ‘Not Estimated’ for this source. There is no oil or gas production in any of the OTs and CDs, and only limited well drilling and initial exploration activity (i.e. well testing) in waters around the Falklands Islands in 1998, in 2010, 2012 and 2015. There are no fuel use estimates specific to those exploration activities; it is assumed that any fuel use is accounted for within the Falklands energy balance data. Emission factors for N2O for 1A1cii are higher than the IPCC default range, and this issue has been noted by previous UNFCCC expert review teams. The factors applied in the UK inventory are based on operator-reported data from predominantly offshore oil & gas facilities using fuel gas, which is mainly natural gas or associated gas from oil production. These operator data 2000-2001-2002 64,634 – 65,555 – 78,457 – 79,364. The step change 2000 to 2001 is a 19.7% apparent increase, but reflect better data capture (Personal BEIS, 2012)
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 148 are considered to be more representative of combustion emissions at UK installations than There have been no major recalculations to estimates. Improvements (completed and planned) The oil and gas sector improvement project (Thistlethwaite et al , 2022) has assessed all available UK data to improve the quality of the UK GHGI submission across 1A1cii and 1B2, and is described in more detail in Annex 3.1.6. Emission factors and activity data remain under review. Further improvements may be achieved if it becomes possible to obtain more resolved data on fuel gas quality per installation, to improve the assumptions for NCVs and density of fuel gas. The current method applies the best available data from PPRS but this is a separate data reporting mechanism to the EEMS and UK ETS datasets. If a more comprehensive NCV dataset directly from e.g. the UK ETS data reporting, were to become available, this may help to improve data quality. | 70afacf8-8641-4466-819d-f4db8cad9d69 | 266 |
0e7628dc-2a10-48c5-b96c-54de982fb34f | https://cdn.climatepolicyradar.org/navigator/GBR/2023/energy-act-2023_87896593a3bea76cf3ac89af17aba308.pdf | 2,023 | [
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] | cdn.climatepolicyradar.org | (3) Regulations under this section may amend— (b) the Nuclear Installations Act 1965, or (c) any other enactment having effect in relation to a matter to which the CSC (4) In this section, “the CSC” means the Convention on Supplementary Compensation for Nuclear Damage (as amended or supplemented from time to time). (5) Regulations under this section are subject to the affirmative procedure. I400 S. 306 in force at 26.12.2023, see s. 334(3)(k)
Part 14 – Civil nuclear sector Chapter 2 – Civil Nuclear Constabulary Document 2024-10-14 This version of this Act contains provisions that are prospective. Changes to There are currently no known outstanding effects for the Energy Act 2023. (See end of Document for details) 307 Provision of additional police services (1) After section 55 of the Energy Act 2004 insert— 55A Provision of additional police services (1) The Constabulary may, with the consent of the Secretary of State, provide additional police services to any person. (2) In this Chapter, “additional police services” means services relating to the protection of places, persons or materials. (3) In subsection (2), “place” includes— (a) premises, facilities or equipment at a place; (b) any vehicle, vessel, aircraft or hovercraft. (4) The Secretary of State must not give consent for the purposes of subsection (1) unless satisfied, on an application made by the Police Authority, that— (a) the provision of the additional police services in question is in the interests of national security, (b) the provision by the Constabulary of those services will not prejudice the carrying out of its primary function under section 52(2), and (c) it is reasonable in all the circumstances for the Constabulary to (5) Before giving consent for the purposes of subsection (1), the Secretary of State must consult the chief constable. (6) The chief constable must ensure that the provision by the Constabulary of additional police services does not prejudice the carrying out of its primary (7) Consent given for the purposes of subsection (1)— (a) must specify the period of time (not exceeding 5 years) for which it (b) may, subject to subsections (8) and (9), be withdrawn at any time if the Secretary of State is no longer satisfied of the matters mentioned (8) Where the Secretary of State proposes to withdraw consent given for the purposes of subsection (1), the Secretary of State must consult the Police (9) If, following consultation under subsection (8), the Secretary of State decides to withdraw consent given for the purposes of subsection (1), the Secretary of State must give such notice to the Police Authority as is reasonably practicable of the date on which the consent will cease to have effect. Part 14 – Civil nuclear sector Chapter 2 – Civil Nuclear Constabulary Document 2024-10-14 This version of this Act contains provisions that are prospective. Changes to There are currently no known outstanding effects for the Energy Act 2023. (See end of Document for details) (10) The Police Authority may enter into an agreement with any person for the provision of additional police services by the Constabulary under this section. (11) The Police Authority must publish, as soon as is reasonably practicable and in such manner as the Authority considers appropriate— (a) the name of any person or persons to whom additional police services are to be provided under this section, and (b) (subject to subsections (12) and (13)) such information about the place or places at which those services are to be provided as the Police Authority considers may be published without prejudicing the interests of national security. (12) The Police Authority must consult the Secretary of State before publishing the information referred to in subsection (11)(b). (13) The Secretary of State may direct the Police Authority not to publish information about the place or places at which additional police services are to be provided where the Secretary of State considers that publication of the information would prejudice the interests of national security. (14) The Police Authority must comply with a direction given by the Secretary of (2) In section 56 of that Act (jurisdiction of Constabulary), after subsection (3) insert— “(3A) A member of the Constabulary has the powers and privileges of a constable at every place where additional police services are being provided (3) In section 71(1) of that Act (interpretation), at the appropriate place insert— ““additional police services” has the meaning given in section 55A(2);”. (4) The Counter-Terrorism Act 2008 is amended as follows— (a) in section 85(2) (costs of policing at gas England and Wales), after paragraph (a) omit “or” and insert— “(aa) the services of the Civil Nuclear Constabulary provided under section 55A of the Energy Act 2004, or”; (b) in section 86(2) (costs of policing at gas Scotland), after paragraph (a) omit “or” and insert— “(aa) the services of the Civil Nuclear Constabulary provided under section 55A of the Energy Act 2004, or”. I401 S. 307 in force at Royal Assent, see s. 334(2)(n) 308 Provision of assistance to other forces (1) The Energy Act 2004 is amended as follows. (2) After section 55A (inserted by section 307 of this Act) insert—
Part 14 – Civil nuclear sector Chapter 2 – Civil Nuclear Constabulary Document 2024-10-14 This version of this Act contains provisions that are prospective. Changes to There are currently no known outstanding effects for the Energy Act 2023. (See end of Document for details) “55B Provision of assistance to other forces (1) The chief constable may, on the application of the chief officer of a relevant force, provide members of the Constabulary or other assistance for the purpose of enabling that force to meet any special demand on its resources. | 4808927e-67c0-4e83-803d-e07fd0d4a019 | 117 |
0e76fbef-db87-4775-862e-06769ec4ac31 | https://cdn.climatepolicyradar.org/navigator/GBR/2024/united-kingdom-biennial-transparency-report-btr1_0e77f9e4d928e6e9d64ea26cd95945e1.pdf | 2,024 | [
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] | cdn.climatepolicyradar.org | 4.5.10.2 Africa Clean Energy Programme (ACE) • The Africa Clean Energy Programme (ACE) is a regional programme including a Challenge Fund supporting start-ups or expansion of household solar energy businesses in nine countries in Sub-Saharan Africa and supporting the deployment of mini grids through the African Development • During the Ayrton Fund period, the programme leveraged £2.8 million in private finance in support of programme activities and is estimated to have provided 0.67 MW of installed off-grid clean energy capacity. 4.5.10.3 Global Facility to Decarbonise Transport (GFDT) • The GFDT is a new, first of its kind World Bank Trust Fund486 that provides financial and technical assistance to support transport decarbonisation in low and middle-income countries. Its mission is to accelerate innovation and investment in climate-smart mobility solutions, with the goal of achieving net zero in the global transport sector by 2050. GFTD funding and project preparation helps move big transport decarbonisation projects that otherwise would not go forward. In doing so, the Fund empowers low and middle- income countries to build transport systems that not only reduce emissions, but are also safe, modern, inclusive, and resilient. • Three GFDT innovation-focused projects have been badged as Ayrton to date, including in India (developing a new business model to help unlock commercial financing at scale for e-buses, e-motorcycles and electric 3- 4.5.11 Efforts to accelerate, encourage and enable innovation , including research, development and deployment efforts, and collaborative approaches to research and development Examples of Ayrton Fund activities accelerating innovation 4.5.11.1 International Science Partnership Fund (ISPF) • International Science Partnership Fund (ISPF)487 will facilitate participation of world-class UK academic researchers and their international partners in cutting-edge research. This is an existing fund that supports world-class 486 Global Facility to Decarbonize Transport (GFDT) 487 International Science Partnerships Fund (ISPF)
research in cutting-edge science and innovation to tackle the major themes of our Planet, Health, Tech, and Talent. • Under the theme of ‘Resilient Planet’, ISPF will give researchers and innovators access to global talent, large-scale facilities, research ecosystems and markets to swiftly move forward ideas to greater maturity, applicability, • The programme will build on DSIT’s small portfolio of energy research and ensure a strong strategic direction of the work and coherence with other government departments. It will comprise a combination of scaling-up of existing activities, such as Innovate UK’s Energy Catalyst and EPSRC’s energy access projects, and new thematic projects in areas such as solar/biofuels, whole systems, heating/refrigeration, sustainable transport, and • The fund launched in December 2022 with an initial £119 million. A further £218 million was announced in November 2023 for research and innovation partnerships with low and middle-income countries to support sustainable • Research partnerships that bring together multiple countries and both university and private sector expertise, produce game-changing technologies, innovations and evidence, benefiting hundreds of millions of people in lower- income countries. The UK’s International Science Partnerships Fund is an example of how we can foster prosperity by solving shared global research and innovation challenges. Genuine partnerships are essential to achieve the ambitions set out in the UK’s Science and Technology Framework and the International Technology Strategy. Transforming Energy Access (TEA) platform • The £265m FCDO Transforming Energy Access488 (TEA) platform funds the research, development and demonstration of new clean energy technologies and business models for developing countries. • Between 2016 and 2024, through effective partnerships and collaborative approaches with the private sector, academia, NGOs and international organisations, TEA has stimulated UK-led research and development of 662 new clean energy technologies and business models in areas such as energy storage489, sustainable cooling, electric pressure cookers, remote network management, energy access crowdfunding490, improving clean 488 Transforming Energy Access (TEA) - supporting renewable energy projects, energy access and green technologies in Africa and Asia. 489 MOPO — Redefining energy and transport in Africa 490 Energise Africa | Change the world & target a return of up to 6%
energy access for 27 million people in developing countries (including 13 • It has also leveraged £1.5 billion of additional investment into clean energy technology research, innovation and scale-up from both private and public sources; created and supported 125,000 sustainable long-term jobs (including 27,000 jobs for women); supported 759 young Africans with job placements and 1135 managers with specialist training in clean energy access businesses; and led to the avoidance of 2.7 million tonnes of 4.5.12 Clean Energy Innovation Facility (CEIF) • The CEIF 1.0 programme, under the umbrella CEIF platform, aims to accelerate the commercialisation of innovative clean energy technologies in developing countries along key themes such as industrial decarbonisation, sustainable cooling, smart energy, and energy storage. A programme extension of up to £55m (CEIF 2.0) has been approved and started in March 2024. The CEIF 2.0 programme will focus on piloting and demonstrating innovative technologies across three key themes - industrial decarbonisation, sustainable cooling, and smart energy. • Up to 2023/24, CEIF 1.0 supported 55 sustainable cooling technologies with 62 pilots in Colombia, Mexico, Nigeria, Kenya, Rwanda, India, and Bangladesh. The pilots focused on key themes, namely cooling in cities, cold chains, temperature-controlled logistics, space cooling, and cooling-as-a- service (CaaS) business models. Alongside this, the International Finance Corporation (IFC) - delivery partner for CEIF - launched the India Cooling Innovation Lab491 in December 2023 bringing together technology innovators and local companies to pilot innovative smart energy technologies. • Under the Industrial Decarbonisation theme, in 2023 CEIF supported 17 ongoing projects in Morocco, Mexico, Dominican Republic, Colombia, Türkiye, Pakistan, India, Vietnam, Bangladesh, as well as regional activities in East Asia and Pacific and those with a global reach. Under the Smart Energy theme, CEIF redefined the fund based on lessons learnt over the past 4 years and planned a strong pipeline of projects showcasing the impact of these • The UK’s Climate Compatible Growth (CCG) programme has produced knowledge products which are being used in teaching and research within seven universities or research institutes in Low and Middle-Income Countries. | 2ae0b548-ef04-451f-aba3-617d0f3c41f8 | 231 |
0e7730a4-a205-4b71-a9e1-8ef296b4ac38 | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32021R2116 | 2,013 | [
"Agriculture and forestry",
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] | eur-lex.europa.eu | In order to give Member States legal and financial assurances as to expenditure effected in the past, a limitation period should be set for the Commission to decide what the financial consequences of non-conformity should be. (47)
Member States are obliged, under Article 9 of Regulation (EU) 2021/2115, to implement their CAP Strategic Plans as approved by the Commission in accordance with Articles 118 and 119 of that Regulation. Since that obligation constitutes a basic Union requirement, the Commission should, where serious deficiencies in a Member State s implementation of its CAP Strategic Plan are detected, be able to decide to exclude from Union financing the expenditure at risk that is affected by such deficiencies. (48)
In order to safeguard the financial interests of the Union budget, Member States should put in place systems in order to ensure that interventions financed by the EAGF and EAFRD are actually carried out and are executed correctly, while maintaining the current robust framework for sound financial management. Those systems should include performing checks on beneficiaries by assessing their compliance with the eligibility criteria and other conditions, as well as obligations set out in the CAP Strategic Plans and applicable Union rules. (49)
In accordance with the Financial Regulation, Regulation (EU, Euratom) No 883/2013 of the European Parliament and of the Council (10) and Council Regulations (EC, Euratom) No 2988/95 (11), (Euratom, EC) No 2185/96 (12) and (EU) 2017/1939 (13), the financial interests of the Union are to be protected by means of proportionate measures, including measures relating to the prevention, detection, correction and investigation of irregularities, including fraud, to the recovery of funds lost, wrongly paid or incorrectly used and, where appropriate, to the imposition of administrative penalties. In particular, in accordance with Regulations (Euratom, EC) No 2185/96 and (EU, Euratom) No 883/2013, the European Anti-Fraud Office (OLAF) has the power to carry out administrative investigations, including on-the-spot checks and inspections, with a view to establishing whether there has been fraud, corruption or any other illegal activity affecting the financial interests of the Union. The European Public Prosecutor s Office (EPPO) is empowered, in accordance with Regulation (EU) 2017/1939, to investigate and prosecute criminal offences affecting the financial interests of the Union as provided for in Directive (EU) 2017/1371 of the European Parliament and of the Council (14). In accordance with the Financial Regulation, any person or entity receiving Union funds is to fully cooperate in the protection of the financial interests of the Union, to grant the necessary rights and access to the Commission, OLAF, the Court of Auditors and, in respect of those Member States participating in enhanced cooperation pursuant to Regulation (EU) 2017/1939, the EPPO and to ensure that any third parties involved in the implementation of Union funds grant equivalent rights. (50)
Member States should have the systems in place allowing them to report to the Commission, for the purpose of enabling OLAF to exercise its powers and ensure an efficient analysis of cases of irregularity, on detected irregularities and other cases of non-compliance with the conditions established by Member States in the CAP Strategic Plans, including fraud, and on their follow-up, as well as on the follow-up of OLAF investigations. To ensure the effective examination of complaints concerning the EAGF and EAFRD, Member States should have in place the necessary arrangements. (51)
In accordance with the principle of subsidiarity, Member States should, upon the request of the Commission, examine complaints submitted to the Commission falling within the scope of their CAP Strategic Plans and should inform the Commission of the results of those examinations. | 8f9bf1c1-a150-4ba5-bf0e-b248d1eace93 | 11 |
0e8065f0-bf53-4fc2-813a-b5ad2dec34df | https://www.gov.uk//guidance/oil-and-gas-eems-database | 2,013 | [
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A new user group is being established to take forward further development and maintenance of the EEMS database. Minutes of the meetings and any relevant documents or presentations discussed at the meetings will be added to the website. | cc7d3753-fb24-4a2b-94c2-9cef68a97bb7 | 1 |
0e8560b5-f5d5-4e0e-8c99-336ff63bb12d | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:31998L0069 | 1,998 | [
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] | eur-lex.europa.eu | 5.1.4.3. In the case of mechanical fuel-injection pumps fitted to compression-ignition engines, manufacturers must take adequate steps to protect the maximum fuel delivery setting from tampering while a vehicle is in service. 5.1.4.4. Manufacturers may apply to the approval authority for an exemption to one of these requirements for those vehicles which are unlikely to require protection. The criteria that the approval authority will evaluate in considering an exemption will include, but are not limited to, the current availability of performance chips, the high-performance capability of the vehicle and the projected sales volume of the vehicle. | 282d51c7-9418-4d78-8dce-aec1567a8b80 | 13 |
0e8ab0ca-3f05-4497-9706-c5ee56888da4 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-adaptation-plan-nap3_5fe848c63d8d53eb88129bb189320aee.pdf | 2,023 | [
"climate",
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] | cdn.climatepolicyradar.org | This will support long term resilience from surface water flood risk by reducing the impact of rainfall on new developments, using features such as soakaways 9. The Environment Agency will update the National Flood Risk Assessment by 2024 to provide better data and information to support flood risk mapping, improved ways of measuring changes in risk, as well as future investment choices. It will significantly improve understanding of surface water flood risk and will be available as open data. 10. Defra will continue to encourage uptake of property flood resilience measures. For example, in April 2022 we amended legislation to enable the Flood Re Scheme to pay claims from insurers, which include up to £10,000 towards resilient repair to help build resilience of households impacted by flooding. 11. Defra will continue to support affordable flood insurance through the Flood Re Scheme through the NAP3 implementation period to 2028 and beyond. More than 450,000 properties have benefitted since the scheme’s launch in 2016. 12. Defra and the Environment Agency will invest in improving flood forecasting capabilities in higher-risk areas to improve surface water flood risk information and improve the speed of communication of forecasts to local responders. This will include identifying feasible and realistic improvements to the forecasting capability for surface water flooding through a ‘testbed’ approach using the Met Office systems by December 2023. 1. FCERM Policy Statement (Actions 1, 2, 4, 5, 6, 7, 10 and 11) 2. Flood and coastal defence investment programme (Actions 1 and 6) 3. Flood and Coastal Resilience Innovation Fund (Actions 1 and 2) 4. FCERM Strategy Roadmap (Action 4) 6. Flood and Water Management Act 2010 (Action 8) 7. National Flood Risk Assessment (Action 9) 8. Flood Reinsurance (Amendment) Regulations 2022 (Action 11)
