id stringlengths 36 36 | url stringlengths 0 422 | year int64 -1 2.03k | keywords listlengths 0 27.8k | source stringclasses 47 values | text stringlengths 0 53.4k | doc_id stringlengths 36 36 | chunk_num int64 0 503 |
|---|---|---|---|---|---|---|---|
0bce8be3-af69-45f3-b358-61b18e37e3bb | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_8122f7d823bf366105239091fb57ffd2.pdf | 2,023 | [
"data",
"energy",
"emissions",
"inventory",
"environment"
] | cdn.climatepolicyradar.org | 1A1 Residual Fuel Oil 5.50% 2.55% 1.25% 2.55% ETS-based data, so low uncertainties. 1A1 Scrap Tyres 15.00% 10.00% 15.00% 10.00% Limited reported use of this fuel; only a small amount of reporting (typically cement kilns) within EU ETS and a modest number of fuel quality analyses either through the BCA/MPA (trade body) or the EU ETS. | 9ce0b96e-2800-424e-bffb-cd8ba36e0902 | 50 |
0bd0608a-568d-4f5f-92c5-a3338f92f35b | http://arxiv.org/pdf/2505.02989v1 | 2,025 | [
"Opinion dynamics",
"social networks",
"social media",
"dyadic interactions",
"graph models",
"temporal hypergraphs",
"group dynamics",
"conversational threads",
"climate change",
"Reddit",
"opinion formation",
"stance",
"individual users",
"large language models",
"ground truth",
"simulations",
"empirical validation",
"microscopic dynamics",
"online spaces",
"collective change",
"information flow."
] | arxiv.org | V. DISCUSSION
Modeling conversational networks using (temporal) hy pergraphs consistently enables more accurate identification of users’ initial opinion shifts, regardless of the size of the time window used to model the influence of comments on the readers. Our analysis found no clear patterns indicating
Analysis of accuracy scores for criterion C1 across all datasets and time window parameter ∆ demonstrates that the hypergraph model consistently surpasses both the graph model and, in most cases, the clique-based model in performance. This indicates that the hypergraph model is more effective at predicting the first opinion drift for a larger percentage of users, regardless of the granularity of the observed interactions. These findings highlight the advantages of modeling conversational networks with high-order structures, as the hypergraph model captures subtle group dynamics within conversational threads that other models may overlook. This advantage likely arises from the inherent nature of the hypergraph model, which accounts for the cumulative effects of group interactions on individual opinions. In contrast, the graph model only considers direct user-to-user interactions, while the clique model, though accounting for group interactions, limits its scope to pairwise relationships within groups rather than their cumulative effects, hence potentially failing to fully capture the influence of groups and information exposure on opinion dynamics. Our analysis reveals that performance generally decreases with broader time windows, indicating that extended sampling periods may complicate the tracking of opinion evolution. This degradation may occur because averaging opinions over longer periods can dilute the representation of a user’s true stance, while relying on only the most recent opinion risks missing significant opinion shifts. These findings emphasize the critical importance of precisely defining the temporal relevance of comments—the period during which they maintain their potential to influence readers—as broader time windows can lead to less accurate representations of user opinions and subsequently less reliable predictions of opinion shifts. Contrary to initial expectations, we found no consistent pattern in the timing of the simulated opinion changes across models. One mightintuitively assume thatincorporating group interactions with the hypergraph model would lead to an earlier prediction of opinion changes due to the compounded influence of group dynamics, while the graph model, focused on pairwise interactions, would be expected to postpone opinion shifts. While this expectation holds somehow true for the latter model, the former exhibits different behavior than expected. | 04410014-9af0-41b0-bd63-440c99ee8296 | 16 |
0bd80958-d8d7-4096-859e-dde5e3d06696 | 2,025 | [
"additional final energy savings",
"local governments",
"annex i.",
"environmental organisations",
"intensification measures"
] | HF-national-climate-targets-dataset | Some of these saving measures concern long-term energy saving policies, such as energy taxes and covenants with the business community. The Netherlands is also stepping up policy measures arising from the Energy Agreement for Sustainable Growth (Social Economic Council (SER), 2013), which brings together the activities of more than 40 organisations, including central, regional and local governments, employers' and employees' organisations, nature and environmental organisations, other civil society organizations and financial institutions. The national government is responsible for the elaboration, implementation, execution and evaluation of the policy measures specified in the agreement and will be accountable for this to parliament. The Energy Agreement aims to achieve an average annual saving of 1.5 percent on final energy consumption. In addition, in this context, the Parties agree on a package of measures, which is expected to enable approximately 100 PJ of additional final energy savings to be achieved in 2020 compared to a reference scenario without an Energy Agreement (Daniels et al. 2013, p. 19). The monitoring and assurance of the results of the Energy Agreement is carried out by a permanent committee within the SER in which all parties, including the government, participate. In 2016 it was decided to intensify the agreements in the Energy Agreement in order to guarantee the national target of 100 PJ additional final energy savings. Some of these intensification measures have already been implemented. These measures are also included in Annex I. | 984c8592-133a-40d2-8616-6495b9d04fea | 0 | |
0bdcb524-e189-4b26-b429-60951517faa5 | 2,025 | [
"allocation element",
"b.",
"company",
"installation",
"activity level"
] | HF-national-climate-targets-dataset | has. by 50%, if the activity level of the attribution element is reduced by at least 50% and by less than 75%; b. 75%, if the activity level of the attribution element is reduced by at least 75% and by less than 90%; vs. by 100%, if the activity level of the attribution element is reduced by at least 90%. SL Increase in the quantity of emission rights allocated free of charge ¹ The quantity of emission rights allocated each year free of charge to a company covered by the ETS is increased when a physical modification of a fixed installation or the construction of a new fixed installation leads to an increase of at least less than 10% of the installed capacity of an allocation element. | 889e9b47-dd1b-4d79-9a8c-29c9efc5b7d0 | 0 | |
0be1976e-97e0-49d9-a58c-64ac5ef9b8d2 | https://committees.parliament.uk/publications/44325/documents/220225/default/ | 2,024 | [
"trustees",
"duties",
"climate",
"change",
"fiduciary"
] | parliament.uk | Given that legislation to bring investment consultants into the FCA’s regulatory perimeter has not been brought forward, it would be helpful if you could explain how DWP and TPR are working with the FCA to ensure that they use appropriate models of I would be grateful for your response to these questions by Wednesday 1 May. As is usual practice with the Committee’s correspondence, I will be publishing this letter and your response on the Committee’s website. Chair, Work and Pensions Committee | cd59f629-4d80-4e97-9b96-425b2cfc4dbe | 1 |
0be34ade-6966-4b12-b3f0-cd0220a7c7dd | https://www.gov.uk/government/news/60-million-boost-for-floating-offshore-wind | 2,022 | [
"energy",
"development",
"article",
"management",
"protection",
"water",
"measure",
"environment",
"consist",
"resource"
] | gov.uk | More than GBP 60 million in public and private funding will be invested in floating offshore wind projects to develop new technologies that will allow turbines to be placed in the most windy areas along the UK's coastline. More than GBP 31 million is funded by the government and more than GBP 30 million is funded by industry. The cash boost will further research and development in floating offshore wind with projects across the United Kingdom. The research will focus on areas such as how turbines are moored to the seabed, undersea cabling, and developing foundation solutions. | e1169632-8b43-46e8-aabd-925b3f5a5d2e | 0 |
0be46202-5341-4d7c-a402-9c573c5b3c08 | 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 | 6. For the purposes of points d and e of paragraph 3,
approval authorities shall not approve a vehicle if the informa-
tion submitted by the manufacturer is inappropriate for fulfilling
the requirements of section 3 of Appendix 1 to Annex XI. Sections 3.2, 3.3 and 3.7 of Appendix 1 to Annex XI shall apply
under all reasonably foreseeable driving conditions. For the assessment of the implementation of the requirements set
out in the first and second subparagraphs, the approval authori-
ties shall take into account the state of technology. | d3fc6859-41cb-4ee2-997b-90ebc4f9b481 | 14 |
0be82597-54ef-479f-87fc-5a8c9cec8161 | http://arxiv.org/pdf/2402.01784v2 | 2,024 | [
"emissions",
"convergence",
"club",
"energy",
"countries"
] | arxiv.org | Furthermore, that sector has not experienced the same gradual decline in emissions as others: in 2017, GHG emissions from transport were 19.2% higher than in 1990, with the largest increases registered in Poland (203%), Ireland (133%), Luxembourg (116%), Slovenia (103%), Malta (92%), Austria (74%), Croatia (71%), Cyprus (69%), Portugal (68%), the Czech Republic (63%), and Spain (51%). As a rule, the EU countries have maintained a high share of oil and petroleum products in their consumption. The use of oil products has decreased in the industry and residential sectors in recent years, but still makes up 94% of final energy consumption in the transport sector. More precisely, around 82% of EU's final energy consumption in the transport sector can be attributed to road transport, with aviation having a growing share of overall transport energy consumption in recent years. Thus, strengthening the use of renewable energy sources in the transport sector seems vital in order to control GHG emissions and reduce dependence from third countries. As commented above, it is important to conduct the above analysis separately for the subperiod from 2005 on, since some of the countries in the study had recently joined the EU, and some of the policies, mechanisms and objectives on climate change have been formulated in the years thereafter. This perspective will also allow us to separately analyze emissions under two instruments of EU's climate and energy policy, namely ETS and ESD. Table 2 andFigure With the only exception of Romania, none of the newer Member States is now among the top performing countries. Indeed, the worst evolution is observed for some former Communist states, along with Ireland. Briefly, and for ease of comparison, Table 3 includes the classification of each country for each reference year (respectively, 1990 and 2005). The most abrupt changes in club membership occur in Latvia, Germany, and to a lesser extent Lithuania, which move from groups with emissions below the mean of the EU-28 to clubs exhibiting transition paths slightly above 1 and growing trends. Additionally, the inclusion of Ireland in Club 1 seems to be motivated by its evolution since 2015, with sharp GDP growth accompanied by mild decreases in energy consumption. At the other end, Italy and Greece shift from clubs with transition paths slightly over 1 to having below-average evolution. Those countries suffered major setbacks in both energy consumption and GDP (Table A.2) as a consequence of the economic crisis in that period. Denmark, the United Kingdom and Romania remain in the best-performing clubs, regardless of the reference year employed. Romania, despite its high growth, exhibits one of the sharpest reductions in gross inland energy consumption. In the case of the United Kingdom that decrease is even more impressive. In order to facilitate a more in-depth examination of the 2005-2017 period, a separate analysis of the evolution of emissions under ETS and ESD will be conducted in the following subsections. The ETS is the world´s first and biggest carbon market. It aims at limiting the emissions from large point sources (mostly power and heat production and industrial installations) and other activities like cement, iron and steel production, and oil refining. Since 2012, the EU-ETS also encompasses emissions from aviation. Overall, it covers around 45% of the EU´s GHG emissions. Total emissions have been in a downward trend in recent years. Thus, in year 2017, emissions from stationary installations under the EU-ETS were 26% below 2005 levels, mainly due to decreases in the emissions linked to power generation. This is quite a drop, as the EU-ETS target was to reduce emissions by 21% between years 2005 and 2020; moreover, forecasts submitted by the Member States in 2017 indicate that emissions from stationary installations are projected to decrease by 5% throughout the 2017-2020 period and by 7% between 2020 and 2030, with energy industries being the main driver of that reduction. However, the evolution of the aviation sector reveals a very different pattern, with 22% growth in 2017 in relation to 2013 (Table A.2) and an increase in its share to around 4% of total EU28 GHG emissions and 13% of the emissions from transport. Since data from aviation are only available from 2012 on, and with the aim of obtaining a homogeneous time series, emissions from that sector are not included in this study. In addition, in order to more accurately reflect the current scope of the EU-ETS (third trading period 2013-2020) and to ensure that the series analyzed were time consistent, we included the verified emissions from stationary installations plus estimates of emissions and allowances (EEA data) for the 2005-2012 period. (Qualitatively similar results, only including verified emissions, are available from the authors upon request). The results for stationary installations (Table 2 and Figure 2, panel B) lead us to reject the null of convergence, with the following 4 convergence clubs being detected by the algorithm:
-Club 1 has a growing trend in its transition path and is integrated by Estonia and the Netherlands. The only country in the EU-28 that increased its ETS emissions in 2017 as compared with 2005 is Estonia, that heavily relies on its -highly emissions intensive-shale oil resources. For its part, Dutch ETS emissions in 2017 were similar to those of 2005, perhaps as a consequence of the fact that its local electricity system mostly uses fossil fuels for power generation, with the north of the country being rich in that resource. -Club 2 is the largest group and had a transition path with values around the mean until year 2014, although showing a tendency to separate thereafter. -Club 3 is characterized by a transition path below 1. The merging algorithm allows Italy to be included in this club, although convergence would be weak in that case. -The most favorable evolution is observed for Romania and Lithuania (Club 4), in addition to Luxembourg, Malta and the United Kingdom (which diverge). Table A.2 reports data on aviation emissions. | e624935f-3266-420a-a77b-8d8f43aa6900 | 5 |
0bf43ae8-2ca9-4c82-b662-1e95ab98ec26 | http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32009L0073 | 2,009 | [
"Electricity and heat",
"Gas",
"Energy efficiency",