H4 – Risks to the viability of coastal communities from sea level rise (DEFRA and DLUHC) Improve the nation’s resilience to future flood and coastal erosion risks, thereby reducing the risk of harm to people, the environment and the economy. 1. Defra and the Environment Agency will invest £5.2 billion to build new flood and coastal defences to better protect communities across England by 2027. This will include projects which focus on better protection for coastal 2. Defra will support innovation in a small number of coastal communities at significant risk of erosion between 2022 and 2027 through the Coastal Transition Accelerator Programme to adapt to a changing climate. The programme will act as a catalyst for strategic, long-term planning and will help test innovative practical actions which will be shared across England. 3. The Environment Agency and partners will deliver the National FCERM Strategy Roadmap for England by 2026, which will provide practical actions to 4. The Environment Agency will update the National Coastal Erosion Risk Map and its assessment of properties and infrastructure at risk from erosion in a changing climate by the end of 2023. This will improve evidence and inform decision-making along the coast. 5. A Defra research project carried out by the British Geographical Survey, which concluded in May 2023, has reviewed and collated historical coastal change evidence and created a methodological framework to monitor, document and present historical coastal change. Data from this project will be used to inform future coastal management decisions. 6. The Environment Agency will support local authorities to update and strengthen Shoreline Management Plans by the end of 2024 to ensure they remain relevant for future shoreline planning, including taking into account up- to-date information on climate risk. 7. Defra will review national policy for Shoreline Management Plans by the end of 2026 to ensure they are transparent, continuously review outcomes and enable local authorities to make robust decisions on shoreline management. 8. Defra will review the tools that coastal erosion risk management authorities (RMAs) use to manage the coast and explore the availability of products or services which support coastal transition and manage coastal erosion risk by 9. Defra and DLUHC will review national planning policy, following the passage of the Levelling-up and Regeneration Bill, to ensure it is sufficiently robust to keep future developments safe from flooding and not increase risk elsewhere. This includes reviewing the planning policy approach for areas at the coast in managing and adapting to coastal change and sea level rise. 10. DLUHC will provide regeneration funding which will be accessible to coastal communities for a variety of reasons, including to better protect them from climate risks including flooding and coastal erosion. For example, the UK Shared Prosperity Fund, which will ramp up to £1.5 billion per year by 2024- 25, is allocated to lead local authorities and will provide funding to coastal communities of all sizes, often as part of wider programmes. 1. Flood and coastal defence investment programme (Action 1) 2. Flood and Coastal Innovation Fund, Coastal Transition Accelerator 3. FCERM Strategy Roadmap (Actions 3 and 4) 4. The National Coastal Erosion Risk Map (Action 4) 5. Coastal monitoring and historical coastal change project (Action 5) 6. Shoreline Management Plans refresh (Action 6) 7. Policy review of Shoreline Management Plans (Action 7) 8. Policy review of coastal erosion risk management tools (Action 8) 9. National Planning Policy Framework (Action 9) 10. Regeneration Fund, Levelling-up Fund, UK Shared Prosperity Fund and Rural England Prosperity Fund (Action 10)
H5 – Risks to building fabric (DESNZ AND DLUHC) Understand the impact to the different building fabrics and approaches to mitigate impacts from climate change induced hazards including extreme weather events, winds, and wildfires in the UK under different warming scenarios considering vulnerabilities and equality duties. DESNZ will ensure that measures to deliver net zero and retrofit existing buildings, as described in the Heat and Building s Strategy, will seek to minimise risks to building fabric due to the impacts of climate change. This will result in an existing building stock that is appropriately retrofitted to deliver net zero by 2050 and more resilient to climate hazards. 1. | daa6054e-a061-4a6e-abc6-3fa1147f5608 | 36 |
0e8c6d98-90c5-4ccd-8614-090821daf503 | https://www.ecolex.org/details/legislation/regulatory-reform-scotland-act-2014-consequential-modifications-order-2015-si-no-374-of-2015-lex-faoc143661/?type=legislation&xsubjects=Mineral+resources&page=892 | 2,015 | [
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] | ecolex.org | This Order, among other things, amends: the Marine and Coastal Access Act 2009 to provide for a statutory appeal to the Inner House of the Court of Session by any person or body who is aggrieved by certain specified decisions of the Scottish Ministers made under that Act in relation to marine licensable activities concerning electricity generating stations to be situated in the Scottish offshore region; the Environmental Protection Act 1990 and the Environment Act 1995 in relation to controlling the emission into the atmosphere of noxious or offensive substances from premises, and for a general duty on persons in control of certain premises in relation to harmful emissions into the atmosphere. | 0ab66573-8ff9-481b-a390-dfafc0eed779 | 0 |
0e8c70f3-3b52-47f8-a9d7-42a6cc35f6c7 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_e2ed2f6c199088dc30a95fddf6e84c72.pdf | 2,023 | [
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"emission"
] | cdn.climatepolicyradar.org | Activity data for traffic-based emission Hot exhaust emission factors are dependent on average vehicle speed and therefore the type of road the vehicle is travelling on. Average emission factors are combined with the number of vehicle kilometres travelled by each type of vehicle on rural roads , higher speed motorways/dual carriag eways and different types of urban roads with different average
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 179 speeds. The emission results are combined to yield emissions on each of these main road • Rural single carriageway; and DfT estimates annual vehicle kilometres (vkm) for the road network in Great Britain by vehicle type on roads classified as motorways, trunk, principal and minor roads in urban and rural areas (DfT, 2022a). DfT provides a consistent time series of vehicle km data by vehicle and road types going back to 1993 for the 20 21 inventory, taking into account any revisions to historic data. The vkm data are derived by DfT from analysis of national traffic census data involving automatic and manual traffic counts. Additional information discussed lat er (e.g. Automatic Number Plate Recognition data) (DfT, 2022b) are used to provide the breakdown Vehicle kilometre data for Northern Ireland by vehicle type and road class were provided by the Department for Regional Development, Northern Ireland, Road Services (DRDNI, 2016). This gave a timeseries of vehicle km data from 2008 to 2014. To create a timeseries of vehicle km data for 1990 to 2007, the vehicle km data from DRDNI (2013) was used. The data were scaled up or down based on the ratio of the data for 2008 between DRDNI (2016) and DRDNI (2013) for the given vehicle type and road type considered. Data for 2015 -2021 were not available for the current inventory compilation and thus they were extrapolate d from 2014 vehicle km data for Northern Ireland based on the traffic growth rates between 2014 and 2021 in Great Britain. Motorcycle vehicle km data were not available for Northern Ireland so they were derived based on the ratio of motorcycles registered in Northern Ireland relative to Great Britain each year. The ratios were then applied to the motorcycle vehicle km activity data for Great Britain. Information about the petrol/diesel split for cars and LGVs in the traffic flow are based on licensing data for Northern Ireland as provided by DfT (2022d). The Northern Ireland data has been combined with the DfT data for Great Britain to produce 3.12 shows the time-series of total UK vehicle kilometres by vehicle and road type for selected Billion vkm 199056 2000 2005 2010 2015 2019 2020 2021 Petrol cars urban 142.2 134.8 118.1 97.8 89.2 88.0 70.3 78.5 rural 140.9 134.1 127.6 110.5 95.5 101.1 76.5 86.0 m-way 49.3 53.0 48.9 41.7 34.3 36.3 26.6 32.8 Diesel cars urban 5.8 26.1 40.3 53.1 65.1 68.6 52.7 56.6 rural 6.1 28.3 47.8 66.6 90.2 98.0 72.1 78.7 m-way 2.8 14.7 25.2 33.6 45.9 46.8 29.5 31.3 Petrol LGVs urban 11.2 4.5 2.1 1.2 1.0 0.9 0.8 0.8 rural 11.6 5.4 2.6 1.7 1.3 1.4 1.2 1.3 m-way 4.0 2.1 1.1 0.6 0.6 0.6 0.5 0.6 56 Prior to 1993, a different definition was used for urban and rural areas; areas were defined as 'built-up'/'non-built-up'. ‘Non- built-up’ roads were those with a speed limit of more than 40mph, and ‘built-up’ roads were those with a speed limit of 40mph or
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 180 Billion vkm 199056 2000 2005 2010 2015 2019 2020 2021 Diesel LGVs urban 5.7 15.2 20.7 22.3 25.4 26.4 24.2 26.1 rural 5.9 18.4 25.9 30.1 35.2 40.9 36.6 41.2 m-way 2.0 7.2 10.3 11.4 14.7 17.0 15.7 18.3 Electric cars urban 0.0 0.0 0.0 0.0 0.2 1.2 1.6 3.2 rural 0.0 0.0 0.0 0.0 0.3 1.5 1.9 3.9 m-way 0.0 0.0 0.0 0.0 0.1 0.6 0.7 1.5 Electric LGVs urban 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.2 rural 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.3 m-way 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 Rigid HGVs urban 4.5 3.9 4.0 3.2 3.0 2.5 2.4 2.5 rural 7.1 7.2 7.5 6.7 6.4 6.1 5.5 5.9 m-way 3.7 4.2 4.2 4.1 3.9 4.0 3.6 3.9 Artic HGVs urban 1.1 1.1 1.1 0.8 0.9 1.0 0.9 1.0 rural 4.4 5.2 5.4 5.1 5.3 5.9 5.6 6.1 m-way 4.7 7.4 7.9 7.5 8.4 9.0 8.9 9.5 Buses urban 2.4 3.0 3.1 3.0 2.7 2.3 1.6 1.8 rural 1.7 1.7 1.5 1.6 1.4 1.2 0.9 1.0 m-way 0.6 0.5 0.5 0.5 0.4 0.4 0.1 0.1 M/cycle urban 3.3 2.3 2.9 2.5 2.2 2.2 1.9 2.3 rural 2.0 2.0 2.2 1.8 1.9 1.8 1.5 1.6 m-way 0.3 0.4 0.4 0.4 0.4 0.4 0.2 0.2 Total 423.3 482.7 511.3 507.8 535.9 566.4 444.4 497.3 In the current inventory, a new road classification and traffic speed assignments is developed to improve the representation of total road transport emissions and their spatial distribution. Speed limit classification data has been assigned to OS Openroads geometry based on the length weighted median speed limit for each road link. The underlying speed limit dataset has been provided by Basemaps for Great Britain (Speed Limit Data Basemap, 2021). The vehicle speeds assigned to each category were derived from an analysis of GPS vehicle speed observations (Teletrac Navman, 2021) for England provided by DfT. The observed average speeds for England were applied across the UK. The vehicle speeds are used to derive the emission factors for each vehicle and road type from the emission factor-speed relationships available for different pollutants. Vehicle kilometre data based on traffic surveys does not distinguish between the type of fuels the vehicles are being run on (petrol and diesel) nor on their age. | 70afacf8-8641-4466-819d-f4db8cad9d69 | 280 |
0e8d519b-2e64-43ba-982b-2c3db565dde7 | https://assets.publishing.service.gov.uk/media/6424b2d760a35e000c0cb135/carbon-budget-delivery-plan.pdf | 2,023 | [
"carbon",
"delivery",
"additional",
"plan"
] | www.gov.uk | Rebalancing will generate the clear short- term price signal necessary to shift households and businesses to lower- technologies such as heat pumps. CB 4 This policy is intended to support delivery from CB4 onwards by ensuring consumers are not penalised for making green choices through reducing running costs of low carbon heating, relative to fossil fuel alternatives. reduction in pigs. Endemic production- limiting disease is a major at on efficient livestock production and will have an impact on the carbon footprint of livestock farming. Improving health status would be expected to lead to reductions in emissions intensity. The Animal Health and Welfare Pathway aims to improve farm animal health and welfare across our national herds and flocks, including an in-development Porcine Reproductive Improving the health status of pigs would be expected to lead to reductions in the emissions intensity of pork production. This is emerging work and the potential emissions reductions are contingent on research. Defra is currently undertaking research to quantify the emissions savings associated with improved pig health but this has not
No. Sector Policy name and description How the policy supports delivery/ and Respiratory Syndrome virus control Development of more sustainable protein sources for human diets. Alternative proteins could offer environmental benefits. However, the sector is diverse and at different stages of readiness and investment, and so further research is needed to overcome technological barriers, increase understand consumer acceptance preferences and accomplish an optimal regulatory alignment that meets the needs of the sector and consumer safety. Within a broad and varied market, some alternative proteins may offer environmental benefits through low emissions intensity associated with production. Emissions savings towards the carbon budgets could be delivered via a shift in the agricultural sector in response to market drivers. This is emerging work and the potential emissions reductions are contingent on research and market drivers. Developing the evidence base on controlled environment agriculture (CEA) systems/vertical agriculture. These systems make it possible to consistently and reliably control and/or manipulate the growing environment. This effectively controls crop nutrition and growth along with potential pathogens (pests and diseases) on the crop, and CEA/vertical farming could improve the energy efficiency of production (including reducing transport emissions). This could lead to reductions in the emissions intensity of the arable/horticulture sector. This is emerging work and the potential emissions reductions are contingent on research. These systems are likely to increase GHG emissions until renewable energy sources become more widely available. We continue to undertake research and monitor the
No. Sector Policy name and description How the policy supports delivery/ increases the potential to reduce transport/import emissions and improve Methanisation, methane capture and combustion. Additional mitigation intervention whereby the methane generated during storage of liquid manure is collected and burnt, converting it to carbon dioxide, a less potent GHG. There may also be potential to utilise heat or energy produced on combustion Methane, generated during storage of liquid manure, is collected and burnt. This converts the methane to carbon dioxide, a less potent greenhouse gas, which may deliver carbon savings. There may also be potential to utilise the heat and energy produced. This is emerging work and the potential emissions reductions are contingent on research. Although initial quantification has been attempted, significant uncertainty remains and further work is needed, and further Biorefinery as nutrient recovery. We continue to support research and development in this area such as through the Farming Innovation Programme. The Programme funds industry-led research and development to drive innovation that will enhance the productivity and profitability of England’s farming sectors, whilst enhancing the environment and reducing greenhouse gas emissions. It has already supported a range of projects, including ones which focus on biorefinery as nutrient recovery. For instance, the ‘Bringing H2OPE to Agriculture’ project looks at on-site Producing high-value products, such as livestock feed or fertilisers from waste could support a more circular economy in which emissions are avoided or reduced from feed or fertiliser production. This is emerging work and the potential emissions reductions are contingent on research. Although initial quantification has been attempted, significant uncertainty remains, and further work is needed. No. Sector Policy name and description How the policy supports delivery/ transformation of dairy cow slurry into valuable byproducts including fertiliser Using insect protein as animal feed. Feeding insect protein to animals has the potential to reduce overall global emissions from feed production (in comparison to conventional protein production e.g. soya grown overseas) and support a circular economy (e.g. if insects are raised on waste). There is ongoing research to determine the potential of these measures and the sector is at an early stage of development. This measure is unlikely to have significant UK GHG or land use impacts. It could, however, reduce supply chain emissions from feed supply occurring outside the scope of UK carbon Feeding insect protein to animals may reduce overall global emissions from feed production by displacing soya grown in deforested areas and support a more circular economy. Whilst this may be an important technology to reduce emissions across the livestock supply chain, it may have limited impacts on UK emissions. Further work is required to understand the impacts on UK territorial emissions within scope of the Climate Change Act versus wider international This is emerging work and the potential emissions reductions are contingent on research (including an assessment of any potential impacts on animal and public
No. Sector Policy name and description How the policy supports delivery/ Policy roadmap for the safe use of timber in construction. Increasing the safe use of timber in construction was a commitment in the England Trees Action Plan and the Net Zero Strategy, as it can support storing carbon safely, for example through using timber to build houses. This work will be taken forward in particular through the cross-government and industry timber in construction working group, which will design a policy roadmap identifying key actions for government and industry to safely increase timber use in construction. | 15a3290f-77f0-4f00-b9be-47c5b73d4f14 | 35 |
0e8f6482-4d66-4ddc-bcd5-f2bea5fa3c44 | http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32015L1513 | 2,015 | [
"Transport",
"Electricity and heat",
"Industry",
"Renewables",
"Renewables"
] | eur-lex.europa.eu | . (1)
(+)
(2)
(++)
(*6) Regulation (EC) No 1069/2009 of the European Parliament and of the Council of 21 October 2009 laying down health rules as regards animal by-products and derived products not intended for human consumption and repealing Regulation (EC) No 1774/2002 (Animal by-products Regulation) (OJ L 300, 14.11.2009, p. 1). . (*4) The mean values included here represent a weighted average of the individually modelled feedstock values. (*5) The range included here reflects 90 % of the results using the fifth and ninety-fifth percentile values resulting from the analysis. The fifth percentile suggests a value below which 5 % of the observations were found (i.e. 5 % of total data used showed results below 8, 4, and 33 gCO2eq/MJ). The ninety-fifth percentile suggests a value below which 95 % of the observations were found (i.e. 5 % of total data used showed results above 16, 17, and 66 gCO2eq/MJ). | 4fe696dc-952d-4f2f-9b63-404e8a63dbc7 | 37 |
0e963626-2734-4454-80ed-77adf283fbf6 | http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2008:199:0001:0136:EN:PDF | 2,008 | [
"Transport",
"Light-duty vehicles",
"Energy efficiency"
] | eur-lex.europa.eu | If the approval authority which granted the original type-
approval establishes that no agreement can be reached, the pro-
cedure pursuant to Article 303 and 4 of Directive 200746EC
shall be initiated
1. The manufacturer shall submit to the approval authority an
application for EC type-approval of a type of replacement pollu-
tion control device as a separate technical unit. The application shall be drawn up in accordance with the model
of the information document set out in Appendix 1 to Annex XIII. | d3fc6859-41cb-4ee2-997b-90ebc4f9b481 | 23 |
0e9fb68d-e296-4a44-a929-1189db4295c2 | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32018R0841 | 2,018 | [
"Agriculture and forestry",
"Agricultural CH4",
"Agricultural CO2",
"Agricultural N2O",
"Non-energy use"
] | eur-lex.europa.eu | In particular, to ensure equal participation in the preparation of delegated acts, the European Parliament and the Council receive all documents at the same time as Member States experts, and their experts have systematic access to meetings of Commission expert groups dealing with the preparation of delegated acts. (30)
As part of its regular reporting under Regulation (EU) No 525/2013, the Commission should also assess the outcome of the 2018 Facilitative Dialogue under the UNFCCC ( Talanoa dialogue ). This Regulation should be reviewed in 2024 and every five years thereafter in order to assess its overall functioning. The review should be informed by the results of the Talanoa dialogue and the Global Stocktake under the Paris Agreement. The framework for the period after 2030 should be in line with the long-term objectives and the commitments made under the Paris Agreement. (31)
In order to ensure that there is efficient, transparent and cost-effective reporting and verification of greenhouse gas emissions and removals, and reporting of any other information necessary to assess compliance with Member States commitments, reporting requirements should be included in Regulation (EU) No 525/2013. (32)
To facilitate data collection and methodology improvement, land use should be inventoried and reported using geographical tracking of each land area, corresponding to national and Union data collection systems. The best use should be made of existing Union and Member State programmes and surveys including the Land Use/Cover Area frame Survey ( LUCAS ), the European Earth observation programme Copernicus and the European satellite navigation system Galileo for data collection. Data management, including sharing of data for reporting, reuse and dissemination, should conform to the requirements provided for in Directive 2007/2/EC of the European Parliament and of the Council (13). (33)
Regulation (EU) No 525/2013 should be amended accordingly. (34)
Decision No 529/2013/EU should continue to apply to the accounting and reporting obligations for the accounting period from 1 January 2013 to 31 December 2020. For the accounting periods from 1 January 2021, this Regulation should apply. | 1ac45cba-01c5-4717-9fde-43e6e7fae3e1 | 7 |
0ea69c9d-53a3-478c-bba9-436a12d85497 | https://committees.parliament.uk/publications/39836/documents/193860/default/ | 2,023 | [
"solar",
"energy",
"grid",
"government",
"electricity"
] | parliament.uk | One of the key constraints for solar + battery grid connections is the line capacity – current rules require that the peak capacities of the solar panels and battery asset are summed when making the connection. In reality, we were told that electricity generated from solar installations is likely be stored at peak generation times, resulting in a reduction in the peak line capacity required.20 The Government’s introduction of a zero-rate of VAT for the installation of certain Energy Saving Materials in March 2022 effectively provides a 20% discount on the installation of solar PV. This is very welcome and has no doubt contributed – alongside high electricity bills – to the large growth seen in PV installation in the last year. We were told in the evidence session that although this VAT discount is available to those wish to install solar and storage together, it is not available to anyone who wishes to install storage to an existing PV array retrospectively. Increasing household storage capacity brings many 20 Public Power Solutions (OSE0020)
benefits not only for households but also for the grid – for instance increasing its capacity to use and store wind power when it is being generated.21 We recommend that the Chancellor of the Exchequer extend the VAT discount to household battery storage at the next opportunity. Skills and supply chain issues We heard that in common with other internationally connected industries there have been supply chain delays post-Covid. We also heard worrying concerns raised about the potential use of forced labour in Chinese solar manufacturing.22 The sector is also concerned about the availability of trained staff. We were told by Ian Rippin that the industry – in common with other sectors – is facing a ‘labour shortage’ and ‘a challenge for skilled resources’.23 We were told by Dr Chris Case of Oxford PV that ‘about 40% of the world’s production is probably subject to these concerns about forced labour’.24 The industry told us that it was working to improve transparency in this area.25 We welcome the announcement of the Joint Government Industry taskforce to work on these skills and supply chain issues. These issues further reinforce the case for the Government to encourage solar manufacturing in the UK. If barriers identified in this letter are not addressed with some urgency there is likely to be a very considerable shortfall in installed capacity compared with the Government's target set out in British Energy Security Strategy. Accelerating the solar transition will enhance the UK’s energy security, help enable households and businesses to slash their energy bills, and make a significant contribution to decarbonising the UK’s electricity The Committee would be grateful to receive a response to this letter not later than 17th May 2023 in time for your next scheduled appearance before the Committee. This letter will be published on the Committee’s website, and I expect the Committee will wish to Chairman of the Environmental Audit Committee | 96602c06-3ffa-4120-a144-de6060277fec | 2 |
0ea80a88-f359-4a3f-930d-7122b3c2d912 | 2,025 | [
"average national final energy consumption",
"greenhouse gas emissions",
"transport fuel market",
"biofuels",
"sectors"
] | HF-national-climate-targets-dataset | Pursuant to the decisions taken within the framework of the energy and climate package, Poland is obliged to reduce its greenhouse gas emissions by 21% in the years 2013-2020, compared to 2005, and has the potential to increase by 14% emissions from the sectors not covered by the system. In addition, Poland has committed itself to increase, by up to 15%, the share of final energy production from renewable energy sources and, by up to 10%, the share of biofuels in the transport fuel market, as well as to improve the energy efficiency of the economy by 2016, to the level of 9% of the average national final energy consumption. | dab42f7a-b571-4d48-b53b-400456c8b29b | 0 | |
0eb41c07-6875-43ca-8bc1-b2ed3c62d666 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_e2ed2f6c199088dc30a95fddf6e84c72.pdf | 2,023 | [
"emissions",
"data",
"inventory",
"energy",
"emission"
] | cdn.climatepolicyradar.org | The IEF variation is driven by fluctuations in the ratio of coal to petroleum coke inputs and by the ratio of inputs to solid smokeless fuel outputs . The activity data and emission factors for these sources can be found in the accompanying spreadsheet “Energy_background_data_uk_2023.xlsx” help explain the underlying data for these Due to the nature of the mass balance approach used for SSF manufacture, uncertainty in both the estimated carbon content of input products and the carbon content of SSF delivered to market both contribute to a substantial uncertainty in the difference (i.e., the carbon assumed to be emitted during manufacture). This uncertainty is further increased by the range
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 232 of SSF products, including SSF products which include biomass inputs, introducing an uncertainty on the proportion of the carbon which might be biogenic. Non-CO2 emissions for this category only contribute a small proportion of the total emissions, and therefore do not make a major contribution to overall uncertainty
Industrial Processes (CRF Sector 2) 4 UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 233 4 Industrial Processes and Product Use (IPPU; the Approach 1 and Approach 2 analyses. The uncertainty estimate has been taken from Monte Carlo analysis. Emission trends are presented for 1990-2021 and 2020-2021. A description of the trends and the main drivers behind these can be found in processes 32.33 -61% -5% 0% 3% A. Mineral industry 6.08 -41% 10% -2% 1% 1. Cement production CO2 (L1) 3% 4.22 -42% 8% 0% 0% CO2 4.2 T2 CS 3. Glass production 5% 0.34 -17% 5% 0% 0% CO2 4.4 T2 CS
Industrial Processes (CRF Sector 2) 4 UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 234 B. Chemical industry CO2, N2O, HFCs production N2O (T1) 10% 0.03 -99% -36% 0% 0% N2O 4.7 T2 CS production N2O (L1, T1) N/A 0.00 -100% N/A N/A 0% N2O 4.8 T2 CS 5. Carbide production N/A 0.00 N/A N/A N/A N/A N/A 4.10 N/A N/A production 10% 0.16 48% 15% 0% 0% CO2 4.11 CS CS 7. Soda ash production 6% 0.13 -41% -7% 0% 0% CO2 4.12 CS CS carbon black production CO2 (L1) 30% C. Metal industry 8% 10.73 -59% -1% 1% -4%
Industrial Processes (CRF Sector 2) 4 UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 235 production 0.00 N/A N/A N/A N/A N/A 4.17 N/A N/A production 0.06 -92% 6% 0% 12% CO2, production 0.04 -90% 37% 0% 0% HFCs, 5. Lead production 0.00 N/A N/A N/A N/A N/A 4.20 N/A N/A 6. Zinc production 0.00 -100% N/A N/A 0% CO2 4.21 CS CS 1. Lubricant use 0.32 -39% 9% -3% 0% CO2 4.22 T1 CS 2. Paraffin wax use 0.02 -30% -5% 0% 0% CO2 4.23 T1 D
Industrial Processes (CRF Sector 2) 4 UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 236 E. Electronics industry 46% 0.02 75% -7% 0% 0% semiconductor 0.02 75% -7% 0% 0% HFCs, 2. TFT flat panel display 0.00 N/A N/A N/A N/A N/A 4.26 N/A N/A 3. Photovoltaics 0.00 N/A N/A N/A N/A N/A 4.27 N/A N/A 4. Heat transfer fluid 0.00 N/A N/A N/A N/A N/A 4.28 N/A N/A substitutes for ODS(2) HFCs (L2, T2) 10% 10.80 1247% -6% 0% -2% 2. Foam blowing agents 0.35 111% -7% 0% 0% HFCs 4.30, 4.31 T2 CS 3. Fire protection 0.29 19873% -9% 0% 0% HFCs, 5. Solvents 0.02 N/A -1% 0% N/A HFCs 4.34 T1a OTH 6. Other applications 0.03 28% -6% -15% -34% HFCs 4.35 CS CS
Industrial Processes (CRF Sector 2) 4 UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 237 manufacture and use N2O (L2, T2) 59% 1.12 -28% -1% 0% 1% 1. Electrical equipment 0.33 -60% -3% 0% 1% SF6 4.36 T3 CS 4. Other 0.07 N/A N/A 0% 10% N2O, 4.42 CS CS * CH4 emissions from fletton brick production are reported under 2H in the CRF tables, as not possible to report in 2A4 alongside CO2 emissions from this source. ** N2O emissions from 2B8 are reported under 2B10 in the CRF tables ***N2O emissions from 2C1 are reported under 2C7 in the CRF tables
Industrial Processes (CRF Sector 2) 4 UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 238 The industrial processes and other product use sector (IPCC Sector 2) contributes 7.6% to total greenhouse gas emissions. Emissions from this sector include non -energy related emissions from mineral products, chemical industry and metal production and prod uct use, including emissions of F -gases. Since 1990, this category has seen a 60% decline in emissions, mostly due to changes in the emissions from the chemical production and halocarbon and SF6 production industries. The step-change in emissions between 1998 and equipment at the UK’s only adipic acid production plant (this plant has since closed). UK have been declining since 1990. While this is partly due to the closure of some small er sites, perhaps with growth in capacity at remaining sites, it is predominantly a reflection of decreasing production of many industrial materials in the UK. A large number of closures in the period 2007 -2009 were due to decreased demand for many products as a result of the general economic situation in the UK and elsewhere, with falling demand for steel, cement, bricks and aluminium, for example, leading to plant closures. Industrial Processes (CRF Sector 2) 4 UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 239 Emissions of CO 2 from fuels burnt in cement kilns are reported under CRF category 1A2f, whilst emissions from calcination of non-fuel feedstocks are reported under category 2A1. Fuel combustion also gives rise to emissions of nitrous oxide, reported under 1A2f. Emissions of methane also occur, both due to fuel combustion but also due to the evaporation of organic components present in the raw materials. | 70afacf8-8641-4466-819d-f4db8cad9d69 | 305 |
0eb8372a-251c-4361-a64e-1b501cccc5ee | http://arxiv.org/pdf/2505.01115v1 | 2,025 | [
"Climate change",
"policy",
"Integrated Assessment Models (IAMs)",
"multi-objective optimization",
"climate justice",
"equity",
"economic growth",
"trade-offs",
"multi-agent reinforcement learning (MOMARL)",
"policy recommendations",
"deliberation",
"Pareto-optimal policies",
"climate policy",
"scientific reports",
"inequality",
"policy negotiations",
"decision-making",
"climate action",
"sustainability",
"justice",
"framework."
] | arxiv.org | GEO t,n =
N � Y t,n [NET] , GEO t,n ∈ includes additional details. 4.1 Performance Indicators
Evaluating and comparing solution sets in MOMARL is more complex than in single-agent, single-objective RL due to the lack of inherent ordering of solution sets and intertwined performance across objectives. This added complexity leadsto varied evaluation methods in MOMARL. To study convergence, we use two most commonly used approaches from both MORL and MARL domains for their suitability in MOMARL settings and to study the equality of distribution between agents we use GINI index:
GMT t = FAIR
ε t− 1 ,n
�� n∈N
, GMT t ∈ ,
where VECR t , n is a vector of emission control rates adopted by the agents at the previoustimestep that agent n observes at timestep t . Hypervolume ( ↑ ) representsthe region or (hyper-)volume between the points in the solution set and a reference point. The reference pointindicatesthe lower bound for each objective. | 7c3e1d27-98bf-466b-a75e-da988f6e44f0 | 6 |
0ec099f2-f4ce-4d55-a5d5-47f9067cc6e5 | http://arxiv.org/abs/2205.00133v2 | 2,022 | [
"Great Filter",
"Climate Change",
"Earth",
"Humanity"
] | ArXiv | The drip irrigation system (i.e., micro/low-flow/lowvolume/trickle irrigation system), first introduced by Simcha Blass and Kibbutz Hatzerim in 1959, creates a "dripping" system that maintains soil moisture at a fixed level through water-emitting technologies applying droplets and small streams of water to the soil surface/plant roots Water consumption is tightly controlled at up to 90% water-use efficiency while providing a much more effective and efficient way of applying chemicals and fertilizers to the soil. One example of the drip irrigation system is subsurface irrigation (SDI), which similarly irrigates the crop as the drip irrigation system from underground and within the plant root zone for better water delivery accuracy and overall management. With the more developed technologies -e.g., "pumps/pressurized water system, filtration systems, nutrients application system, backwash controllers, pressure control valves (i.e., pressure regulators), pipes (including main pipelines and branching tubes), control/safety valves, poly fittings, accessories, and emitters" [45], the accuracy of water usage can be greatly improved. By reducing deep percolation/evaporation water run-off to near zero decreases in production input, diseases, and the unpredictability of crop growth result while increasing the yield and quality of the finished crops. Furthermore, the drip irrigation systems can be automated and applied across many climates, conditions, and soils (e.g., salinity, sandy, drought, terrains) that other irrigation systems may not adapt to, supporting a wider variety of permanent/non-permanent crops, fruits, and vegetables. The biggest concern regarding the drip irrigation system is the cost. Due to the many instruments needed for this practice, the initial cost of implementation ($800 to $2,500/hectare) can be considerably high. However, in maintaining the practice, fluctuations of the cost may be affected by unpredictable rainfall, climate/soil conditions, damage to wildlife, and the shifting of piping/instrumentation positions. A more recently developed irrigation system, invented in 2011 by Edward Linacre, is the airdrop irrigation system. This technology essentially harvests H2O molecules or moisture droplets from the air through a turbine that drives and cools the air to that of the underground space in a condensation process until it reaches 100% humidity, resulting in condensate formation. The produced water, stored in an underground tank, is then pumped to the roots of the plants during the watering process. Because "the airdrop irrigation system is a low-tech, self-sufficient solar-powered solution," [48] it is suitable for arid and semi-arid land where water shortage presents as a recurring problem, so less water can be used in a more cost-effective manner. Most irrigation system types are currently widely implemented. However, with better economic management and public awareness, improved technologies and instruments can be applied to integrate the overall benefits provided by these systems. By implementing systems such as the drip and airdrop irrigation systems, water usage can be substantially decreased, while the creation of artificial ponds, lakes, and reservoirs can supply farmers with a constant water supply, relieving otherwise persistent water shortage pressures in some regions. Carbon Capture, Utilization, and Storage: While technologies to decrease greenhouse gas emissions are vital to meeting climate goals, negative emission technologies must also be analyzed and considered to formulate the most optimal combination of strategies. Carbon capture, utilization, and storage (CCUS) is a type of negative emission technology (NET) designed to chemically capture CO2 from the atmosphere, concentrate it, and inject it underground or into a storage reservoir. CCUS systems capture CO2 from either the source of emission or from the atmosphere via direct air capture (DAC) and permanently stores the greenhouse gas underground. Globally, approximately 8 gigatonnes of CO2 must be removed annually to stay within the goals mentioned previously corresponding to a relatively safe range of increasing temperature. The low-end cost of $100 per metric ton of CO2 captured and stored is higher than most other mitigation technologies, mainly due to the high levels of energy needed to separate CO2 from the solutes or sorbents used in the capture of the GHG during the chemical process. In addition, captured CO2 as a commodity does not attract a large market. However, there have been recent technological developments such as enhanced oil recovery and synthetic aggregates that could provide a large enough market to lower the cost barrier of CCUS. This negative emission technology requires very little land overall and does not require such land to be arable -one of its major advantages compared to other mitigation technologies. The water usage associated with CCUS depends on the humidity and ambient temperature of the environment [49]. Designating CCUS plants in cooler, more humid climates can minimize the amount of water lost due to evaporation, thus reducing the amount of water needed in the process. As greenhouse gas emissions rapidly increase, it becomes clear that simply reducing emissions will not be enough to reduce the effects of global warming; instead, climate change will only be fully moderated by removing CO2 directly from the atmosphere in combination with converting to renewable energy. In fact, the IPCC states that "all pathways that limit global warming to 1.5 deg C with limited or no overshoot project the use of carbon dioxide removal" [50], emphasizing the importance of implementing carbon capture, utilization, and storage. One of the major benefits of CCUS is its practical land requirements for the system, which would lessen negative impacts on local food production or other land uses. Compared with other mitigation technologies, CCUS plants require much less space. Captured CO2 can also be sold or recycled to bring in revenue and help lessen the cost of carbon capture such as being integrated into synthetic fuels or building insulation. However, as shown in Table 6, carbon capture, utilization, and storage systems require substantial amounts of energy to power equipment and regulate the rate of carbon capture (i.e., 2000kWh/tonne of CO2 removed). One study found that the energy needed to provide enough power and heat to the process to meet the Paris Agreement objectives was approximately a quarter of global energy supplies by 2100 [51]. | d25fea62-8af9-4da1-a686-b2c4ae9b1f46 | 7 |
0ecd7fe8-7117-40bd-9c4b-c815a0e2fdc4 | http://arxiv.org/pdf/2408.14359v1 | 2,024 | [
"climate",
"investment",
"carbon",
"productivity",
"developing"
] | arxiv.org | A major barrier to international cooperation in the realm of international climate action is an apparent lack of fair and just allocation of responsibility between stakeholder groups. Understanding, isolating, and instituting mechanisms to manage incentives against sharing responsibility can go a long way in sustaining effective long-term cooperation. The campaign against climate change has not been all blue skies and fair winds, and differences are beginning to show. Patience runs thin in the face of calls for more deliberate action due to the lack of visible results; national tempers have begun to flare, and widening fault lines are beginning to hamper effective collaboration (Moos & Arndt, 2023). The main aim of this study is to establish whether climate investment demonstrates diminishing marginal return in terms of carbon productivity, and to evaluate the implications for climate action policy. In the interest of brevity and accuracy (given the exclusive use of secondary data) to minimise subjectivity of analysis, this study will be limited to exploring a binary relationship between the magnitude of cumulative investment and the expected (or observed) return on each additional unit of investment. Efforts by developed economies are very well documented, and often tend to be most visible in terms of awareness and scale; our research seeks to leverage this fact by first understanding whether there is a statistically significant relationship between the relative development of an economy and accumulated impact of climate investment, and using said findings to frame a thesis in terms of the international opportunity cost of domestic climate investment as a function of relative economic development. This research has been divided into three minor studies, each building towards a final conclusion regarding the marginal productivity of climate investment, categorised as follows:
1. Assessing the relationship between cumulative impact of domestic climate investment and the domestic state of economic development. 2. Exploring links between accumulated impact of climate investment and the effectiveness of additional investment. For the purpose of this study, carbon productivity will stand in as a relative indicator of the cumulative impact of climate investment, as it is a well-defined and quantifiable metric for which standardised records can be found. In this paper, we use 'the amount of GDP produced per unit of carbon equivalents emitted' (Beinhocker, et al., 2008) as the definition of carbon productivity. Having defined a quantitative proxy for the cumulative impact of climate investment, we now move on to economic development, for which we use Human Development Index (HDI) to stand in for qualitative development and the relative well-being of economic actors. It would be prudent to note that we also considered State capacity, 'the ability of governments to effectively implement their policies and achieve their goals' (Herre, et al., 2023) to stand in for financial and administrative development as a supporting factor. In the real world, economies with high state capacity are likely to exert their influence to improve domestic standards of living; additionally, indicators used to capture a state's administrative capacity may overlap with factors that influence HDI (Hanson & Sigman, 2021). We have therefore chosen to use HDI as the primary indicator of development, in line with conventional practice. We begin by defining each variable and sourcing raw data for a model as follows:
Carbon Productivity = β 0 + β 1 HDI + β 2 SCI + ϵ 1. HDI in arbitrary units, as an Independent Variable (UNDP, 2022) 2. State Capacity Index (SCI) in arbitrary units, as an Independent Variable (Herre, et al., 2023) 3. CO 2 equivalent emissions in kilograms, as a Dependent Variable (Ritchie, et al., 2020) 4. GDP in US$ as a Dependent Variable (World Bank, 2023) 5. Carbon Productivity as a composite Dependent Variable, GDP GHG in US$ per kilogram. Next, we filter the raw data to eliminate inconsistent values (e.g. some combination of HDI, SCI, GDP, etc. absent) and assign each entry a unique (arbitrary) identifier that communicates country name and year of record, using abbreviations sourced with the data; e.g. records for Afghanistan from 2014 will be linked to AFG2014. Building on the distinction between developing and developed economies, we test each to be fitted through a specific regression model, also tested for functional form misspecification using Ramsey's RESET test (see Appendix II for full results). The fundamental argument in favour of a proposition that the cumulative impact of climate investment is linked to the state of economic development lies in the very nature of 'development' as an economic ideal; given the criteria we have applied (HDI and SCI), a developed economy can be defined as one that is allocatively efficient and makes economically optimal decisions. Whether economic optimality emerges from effective markets, strategically sound decisions made in the past, or some combination of geopolitical factors, it stands to reason that high HDI and SCI scores are achieved by considering the economic 'big picture' which ultimately figures into national climate action policy. Further, it stands to reason that relative economic optimality implies greater carbon productivity, whether by means of climate-conscious investment or simply efficient use of resources; carbon productivity is directly linked to wastage in an economy, such that wasteful practices will necessitate higher emissions by requiring greater energy use in the production process, either at the time of output or in producing additional quantities of input. This positive relationship of HDI, SCI, and Carbon Productivity is illustrated through These visuals suggests that developed countries (i.e. those with higher HDI/SCI) tend to have a less consistent correlation between state of development and Carbon Productivity. Further, we may infer carbon productivity as a universal exponential function of development that decays for large development (also see Charts 1.3 and 1.4); consistent with our initial goals, we have chosen to proceed with a two-period framework to assess the strength of correlation between development and Carbon Productivity. | 80ec4f7f-463c-4f27-8650-77ded3256212 | 0 |
0ed1387d-4437-45a9-93aa-7e8ba5fce79b | https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/739460/road-to-zero.pdf | 2,018 | [
"vehicles",
"emission",
"emissions",
"vehicle",
"road"