"Renewables",
"Other low-carbon technologies and fuel switch"
] | eur-lex.europa.eu | Member States shall ensure that regulatory authorities are granted the powers enabling them to carry out the duties referred to in paragraph 1, 3 and 6 in an efficient and expeditious manner. For this purpose, the regulatory authority shall have at least the following powers:
(a)
to issue binding decisions on natural gas undertakings;
(b)
to carry out investigations into the functioning of the gas markets, and to decide upon and impose any necessary and proportionate measures to promote effective competition and ensure the proper functioning of the market. Where appropriate, the regulatory authority shall also have the power to cooperate with the national competition authority and the financial market regulators or the Commission in conducting an investigation relating to competition law;
(c)
to require any information from natural gas undertakings relevant for the fulfilment of its tasks, including the justification for any refusal to grant third-party access, and any information on measures necessary to reinforce the network;
(d)
to impose effective, proportionate and dissuasive penalties on natural gas undertakings not complying with their obligations under this Directive or any relevant legally binding decisions of the regulatory authority or of the Agency, or to propose to a competent court to impose such penalties. This shall include the power to impose or propose the imposition of penalties of up to 10 % of the annual turnover of the transmission system operator or of up to 10 % of the annual turnover of the vertically integrated undertaking on the transmission system operator or on the vertically integrated undertaking, as the case may be, for non compliance with their respective obligations pursuant to this Directive; and
(e)
appropriate rights of investigations and relevant powers of instructions for dispute settlement under paragraphs 11 and 12. | 468e5f96-94f7-4694-bfed-829608c266ef | 54 |
0bfa6d94-60e2-4e50-aa7a-cca640daa23e | 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 | (2) The regulations are subject to affirmative resolution procedure if- (a) they are the first regulations to be made under those sections, (b) they specify a carbon unit of a kind not previously specified in regulations made under those sections, (c) they alter the amount by which- (i) a carbon unit that is credited to the net UK carbon account for a period reduces the net UK carbon account for that period, or (ii) a carbon unit that is debited from the net UK carbon account for a period increases the net UK carbon account for that period, or (d) they make modifications of an enactment contained in primary legislation. (3) Otherwise the regulations are subject to negative resolution procedure. (4) The Secretary of State must consult the other national authorities- (a) in the case of regulations subject to affirmative resolution procedure, before laying before Parliament a draft of a statutory instrument containing the regulations; (b) in the case of regulations subject to negative resolution procedure, before making the regulations. (5) The Secretary of State must obtain, and take into account, the advice of the Committee on Climate Change before laying before Parliament a draft of a statutory instrument containing- (a) the first regulations to be made under those sections, or (b) regulations making provision of the kind described in paragraph (b) or (c) of subsection (2). Other supplementary provisions U.K. 29 UK emissions and removals of greenhouse gases U.K. (1) In this Part- (a) " UK emissions ", in relation to a greenhouse gas, means emissions of that gas from sources in the United Kingdom; (b) " UK removals ", in relation to a greenhouse gas, means removals of that gas from the atmosphere due to [ F5 processes, mechanisms or ] activities in the United Kingdom; (c) the " net UK emissions " for a period, in relation to a greenhouse gas, means the amount of UK emissions of that gas for the period reduced by the amount for the period of UK removals of that gas. (2) The amount of UK emissions and UK removals of a greenhouse gas for a period must be determined consistently with international carbon reporting practice. 29(1)(b) substituted (26.12.2023) by Energy Act 2023 (c. 52) , ss. 160 , 334(3)(f) 30 Emissions from international aviation or international shipping U.K. (1) Emissions of greenhouse gases from international aviation or international shipping do not count as emissions from sources in the United Kingdom for the purposes of this Part, except as provided by regulations made by the Secretary of State. (2) The Secretary of State may by order define what is to be regarded for this purpose as international aviation or international shipping. Any such order is subject to affirmative resolution procedure. (3) The Secretary of State must, before expiry of the period ending with 31st December 2012- (a) make provision by regulations as to the circumstances in which, and the extent to which, emissions from international aviation or international shipping are to be regarded for the purposes of this Part as emissions from sources in the United Kingdom, or (b) lay before Parliament a report explaining why regulations making such provision have not been made. (4) The expiry of the period mentioned in subsection (3) does not affect the power of the Secretary of State to make regulations under this section. (5) Regulations under this section- (a) may make provision only in relation to emissions of a targeted greenhouse gas; (b) may, in particular, provide for such emissions to be regarded as emissions from sources in the United Kingdom if they relate to the transport of passengers or goods to or from the United Kingdom. (6) Regulations under this section may make provision- (a) as to the period or periods (whether past or future) in which emissions of the targeted greenhouse gas are to be taken into account as UK emissions of that gas, and (b) as to the manner in which such emissions are to be taken into account in determining UK emissions of that gas for the year that is the base year for that gas. (7) They may, in particular- (a) designate a different base year, or (b) designate a number of base years, and provide for the emissions in that year, or the average amount of emissions in those years, to be treated for the purposes of this Act as UK emissions of that gas for the year that is the base year for that gas. (8) For the purposes of this section the base year for carbon dioxide is the year that is the baseline year for the purposes of this Part. 31 Procedure for regulations under section 30 U.K. (1) Before making regulations under section 30, the Secretary of State must obtain, and take into account, the advice of the Committee on Climate Change. (2) 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. (3) If the regulations make provision different from that recommended by the Committee, the Secretary of State must publish a statement setting out the reasons for that decision. (4) The statement may be published in such manner as the Secretary of State thinks fit. (5) Regulations under section 30 are subject to affirmative resolution procedure. | 5f6e0789-61b6-4280-9f82-c3a8e25857fa | 5 |
0bfac813-e066-40df-b911-91564139d3b3 | http://arxiv.org/pdf/2505.10556v1 | 2,025 | [
"Air pollution",
"public health",
"respiratory diseases",
"cardiovascular diseases",
"climate change",
"extreme weather",
"wildfires",
"heatwaves",
"personal sensing",
"behavioral data",
"physiological data",
"healthcare",
"AI",
"time series prediction",
"health outcomes",
"personalized health",
"wearable fitness devices",
"environmental exposures",
"data security",
"ethical AI",
"Adversarial Autoencoder",
"transfer learning",
"smartwatch",
"nonlinear responses."