] | assets.publishing.service.gov.uk | We have committed to providing a greater emphasis on the delivery of chargepoints as part of the rail franchising process in England to incentivise more ambitious chargepoint roll-out by Train Operating Companies. Connecting chargepoints to the Smaller capacity (e.g. home chargers) grid connections will usually be able to be accommodated within an existing network connection. Installers can fit chargepoints and then notify the distribution network operator. Where larger capacity or multiple chargepoints are being installed, a new connection to the network will be needed or an existing connection will need to be Supporting chargepoint installation through building regulations In addition to new domestic buildings, we are also planning to support charging facilities in new non-residential buildings and we will consult on amending Building Regulations to introduce relevant requirements for new non-residential buildings with appropriate associated car parking, to future proof them for chargepoint provision. Since 2010, 1.4 million new customers were linked to the distribution network, including around 16GW of new distributed generation (e.g. wind turbines, solar photovoltaic). The UK’s process of connecting up new customers to the electricity network has been recognised as one of the best of the world; the 2018 World Bank Ease of Doing Business Survey ranked the UK in the top 10 countries worldwide for obtaining a In November 2017 , Ofgem launched its Electricity Network Access project to review how parties get access to the electricity network, the nature of access arrangements arrangements could offer more choice for how consumers gain access to the system, leading to more efficient use of the network. More defined flexible access arrangements could incentivise EV users to allow network operators to constrain access to the network, subject to certain considerations, in return for a reduced connection charge. Changes to network charges could give better signals to users about the cost of using the network at different times and locations and, as a result, support more efficient use of the network. Ofgem is working with industry on options and will consult on their Initial Proposals for Reform In recent years, industry and the regulator, Ofgem, has been working together to strengthen the regime further with the introduction of a range of new incentives and customer engagement mechanisms. Building on the learning from a range of innovation trials, industry has begun introducing ‘smart’ connection offers where the higher cost of investing in conventional infrastructure is avoided by incorporating other technologies such as storage or through actively managed connections. Government has also legislated to help ensure a fairer sharing of costs, help ensure independent connection provides can compete on a level playing-field and streamline the connection quotes service through revisions to the ‘Second Comer’ regime and the introduction of Assessment Electric vehicle batteries have performance guarantees of around 8 years of service or 100,000 miles, depending on manufacturer. There are various second life opportunities for batteries – including in-home storage. One second life application being developed is for batteries to act as home energy storage systems. Nissan are collaborating on a scheme called xStorage with power management company Eaton. The objective of this partnership is to develop energy storage solutions for houses, buildings and commercial facilities that have the capacity to store energy, saving money to the customer and supporting the entire energy system. Users can contribute to the de-carbonisation of the energy supply by storing, consuming or feeding renewable energy back to the grid. The systems also support sustainability by providing a second life for Nissan’s electric vehicle batteries. The Road to Next steps towards cleaner road transport and delivering our Industrial Strategy
As part of the forthcoming call for evidence on last mile deliveries, we will gather further evidence of any potential key network connection infrastructure barriers, which may prevent further uptake of ultra low emission vehicles, specifically for fleet Despite only making up 2% of roads in England, the Strategic Road Network (SRN) England (HE) has a key role supporting the decarbonisation commitments, working with its partners to support a future zero emission road network. As part of the first Road Investment Strategy (2015-2020), HE committed £15 million to ensure that its users are always within 20 miles of a rapid chargepoint along 95% of the SRN in England and are delivering a programme that will install at least 65 chargepoints in 2018/19 to meet the commitment. As a result, drivers can be confident that they will have access to rapid charging capability on long journeys undertaken on the SRN. HE intend to fund the installation of rapid chargepoints that are no more than 2.5 miles or 5 minutes’ drive from the SRN and are undertaking two parallel procurement approaches to i) providing grants to local authorities installing chargepoints at between 15 and 20 locations; and ii) running a competitive procurement exercise that will install chargepoints at the remaining locations required to meet the target. It is vital that our motorways and strategic roads are appropriately equipped for mass EV uptake. Our road network must meet the needs of drivers for use when they are undertaking longer journeys, and to ensure drivers do not become stranded. We expect the market will deliver a large proportion of this, as EV uptake increases, but if regulatory intervention is deemed necessary, the Automated and Electric Vehicles Bill, currently in Parliament, will play an important role in ensuring provision of chargepoints in key locations. This would provide government the powers to ensure sufficient, accessible and appropriate types of chargepoints are available in MSAs and at By their nature MSA tend to be in rural areas with a requirement for rapid charging which means that it can be expensive to provide the additional electrical capacity required to meet future demand. To continue the work of future proofing the Strategic Road Network, we will run a pilot working closely with Highways England to increase electrical capacity at a MSA in the RIS 1 period. | 6f4d6aa6-ed0a-4249-953a-e79443902479 | 30 |
0ed23bb4-95fb-40bf-88da-4a83606e54d2 | 2,025 | [
"european parliament",
"council",
"committee",
"november",
"regions"
] | HF-national-climate-targets-dataset | After consulting the Committee of the Regions, of 25 November 2009 REGULATION (EC) No 1222/2009 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL | 6f8cc1de-2d7b-4a42-b0ee-bf95a3fac48e | 0 | |
0ed3cc7a-0a62-43e4-86aa-eb37366e8038 | https://cdn.climatepolicyradar.org/navigator/GBR/2021/budget-2021_c28084dfc4b588504fe4c17a6d60205c.pdf | 2,021 | [
"Cross Cutting Area",
"Finance",
"Banking",
"Green Bonds",
"Central Bank",
"government",
"support",
"billion",
"million",
"public"
] | cdn.climatepolicyradar.org | Continuing the freeze on alcohol duty will benefit the spirits sector by avoiding an increase of 30p on a 70cl bottle of spirits, while the freeze to fuel duty will support hard-working people across the UK, particularly Strengthening the public finances 3.17 The stability and certainty that come from ensuring the public finances are on a sustainable path will support economic recovery across the UK. 3.18 The Budget takes steps towards this by maintaining certain personal tax allowances and thresholds, while, from 2023, the rate of corporation tax paid by the largest and most profitable businesses will increase. The government’s policy on corporation tax is timed to take effect only when the when the recovery is expected to be durably underway. This is the fair, progressive way to continue to fund public services and provide certainty for people’s jobs, investments and 3.19 Future vaccination strategy – Building on the UK-wide success of our current rollout and approach, the government is investing in UK life sciences to enhance our ability to respond to new variants and get ahead of this and future pandemic threats. This approach gives hope and stability to all UK citizens and businesses as the country builds back • capitalising on the country’s strengths in biosciences, the government is investing £5 million on top of £9 million funding to help create a ‘library’ of mRNA vaccines for COVID-19 variants for possible rapid response deployment, and £28 million to boost the UK’s vaccine
• the government is providing £22 million for new and expanded vaccine studies. This will fund the expansion of the world’s first trial of combining different vaccines as part of a two-dose regime. This will also fund the world’s first study assessing the effectiveness of a third dose of vaccine to improve the response against current and future variants of 3.20 Driving UK-wide investment and innovation – The government is committed to stimulating private sector investment to create jobs, develop hubs of innovation, and revitalise local areas and regions across every part of the UK. Businesses in Scotland, Wales and Northern Ireland will directly benefit from Budget measures such • a new super-deduction, allowing companies to cut their tax bill by up to 25p for every £1 they invest in qualifying new plant and machinery assets, ensuring the UK capital allowances regime is amongst the world’s most competitive • the UK Infrastructure Bank, which will partner with the private sector and local government to increase infrastructure investment to help tackle climate change and promote economic • Help to Management, the government’s new management programme to upskill up to 30,000 SMEs across the UK over three years • Help to Digital, the government’s new scheme to provide free online advice and a discount to adopt productivity-enhancing software that will help up to 100,000 SMEs across the UK save time and money • the £375 million Future Breakthrough, a new direct co-investment product to support the scale-up of the most innovative, R&D-intensive businesses • green energy innovation schemes from the government’s £1 billion Net Zero Innovation Portfolio to support the development of new solutions to cut carbon emissions and accelerate near-to-market low-carbon energy innovation 3.21 Levelling up and empowering all UK communities – Communities in Scotland, Wales and Northern Ireland will benefit from policies aimed at supporting people and places directly, in all parts of the UK. Examples of these policies • the £4.8 billion Levelling Up Fund, which will support local areas across the UK to invest in infrastructure that improves everyday life. This will include regenerating town centres and high streets, upgrading local transport and investing in culture and heritage, ensuring that community assets continue to serve local people across the whole UK • the £220 million UK Community Renewal Fund prospectus launch, providing funding for local areas across the UK in 2021-22 for projects investing in people, communities and • the £150 million Community Ownership Fund, helping to ensure that communities across the UK can continue to benefit from the local facilities and amenities that are most • £27 million, subject to business case, for the Aberdeen Energy Transition Zone, £5 million, subject to business case, in additional support for the Global Underwater Hub and up to £2 million to further develop industry proposals as part of the government’s support for the • £4.8 million, subject to business case, for a Holyhead hydrogen hub, which will create high-skilled green jobs in Anglesey, Wales
• up to £30 million, subject to business case, that the government will match fund for the Global Centre for Rail Excellence in South Wales, which would support innovation in the UK’s rail industry, including the testing of cutting-edge, green technology • the £400 million New Deal for Northern Ireland (NDNI) package, almost half of which has been allocated across four areas, subject to business new systems for supermarkets and small traders to manage new trading arrangements; building greater resilience in medicine supply chains; promoting Northern Ireland’s goods and services overseas; and 3.22 Celebrating the United Kingdom – The Budget celebrates the shared values, culture and institutions that make up the Union, including • £28 million to support the Queen’s Platinum Jubilee event in 2022, delivering a major • £2.8 million to enable a UK & Ireland bid for the 2030 FIFA Men’s World Cup, as well as an investment of £25 million in UK grassroots community sports facilities, supporting the Working in partnership to produce better outcomes 3.23 SR20 confirmed an additional £4.7 billion for the devolved administrations through the Barnett formula in 2021-22, on top of their combined baseline of over £60 billion. The government has also provided £1.4 billion to the devolved administrations in addition to that provided through the Barnett formula. | 51e4a741-ced6-4d30-9268-128e174fffe6 | 30 |
0ed75f84-662d-4249-9ef9-9835013a0275 | https://www.europarl.europa.eu/RegData/etudes/BRIE/2018/621902/EPRS_BRI(2018)621902_EN.pdf | 2,018 | [
"Electricity and heat",
"Industry",
"Energy service demand reduction and resource efficiency",
"Energy efficiency",
"Renewables",
"Other low-carbon technologies and fuel switch",
"Non-energy use"
] | www.europarl.europa.eu | The
900 million backloaded allowances will be placed directly in the MSR. Complementary policies
Emissions from sectors not covered by the ETS, such as road transport, waste, agriculture
and buildings, are subject to the Effort Sharing Decision 4062009EC that sets national
emission targets for the non-ETS sector5 The Renewable Energy Directive 200928EC
seeks to ensure that by 2020 renewable energy such as biomass, wind, hydroelectric and
solar power make up at least 20 of the EUs total energy consumption. The Energy
Members Research Service
Page 3 of 8
EPRS
Post-2020 reform of the EU Emissions Trading System
Efficiency Directive 201227EU sets legally binding rules for end-users and energy
suppliers, and requires Member States to establish indicative national energy efficiency
targets for 2020. | 0c32e5ad-c7d3-49f9-9ee9-a6a3197100b6 | 4 |
0ed86343-ed10-42f4-8eca-38c912ffac9b | http://arxiv.org/pdf/2504.01162v1 | 2,025 | [
"MANILA24 Workshop",
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"Climate Change Impacts",
"Research Problems",
"Collaboration",
"Academia",
"Industry",
"Government",
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"Natural Language Processing",
"Systematic Reviews",
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"Climate Science",
"Technical Research Agenda",
"Climate Modeling",
"Data Science",
"Knowledge Discovery",
"Scientific Research",
"Interdisciplinary Research",
"Climate Change."
] | arxiv.org | This requires effective communication and collaboration. 6 Final Note
Climate change is real. The information retrieval community has a unique opportunity to inform and foster a collaborative ecosystem of researchers and practitioners that contribute to effective information retrieval solutions in support of research and decision-making to help address the reality of climate change impacts. The agenda setting activities of the MANILA24 workshop were meant to do just that. Preparations for MANILA25, the second edition of the workshop, to be held at SIGIR 2025, are well under way, continuing the goal of developing, maintaining, and executing an effective research agenda for information retrieval for climate change impacts. Acknowledgements
We would like to thank the organizers of SIGIR 2024 for hosting the MANILA24 workshop. AAK was supported by the European Union’s Horizon Europe research and innovation programme. GD was funded by the Academy of Finland Digital Water Flagship Project, European Chist Era Waterline Project. LF was funded by the Old Dominion University Division of Student Engagement & Enrollment Services, Graduate Student Travel Award. MH was funded by the Dutch Research Council. SH acknowledges the support of the Australian Research Council Centre of Excellence for the Weather of the 21st Century. | 35b8c024-1d6c-4178-be43-da52ad2ecfd6 | 9 |
0ee3b6c6-c984-42cd-9c21-182505268426 | http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32006L0040 | 2,006 | [
"Transport",
"Non-energy use"
] | eur-lex.europa.eu | Done at Strasbourg, 17Â May 2006. For the European Parliament
The President
J. BORRELL FONTELLES
For the Council
The President
H. WINKLER
(1)
OJ C 108, 30.4.2004, p. 62. (2) Opinion of the European Parliament of 31 March 2004 (OJ C 103 E, 29.4.2004, p. 600), Council Common Position of 21 June 2005 (OJ C 183 E, 26.7.2005, p. 17) and Position of the European Parliament of 26 October 2005 (not yet published in the Official Journal). Legislative Resolution of the European Parliament of 6 April 2006 and Council Decision of 25 April 2006. (3)
OJ L 130, 15.5.2002, p. 1. (4) See page 1 of this Official Journal. (5)
OJ L 184, 17.7.1999, p. 23. (6)
OJ L 42, 23.2.1970, p. 1. Directive as last amended by Commission Directive 2006/28/EC (OJ L 65, 7.3.2006, p. 27). (7)
OJ C 321, 31.12.2003, p. 1. (8)
OJ L 76, 6.4.1970, p. 1. Directive as last amended by Commission Directive 2003/76/EC (OJ L 206, 15.8.2003, p. 29). (9)
OJ L 350, 28.12.1998, p. 1. (10)
OJ L 244, 29.9.2000, p. 1. | d8fef834-b7ca-4a3a-a38f-4da679dc0fb3 | 5 |
0ee7bc24-33e5-4f09-868a-9a55662593ad | https://cdn.climatepolicyradar.org/navigator/GBR/2025/united-kingdom-national-inventory-report-nir-2025_3d22864cf237013c86452d4c6455250a.pdf | 2,025 | [
"emissions",
"data",
"inventory",
"emission",
"used"
] | cdn.climatepolicyradar.org | Also, only the larger ships will tend to do these long-distance journeys, and these larger ships use fuel oil as it is a heavier fuel and 66
UK NID 2025 (Issue 1) Ricardo Page 185 a larger engine is required to use it efficiently. Emission factors are assumed to be the average of all vessels involved in UK international voyages. Data provided by various data sources are assumed to be complete. There have been minor recalculations (less than 1%) to the activity in 2021 due to revised vessel type splits as a result of updated DfT port activity data. Improvements (completed and planned) This emission source was introduced in response to the UNFCCC ERT in 2012. Improvements may be considered in the scope of wider improvements to shipping planned for the inventory This source category is covered by the general QA/QC of the greenhouse gas inventory in Annex 4. There are no official statistical data sets available to verify the information provided for the calculation of these estimates. They are considered to be the best available data. The method approach section above details which years data were available for. Gaps have been filled for the early part of the time -series based on other statistics, to ensure that the inventory is complete for all years. The uncertainty analysis is set out in Annex 2. The uncertainty in this particular source is high although the contribution to the total inventory is low and as such, it does not warrant further research. Estimates are included for completeness, following a recommendation from the
UK NID 2025 (Issue 1) Ricardo Page 186 Relevant Categories, source names 1A3d Inland goods-carrying vessels Motorboats / workboats (e.g. canal boats, dredgers, service boats, tourist boats, river Personal watercraft e.g. jet ski Sailing boats with auxiliary engines The category 1A3dii Waterborne Navigation includes emissions from fuel used for small passenger vessels, ferries, recreational watercraft, other inland watercraft, and other gasoline- fuelled watercraft. Methods for estimating emissions for these small vessels are presented separately here as they are calculated using different approaches to other marine emissions Walker et al (2011), ONS Social Trends, Visit England, OECD Stat, DfT Maritime Statistics (elaborated under Method approach, below). Emission EMEP/EEA 2009, IMO 2015 An accompanying spreadsheet “Energy_background_data_uk_2025.xlsx” lists all emission information for common activity data sources. The Guidelines recommend national energy statistics be used to calculate emissions, but if these are unavailable then emissions should be estimated from surveys of fuel suppliers, vessel movement data or equipment (engine) counts and passenger and cargo tonnage counts. The UK has no separate nati onal fuel consumption statistics on the amount of fuel used by inland waterways in DUKES. However, they are included in the overall marine fuel statistics. A Tier 3 bottom -up approach based on estimates of population and usage of different types of inland waterway vessels is used to estimate their emissions. In the UK, all emissions from inland waterways are included in domestic shipping totals. The methodology applied to derive emissions from the inland waterways sector uses an approach consistent with the 2016 EMEP/EEA Emissions Inventory Guidebook (EMEP, Emissions from individual vessel types are calculated using the following 𝐸 = ∑ 𝑁 × 𝐻𝑅𝑆 × 𝐻𝑃 × 𝐿𝐹 × 𝐸𝐹𝑖
UK NID 2025 (Issue 1) Ricardo Page 187 𝐸 = mass of emissions of pollutant i or fuel consumed during inventory period, 𝑁 = source population (units), 𝐻𝑃 = average rated horsepower, 𝐸𝐹𝑖 = average emissions of pollutant i or fuel consumed per unit of use (e.g. • a categorisation of the types of vessels and the fuel that they use (petrol, DERV or gas • numbers for each type of vessel, together with the number of hours that each type of • data on the average rated engine power for each type of vessel, and the fraction of this (the load factor) that is used on average to propel the boat; and • g/kWh fuel consumption factors and fuel-based emission factors. The inland waterways class is divided into four categories and sub -categories (Walker et al, • Sailing Boats with auxiliary engines; • Motorboats / Workboats (e.g. dredgers, canal, service, tourist, river boats); o recreational craft operating on inland waterways; o recreational craft operating on coastal waterways; • Personal watercraft i.e. jet ski; and • Inland goods carrying vessels. A bottom-up approach was used based on estimates of the population and usage of different types of craft and the amounts of different types of fuels consumed. Estimates of both population and usage were made for the baseline year of 2008 for each type of v essel used on canals, rivers and lakes and small commercial, service and recreational craft operating in estuaries / occasionally going to sea. For this, data were collected from stakeholders, including the British Waterways, DfT, Environment Agency, Maritime and Coastguard Agency (MCGA), As it was only possible to estimate population and activities for one year (2008), proxy statistics were used to estimate activities for different groups of vessels for other years in the household expenditure on "Recreation and culture"67. No data were available for this dataset after 2009, therefore a second dataset was used to estimate the activity from 2010: OECD - ‘Final consumption expenditure of household, UK, • Commercial passenger/tourist craft – Visit Britain, Visitor Attraction Trends in England 2023, Full "Total England Attractions"69. 67 68 69
UK NID 2025 (Issue 1) Ricardo Page 188 • Freight – DfT - Waterborne transport in the goods lifted and moved by traffic type, One of these three proxy data sets was assigned to each of the detailed vessel types covered in the inventory and used to define the trends in their fuel consumption from the 2008 base year estimate to all other years in the inventory. The fuel-based emission factors used for all inland waterway vessels for CH4 were taken from the EMEP/EEA 2009. Emission factors for carbon are from Baggott et al, 2004. For N2O, the emission factor for fuel oil is taken from EMEP/EEA 2009. | 95866fde-5b53-4214-b279-97a1078c466c | 268 |
0eeb5f11-53a7-44e7-8450-c1b84149f8de | http://arxiv.org/pdf/2302.01236v1 | 2,023 | [
"variation",
"using",
"weather",
"exposure",
"heat"
] | arxiv.org | I implement Lasso, NNet, and OLS estimators on a county-level dataset of corn and soy yields from 1990 to 2019. I compare estimates of the elasticity using short-run and long-run variation. I take 500 bootstrap trials of the estimated elasticity, using the three sets of weather variation as in the simulation exercise. Using the simple annual set of weather variables as in Schlenker and Michael J Roberts (2009) and Burke and Emerick (2016), I find that there has been little to no significant adaptation to climate change in corn or soy production. This confirms the results from Burke and Emerick (2016). Using more flexible sets of weather variation, I find that a large share of short-run impacts from damaging heat exposure are offset in the long run. With short-run variation, I find statistically and economically significant declines in yield from a marginal increase in damaging heat exposure. However, I do not find evidence of such declines when using long-run variation. These results hold for both corn and soy. The primary difference comes from using a richer set of weather variables. I make this same conclusion using OLS with the more flexible set of weather variation, although the DML approach results in smaller confidence intervals. This shows that a substantial degree of the short-run impacts from damaging heat exposure are offset in the long run, suggesting substantial adaptation to this heat exposure. This result differs dramatically from the conclusions by Burke and Emerick (2016) and other analyses (Schlenker and Michael J Roberts, 2009;Lemoine, 2018). This is likely explained by model misspecification for the impact of a long-run shift in heat exposure on crop yields. I show that in the panel with long-run variation, the simple model from Schlenker and Michael J. Roberts (2006) does not adequately summarize the flexible role of temperature variables. While damaging heat exposure is correlated with declines in crop yield, other temperature variation is better able to explain these declines. This suggests that there is limited adaptation to some damaging feature of climate change, but not to the specific feature of marginal increase in damaging heat exposure. This paper is related to several literatures. First is a literature on estimating the degree of adaptation to climate change. Measuring adaptation to climate change requires understanding how weather influences economic outcomes. For a review of economics literature on measuring the economic impacts of the weather, see Dell, Jones, and Olken (2014). Hsiang (2016) provides an overview of econometric approaches to measuring these impacts. Much of this literature focuses on agriculture, as this sector is directly exposed to weather and hence is particularly vulnerable to climate change (Shukla et al., 2019). The first approach to studying impacts of climate change used the Ricardian approach, where researchers compare the value of agricultural land in cross sections. Mendelsohn, Nordhaus, and Shaw (1994) forecast the impacts of climate change by regressing average temperature and agricultural property value in a cross section of U.S. counties. This approach is susceptible to omitted variable bias, and subsequent work has focused on addressing specific omitted variables such as endogenous changes in farmer technology (Kurukulasuriya, Kala, and Mendelsohn, 2011) or nonfarm income (Ortiz-Bobea, 2020). Other approaches to estimate the potential for adaptation in agriculture involve economy-wide simulations (Costinot, Donaldson, and Smith, 2016), production changes in historical migrations (Sutch, 2011;Olmstead and Rhode, 2011), natural experiments (Hornbeck, 2012;Hagerty, 2021), or panel approaches. Panel approaches address omitted variable bias by identifying adaptation from annual or longterm variation within a panel dataset. Schlenker and Michael J Roberts (2009) uses panel data to estimate the elasticity of crop yields with respect to extreme heat exposure, and conclude that there is limited potential to adapt to climate change because these damages are similar in the southern and northern U.S. despite climatic differences. Barreca et al. (2016) use a flexible model of temperature exposure to document how the mortality consequences of extreme heat declined over the 20 th century. Burke and Emerick (2016) show that panel variation can be used to estimate adaptation to recent climate change by using separate sources of variation to identify the impacts of weather shocks and shifts in average temperature. Lemoine (2018) provides an alternate approach that partially identifies the degree of possible adaptation by considering the role of ex-ante and ex-post adaptation to heat exposure shocks. My paper is most closely related to Burke and Emerick (2016). Like their paper, I estimate the degree that damages to corn and soy yields from short-run changes in weather are offset over longer exposures. I also use crop and weather data from U.S. agriculture. My approach differs because I consider richer sets of weather variables, and use DML to model learn the relationship between these data and crop yields. I conclude that there has been a higher degree of adaptation to damaging heat exposure. Second is a growing literature on applying ML methods in economics. Kleinberg et al. (2015) discuss applications of predictive machine learning in economics, and Varian (2014) and Mullainathan and Spiess (2017) provide a practical guide to algorithms. Several recent papers have used ML to measure important outcomes in environmental economics. Crane-Droesch (2018) proposes a semiparametric NNet and uses it to study the impact of climate change on corn yields. Deryugina et al. (2019) uses a ML approach to measure the costs of air pollution. Burlig et al. (2020) use ML to refine estimates of energy efficiency improvements. Stetter, Mennig, and Sauer (2022) use a DML approach to measure effectiveness of an agricultural intervention, and Klosin and Vilgalys (2022) introduce a DML approach to measure elasticities in a panel setting. There are also numerous applications within agriculture; for a review, Liakos et al. (2018). My paper is most related to Crane-Droesch (2018) and Klosin and Vilgalys (2022). Crane-Droesch (2018) estimates a NNet that accounts for unobservable county-level fixed effects, and uses the model to predict yield under counterfactual climate change scenarios. | c4cc5be7-4427-416c-9b26-0075eb958e0f | 1 |
0eecc4d6-ddbc-4b7e-a0db-d74b74b5fd07 | http://arxiv.org/pdf/2111.00987v1 | 2,021 | [
"electricity",
"model",
"market",
"energy",
"learning"
] | arxiv.org | In this section, we review the literature that investigates how artificial intelligence and machine learning can be integrated into agent-based models for the electricity sector. To select the related articles to review, we conduct a systematic analysis of relevant research in the field. We limited our search to literature published in the five most recent years (2016-2021). As a result of this, we provide a comprehensive status of the applications of ML and AI in agent-based models for the electricity sector. For this purpose we used the Elsevier Scopus database. To find the articles, we used the following set of search terms to select our articles:
1. Machine Learning, Artificial Intelligence, Deep Learning, Neural Networks, Decision Tree, Support Vector Machine, Clustering, Bayesian Networks, Reinforcement Learning, Genetic Algorithm, Online Learning, Linear regression. 2. Agent-based modelling. We searched using each of the keywords in each of the bullet points. For instance, the first keyword search was: Machine Learning, Agent-Based Modelling and Electricity. The second was: Artificial Intelligence, Agent-based modelling and Electricity. We selected these search terms to focus this review on agent-based models applied to the electricity sector and machine learning, which is the focus of this thesis. These search terms resulted in 149 research articles. However, not all of these were related to our research focus. For instance, a number of electric vehicle, buildings and biological papers were returned. After a further manual review, these 149 papers were reduced to 55 papers which were specifically related to agent-based modelling, electricity, artificial intelligence and machine learning. Figure 2.1 shows the amount of articles published each year between 2016 and the present date. Whilst the number of articles published in this field has increased per year since 2018 to Background and Literature Review 2020, the number of papers published in 2017 was lower when compared to the other years, with a large number published in 2016. We reviewed these 55 papers systematically in the following sections. In this literature review, we make three different market type distinctions: international/national energy market, local energy market and a microgrid. The international/national energy market typically considers a country, multiple countries or the world. A local energy market is a smaller region than the international/national energy market, for instance, a city or region. Whereas a microgrid serves a discrete geographic footprint, such as a university campus, business centre or neighbourhood. Whilst there is some cross-over between a local energy market and microgrid, a microgrid can be disconnected from the traditional grid and operate autonomously. Tables 2.4, 2.5 and 2.6, 2.7 and 2.8 categorise each of the market types respectively. The papers have been displayed in chronological order and categorise the market type, machine learning (ML) type used, the application in which it was used and the algorithm used. These different criteria are explored in the following subsections. Within this work, we have covered five different type of artificial intelligence paradigms. These are: supervised learning, unsupervised learning, reinforcement learning, optimisation and game theory Each of these techniques have been utilised in the papers surveyed. However, a particular focus has been placed on reinforcement learning within the research community. As shown by Figure 2.2, 37 out of the 55 papers used a reinforcement learning algorithm. This greatly outweighs the other machine learning types. The second most used machine learning type was supervised learning, used by eight papers. The fact that reinforcement learning has been used so extensively within the agent-based modelling community for electricity highlights the usefulness of this technique within this field. Within each of the different machine learning types there exist many algorithms. The algorithms used in the papers surveyed are now presented. Within reinforcement learning the deep deterministic policy gradient (DDPG), Deterministic Policy Gradient (DPG) Deep Q-Network (DQN), Deep Q-Learning, Fitted Q-iteration (FQI), long short-term memory neural network (LSTM), Multi-Agent Deep Deterministic Policy Gradient (MADDPG), Markov Decision Process (MDP), Novel WoLF-PHC, Policy Iteration (PI), Probe and Adjust, Q-Learning, Roth-Erev, SARIMAX and Variant Roth-Erev are used. Within supervised learning, the following algorithms were used: Artificial Neural Network (ANN), Bayesian networks, Classification trees, Extreme Machine Learning, Lasso regression, Linear regression and Support Vector Machine (SVM) were used. Fewer algorithms were used for both unsupervised learning and optimisation. For supervised learning, the following algorithms were used: Bayesian classifier, K-Means Clustering, Naive Bayes classifier. For optimisation the following algorithms were trialled: Bi-level coordination optimisation, Genetic Algorithm, Iterative algorithm and Particle Swarm Optimisation. For the game theory method, a game theoretic algorithm was used. Within this work, we classified each paper by the problem domain which they are trying to solve, or the application. The applications are: agent behaviour, bidding strategies, bilateral trading, demand forecasting, demand response, electricity grid control, expansion planning, forecasting carbon emissions, load scheduling, market investigation, microgrid management, peer to peer trading, price forecasting, risk management, scheduling of flexibility, secure demand side management and tariff design. Figure 2.3 displays the number of applications used by each machine learning type. The most utilised application was bidding strategies, with price forecasting and tariff design following behind. However, the bidding strategies application was investigated 27 times, with price forecasting investigated only 8 times. This demonstrates a considerable research effort in this area. Figure 2.4 displays the number of applications per machine learning type area. We can see that bidding strategies is highly used within the reinforcement learning machine learning type. The reinforcement learning algorithm, however, is shown to be highly versatile, with different applications investigated, from demand response, flexibility scheduling to expansion planning. This is due to the ability for reinforcement learning to learn different policies based upon solely the reward and observations within an environment. Within supervised learning, a large amount of research effort has been put into price forecasting. This is likely due to the strong ability of supervised learning techniques at making predictions. However, outside of classification and making predictions, supervised learning is not so versatile, when compared to reinforcement learning. Optimisation is used for five different applications. | d602c796-019d-4603-b326-d7f62c6a33dd | 9 |
0eece0fa-cb69-4522-ace2-7641c8c5e73b | 2,025 | [
"clean coal technologies",
"electricity generation",
"electricity distribution objective b1",
"energy efficiency",
"greenhouse gas emissions"
] | HF-national-climate-targets-dataset | OBJECTIVE E3. LIMITING THE GREENHOUSE GAS EMISSIONS FROM THE USE OF COAL IN ELECTRICITY GENERATION BY IMPLEMENTING CLEAN COAL TECHNOLOGIES AND EFFICIENCY ENHANCING MEASURES OBJECTIVE E4. REDUCING LOSSES AND LEAKS IN ELECTRICITY DISTRIBUTION OBJECTIVE B1. INCREASING ENERGY EFFICIENCY IN BUILDINGS | 09e4a97c-ff3f-4e0a-9af7-4979da5b31c5 | 0 | |
0eefbbe9-246b-49bb-87e4-c574180f9c44 | http://arxiv.org/pdf/2506.20105v2 | 2,025 | [
"Thailand",
"economic growth",
"temperature fluctuations",
"subnational",
"gross provincial product",
"GPP",
"per capita",
"climate",
"Thailand economy",
"1982-2022",
"annual data",
"regional development",
"weather",
"climate change",
"economic impact",
"temperature",
"productivity",
"development economics",
"Southeast Asia"
] | arxiv.org | All models with delayed impacts project that Thailand will lose
95-99% of its output in the absence of climate change, with very unlikely positive impacts. 4.4 Results: projected impacts of climate change at various aggregate levels with bias-correction
To examine the impacts of potentially upward biases in future climate projections, this subsection presents the projected impacts on provincial output per capita using the bias-correction strategy discussed previously. Analogous to Figure
4, Figure 6 A displays the median projected impacts of climate change on provincial output per capita with baseline output growth assumption under RCP4.5 (blue lines) and RCP8.5 (red lines) emission scenarios between 2023-2090. All projections were based on the \" bias-corrected \" differential effect of temperature changes on output growth δ py ′ [, as]
estimated using Equation 12 and regression estimates from the second-order polynomial Equation 6 with no lags and assuming that both high- and low-income provinces respond identically to changes in temperature. Figure 6 A shows the projected impacts of climate change \" with bias-correction \" on output per capita in the \"baseline\"
output growth scenario of each province, relative to its output per capita in the absence of climate change, between
2023-2090, with red lines representing median impacts under RCP8.5 and blue line under RCP4.5. | 204f66ab-3478-4548-97ea-18fe74c73224 | 35 |
0ef16a5a-9d0d-421c-a449-379ae5da0375 | http://arxiv.org/pdf/2409.17378v1 | 2,024 | [
"climate",
"change",
"activism",
"treatment",
"information"
] | arxiv.org | However, those who have previous pro-social behaviors and have contributed to other activist causes unrelated to the environment are not considered in these questions. As younger donors are more likely than older donors to engage in advocacy for an organization or cause (Dorothy A. Johnson Center, 2024) and 70% would rather donate time than money to a cause (Canagarajah, 2021), this subset of non-environmentally engaged volunteers is important to capture. Thus, we add an additional four questions in the same style of the proenvironmental behavior (PEB) questions to capture general pro-social behavior (PSB). Finally, participants respond to a brief set of questions about individual attributes including age, race, gender, and work status. All surveys can be seen in Appendix B. In this section, we present the data used in our analysis, including summary statistics on our participants and details on our independent variables and control covariates. We recruited 367 students from a large, R1 university in the western United States through email recruitment lists. The experiment ran from October 19 to December 19, 2023, through the Qualtrics survey platform. All subjects were informed that the survey was on climate solutions and attitudes and was open only to undergraduate students at the university. Our focus on a student population presents us with a lower bound of observed effect size as students are likely to donate less than other populations in dictator games (Shreedhar & Mourato, 2019). In our sample, 64% are women and 31% are men. The average age of a participant was between 18 to 24 years old and 53% of the sample were full time students only with the rest being partially or fully employed while being a student. Of our sample, only 13% say they never donate to charity while most donate either rarely (33%) or sometimes (40%). 42% of participants report they have never donated to support local environmental protection. In our experiment we used three dependent variables: donation amount (see Figures 1234
We also measured several independent variables before and after the treatment. Before our treatment, we gathered information on individuals' climate literacy and on pre-treatment climate attitudes. Pre-treatment climate attitudes are divided into climate change concern and assuredness. After our treatment and our subsequent attitudes survey and dictator game, we assessed previous pro-environmental behavior, inclusive of environmentally conscious habits such as limiting energy usage all the way to participating in an environmental activism group, and pro-social behavior. Finally, we gathered demographic data and information on people's political leanings, which was determined using a sliding scale that went from zero (the furthest left) to 100 (the furthest right). All variables are presented in Table 1. We used a between-subjects design with exposure to multiple treatments with information and exposure to cross-cutting treatment with protest imagery. Our random assignment of subjects into treatment groups controls heterogeneity in the subject pool, along with our control of the individual attribute variables. Before our regressions, we examined correlations to determine which variables had a statistically significant relationship with one another. Afterwards, to control for heterogeneity in participants, we selected the covariates of participation in climate solutions, gender, political orientation, climate literacy, and the level of climate concern. In our regressions, we were interested in three treatments. First, we have the treatment variable of images of CCL gathering versus images of protest. Secondly, we will have the treatment variable of climate activism information. Thirdly, we will have the combined protest imagery treatment and climate activism information treatment. We then conducted our first analysis: a censored model of a Tobit regression. Donations are measured as a continuous variable between 0 and 30. Afterwards, we used an ordered logit regression to further explore donation behavior, with donations binned into eight different donation groups. For ease of understanding, I will continue to refer to the donation amounts in these bins in number format and the bin number in word format. Seven of these bins were split up into intervals of five for the integers 1 through 30, with the smallest bin, bin one, being 0 alone. From this, we analyzed the treatment effect on the likelihood of people donating within different categorical bins. Finally, to explore the effect of information on climate attitudes, we again used a Tobit regression, censored at the minimum, 5, and maximum, 21, climate concern scores. In this section, we discuss our findings. The section begins with a review of summary statistics and the examination of some general relationships between our variables of interest and independent variables. We then present our findings from our econometric specifications. The section concludes with a discussion of the findings. We find that the average donation was $14.28 or 47.6% of the allocation. We also find that 86.92% of participants donated, with 16.35% of participants donating all their endowment, while 13.08% donated nothing. The median amount given was $15 (18.26% of the sample). The amount donated is higher than expected, though coincides with upper limit of the average donation in previous charitable giving experiments, which ranges from 30% to 50% of the allocation, (Cartwright & Thompson, 2022) though contrasts with the average dictator game donate, which is around 20% of the allocation (Levitt & List, 2007). Yet, what does not coincide with the literature, is how many people gave their entire endowment. In comparison to normal dictator games, in which around 5% of the sample give their endowment (Engel, 2011), or even a charitable giving experiment, where donations seem to be slightly higher at around 6% (Shreedhar & Mourato, 2019), our experiment had over three times that amount give their entire endowment. Figure 2 illustrates the donation amounts from all participants in a histogram. In this histogram, we can also see clustering of donations around intervals of $5, indicating that more people donate in round figures. This follows the natural human behavior to donate in round number intervals, due to round number bias (Coupland, 2011). Next, we consider donations by treatment groups. This is presented in Figure 2. | aeaac3d9-de1d-4d03-acc5-21808f2be1ea | 3 |
0ef287e3-58c1-4eea-b33d-21ab25422dea | https://ec.europa.eu/environment/system/files/2021-11/COM_2021_706_1_EN_ACT_part1_v6.pdf | -1 | [
"Agriculture and forestry",
"Forestry",
"Non-energy use"
] | ec.europa.eu | Facultative measures in letters e to h include on-site inspection and
technical and scientific checks adequate to determine the exact place where the relevant
commodity or product was produced and whether it was deforestation free. Article 19 Reporting
Article 19 outlines Member States reporting obligations regarding the implementation of the
proposed Regulation. This Article builds on Article 20 of the EUTR Reporting, as
subsequently amended by Regulation 20191010, which aligned reporting obligations in
environmental legislation12. Therefore, Article 19 confirms that Member States shall report on
the application of this Regulation on an annual basis paragraph 1 and that the Commission
services will make publicly available, on an annual basis, a Union-wide overview on the basis
of the data submitted by the Member States paragraph 3. Paragraph 2 further qualifies the information Member States are to provide so to strengthen
reporting obligations and to enable the Commission to analyse more accurately the quality of
Member States monitoring activity. | fdc8afd5-2a2d-4946-a4da-be36ebf11749 | 24 |
0ef4726f-6585-4e0c-994a-db79dab55394 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_e2ed2f6c199088dc30a95fddf6e84c72.pdf | 2,023 | [
"emissions",
"data",
"inventory",
"energy",
"emission"
] | cdn.climatepolicyradar.org | Annually, and prior to submission, the National Inventory Steering Committee (NISC) reviews the emissions inventory datasets. The NISC i s tasked with the official consideration and approval of the national inventory prior to submission to the UNFCCC . | 70afacf8-8641-4466-819d-f4db8cad9d69 | 108 |
0ef5a79f-ef7b-4463-aa17-e792cdfdb379 | https://cdn.climatepolicyradar.org/navigator/GBR/2020/the-sixth-carbon-budget_2cb9fc7e21801940b0a9c50cbe4bc1ad.pdf | 2,020 | [
"Waste",
"Transport",
"Economy-wide",
"Energy",
"Adaptation",
"Carbon Pricing",
"Institutions / Administrative Arrangements",
"Energy Supply",
"Research And Development",
"Energy Demand",
"emissions",
"zero",
"carbon",
"budget",
"costs"