] | arxiv.org | Interactive applications, including Jupyter Notebook, R Studio, and MATLAB, are integrated into the platform, providing a flexible workspace for researchers to perform in-depth analyses, run complex models, and visualise results. 4 Data Integration, Model Development, and Training Strategy
4.1 Data Acquisition
This study uses three main data streams: physiological and environmental data from the INHALE cohort, personal smartwatch data and publicly available pollution and weather data via the OpenWeather API. The subset of INHALE dataset used for this analysis included 10 healthy participants monitored using AIRSpeck (air quality) and RESpeck (respiratory rate and activity) sensors across two seasonal periods: Summer and Winter. Data were recorded hourly and geotagged with GPS coordinates, enabling alignment with external datasets. This dataset was temporally and spatially matched with OpenWeather pollution and meteorological records, retrieved using timestamps and GPS coordinates. Personal data were collected independently from a single user over 8 months via Apple Health (heart rate, step count) and Google Maps Timeline (location). This dataset was temporally and spatially matched with OpenWeather pollution and meteorological records, retrieved using timestamps and GPS coordinates. | aa3281a4-81f1-4957-abd6-af44f10d3d68 | 8 |
0bfd1df4-3789-4f03-8d8a-59e65225ccd8 | 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 | . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.12.2.6.4.3. Parameters to determine the level of loading required before regeneration occurs i.e. temperature, pres-
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . | d3fc6859-41cb-4ee2-997b-90ebc4f9b481 | 432 |
0c025d4c-79d0-4b95-a968-7affcb0de1d7 | https://ec.europa.eu/environment/archives/natres/pdf/final_report_wg1.pdf | 2,000 | [
"General",
"Energy service demand reduction and resource efficiency",
"Energy efficiency",
"Renewables",
"Other low-carbon technologies and fuel switch",
"Non-energy use"
] | ec.europa.eu | It is necessary to
identify the vulnerabilities of some of these components and to design technically effective
and economically efficient impact prevention strategies. 3
4
Available here httpwww.gmes.infolibraryindex.php?direction0orderdirectoryCross-Cutting
20Studies20Documents
In average metallic minerals are much less abundant in the EU, although modern systematic exploration
which has never been undertaken in some regions may yield some good surprises. 5 Much valuable progress is made. Since 01102004 EuroStat trade data became freely accessible here
httpepp.eurostat.cec.eu.intportalpage?_pageid1090,1137397_dadportal_schemaPORTAL
and in 2004, DG Enterprise published the first ever Sustainable Development Indicators for the EU mining
industry see p. 82. Available here httpminerals.usgs.govminerals
6
Page 3
Data issues pp. 90 ff. are a limiting factor for the definition of the future Strategy, and
stable resources at the EU and national regional levels will need to be allocated to address
this situation. Progress is also needed in turning data into information and knowledge, as underlined by
some examples pp. 91 ff. EU wide coordination and more interdisciplinary work is required
to derive the kind of information and knowledge required for policy making, be it at local,
regional, national or the European level. The current situation as reflected in this report may lead to inadequate decisions and
inefficient use of budgetary and other resources, or to a blanketing application of the
precautionary principle, with the risk to penalise growth and jobs without achieving the
desired reduction of environmental impacts. This would be contrary to the objectives of the
stategy which is to achieve the growth and employment objectives of the Lisbonne agenda. How to progress towards decoupling? The use of renewable biotic resources as substitutes for non-renewable abiotic resources is
constrained by the availability of land and competing land uses see p. 79 for an example
related to biofuels. Research and innovation are to play a considerable role in support of the decoupling
objective pp. 133 ff.. There is a need for sustained, financed, public applied research to
o develop our knowledge of the environmental components and of their interaction as well
as of the impacts of anthropogenic pressures
o collect and disseminate data and information on material flows through the EU economy,
including in relation with trade, as well as on the related economic, environmental and
social impacts within the EU, and outside its borders
and to develop innovative technologies for better, more efficient production technologies, for
the reduction and the re-use of waste. The efforts and resources of different European Commission Directorate Generals need to
be harmonised and integrated, in support of the Strategy. The Chemicals, Development,
Industrial, Agriculture, Fisheries, Energy, Transport, Space, Research policies all have an
effect on how we use natural resources and how this use is sustainable now, and will be in
the future. Report structure
This report concludes about nine months of work on a voluntary basis, having involved over
50 stakeholders p. 23 ff., representing industry, employers, national authorities, academia
and research consultancies as well as NGOs. It also involved representatives of five
Directorates General of the European Commission. The stakeholders and the troika having
chaired the Working Group have worked on a voluntary basis, and had no specific resources
except those internal to the organisations they represent to perform their job. The purpose of this report is to provide the European Commission Steering Committee
members with the inputs resulting from the participation of the stakeholders to the activities
of Working Group 1. It reflects the contributions received from the 58 stakeholders having participated to the
Working Group 1 activities. In total, about 100 stakeholders participated to one, or to both,
Working Groups. Page 4
The commitment and the dedication of those who participated should be underlined. The
draft of this report, with the exception of this Executive Summary and of comparatively minor
changes in its text, has been made available to the Working Group members and to the
general public since August 26th, 2004. This report includes a bibliography and Internet links which can be used as possible starting
points by those interested in deepening the analysis of the issues related to the sustainable
use of natural resources. This report is structured as follows
o Chapter 1, in introduction first briefly recalls the importance of natural resources for
human development and puts the development of the Thematic Strategy on the
Sustainable Resources in perspective. It then details the organisation of the stakeholder
consultation and recalls the scope of the Thematic Strategy
o After due acknowledgements Chapter 2 of the inputs delivered by the many
contributors to this report, the Chapter 3 details the origins and the European policy
context of the Strategy development, comprising the conclusions of several European
Summits and the 6th European Action Programme
o Chapter 4 details the work of the Working Group 1, with a detailed breakdown of the
stakeholders and the sectors represented. It presents the Steering Committee. It briefly
recalls the activities of the Advisory Forum, the liaison with the activities of the Working
Group 2, the Mandate given to Working Group 1. | a5fe6535-9c80-4d16-a22c-92e1e4ed7d30 | 11 |
0c02b4ac-8aab-45ed-8803-d55ef0bf9564 | https://www.gov.uk//government/publications/industrial-decarbonisation-and-energy-efficiency-roadmaps-to-2050 | 2,015 | [
"Decarbonization",
"energy efficiency",
"industrial sectors",
"greenhouse gas emissions",
"cement",
"ceramics",
"chemicals",
"food and drink",
"glass",
"iron and steel",
"oil refining",
"paper and pulp",
"government",
"industry",
"reports",
"techno-economic",
"pathways",
"emissions reduction",
"low carbon economy",
"collaboration",
"stakeholders",
"supply chains",
"customer demand",
"global perspective",
"technical challenges",
"commercial challenges",
"DECC",
"BIS."