] | cdn.climatepolicyradar.org | 37 IPCC (2018) Chapter 3 - Impacts of 1.5°C of Global Warming on Natural and Human systems. 38 Ebi, K.L. et al. (2017) Detecting and attributing health burdens to climate change. Environmental Health Perspectives, 125 (8), 085004. 39 Jones, M. et al. (2020) Climate Change Increases the Risk of Wildfires. 40 IPCC (2014) Summary for policymakers, Working Group 2 - 5th Assessment Report. 41 Alfieri, L. et al. (2017) Global projections of river flood risk in a warmer world. Earth’s Future, 5, 2, 42 Warren, R. et al. (2018) The projected effect on insects, vertebrates, and plants of limiting global warming to 1.5°C rather than 2°C. Science, 360, 6390, 791-795. 43 Arnell, N. et al. (2015) The global impacts of climate change under 1.5ºC, 2ºC, 3ºC and 4ºC 44 Warren, R. et al. ( 2018) The implications of the United Nations Paris Agreement on climate change for globally significant biodiversity areas. Climatic Change, 147 (3-4), 395-409 45 MacDougall, A. et al. (2020) Is there warming in the pipeline? A multi-model analysis of the Zero Emissions Commitment from CO2. Biogeosciences, 17, 2987–3016. 46 CCC (2020) How much more climate change is inevitable for the UK? 47 Climate Action Tracker (2020) Biden’s election could bring a tipping point putting Paris Agreement 1.5 degree limit ‘within striking distance’. 48 Forster, P. et al. (2020) Current and future global climate impacts resulting from COVID-19. Nature Climate Change, 10, 913–919. 49 CCC (2019) Progress in preparing for climate change – 2019 Progress Report to Parliament. Chapter 9: The shape of the emissions path to Net Zero 384 The shape of the emissions path to 1. Delivering on the Paris Agreement 389 2. Supporting the recovery and maintaining momentum 391 3. Making progress in every sector in the 2020s 394 4. Why the recommendation does not require faster progress 408
Chapter 9: The shape of the emissions path to Net Zero 386 Our recommended Sixth Carbon Budget (i.e. a 78% reduction in emissions from 1990 to 2035), requires faster progress prior to 2035 than it does thereafter to 2050. Emissions must fall by an annual average of 21 MtCO2e from 2019 to 2035, then by an annual average of 13 MtCO2e to 2050. As a percentage of the previous year’s emissions, the emissions reduction generally increases over time, given the falling level of remaining emissions (e.g. an emissions reduction that would represent a 10% reduction in 2040 might be a 50% reduction in 2049). The shape of our emissions trajectory is an outcome of our bottom-up scenario construction, reflecting the principles that we have built into them (see Chapter 1). This chapter addresses the question of whether it would be better to act more slowly and benefit later from learnings that lead to lower costs and having longer to scale up solutions. The Committee concludes that it would not be appropriate to act more slowly, reflecting four key considerations laid out in this • The UK’s global contribution. Delivering the goals of the Paris Agreement requires deep global emissions reductions over the next decade as well as reaching global Net Zero emissions of long-lived greenhouse gases (GHGs) in the longer term. To align to the Paris Agreement, UK carbon budgets must reflect the ‘highest possible ambition’ for near-term emissions reduction. This is particularly important given the UK’s role as President of COP26. Minimising the cumulative emissions of long-lived GHGs on the path to Net Zero, alongside ambitious reductions in other GHGs will keep the contribution from UK territorial emissions as low as possible. • Investing for the recovery, and for the future. The changes under our pathways are highly capital-intensive. The required investment programme can help boost the UK’s economic recovery from the COVID pandemic to the benefit of GDP and employment (see Chapters 5 and 6). Record-low interest rates currently provide a further reason to fast-track investments. Investing in low-carbon solutions will ensure that the UK is preparing for the future as the world increases its ambition on climate action. A slower emissions reduction would mean a smaller investment programme and a lower boost to the economy and jobs, with greater risk of stranded assets • Building on current momentum. Our proposed budget would send a clear signal that the UK is open for low-carbon investment. Since the UK set its Net Zero 2050 target in mid-2019, considerable momentum has built in businesses, in local/regional Government, in policymaking and in the UK population at large. Net Zero has brought a clarity that all emissions must go, and that no sector can be left behind. Our proposed budget aims to extend that clarity to the coming 15 years by requiring strong action across every emitting part of the economy. A weaker carbon budget would undermine that clarity, adding risk and costs to businesses looking to support the transition to Net Zero in 2050. • Making progress in every sector. Our bottom-up scenarios (described in Chapters 2 and 3) reflect the challenges and opportunities in every sector of the economy in reducing emissions towards Net Zero. Our pathways reflect the need to make progress to prepare for the 2050 target, and the benefits of making that progress. The pathways see the most rapid emissions reductions over 2025-2035, once opportunities have been created during an initial period to develop low-carbon supply chains, points to rapid action to 2035. the investments to get on track UK businesses investing in low-
387 Sixth Carbon Budget – The path to Net Zero • Cost-saving opportunities. Many low-carbon choices can save money compared to high-carbon alternatives. These include improvements to energy efficiency and resource efficiency across the economy, deployment of wind farms, and a rapid shift towards electric vehicles. We have included deployment of these at a rapid but feasible rate. • Health benefits. Our Balanced Pathway features actions over the next 15 years that would both reduce emissions and have significant benefits to health. | 083c769d-ace3-415a-9bbf-6c9f1540dcd7 | 125 |
0ef7acc5-f999-4f7c-9bab-0bda70d34ff3 | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32018R0841 | 2,018 | [
"Agriculture and forestry",
"Agricultural CH4",
"Agricultural CO2",
"Agricultural N2O",
"Non-energy use"
] | eur-lex.europa.eu | Member States may also use country-specific sub-categories of any of those categories. ANNEX VI
CALCULATION OF BACKGROUND LEVELS FOR NATURAL DISTURBANCES
1. For the calculation of the background level, the following information shall be provided:
(a)
historical levels of emissions caused by natural disturbances;
(b)
the type(s) of natural disturbance included in the estimation;
(c)
total annual emissions estimations for those natural disturbance types for the period from 2001 to 2020, listed by land accounting categories;
(d)
a demonstration of the time series consistency in all relevant parameters, including minimum area, emission estimation methodologies, coverages of carbon pools and gases. 2. The background level is calculated as the average of the 2001-2020 time series excluding all years for which abnormal levels of emissions were recorded, i.e. excluding all statistical outliers. The identification of statistical outliers shall be undertaken as follows:
(a)
calculate the arithmetic average value and the standard deviation of the full time series 2001-2020;
(b)
exclude from the time series all years for which the annual emissions are outside twice the standard deviation around the average;
(c)
calculate again the arithmetic average value and the standard deviation of the time series 2001-2020 minus the years excluded in point (b);
(d)
repeat points (b) and (c) until no outliers can be identified. 3. After calculating the background level pursuant to point 2 of this Annex, if emissions in a particular year in the periods from 2021 to 2025 and from 2026 to 2030 exceed the background level plus a margin, the amount of emissions exceeding the background level may be excluded in accordance with Article 10. The margin shall be equal to a probability level of 95Â %. | 1ac45cba-01c5-4717-9fde-43e6e7fae3e1 | 27 |
0efc3bfa-9b30-4ec0-ae0b-fa2b38646728 | http://arxiv.org/abs/2302.01152v1 | 2,023 | [
"keyword Carbon dioxide emissions",
"Machine learning model",
"Statistical model",
"Prediction",
"Daily"
] | ArXiv | The benefit of statistical models for prediction is that they will work well when the sample size of data is minimal and the data is stable. Also the number of statistical models' parameters that must be determined is quite few compared with machine learning models. However, such statistical models lack a few key power involved with complex predicting tasks based on long and fluctuate time series data. Furthermore, we have observed almost all the researches are based on annual dataset for predicting the next few years' values which we can see as long-term prediction. To fill the gap on the short-term prediction based on univariate daily CO 2 emissions data, we will applied three statistical and three machine learning models for effective prediction of CO 2 emissions, and get the best performing model among them under the evaluation of five performance criteria. The necessary data for this paper is collected from Carbon Monitor project ( which contains 1004 daily near-real-time time series of China's carbon dioxide emissions from January 1st, 2020 to September 30st, 2022, as shown in The research process is divided into three parts and the research framework of this paper is shown in The first part is data preparation. Firstly, we pre-process the collected univariate time series data, including data normalization, data adjustment to model input format, etc. Then, the data are Grey model usually denoted by GM (p,q) where p is the order of the differential equation and q is the number of variables [15]. The most widely used version of Grey model is GM (1,1) model, which will be introduced as follows: Assuming that the primitive time series data X (0) , denoted by where n is the size of data. The accumulated sequence X (1) , defined by the first-order accumulated generating operation of X (0) , denoted by X (1) = (x 1 (1) , x 2 (1) , ...... , x n ( 1) ) where x j (1) = i=1 j x i (0) , j = 1, 2, 3, . . . , n. The generated adjacent mean sequence Z (1) of X (1) is denoted by Z (1) = (z 1 (1) ,z 2 (1) ,......,z n ( 1) ) where z j (1) = x j (1) + x j+1 (1) , j = 1, 2, 3, . . . , n. x j (0) + az j (1) = b, j = 1, 2, 3, . . . , n. is called a GM(1,1) model where -a and b are called the development coefficient and grey action quantity, respectively. Then corresponding whitening equation is: By using least-squares method and initial value x 1 (1) = x 1 (0) , the solution of x j (0) at time j in equation ( 5) is: To get the predicted value of the primitive data at time k, the first-order inverse accumulated generating operation is used to obtain the modeling value: )e a(j1) (1 e a ), j = 2, 3, . . . , n. ARIMA model analyzes and normalizes unsteady time series by adding another process to the ARMA model, where the ARMA model is a mixture of autoregressive model (AR) and moving average model (MA). ARIMA model is one of the most common statistical models used to predict time series data. This model contains three parameters p, d and q, usually denoted by ARIMA (p,d,q) where p represents the lags of the time series data itself used in the prediction model, also known as Auto-Regressive (AR) term; d represents the order of difference that makes the time series data stable, also known as Integrated (I) term; q represents the lags number of prediction errors adopted in the prediction model, also known as Moving Average (MA) term. The mathematical expression of ARIMA model is: where y t is the original time series data; p is the autoregressive coefficient; B represents the backward shift operator; d denotes the order of difference; q is the moving average coefficient; t represents a white noise sequence or error term and it follows a normal distribution with constant variance and zero mean [11]. In particular, ARIMA(p,0,0) is the AR model and ARIMA(0,0,q) is the MA model. The modeling process of ARIMA is as follows: Step 1: Check the stationarity of the time series. By observing the time series diagram and unit root test (ADF), we can determine whether the time series is stationary. Step 2: Stabilize the sequence. For a non-stationary sequence, it can be made stationary by difference operation until the sequence is a non-white noise sequence after d differences. Step 3: Determine the order of the model. The appropriate autocorrelation order p and moving average order q are selected according to the autocorrelation and partial autocorrelation of samples, and then the model is fitted. Step 4: Estimate model's parameters. The least square method is used to estimate the regression coefficient of the sequence. Step 5: Test the model. The residual white noise test and parameter type test are carried out to judge whether the model is reasonable. If the residual sequence is not white noise sequence, then go back to step 3 to re-model until the parameter test and residual white noise test of the model are passed. Step 6: Prediction by the model. The ARIMA model which passes the parameter test and residual white noise test is used to predict the time series. The advantage of the ARIMA model is its simplicity and the disadvantage is that the model requires the time series to be stable, or stable after difference. Specially, the model has a good fitting effect on linear data, but it is not sensitive to nonlinear data and the prediction effect is poor. In this paper, we determine the use of ARIMA (0,1,3) for CO 2 emissions prediction through GridSearch. If the time series data have seasonal fluctuations, then seasonal differences can be added to the ARIMA model to remove them, denoted as SARIMA. | 23cf3297-4e88-43c9-95d5-a0001dae2a9b | 3 |
0efdf181-1aeb-4c3d-8888-b8568f66ed3a | http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32002L0051 | 2,002 | [
"Transport",
"Light-duty vehicles",
"Energy efficiency"
] | eur-lex.europa.eu | 1. (5) OJ L 226, 18.8.1997, p. 1. (6) OJ L 225, 10.8.1992, p. 72. Directive as last amended by Directive 2000/7/EC of the European Parliament and of the Council (OJ L 106, 3.5.2000, p. 1). ANNEX
AMENDMENTS TO CHAPTER 5 OF DIRECTIVE 97/24/EC
1. Annex II shall be amended as follows:
(a) Section 1.4 shall be replaced by the following: \"1.4. \"Gaseous pollutants\" means the exhaust gas emissions of carbon monoxide, oxides of nitrogen expressed in terms of nitrogen dioxide (NO2) equivalent, and hydrocarbons, assuming a ratio of:
- C1H1,85 for petrol;
- C1H1,86 for diesel.\"
(b) the following sections shall be added: \"1.5. \"Defeat device\" means a device which measures, senses or responds to operating variables (e.g. vehicle speed, engine speed, gear used, temperature, intake pressure or any other parameter) for the purpose of activating, modulating, delaying or deactivating the operation of any component or function of the emission control system such that the effectiveness of the emission control system is reduced under conditions encountered during normal vehicle use unless the use of such a device is substantially included in the applied emission certification test procedure. 1.6. \"Irrational emission control strategy\" means any strategy or measure that, when the vehicle is operated under normal conditions of use, reduces the effectiveness of the emission control system to a level below that expected on the applicable emission test procedure.\";
(c) Section 2.2.1.1 shall be replaced by the following: \"2.2.1.1. Type I test (checking the average value of tailpipe emissions in a congested urban area). 2.2.1.1.1. The test is carried out by the procedure described in Appendix 1. The methods used to collect and analyse the gaseous pollutants are those laid down. 2.2.1.1.2. Figure I.2.2 illustrates the routes for type I test. 2.2.1.1.3. The vehicle is placed on a chassis dynamometer equipped with a means of load and inertia simulation. 2.2.1.1.4. During the test the exhaust gases are diluted and a proportional sample collected in one or more bags. The exhaust gases of the vehicle tested are diluted, sampled and analysed, following the procedure described below, and the total volume of the diluted exhaust is measured. Figure I.2.2. Flow chart for the type I test
>PIC FILE= \"L_2002252EN.002601.TIF\">
2.2.1.1.5. Subject to the requirements for 2.2.1.1.6, the test must be repeated three times. The resulting masses of gaseous emissions obtained in each test must be less than the limits shown in the table below (rows A for 2003 and rows B for 2006):
>TABLE>
2.2.1.1.5.1. Notwithstanding the requirements of 2.2.1.1.5., for each pollutant or combination of pollutants, one of the three resulting masses obtained may exceed, by not more than 10 %, the limit prescribed, provided the arithmetical mean of the three results is below the prescribed limit. Where the prescribed limits are exceeded for more than one pollutant, it is immaterial whether this occurs in the same test or in different tests. | ae3cde5f-70ab-4efa-b499-fe02985dd404 | 22 |
0eff829e-b4c0-4b1a-885b-6a73f3614a4e | https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2004:0394:FIN:EN:PDF | 2,000 | [
"Electricity and heat",
"Transport",
"Energy service demand reduction and resource efficiency"
] | eur-lex.europa.eu | The
adoption in 2004 of a Commission proposal for a regulation on the structural and cohesion
funds in the period post-2006, setting new guidelines, will provide an opportunity to better
integrate the environmental, economic and social pillars of sustainable development into
cohesion policy. 34
See Communication from the Commission to the European Parliament and the Council, The
Commissions legislative and work programme for 2004, COM2003645 final of 29 October 2003 p. 5. EN
37
EN
integration
Environmental
towards sustainable
development. | 84e2ea09-1d7f-46b5-b066-7956ace9a8aa | 28 |
0f01cbc9-6aee-47ed-9298-39d2aa36282f | https://committees.parliament.uk/publications/6617/documents/71408/default/ | 2,021 | [
"assembly",
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] | parliament.uk | Business, Energy and Industrial Second Report of Session 2021–22 Report, together with formal minutes relating Ordered by the House of Commons by authority of the House of Commons
Business, Energy and Industrial Strategy Committee The Business, Energy and Industrial Strategy Committee is appointed by the House of Commons to examine the expenditure, administration and policy of the Department for Business, Energy and Industrial Strategy. Darren Jones MP (Labour, Bristol North West) (Chair) Alan Brown MP (Scottish National Party, Kilmarnock and Loudoun) Judith Cummins MP (Labour, Bradford South) Richard Fuller MP (Conservative, North East Bedfordshire) Ms Nusrat Ghani MP (Conservative, Wealden) Paul Howell MP (Conservative, Sedgefield) Mark Jenkinson MP (Conservative, Workington) Charlotte Nichols MP (Labour, Warrington North) Sarah Owen MP (Labour, Luton North) Mark Pawsey MP (Conservative, Rugby) Alexander Stafford MP (Conservative, Rother Valley) The Committee is one of the departmental select committees, the powers of which are set out in House of Commons Standing Orders, principally in SO No 152. These are available on the internet via © Parliamentary Copyright House of Commons 2021. This publication may be reproduced under the terms of the Open Parliament Licence, which is published at Committee reports are published on the Committee’s website at and in print by Order of the House. The current staff of the Committee are Bradley Albrow (Second Clerk), Dawn Amey (Committee Operations Manager), Zereena Arshad (Committee Specialist), Gary Calder (Media Officer), Dr Rebecca Davies (Clerk), Beth Dingley (POST Fellow), John Hitchcock (Committee Specialist), Catherine Kisanji (Inquiry Manager Intern), Becky Mawhood (Senior Committee Specialist), Louise Whitley (Senior Committee Specialist), and Sue Wrightman (Committee Operations Officer). All correspondence should be addressed to the Clerk of the Business, Energy and Industrial Strategy Committee, House of Commons, London SW1A 0AA. The telephone number for general enquiries is 020 7219 4494; the Committee’s email address is beiscom@parliament.uk You can follow the Committee on Twitter using @CommonsBEIS
1 Climate Assembly where are we now? The importance of engagement and education 6 Government progress on public engagement 7 The importance of deliberative engagement 9 Government response to the Assembly 11 The importance of a fair transition 15 Fairness in the Government’s plans for net zero and the Net Zero Review 16 Leadership, coordination and transparency 16 Conclusions and recommendations 20 List of Reports from the Committee during the current Parliament 25
3 Climate Assembly where are we now? 1. In June 2019, the Climate Change Act (2050 Target Amendment) Order 2019 was passed into legislation committing the UK to reduce net emissions of greenhouse gases by 100% (to “net zero”) by 2050 (compared to 1990 levels).1 As a step towards reaching this target, on 21 April 2021, the Government committed to reducing UK emissions by 78% by 2035.2 The Government has stated its intention to publish a Net Zero Strategy before November 2021, which will set out its plan, policy and milestones to achieve the 2050 net 2. In November 2019, the Government accepted the Climate Change Committee’s (CCC) recommendation that HM Treasury should run a Net Zero Review, investigating “how the costs of achieving net zero emissions are distributed and the benefits returned […] across the whole economy”, and “the full range of policy levers, including carbon pricing, taxes, financial incentives, public spending, regulation and information provision”.4 The final report from the Review was originally due in Autumn 2020. An interim report was published December 2020, but the final report is yet to be published. 3. During the 2017–19 Parliament, six select committees jointly commissioned a citizen’s assembly to deliberate on potential pathways to achieve the Government’s net zero target— the statutory target to reduce UK greenhouse gas emissions by 2050.5 Climate Assembly UK (CAUK) was designed to harness the attitudes of an informed public, through a citizens’ assembly, to help both Parliament and the Government gauge public opinion on a wide range of climate change policies and proposals. 4. CAUK was the first such UK-wide Assembly on climate change. It comprised 108 Assembly members randomly selected from across the UK, who were reflective of the UK population in terms of age, gender, geography, and attitudes towards climate change. The Assembly took place across six weekends in early 2020, three in person, with the remainder moved online due to Covid restrictions. Over these weekends, the Assembly members heard talks about climate change from a range of expert stakeholders and researchers, and they discussed and debated potential solutions and policy options. The Assembly members voted on their final recommendations by secret ballot.6 5. CAUK’s report, ‘The path to net zero’,7 was published on 10 September 2020 and sets out the Assembly’s recommendations in eight key policy areas, reducing emissions from travel on land and air, UK’s electricity generation, energy in the home, 1 Climate Change Act (2050 Target Amendment) Order 2019, section 1 . 2 HM Government, UK enshrines new target in law to slash emissions by 78% by 2035 , 20 April 2021 3 HM Government, The Government Response to the Committee on Climate Change’s 2020 Progress Report to Reducing UK emissions , October 2020 4 Climate Change Committee, Net The UK’ s contribution to stopping global warming , May 2019, p 196 5 The six commissioning committees were Business, Energy and Industrial Strategy; Environmental Audit; Housing, Communities and Local Government; Science and Technology; Transport; and Treasury. 6 To find more information about the Assembly’s process and participant selection see Climate Assembly UK, The path to net zero (10 September 2020), p 34–55 7 Climate Assembly UK, The path to net zero (10 September 2020)
Climate Assembly where are we now? 4 things that we buy, food and land-use, greenhouse gas removals, and the Covid-19 recovery. The report also identified underlying principles which should underpin the transition to net zero, including “informing and educating everyone”, “fairness within the UK”, “leadership from government”, and “protecting and restoring the natural world”.8 The Government welcomed the report. | 6c3c9b15-ca44-4dc4-a6ed-3bd9b13e6f48 | 0 |
0f04ea53-9e21-4a3c-821d-e1667279c266 | https://www.legislation.gov.uk/ukpga/2008/27/schedule/2/paragraph/16 | 2,008 | [
"u.k.",
"obligation",
"total amount",
"trading",
"impose"