] | gov.uk | They were produced by a consortium of Parsons Brinckerhoff and DNV GL, based on a collaborative process featuring contributions from industry sector trade associations, their members, officials from DECC and BIS, and other experts. Each of the eight sector-specific reports explains the specific features of that industry, how the processes work and what fuels they currently use. The report then sets out a range of techno-economic and business decision-making evidence on the decarbonisation issues that are most relevant to that sector. This evidence is synthesised to produce a series of potential pathways for emissions reduction. Finally, the reports draw together conclusions from the evidence and pathways analysis to identify potential ways that progress could be made to help enable transition towards a low carbon economy with a competitive industrial sector. The emphasis is on collaborative working between industry, government and other stakeholders, considering issues such as supply chains, customer demand and the wider global perspective as well as technical and commercial challenges. | 03ef093e-9841-482c-b38e-a9742f313baa | 1 |
0c050ad6-2692-4c3a-b978-27f2c222b769 | https://www.itf-oecd.org/sites/default/files/docs/01shortsea.pdf | 2,001 | [
"Transport",
"Shipping",
"Other low-carbon technologies and fuel switch"
] | www.itf-oecd.org | Moreover, this quantity also contains present land traffic flows -- for
example between Scandinavia and South Europe which might be shifted to sea transport without using
ports either in German or Benelux countries. A statistical analysis of European cargo flows showed that during the period 1990-1995 freight
flows by sea within European trades have increased by about 4 p.a. feeder traffic excluded. It has
been a smooth and steady growth, without sudden increases as is sometimes expected from promoters
of short sea shipping. | 0efe3d52-645b-46f1-9661-6cfad3222525 | 19 |
0c139d6a-0c87-4621-8102-2ef588e303a3 | http://arxiv.org/abs/2504.20521v2 | 2,025 | [
"extratropical storms shape midlatitude weather",
"synoptic scale dynamics",
"numerical weather prediction models",
"0.35(+/-0.017)%",
"eddy flow"
] | ArXiv | Text S1: Data for the climatological model The resolution of both the input and output images is 6 in the zonal direction, 3 in the meridional direction, and the levels 300, 500, and 850 hPa are used in the vertical. Using this resolution, the inputs and outputs are images of 20 by 60 pixels, with 9 channels for the input (three levels of three variables) and 3 channels for the output (three levels of one variable). The meridional direction of the SH data is flipped to match the NH. The data is sampled in 10-day intervals to ensure significant differences between data points while obtaining a large dataset. Overall, there are about 6,000 data points (36 images per year for each hemisphere for 84 years) divided into train-validation-test set in ratios of 0.5 0.2 0.3. The division between sets is done by splitting the data into chunks of 108 consecutive samples (i.e., about 3 years), with a margin of five samples between chunks that were not included in any data sets. Then, given that the maximum window that was used was 90 days (45 on each side), no data leak was introduced. For training and validation, data augmentation is performed by randomly shifting the central longitude pixel, leveraging the system's symmetry with respect to the central longitude. Each epoch consists of three repetitions of the input data, with each sample shifted by a different randomly chosen integer. The input images are normalized using the mean and standard deviation computed along the zonal direction and over time, ensuring symmetry is preserved in these dimensions. The output is normalized using the global standard deviation (computed across all pixels and time) to prevent feeding extremely large or small values into the model, improving numerical stability. However, the mean is not removed to maintain the positivity of the output. Notably, the loss function itself accounts for per-pixel normalization based on the input (see next section). To capture the variability in each pixel's EKE, which can differ substantially based on the mean flow, we adopt a negative log-likelihood framework that estimates variance on a per-pixel basis. Since EKE is strictly positive, we model its distribution using a Gamma distribution: p(y; , ) = y 1 e y/ () , y > 0, > 0, > 0. (3) The authors have no conflicts of interest to disclose. Text S1: Data for the climatological model The resolution of both the input and output images is 6 in the zonal direction, 3 in the meridional direction, and the levels 300, 500, and 850 hPa are used in the vertical. Using this resolution, the inputs and outputs are images of 20 by 60 pixels, with 9 channels for the input (three levels of three variables) and 3 channels for the output (three levels of one variable). The meridional direction of the SH data is flipped to match the NH. The data is sampled in 10-day intervals to ensure significant differences between data points while obtaining a large dataset. Overall, there are about 6,000 data points (36 images per year for each hemisphere for 84 years) divided into train-validation-test set in ratios of 0.5 0.2 0.3. The division between sets is done by splitting the data into chunks of 108 consecutive samples (i.e., about 3 years), with a margin of five samples between chunks that were not included in any data sets. Then, given that the maximum window that was used was 90 days (45 on each side), no data leak was introduced. For training and validation, data augmentation is performed by randomly shifting the central longitude pixel, leveraging the system's symmetry with respect to the central longitude. Each epoch consists of three repetitions of the input data, with each sample shifted by a different randomly chosen integer. The input images are normalized using the mean and standard deviation computed along the zonal direction and over time, ensuring symmetry is preserved in these dimensions. The output is normalized using the global standard deviation (computed across all pixels and time) to prevent feeding extremely large or small values into the model, improving numerical stability. However, the mean is not removed to maintain the positivity of the output. Notably, the loss function itself accounts for per-pixel normalization based on the input (see next section). To capture the variability in each pixel's EKE, which can differ substantially based on the mean flow, we adopt a negative log-likelihood framework that estimates variance on a per-pixel basis. Since EKE is strictly positive, we model its distribution using a Gamma distribution: p(y; , ) = y 1 e y/ () , y > 0, > 0, > 0. (3) | 319e8543-2bbc-4b5c-9d26-ac707c605f2c | 4 |
0c173ad2-6ba9-420e-8807-65e0dcef65f2 | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32023R2405 | 2,023 | [
"Transport",
"Other low-carbon technologies and fuel switch"
] | eur-lex.europa.eu | In order to help to safeguard the air-connectivity of regions with fewer alternative transport options, attention should be paid to the possible effects of the provisions in this Regulation with regards to the affordability, competitiveness and potential price increases of air routes connecting remote regions and other areas of the Union. (20)
Development and deployment of SAF with a high potential for sustainability, commercial maturity and innovation and growth to meet future needs should be promoted. This should support the creation of an innovative and competitive market for SAF and ensure the sufficient supply of SAF for aviation in the short and long term to contribute to Union transport decarbonisation ambitions, while strengthening the Union s efforts towards a high level of environmental protection. Incentives on the use of renewable fuels of non-biological origin in transport granted under other Union law will have a positive impact on the uptake of such fuels in aviation. A single, clear and robust sustainability framework is necessary to provide legal certainty and continuity for the aviation and fuels industries actors, on the eligibility of SAF under this Regulation. For this purpose, all aviation biofuels which comply with the sustainability and lifecycle emissions criteria laid down in Directive (EU) 2018/2001 and are certified in accordance with that Directive, with the exception of biofuels produced from food and feed crops and certain feedstock listed in Article 4(5) of this Regulation, synthetic aviation fuels and recycled carbon aviation fuels complying with the lifecycle emissions savings threshold referred to in that Directive should be eligible. In that respect, to ensure consistency with other related Union policies, the eligibility of aviation biofuels, synthetic aviation fuels and recycled carbon aviation fuels should be based on the sustainability criteria and thresholds established in Directive (EU) 2018/2001. In particular, SAF produced from feedstock listed in Part B of Annex IX to Directive (EU) 2018/2001 are essential, as currently the most commercially mature technology to decarbonise air transport in the short term. The renewable share of fuels produced through co-processing should be eligible under the definition of SAF, as long as the renewable share is produced from feedstock listed in Directive (EU) 2018/2001 with the exception of biofuels produced from food and feed crops as defined in that Directive, and of certain feedstock listed in Article 4(5) of this Regulation, determined in line with the methodology to be set out in a Commission delegated regulation adopted pursuant to Directive (EU) 2018/2001. Renewable hydrogen for aviation and low-carbon aviation fuels achieving at least same level of lifecycle emissions savings as synthetic aviation fuels can play a role in substituting conventional aviation fuels and support aviation decarbonisation and therefore should also be included within the scope of this Regulation. (21)
Given the use of feedstock for cosmetics and animal feed, aviation biofuels other than advanced biofuels as defined in Directive (EU) 2018/2001 and other than biofuels produced from the feedstock listed in Part B of Annex IX to that Directive supplied across Union airports by each aviation fuel supplier should account for a maximum of 3 % of aviation fuel supplied for the purposes of complying with the minimum shares of SAF to be supplied at each Union airport under this Regulation. (22)
A wide pool of eligible feedstock is essential to maximise the potential for scaling up the production of SAF at affordable costs, while at the same time guaranteeing its sustainability. This Regulation excludes certain types of feedstock unless such feedstock is included in Annex IX of Directive (EU) 2018/2001, and meets all applicable conditions if such conditions are set out in that Annex. The list of feedstock eligible under this Regulation should therefore not be static but should evolve over time to include new sustainable feedstock in line with that Directive. Changes in the list of feedstock in Annex IX of that Directive, fulfilling the relevant conditions of that Annex, should be directly reflected in the list of eligible fuels under this Regulation for the production of SAF. (23)
For sustainability reasons, feed and food crop-based aviation biofuels, including high indirect land-use change risk biofuels, should not be eligible. In particular, indirect land-use change occurs when the cultivation of crops for biofuels displaces traditional production of crops for food and feed purposes. Such additional demand increases the pressure on land and can lead to the extension of agricultural land into areas with high-carbon stock, such as forests, wetlands and peatland, causing additional greenhouse gas emissions and loss of biodiversity concerns. Research has shown that the scale of the effect depends on a variety of factors, including the type of feedstock used for fuel production, the level of additional demand for feedstock triggered by the use of biofuels and the extent to which land with high-carbon stock is protected worldwide. The highest risks of indirect land-use change have been identified for biofuels, fuels produced from feedstock for which a significant expansion of the production area into land with high-carbon stock is observed. Therefore, feed and food crop-based fuels should not be promoted. | e24fd56a-133a-418d-a758-49d3fefcce80 | 6 |
0c26746d-e913-43e2-9bc5-b672f51a6ec2 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_8122f7d823bf366105239091fb57ffd2.pdf | 2,023 | [
"data",
"energy",
"emissions",
"inventory",
"environment"
] | cdn.climatepolicyradar.org | There are also inconsistencies in terminology used to define types of fuel; the research indicated that the terms “gas oil”, “red diesel” and “diesel” are used interchangeably by fuel suppliers and consumers and this confuses the situation when considering fuel allocations As with fuel oil, the introduction of the results of a major research project into the shipping sector in the 2018 submission, whereby Automatic Identification System (AIS) data was used to calculate shipping movements along the coast of the UK and the Crown Dependencies, however suggested that gas oil consumption reported by DUKES for national navigation is an underestimate. As a result, total gas oil use (not including DERV) deviates from DUKES as any further consumpti on in the national navigation sector are considered additional to DUKES and are not reconciled elsewhere in the inventory. Note that in DUKES, port machinery fuel use is included as part of national navigation, and therefore, similar to the estimates of gas oil use for shipping, the bottom- up estimates for fuel consumption by port machinery also deviates from DUKES and are not reconciled elsewhere in the inventory. 0.058 Power Stations 1A1ai 0.059 -0.001 Autogenerators 0.028 Autogenerators (inc. 1A2b - 0.028 Fuel reallocated to iron Oil gas extraction 0.533 Upstream Oil/Gas - Refineries - combustion 1A1b - - Other industries 1.487 Other industrial 1A2gviii 0.069 1.419 Calculated as a residual Iron and steel 0.004 Iron and steel - 1A2a 0.003 0.001 Data provided by Non ferrous metals 0.007 Non-ferrous metal Cement processes 1A2f 0.005 - Data provided by Chemicals 0.080 Chemicals food beverages 0.041 Food & drink, tobacco Paper printing 0.031 Pulp, Paper and Print