] | legislation.gov.uk | 16 U.K. The regulations must, for each trading period- (a) set a target for the total amount of the activities, and (b) impose, or provide for the imposition of, an obligation on each participant in relation to the carrying on of a specified amount of the activities in the period. | 5b0cebe9-2641-4278-be2a-a6995ee1051a | 0 |
0f1f29ca-6da1-46c0-aaba-95ae2d7a44e4 | https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1009448/decarbonising-transport-a-better-greener-britain.pdf | 2,021 | [
"transport",
"zero",
"emissions",
"emission",
"carbon"
] | assets.publishing.service.gov.uk | They are easier and cheaper to maintain, and far more efficient to run. While these benefits will be attractive for the private car owner, they could be transformative for the commercial fleets, freight, logistics, bus, Over time, the use of zero emission vehicles will become cleaner still as the use of renewable energy in the UK’s electricity mix continues to increase – the carbon intensity of the grid reduced by over 40 per cent in the last five years alone. | 8f0273a5-decd-4a43-ab49-4f3473699e66 | 45 |
0f20736a-b47a-441b-aae4-7cd6ff225a77 | https://assets.publishing.service.gov.uk/media/677bc80399c93b7286a396d6/clean-power-2030-action-plan-main-report.pdf | 2,024 | [
"solar",
"additional",
"april",
"updated"
] | www.gov.uk | On a sector-by-sector basis, there are specific issues that prevent or delay transport and deployment of supply chain components – most prominently in transmission networks, offshore and onshore wind, where ports, vessels, and abnormal load The wider transition to net zero is expected to support hundreds of thousands of jobs, with Clean Power 2030 playing a key part in stimulating a wealth of new jobs and economic opportunities across the country 125 C C C (2023), ‘A Net Zero Workforce’ (viewed in November 2024). These jobs will cross a range of skill levels and occupations, including technical engineers at levels 4–7 (and particularly 6+ including roles in civil, mechanical, electrical and design), along with electrical, welding, and mechanical trades at levels 2–7, and managerial roles including project and delivery managers at levels 4–7 126 U K Government, ‘What qualification levels mean’ (viewed in December 2024). Many of these occupations are already in high demand across other sectors such as house building, construction, and wider manufacturing, and there also is a relatively high degree of transferable skills and knowledge between many carbon-intensive sectors and clean energy sectors, so wider sectors to clean energy sectors, suggesting workers in carbon-intensive sectors are likely to have many of the skills needed across the Clean Power workforce. The challenge will be in enabling the reskilling of these workers, quickly. of the Clean Energy Skills Challenge’ evidence annex sets out further evidence on key clean energy occupations, gathered
The challenge of finding employees with the right skills to take on these roles is already significant and expected to remain so. Through industry engagement, we have identified several key barriers to securing the • Delivering future skills There are a number of gaps and key occupations that need to be better targeted in the post-16 skills system. Exacerbating the challenge is the high proportion of small and medium sized enterprises in clean energy sectors, some of whom have struggled to engage with the existing skills system. The U K also has an ageing workforce, and many individuals with the skills we need have left the workforce or • Reskilling and Most of the workforce we need for 2030 is already employed, so retraining, upskilling, and increasing the transferability of workers between sectors accessibility of clean power Lack of awareness of green sector jobs is exacerbating role shortages and putting future skills supply at risk. The Learning and Work Institute reported that 87% of 16–24-year-olds did not know what ‘green skills’ were when asked 128 Learning and Work Institute (2023), ‘Skills for a net-zero Insights from employers and young people’ (viewed in November 2024). reducing uptake of skills and training provision. In addition, we are not fully utilising the talent and ambitions of our workforce, for example, only 16.5% of the engineering workforce is female 129 EngineeringU K (2022), ‘Women in Trends in women in the engineering workforce between 2010 and 2021’ - Based on O N S Labour Force Survey data (viewed in December 2024). only 7% of the offshore wind workforce are from non-white backgrounds 130 Offshore Wind Industry Council (2023), ‘Offshore Wind Skills Intelligence Report’ – Based on job record data provided by employers • Regional Several clean energy sectors, like offshore wind and carbon capture, are heavily clustered in specific regions of the U K . With limited data on skills needs, local skills providers are struggling to identify and tailor skills requirements around the rapidly evolving needs of their local areas. They can also find it challenging to respond to these needs given constraints on the teaching workforce and on the availability of facilities and equipment that support clean energy skills development. intensive and clean energy sectors Manufacturing and production sectors ‘Similarity’ refers to cosine similarity, calculated using skills and their prominence across S I C groupings and clean energy sectors. The following traditional sectors are Construction (Section F), Water (Section E), Electricity and Gas Supply (Section D), Manufacturing (Section C), Mining excl. Oil and Gas (S I C 05, 07, 08, 099), Oil and Gas (S I C 06, 091). There may be a small proportion of job adverts which fall into both D E S N Z experimental analysis of Lightcast online job advertisement data (2024). The Clean Energy Job Adverts Charts and Methodology document provides more detail on this analysis. Electricty NetworksHeat and Buildings Smart Systems andStorage Flexibility ‘Similarity’ refers to cosine similarity, calculated using skills and their prominence across S I C groupings and clean energy sectors. The following traditional sectors are Construction (Section F), Water (Section E), Electricity and Gas Supply (Section D), Manufacturing (Section C), Mining excl. Oil and Gas (S I C 05, 07, 08, 099), Oil and Gas (S I C 06, 091). There may be a small proportion of job adverts which fall into both D E S N Z experimental analysis of Lightcast online job advertisement data (2024). The Clean Energy Job Adverts Charts and Methodology document provides more detail on this analysis. We will take action to address these barriers, through broad U K government industrial policy, English skills reforms and through targeted Clean Power 2030 initiatives. Similar approaches are being taken across the devolved governments, such as those outlined in the Scottish Green Industrial 131 Scottish Government (2024), ‘Green Industrial Strategy’ (viewed in December 2024). 132 Welsh Government (2023), ‘Economic priorities for a stronger economy’ (viewed in December 2024). and the Northern Ireland Executive’s Path 133 Northern Irish Executive (2021) ‘Path to Net Zero Energy’ (viewed in December 2024) developers of clean power infrastructure the best chance of securing the supply chains and workforce they need to deliver Clean Power 2030, and we are committed to delivering Clean Power by 2030 in such a way that retains value for money and balances cost considerations with delivery. This starts with giving developers greater clarity and certainty over their routes to market, to enable them to plan and mobilise the supply chains and workforce they need to deliver new generation. | d71959a5-3dfe-4210-9d55-e671cf4f3ce6 | 37 |
0f26525a-3e7c-42b5-ab3d-899de6726609 | https://cdn.climatepolicyradar.org/navigator/GBR/2015/infrastructure-act-2015_fb5ac70eeceb97277b5a2dd914ba86ed.pdf | 2,015 | [
"Energy",
"Transport",
"Cycling",
"Infrastructure",
"Walking",
"section",
"highways",
"strategic",
"company",
"insert"
] | cdn.climatepolicyradar.org | (2) In subsection (1) “specified public body” means a public body which is for the time being specified, or of a description specified, by regulations made by (3) On the date specified by a scheme as the date on which the scheme is to have effect, the designated property, rights or liabilities are transferred and vest in (4) The Secretary of State may not make a scheme under this section unless the specified public body to which the scheme relates has consented to its (5) A scheme under this section may not make provision in relation to land which is held by the Secretary of State and was acquired, or is treated as having been acquired, under section 39 of the Forestry Act 1967 (power to acquire land which is suitable for afforestation or purposes connected with forestry). “designated”, in relation to a scheme, means specified in or determined in accordance with the scheme; “public body” means a person or body with functions of a public (7) This section and sections 333DB and 333DC bind the Crown, but do not have effect in relation to property, rights or liabilities belonging to— (a) Her Majesty in right of the Crown, (b) Her Majesty in right of Her private estates, (c) Her Majesty in right of the Duchy of Lancaster, or (8) The reference in subsection (7) to Her Majesty’s private estates is to be construed in accordance with section 1 of the Crown Private Estates Act 1862. 333DB Further provisions about transfer schemes (a) create for the transferor interests in, or rights over, property transferred by virtue of the scheme,
Infrastructure Act 2015 (c. 7) PART 5 – Planning, land and buildings Document 2023-04-26 This is the original version (as it was originally enacted). (b) create for a transferee interests in, or rights over, property retained by the transferor or transferred to another transferee, (c) create rights or liabilities between the transferor and a transferee or (2) A transfer scheme may provide for the transfer of property, rights or liabilities that would not otherwise be capable of being transferred or assigned. (3) In particular, a transfer scheme may provide for the transfer to take effect regardless of a contravention, liability or interference with an interest or right that would otherwise exist by reason of a provision having effect in relation to the terms on which the transferor is entitled to the property or right, or subject to the liability, in question. (4) It does not matter whether the provision referred to in subsection (3) has effect under an enactment or an agreement or in any other way. (5) A certificate by the Secretary of State that anything specified in the certificate has vested in any person by virtue of a transfer scheme is conclusive evidence for all purposes of that fact. (6) A transfer scheme may contain provision for the payment of compensation by the Secretary of State to any person whose interests are adversely affected (7) A transfer by virtue of a transfer scheme does not affect the validity of anything done by or in relation to the transferor before the transfer takes effect. (a) is done by the transferor for the purposes of, or otherwise in connection with, anything transferred by virtue of a transfer scheme, (b) is in effect immediately before the transfer date, is to be treated as done by the transferee. (9) There may be continued by or in relation to the transferee anything (including (a) which relates to anything transferred by virtue of a transfer scheme, (b) which is in the process of being done by or in relation to the transferor immediately before the transfer date. (10) Subsection (11) applies to any document— (a) which relates to anything transferred by virtue of a transfer scheme, (b) which is in effect immediately before the transfer date. (11) Any references in the document to the transferor are to be read as references (12) A transfer scheme may include supplementary, incidental, transitional and
34 Infrastructure Act 2015 (c. 7) PART 5 – Planning, land and buildings Document 2023-04-26 This is the original version (as it was originally enacted). “enactment” includes subordinate legislation within the meaning of the Interpretation Act 1978; “transfer scheme” means a transfer scheme under section 333DA; “transfer date” means a date specified by a transfer scheme as the date on which the scheme is to have effect. | 079fda04-5438-4ec9-9c30-a7a0396093f2 | 11 |
0f2b1857-22ca-4a39-ab8a-8e60cab32c87 | 2,025 | [
"lower residual emissions",
"low carbon hydrogen generation requirements",
"high innovation scenario",
"aviation",
"buildings"
] | HF-national-climate-targets-dataset | In scenarios 1 and 2, end users of energy such as transport, industry, and buildings are decarbonised extensively, while accounting for residual emissions in aviation and baseline assumptions on the technological potential for carbon capture. In this scenario more optimistic assumptions around carbon capture and aviation, such as the availability of sustainable fuels at scale and zero emission aircraft, cause a divergence from scenarios 1 and 2 in the deployment of certain technologies. With lower residual emissions in aviation and improvement in capture or negative emission potential, end use sectors such as transport, buildings, agriculture and industrial dispersed sites can decarbonise to a lesser extent. This pathway sees electricity and low carbon hydrogen generation requirements in between the two scenarios explored previously, at 670 TWh and 330 TWh respectively. Figure 11: High innovation scenario: residual emissions in 2050 Figure 10: High innovation scenario: energy generation and end uses in 2050 | b9e49080-33d9-43e8-b73d-3242b15a8300 | 0 | |
0f2d5ad9-5bd2-4db9-acc1-ed2aef66e2c3 | https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:1998:0246:FIN:EN:PDF | 1,999 | [
"General",
"Energy efficiency"
] | eur-lex.europa.eu | COMMISSION OF THE EUROPEAN COMMUNITIES
Brussels, 29.04.1998
COM1998 246 final
COMMUNICATION FROM THE COMMISSION
Energy Efficiency in the European
Community Towards a Strategy for the
Rational use of Energy
1. The need for renewed efforts to promote Energy Efficiency
There is an urgent need to reinvigorate commitment both at Community and Member
State level to promote energy efficiency more actively, especially, but not only, in the
light of the Kyoto agreement to reduce C02 emissions. Improved energy efficiency
will lead to a more sustainable energy policy and enhanced security of supply, as well
as to many other benefits. It is important to underline, however, that it will play a key
role in helping the Community to meet its challenging Kyoto target economically. The underlying assumption behind this Communication is that, whilst energy intensity
has decreased slowly but surely over recent years, it is essential to take the necessary
steps to ensure that energy efficiency is substantially improved, and reflected in a
significantly reduced level of energy intensity. The role of Member States and of
regional and local authorities will be crucial in this context as much of the action on
energy efficiency takes place at national level. The Commissions objectives in presenting this Communication at this point in time,
can be summarised as follows
-To underline the economic potential for energy efficiency which exists. -To present both the successes and failures of the policies followed so far, and draw
the necessary conclusions. -To highlight the need for more action at Member State and regional level in parallel
with action at Community level. -To refocus attention on promoting energy efficiency and stimulate discussion
towards a more detailed Action Plan. -To prepare the ground in this specific field for common and coordinated policies and
actions which will need to be undertaken in the light of the Kyoto Agreement. Saving energy has been a stated policy objective of the Community and its Member
States since the first oil crisis in 1973, when energy security became of paramount
concern and saving energy was an important element of the strategy to reduce oil
imports, particularly in a context of high energy prices. However, as these pressures
disappeared, so has much of the effort to improve energy efficiency. A more long-term view of energy demand reduction led in time to the realisation that
it was possible to delink economic growth and energy consumption, allowing GDP
to increase without commensurate increases in energy consumption. Market barriers
and falling prices, however, have limited the scope and extent to which delinking has
occurred, especially regarding the final or end-use of energy. | ad532131-9dd4-4738-9c63-5139bce2852c | 0 |
0f303302-46d9-45c0-b8aa-9f42932bbc12 | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:31998L0069 | 1,998 | [
"Transport",
"Energy service demand reduction and resource efficiency",
"Energy efficiency",
"Renewables",
"Other low-carbon technologies and fuel switch"
] | eur-lex.europa.eu | 2.3.2. On variable-volume enclosures the enclosure must be latched to the nominal volume position. On fixed-volume enclosures the outlet and inlet flow streams must be closed. 2.3.3. The ambient temperature control system is then turned on (if not already on) and adjusted for an initial temperature of 308 oK (35 oC) [309 oK (36 oC)]. 2.3.4. When the enclosure stabilizes at 308 oK ± 2 oK (35o ± 2 oC) [309 oK ± 2 oK (36o ± 2 oC)], the enclosure is sealed and the background concentration, temperature and barometric pressure measured. These are the initial readings CHC,i, Pi and Ti used in the enclosure calibration. 2.3.5. A quantity of approximately 4 grams of propane is injected into the enclosure. The mass of propane must be measured to an accuracy and precision of ± 02, % of the measured value. 2.3.6. The contents of the chamber must be allowed to mix for five minutes and then the hydrocarbon concentration, temperature and barometric pressure are measured. These are the final readings CHC,f, Pf and Tf for the calibration of the enclosure as well as the initial readings CHC,i, Pi and Ti for the retention check. 2.3.7. On the basis of the readings taken in 2.3.4 and 2.3.6 and the formula in 2.4, the mass of propane in the enclosure is calculated. This must be within ± 2 % of the mass of propane measured in 2.3.5.. 2.3.8. For variable-volume enclosures the enclosure must be unlatched from the nominal volume configuration. For fixed-volume enclosures, the outlet and inlet flow streams must be opened. 2.3.9. The process is then begun of cycling the ambient temperature from 308 oK (35 oC) to 293 oK (20 oC) and back to 308 oK (35 oC) [308,6 oK (35,6 oC) to 295,2 oK (22,2 oC) and back to 308,6 oK (35,6 oC)] over a 24-hour period according to the profile [alternative profile] specified in Appendix 2 within 15 minutes of sealing the enclosure. (Tolerances as specified in section 5.7.1 of Annex VI). | 282d51c7-9418-4d78-8dce-aec1567a8b80 | 46 |
0f318403-e864-45c9-971e-fb6b4a70756a | http://arxiv.org/abs/2505.04070v2 | 2,025 | [
"measurement error",
"linear shrinkage estimator",
"optimal fingerprinting"
] | ArXiv | The second structure, denoted as ST , was set to be a separable spatiotemporal covariance matrix, where the diagonals were set to be the sample variances from the climate model simulations without imposing temporal stationarity, and the corresponding correlation matrix was set to be the Kronecker product of a spatial correlation matrix and a temporal correlation matrix, both with autoregressive of order 1 and coefficient 0.1. With the X i , i , , observed responses Y and noisy fingerprints ( X1 , X2 ) were generated from models (1) and ( 2). The regression errors followed a multivariate normal distribution N (0, ). The distribution of the measurement error i for Xi , i {1, 2}, was N (0, n 1 i ) with (n 1 , n 2 ) = (35, 46), consistent with the number of simulation runs in a two-way detection and attribution analysis of the annual mean temperature conducted by Ribes et al. (2013). Control runs Z 1 , . . . , Z m were generated independently from N (0, ) with sample size m {50, 100, 200, 400}. Here m = 50 is typical in OF studies, and m 200 is possible but not easily obtained unless runs from different climate models are pooled, ignoring the model structure differences. For each combination of , and m, we performed 1000 simulation replicates to evaluate the performance of the proposed method with optimally selected tuning parameter , denoted as "Optim", in comparison with two existing ROF methods based on TLS. The first competitor, denoted as "LS-CB", adopts the ROF method of Allen & Stott (2003) with a linear shrinkage estimator LS by Ledoit & Wolf (2004) for prewhitening (LS) and a calibration bootstrap (CB) for interval estimation (Li et al. 2021). The second, denoted as "MV-CB", applied the minimum variance estimator MV from Li et al. (2023) with the same CB adjustment for constructing confidence intervals. For the proposed method "Optim", we constructed the confidence interval from the newly proposed asymptotic results. Since LS falls into the class of linear shrinkage estimators defined in Section 2, our asymptotic results also apply to this setting. As an additional benchmark, we included an uncalibrated version of the ROF method with LS , denoted as "LS". The corresponding confidence intervals were constructed from the same normal approximation as our proposed method. Confidence intervals are essential in detection and attribution studies. Ideally, they should be as short as possible while maintaining empirical coverage rates close to the nominal level. To assess performance, we focus on two key metrics, empirical coverage rate and interval length. Here, we present in Figure 1 the empirical coverage rates and average lengths of the 95% confidence intervals derived from the four competing methods: Optim, LS, LS-CB, and MV-CB, for the ANT forcing, which is usually the main concern in detection and attribution analyses of climate changes. Full numerical results for both ANT and NAT forcings are provided in Table S1 of the Supplementary Material, which demonstrates that all methods yield unbiased point estimates of the scaling factors. For confidence intervals, our proposed method for estimating the asymptotic variance of the scaling factors estimators leads to empirical coverage rates consistently close to the nominal 95% level across nearly all settings. Even in the most challenging case with only m = 50 control runs, the coverage rate remains around 91%, supporting the accuracy of our estimated asymptotic variance. In contrast, both calibrated competitors (LS-CB and MV-CB) still suffer from undercoverage issues in proposed Optim method offers valid confidence intervals with near-nominal coverage and competitive or superior interval widths across a wide range of realistic scenarios. In addition, it also offers substantial computational advantages over calibration-based approaches, as it estimates the asymptotic variance without requiring any bootstrap procedure. To demonstrate the performance of proposed methods in real-world applications, we conducted a detection and attribution analysis of changes in the mean near-surface air temperature at global (GL), continental and subcontinent scales over the year period 1951-2020, utilizing the latest available climate observations and simulations. Following Zhang et al. (2006) and Li et al. (2023), we considered several regions: at the continental scale, Northern Hemisphere (NH), NH midlatitudes (NHM) between 30 and 70 , Eurasia (EA), and North America (NA); and at the subcontinental scale, Western North America (WNA), Central North America (CNA), and Eastern North America (ENA), where spatio-temporal correlation structures are more likely to hold. Detection and attribution analyses for two external forcings, anthropogenic (ANT) and natural (NAT) forcings, were conducted for each region. For each regional analysis, Models (1)-( 2) require three components: the observed mean temperature Y R N , the estimated fingerprints XANT and XNAT , and independent control runs Z 1 , . . . , Z m for estimating the covariance matrix . We first obtained the observational vector Y from the latest HadCRUT5 dataset (Morice et al. 2021), which provides monthly anomalies of near-surface air temperature from January 1850 on 5 x 5 grid boxes relative to the 1961-1990 reference period. At each grid box, annual anomalies were computed from monthly values provided that at least nine months of data were available within a given year; otherwise, the annual mean was marked as missing. Nonoverlapping 5-year averages were subsequently calculated, requiring no more than two missing annual values within each 5-year period. After removing the 1961-1965 period due to centering, 13 values of 5-year averages were obtained per grid box. To reduce spatial dimensionality for the global and continental-scale analyses, available 5 In particular, the fingerprints XNAT for the NAT forcing were obtained directly by averaging over 40 available runs. For the ANT forcing, which is typically the primary focus in climate detection and attribution studies, direct simulation outputs were not available from CMIP6 models. Under the linear additivity assumption, X AN T = X GHG + X AER (Zhang et al. 2006), we constructed XANT by combining the greenhouse gas and aerosol fingerprints for each model. | 8a57ffce-ee1f-4297-957b-962ed53df2e8 | 4 |