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 995 Road 21.727 Road transport 21.593 0.134 Reduced to offset Rail 0.506 Rail transport 1A3c 0.477 0.029 Inventory Agency National navigation 0.584 Inland and small Fishing vessels 1A4ciii 0.140 Naval shipping 1A5b 0.164 Marine bunkers 1.332 Marine bunkers Memo item 1.332 0.000 Domestic 0.123 Domestic combustion 1A4bi 0.123 0.000 1A4bii 0.011 -0.011 Inventory Agency 1A4ai 0.024 0.253 Fuel use offset to account Commercial 0.513 Miscellaneous 1A4ai 0.050 0.702 Fuel use offset to account Miscellaneous 0.239 Agriculture 0.374 Agriculture (stationary 1A4ci - 0.374 Fuel use offset to account 1A4cii 1.503 -1.503 Inventory Agency TOTAL 27.944 TOTAL 28.896 - 0.952 Overall the GHGI reports Rows are shaded to help illustrate reconciliation between sectors For petroleum gases (LPG, OPG), the total fuel use in the inventory is greater than the national statistics in several years, to reflect information from other sources (such as EU ETS data) that indicate potential under -reports in the UK energy statistics. These modifications to the energy
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 996 the petrochemicals sector, and fuel use for upstream oil and gas production. Liquefied Petroleum Gas (LPG) – in DUKES this fuel is reported as propane and butane Iron and steel 0.000 Iron and steel - Other industry 0.320 Other industrial Road transport 0.058 Road transport 1A3bv 0.059 -0.001 Other Petroleum Gases (OPG) – includes Refinery Fuel Gas (RFG). In DUKES, reported as Ethane, Other gases and 1A1b 1.960 -0.356 Refinery (and on-
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 997 0.178 0.178 Backflows from (combustion) 2B8g 1.019 -1.019 Sequences of shaded rows indicate categories which are grouped for purposes of data reconciliation, and should be considered together. UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 998 The UK conducts an annual analysis of how the GHGI reference approach compares to what the UK energy statistics team submit to the IEA. This acts a QA step for the UK GHGI balance, and aids transparency of why these data might differ for different reporting obligations. The fossil Primary fuels Crude oil 1,929,413.8 1,929,354.1 59.7 0.0% liquids 116,775.1 119,706.9 -2,931.8 -2.5% IPCC default NCV used for GHGI RA calculations, which differs from the NCV used in the calculations that provide an estimate for the IEA return by about 2.5%. fuels Gasoline -228,159.4 -231,522.8 3,363.4 -1.5% Imports are expected to be higher in the GHGI due to the inclusion of Overseas territories, which won't be included in the IEA return. In 2021 the Overseas territories imported 3,445 TJ of gasoline, which explains almost the entirety of Jet kerosene -9,795.9 -19,313.0 9,517.1 -97.2% Imports are expected to be higher in the GHGI due to the inclusion of Overseas territories, which won't be included in the IEA return. The scope of international bunkers is also different, as the IEA return will exclude Overseas Territories as part of the UK's coverage for the IEA return, but the OTs are included in the UK's submission. This difference is likely exaggerated this year due to large changes in the aviation sector's behaviour due to the pandemic impacting the different approaches to estimating international / domestic splits that are used for IEA and GHGI reporting. kerosene 31,884.8 31,757.7 127.1 0.4% Imports are expected to be higher in the GHGI due to the inclusion of Overseas territories, which won't be included in the IEA return. In 2021 the Overseas territories imported 118 TJ of other kerosene, which explains almost the
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 999 oil 413,721.3 400,449.7 13,271.6 3.2% Imports are expected to be higher in the GHGI due to the inclusion of Overseas territories, which won't be included in the IEA return. In 2021 the Overseas territories imported 13,090 TJ of Gas/diesel oil, which explains almost the oil -100,380.1 -105,683.7 5,303.7 -5.3% Imports are expected to be higher in the GHGI due to the inclusion of Overseas territories, which won't be included in the IEA return. | 9ce0b96e-2800-424e-bffb-cd8ba36e0902 | 475 |
0c270dc2-c52b-43b9-817a-bc7e577b007d | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_8122f7d823bf366105239091fb57ffd2.pdf | 2,023 | [
"data",
"energy",
"emissions",
"inventory",
"environment"
] | cdn.climatepolicyradar.org | However, when a distribution is skewed the two methods diverge, since the variance is dominated by outliers which aren’t necessarily accounted for in the 95% Calculating the uncertainty using both of these methods allows us to check that the Monte Carlo analysis is behaving in the way we would expect, and that convergence of the distributions is being achieved. Comparing the results using both calculations showed that the uncertainties were almost the same for gases where the distributions used were predominantly normal, but higher for N2O and the GWP weighted total, as expected. | 9ce0b96e-2800-424e-bffb-cd8ba36e0902 | 37 |
0c30700c-8ef1-4bcf-9e51-8adb3707cb02 | https://cdn.climatepolicyradar.org/navigator/GBR/2021/procurement-policy-note-06-21_7033f2a70382e92f9324c6cef5fc2efa.pdf | 2,021 | [
"Public Sector",
"emissions",
"carbon",
"reporting",
"scope",
"reduction"
] | cdn.climatepolicyradar.org | The content and structure of the CRP is detailed in the ‘Template Carbon Reduction Plan’ published alongside PPN 06/21, and the reporting requirements are further detailed in this supporting guidance. Committing to Net Zero by 2050: Within their Carbon Reduction Plan, suppliers must confirm their organisational commitment to achieving Net Zero by 2050 at the latest. This is consistent with the UK Government’s commitment under the Climate Change Act, and will play a significant role in the decarbonisation of the United Kingdom as a whole. Meeting the Reporting Carbon Reduction Plans focus upon the recording and reporting of Scope 1 and 2 emissions, and introduce additional reporting against a subset of Scope 3 emissions. Please read the ‘Scope Guidance’ section carefully to determine which sources are considered to be in-scope. In order to ensure consistency of reporting and ease of comparison between suppliers, Carbon Reduction Plans should be completed in accordance with the latest environmental reporting guidance2 for Scope 1 and Scope 2 emissions, and the reporting of the required subset of Scope 3 emissions should be in line with best industry practice and technical guidance3 detailed below. Suppliers’ Carbon Reduction Plans should be reviewed and updated annually to reflect changes in organisational structure and to take account of the efforts made to reduce their emissions over time. Suppliers should ensure that the same reporting period is used throughout the submission, to ensure the most accurate and meaningful data can be used in the completion of your Carbon Reduction Plan. To this end your Carbon Reduction Plan should be reviewed and updated within 6 months of your organisation’s financial year-end. In order to increase transparency, suppliers should publish their latest Carbon Reduction Plan on their UK website. Suppliers should place the link on a prominent place on your homepage. It is good practice to keep previous CRPs on your website so that your progress can be monitored. If you do not have a website, you must provide a copy of the statement in writing to anyone who requests one within 30 days. Scope The Greenhouse Gas Protocol breaks emissions sources down into three categories or Scopes. All Scope 1 and Scope 2 emissions are to be included when completing your CRP, along with a subset of Scope 3 emissions. 2 3