0f363985-85a5-4a97-818a-34194888898e | https://www.ecolex.org/details/legislation/carbon-accounting-scheme-scotland-amendment-regulations-2017-ssi-no-121-of-2017-lex-faoc165823/?type=legislation&xsubjects=Mineral+resources&page=494 | 2,017 | [
"energy",
"development",
"article",
"management",
"protection",
"water",
"measure",
"environment",
"consist",
"resource"
] | ecolex.org | These Regulations amend the Carbon Accounting Scheme (Scotland) Regulations 2010 by inserting a new regulation 8B so as to provide a method for determining whether a carbon unit is to be credited to or debited from the net Scottish emissions account in respect of the relevant period for 2014 and by inserting a new paragraph (5) into regulation 9 (register of transactions) so as to set out the information to be included in the register for 2014. | 07850b4d-acf6-4f7d-8063-d44d5a73ff60 | 0 |
0f3a5e13-39b8-4977-a540-4a36879497a9 | http://arxiv.org/pdf/2506.13994v1 | 2,025 | [
"CMIIP",
"global climate models",
"GCMs",
"climate models",
"intercomparison",
"climate change",
"climate assessment",
"research",
"science",
"data",
"projections",
"atmosphere",
"ocean",
"Earth system",
"models",
"analysis",
"prediction",
"warming",
"greenhouse gases"
] | arxiv.org | One prominent example of persistent uncertainty in climate science is the assessment of the equilibrium climate sensitivity (ECS), a crucial metric for gauging the response of the climate system to radiative forcing. From Charney et al. to AR6, the ECS uncertainty range has remained relatively unchanged
— if not broadened — as illustrated in Figure 5A. This persistent uncertainty underscores unresolved methodological and scientific challenges. Consensus-based arguments also risk logical fallacies, such as appeals to popularity or authority. In fact,
many individuals, including researchers in climate-related fields, may accept the IPCC conclusions without critically engaging with the uncertainties highlighted within the IPCC’s own reports. Consequently, reliance on such forms of “ consensus ” does little to resolve the crux of the climate debate regarding whether human activity accounts for 100% of observed warming between 1850–1900 and 2011–2020, as asserted by AR6, or whether a more moderate contribution might better align with actual scientific findings. If the latter opinion holds, the projected 21 [st] -century warming based on the CMIP5 and CMIP6 GCMs would be substantially lower, mitigating assessments of future climate change risks and hazards. The following subsections delve into key scientific open issues that question the reliability of the GCMs
and directly challenge the AGWT. These open key issues continue to be debated in the scientific literature. 3.3 The impossibility of testing the main prediction of the GCMs
The scientific method necessitates that the hypotheses, including physical models, are rigorously tested to ensure that their predictions align with empirical evidence. When evidence supports a hypothesis, the model may be retained; however, when results challenge it, the model must be discarded or revised, requiring the formulation of anew hypothesis or model. As discussed in Section 2 and illustrated in Figures 1B and 1D, the claim that human activity accounts for approximately 100% of the observed warming from 1850–1900 to 2011–2020 is derived solely from the climate simulations of the existing GCMs. These simulations rely on specific radiative forcing functions, which are assumed to be complete and accurate. However, the only tangible evidence is that there is no data fully con firming the main GCM prediction. More specifically, no data exists to demonstrate that, absent anthropogenic
forcing, the Earth’s climate would have remained stable from 1850–1900 to the present. Thus, such critical prediction of the GCMs cannot be empirically validated, as there is no “ twin Earth ” devoid of human influence from which to obtain the necessary data. Consequently, the absence of such data — as also reflected in Figures
1B and 1D — highlights the key limitation in the validation of these models. Therefore, the AGWT remains a hypothesis contingent upon the reliability of the current GCMs, which can only be “assumed” but not “proven” correct. | c118d41e-0f6f-4d15-bab3-659618775684 | 14 |
0f3bd4f8-d0d7-4196-ad71-b0b32f99e595 | http://arxiv.org/pdf/1902.01398v1 | 2,019 | [
"economy",
"business",
"world",
"people",
"social"
] | arxiv.org | Capitalism has reached its 'use by' date and a growing number of people can sense the fundamental flaws in the for-profit story. There are certainly holes in the plot, but what are those holes? And how do they lead to the dysfunction we're seeing in today's economy? The for-profit story and our economic system are completely interdependent. The for-profit story supports the capitalist economy and vice versa. This means that we cannot have truly systemic change without also reshaping the underlying stories that support and validate the system. The most obvious way in which the for-profit story and economic behavior mutually reinforce each other is through the profit motive; the notion that economic behavior is the result of individuals seeking to accumulate as much financial wealth as possible. This manifests in capitalists investing in whatever will give them the highest return on investment. It can be seen in the job market, with job-seekers looking for jobs with the highest salaries. It also plays a role for some employers, who will try to pay employees as little as possible without losing them altogether. And it can be observed in shoppers always on the lookout for the best bargains. This leads us to the protagonist of the for-profit world: Economic Man, also known as Homo economicus. Homo economicus represents the idea that individuals are naturally inclined to make economic decisions based on maximizing their own self-interest. Although the term was not used until the 19 th century, it has its roots in the earliest modern economic theories. 237 In 1776, Adam Smith, the 'father of capitalism' wrote, "It is not from the benevolence of the butcher, the brewer, or the baker that we expect our dinner, but from their regard to their own interest." 238 In an 1836 essay, early economist John Stuart Mill described man as "a being who inevitably does that by which he may obtain the greatest amount of necessaries, conveniences, and luxuries, with the smallest quantity of labour and physical self-denial with which they can be obtained." 239 This notion that people base their decisions and behavior on personal gain is pervasive in society. It implies that if you are smart, then you will look at how you can gain as much money as possible (as in the case of investors, shareholders and employees) or how you can lose the least money possible (as in the case of employers and consumers). Paying more than the lowest possible price for something is considered foolish behavior. Yet, if you are a seller, not getting paid the highest possible price for a good is considered equally foolish and even weak. That's the profit motive at work. That's the engine of our economy. But is this really the best way to run an economy and to motivate economic activity (and behavior more generally)? Is it reasonable to hold as a common belief that the smartest people in society are those who take the most for themselves? That the most intelligent are the greediest? What does that say about generous people? On closer inspection, it becomes very clear that when private gain is the primary source of motivation in the economy, people tend to make very selfish decisions that may provide a financial gain for them, but at a cost to the wider community. Take the example of an oil drilling company that, in order to save money, doesn't update its safety measures, risking the lives of its employees as well as the health of the natural environment in which the company is drilling. Or think of a car manufacturer that lies about its cars' emissions in order to boost sales and maximize profit. The profit motive also sets the stage for very unhealthy norms in corporate culture. In publicly-listed companies (i.e. -companies traded on the stock exchange), CEO compensation often depends on share price rather than any other indicators of performance. This detaches performance from real world value creation. In other words, a financial company can be trading toxic financial instruments that harm its own customers, not to mention undermine the entire economy, but if it raises share prices in the next quarter xxi , the CEO will be handsomely rewarded. This was demonstrated very clearly in the U.S. Congressional hearing of Lehman Brothers' CEO, Richard Fuld, who received over $480 million, mostly in bonuses, from 2000-2008, while the company was going bankrupt. 240 Lehman Brothers was the first big financial company to declare bankruptcy in September 2008, triggering the global economic crisis. These Congressional hearings did an important job in questioning the ethics and fairness of Wall Street CEOs taking so much money home, just because share prices were going up. What the hearings failed to note is that this sort of greed and short-termism is built into the very fiber of the profit motive. Although it's easy to point fingers and declare these actions unethical, and label these people a few 'bad apples', this sort of behavior is actually just the rational thing for business managers to do, according to the for-profit story. It naturally flows from the for-profit worldview. If we want systemic change, we need to take a deeper look at the rules of the game, and not get caught up on blaming the individual players. Perhaps people like Fuld are greedy sociopaths, but it's not a coincidence that they're the winners of our economic game. The profit motive was guiding them 100% of the way. They are the epitome of 'rational economic actors' being motivated by the accumulation of private profit and selfinterest. Indeed, they are playing by the rules of capitalism very well. It is a paradox of society to hold the profit motive as a central tenet of business, and then call people who succeed through maximizing personal gain 'greedy', when it would be exceptional for them not to be. Think of Monopoly, the ultimate capitalist board game, where the goal is to win by accumulating the most money and property on the board. | 7aa7f968-38f8-4177-8669-ac6d65db7e5a | 30 |
0f465cfb-b06e-4283-b4d6-2f4792b3bd45 | https://cdn.climatepolicyradar.org/navigator/GBR/1900/united-kingdom-biennial-report-br-br-4_3ed9930a9ceb3d956a389f73b35d0ba4.pdf | 2,021 | [
"climate",
"energy",
"committed",
"emissions",
"grant"
] | cdn.climatepolicyradar.org | Other sectors 110,222.36 1,568.92 393.08 112,184.36 5. Other 5,293.44 3.56 56.12 5,353.12 B. | 025a518f-ffd4-4f95-b5a2-b6052b167c0d | 194 |
0f4e18bb-24a1-4f5e-909f-f0a54ec23e07 | http://arxiv.org/abs/1911.12257v3 | 2,019 | [
"largest comparable plant vegetation models",
"future climate change",
"previous time step t.",
"simulation study",
"destination grid cell"
] | ArXiv | We filtered out those species with only a single recording point in the underlying GBIF data as they were too data deficient, leaving a total of 39,158 species recorded at least twice in Africa. The climate preferences were extracted from GBIF and ECMWF reanalysis datasets at the time and location of the GBIF record, corrected by sampling effort at that spatial location (C. Harris et al., 2021). We took the mean and standard deviation of the temperature and rainfall preferences as the niche mean and niche width for each species. There is little available information on requirements for solar energy and water for most plant species, so we took the environmental conditions they were exposed to as a proxy, assuming that they used all available resource in the areas they were found. Thus, we used the extracted information on resource needs for soil water volume and surface solar radiation, corrected for effort as in the niche preferences. Finally, we used randomised reproduction, mortality and dispersal parameters for this example as this information is unavailable for most plant species. To validate the model, simulations of small-scale ecosystem patches and islands were conducted. These were equal in size and seeded with 100 species / 100km 2 , but boundary conditions differed: islands had hard boundaries that species could not disperse beyond, whereas patches were toroidal and species could disperse in all directions. We set up each example with constant background temperature and ran each simulation for 10 years. We then expanded the case study to a grid with 80km squares and a total area similar to that of a continent. Using this continental backdrop, we investigated how quickly species could colonise large areas, whether they were previously populated or not. In order to initially seed the Africa simulations, we began by filling the ecosystems with the overall summed counts of each GBIF record according to the locations at which they had been previously found. These counts were adjusted by the availability of resource in each grid square, so that the ecosystem began with a number of individuals close to the equilibrium. Then we ran the simulations backwards in time from 2018 to 1901, adding in each species record at each location at the date it was recorded. This enabled us to simulate a baseline for plant diversity in 1901 from which to start the simulations, which could not be gained from a burn in forward through time. The number of individuals of each species added at each time point was scaled by the inverse of collection effort. This correction ensured that both under-and over-collected areas were seeded with similar numbers of plants despite dramatically different sampling efforts. Once the simulations reached 1901, they were cycled through this same year 10 times in order to ensure they were fully equilibrated. From this starting point, we ran the ecosystems ran through the full monthly climate history through to 2018. We performed 10 stochastic realisations, which was chosen after considering the computational expense of the simulations. We confirmed that abundance depends on available resources , here on an island ecosystem with two resources, water and sunlight, each on a gradient West to East and South to North, respectively. All species were seeded with the same resource requirements and vital rates. Abundance increased in cells with more water and sunlight, with some edge effects. As expected, abundances were invariant to the grid resolution , and ecosystems with greater areas could also support more individuals . We also tested ecosystems seeded with varying numbers of species, and similar numbers survive until the simulation ends in each case . Figure 6 shows overall abundance on an island with two species at opposite sides of the island after ten years of simulation: species with higher average dispersal distances moved faster and further into the unpopulated centre. We tested whether individual species' niche preferences and widths functioned as expected, on a small patch with species given different niche preferences and all other parameters kept equal. When all species had equal niche widths, species with niche preferences nearer the 25 C optimum were more abundant ; when all species had a preference for 25 C and varying niche widths, generalists with broader niches were less abundant than specialists with narrow niches . This is expected given the decline in species' match to their optimum environment as niche width increases in Figure 3B. However, if temperature was then increased by 1 C, species with narrowest niches went extinct, and generalists became more abundant , with a preference for species with a niche width of around 1 C, as predicted in Figure 3D. EcoSISTEM was designed to scale to much larger areas, supporting many more species. To illustrate this, we simulated 50,000 plant species at an 80km grid scale over a circular "continent" 8,000km across, with a constant environment of 25 C. When all species have equal fitness in the habitat, all 50,000 co-exist over long time scales of over 100 years . We also explored the selective advantage of invasive species: introducing an invasive with a narrow niche width tuned to the environment into an continent-sized landscape with an existing generalist, the invasive out-competes the generalist and spreads across the continent. Here, we define selective advantage as the difference in niche width between the invasive and generalist. The larger the invasive's selective advantage, the faster it will invade and colonise the landscape . When we simulate 50,000 generalist species coexisting across a landscape and introduce a single competitive invasive, the invasive can out-compete the local established populations . Figure 8D shows the Shannon entropy of communities within individual grid squares, using the Diversity package (Reeve, 2021a). The invasion centre-point, where the invasive dominates, is the most uneven species distribution, with a single species dominating whereas outside, every species coexists. The strength of competitive interaction can be adjusted so that invasives and generalists coexist in the system. | bc1a236e-d609-4b23-8f5b-dc9b1b218512 | 3 |
0f4f7a09-a59a-40ae-81b4-b65ea8d20406 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/financial-services-and-markets-act-2023_932920a8d8da4ed5a2456d9109b47a62.pdf | 2,023 | [
"Finance",
"changes",
"force",
"section",
"financial",
"services"
] | cdn.climatepolicyradar.org | (2) A variation instrument is an instrument that makes provision to reduce or cancel a variation margin payment that a CCP would have otherwise paid to a clearing (3) The power under this paragraph may be exercised only for the purpose of recovering losses arising as a result of a clearing member defaulting on the member’s obligations (4) The power under sub-paragraph (1) does not apply to a clearing member— (a) which falls within Article 1(4) or (5) of EMIR, or (b) in relation to which a direction under regulation 3(1)(f) of the Equivalence Determinations for Financial Services and Miscellaneous Provisions (Amendment etc) (EU Exit) Regulations 2019 (S.I. 2019/541) is in force. (5) In this paragraph, a “variation margin payment” means a payment reflecting an increase in the market value of a clearing member’s position in the market. I629 Sch. 11 para. 33 not in force at Royal Assent, see s. 86(3) I630 Sch. 11 para. 33 in force at 31.12.2023 by S.I. 2023/1382, reg. 8(b) 34 (1) The seventh stabilisation option is for the Bank to make one or more write-down (2) A write-down instrument is an instrument that makes any of the following provision (or any combination of the following)— (a) provision cancelling an unsecured liability owed by the CCP; (b) provision modifying or changing the form of an unsecured liability owed by
Financial Services and Markets Act 2023 (c. 29) SCHEDULE 11 – Central counterparties Document 2025-04-01 This version of this Act contains provisions that are prospective. Changes to Financial Services and Markets Act 2023 is up to date with all changes known to be in force on or before 01 April 2025. There are changes that may be brought into force at a future date. Changes that have been made appear in the content and are referenced with annotations. (See end of Document for details) View outstanding changes (c) provision that a contract under which the CCP has an unsecured liability is to have effect as if a specified right had been exercised under it; (d) provision under paragraph 35(1). (3) The power under this paragraph may be exercised only for the purpose of recovering losses arising otherwise than as a result of a clearing member defaulting on the member’s obligations to the CCP. (4) The power under sub-paragraph (2) may not be exercised so as to affect the following (a) liabilities to employees or workers, including liabilities owed to a pension scheme in respect of those persons; (b) liabilities to commercial or trade creditors arising from the provision to the CCP of goods or services that are critical to the continuity of the CCP’s (c) HMRC debts which are preferential debts within the meaning of section 386 (d) liabilities to designated systems, operators of designated systems, or participants in such systems to the extent that the liabilities arise from their (e) liabilities to interoperable CCPs; (f) liabilities to central banks; (g) liabilities to clearing members so far as these relate to initial margin (h) liabilities to small enterprises. (5) The reference to modifying a liability owed by the CCP includes a reference to modifying the terms (or the effect of the terms) of a contract under which the CCP (6) The reference to changing the form of a liability owed by the CCP includes, for (a) converting an instrument under which a CCP owes a liability from one form (b) replacing such an instrument with another instrument of a different form or (c) creating a new security (of any form or class) in connection with the modification of such an instrument, or (d) converting those liabilities into securities issued by the CCP or a bridge central counterparty or UK parent of the CCP. (7) The Treasury may by regulations amend sub-paragraph (4) by— (a) adding to the list of liabilities; (b) amending or omitting any liability listed. (8) Regulations under this paragraph are subject to the affirmative procedure. “designated system” has the meaning given by regulation 2 of the Financial Markets and Insolvency (Settlement Finality) Regulations 1999 (S.I. 1999/2979) as amended from time to time;
284 Financial Services and Markets Act 2023 (c. 29) SCHEDULE 11 – Central counterparties Document 2025-04-01 This version of this Act contains provisions that are prospective. Changes to Financial Services and Markets Act 2023 is up to date with all changes known to be in force on or before 01 April 2025. There are changes that may be brought into force at a future date. Changes that have been made appear in the content and are referenced with annotations. (See end of Document for details) View outstanding changes “initial margin requirements” means margins provided by clearing members to a CCP to cover the CCP’s potential future exposure in the event “small enterprise” means an enterprise which employs fewer than 50 people and whose annual turnover or annual balance sheet total does not I631 Sch. 11 para. 34 not in force at Royal Assent, see s. 86(3) I632 Sch. 11 para. 34 in force at 31.12.2023 by S.I. 2023/1382, reg. 8(b) Powers in relation to securities 35 (1) A write-down instrument may— (a) cancel, transfer, dilute or modify any securities to which this sub-paragraph (b) convert any such securities from one form or class into another. | 60620217-7ea8-4d25-b12c-cbbb5bd7a3f3 | 131 |
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