Scope 3 emissions represent up to 80% of any organisation’s carbon emissions. There are 15 categories of Scope 3 emissions defined by the GHG Protocol. In completing your CRP, suppliers are required to detail their emissions for five of these categories as detailed Scope 3 Category Category description Minimum boundary 4. Upstream transportation and distribution4 Transportation and distribution of products purchased by the reporting company in the reporting year between a company’s tier 1 suppliers and its own operations (in vehicles and facilities not owned or controlled by the reporting company) Transportation and distribution services purchased by the reporting company in the reporting year, including inbound logistics, outbound logistics (e.g., of sold products), and transportation and distribution between a company’s own facilities (in vehicles and facilities not owned or controlled by the reporting company) The scope 1 and scope 2 emissions of transportation and distribution providers that occur during use of vehicles and facilities (e.g., from energy use) The life cycle emissions associated with manufacturing vehicles, facilities, or infrastructure 5. Waste generated in operations Disposal and treatment of waste generated in the reporting company’s operations in the reporting year (in facilities not owned or controlled by the reporting company) The scope 1 and scope 2 emissions of waste management suppliers that occur during disposal or treatment Emissions from transportation of waste 6. Business travel Transportation of employees for business-related activities during the reporting year (in vehicles not owned or operated by the reporting company) The scope 1 and scope 2 emissions of transportation carriers that occur during use of vehicles (e.g., from energy use) The life cycle emissions associated with manufacturing vehicles or infrastructure 4 The government provides specific guidance for freight transport operators and for companies wishing to report emissions from their work-related
7. Employee commuting5 Transportation of employees between their homes and their worksites during the reporting year (in vehicles not owned or operated by the reporting company) The scope 1 and scope 2 emissions of employees and transportation providers that occur during use of vehicles (e.g., from energy use) Emissions from employee teleworking 9. Downstream transportation and distribution6 Transportation and distribution of products sold by the reporting company in the reporting year between the reporting company’s operations and the end consumer (if not paid for by the reporting company), including retail and storage (in vehicles and facilities not owned or controlled by the reporting company The scope 1 and scope 2 emissions of transportation providers, distributors, and retailers that occur during use of vehicles and facilities (e.g., from energy use) The life cycle emissions associated with manufacturing vehicles, facilities, or infrastructure Your Carbon Footprint The data required to complete your Carbon Reduction Plan will come from completing a carbon footprint for your organisation’s emissions from sources in the United Kingdom. You may already have an existing carbon footprint that you can refer to. To determine your carbon footprint, you may wish to seek advice and guidance from organisations operating within the carbon accounting sector, use available online tools and resources and consult your in-house teams where available, to ensure your carbon footprint is as detailed and accurate as possible. Many tools and resources are available for free if you are an SME or VCSE supplier. Your carbon footprint should be completed in accordance with best industry practice, using the best and latest data you have available. Your carbon footprint should adhere to the Greenhouse Gas Protocol’s Corporate Accounting and Reporting Standard and should be conducted to a reasonable level of assurance. ISO 14064-3 and ISAE 3410 are widely-used standards for the verification of GHG emissions reports, however it should be noted that there is no requirement to have your carbon footprint audited. | 19061716-f6e6-4e88-b453-1dfcfaec06cd | 0 |
0c36d86a-bae4-4bcb-92b6-bf5ec42d7440 | https://www.gov.uk//government/consultations/regulating-third-party-intermediaries-tpis-in-the-retail-energy-market | 2,024 | [
"Energy sector",
"clean energy",
"consumer protection",
"Third-Party Intermediaries (TPIs)",
"regulation",
"retail energy market",
"energy transition",
"climate crisis",
"economic inequality",
"market transparency",
"non-domestic market",
"Ofgem",
"consumer empowerment",
"energy suppliers",
"stakeholder consultation",
"energy procurement",
"energy management",
"regulatory approach",
"transparency",
"mis-selling",
"non-transparent practices."
] | gov.uk | The government envisions an energy sector that prioritises consumers, ensuring they benefit as Great Britain transitions into a clean energy superpower. This approach aims to address economic inequality while tackling the climate crisis, focusing on consumer protection and empowerment within the shift to clean energy. This consultation document seeks views on the regulation of Third-Party Intermediaries TPIs within the retail energy market, aiming to enhance consumer protection and support the transition to a cleaner energy system. This consultation occurs within the broader context of the governments ongoing commitment to support Ofgems efforts to create a well-functioning market for non-domestic customers. This includes collaboration to implement recommendations from Ofgems non-domestic policy consultation from July 2023 swiftly and effectively. Currently, there are concerns about the performance of some TPIs, which often act as intermediaries between consumers and energy suppliers. Issues such as non-transparent practices and mis-selling have been highlighted, particularly within the non-domestic market. This consultation outlines proposals to regulate TPIs, enhance consumer protection, improve market transparency, and ensure that TPIs contribute positively to the energy sectors evolution towards cleaner energy. It also considers the establishment of a general authorisation regime for TPIs as the preferred regulatory approach. The consultation is open to all interested parties, with a particular focus on stakeholders within the energy sector, including TPIs, energy suppliers, consumer protection groups, and businesses relying on TPIs for energy procurement and management. Read our consultation privacy notice. | 1f593fe5-5489-4d2e-8ddc-f9f9020f1554 | 0 |
0c37c8de-0b12-4847-a4f1-811cbf5ee0ae | http://arxiv.org/pdf/2112.09478v1 | 2,021 | [
"able",
"protest",
"survey",
"climate",
"participation"
] | arxiv.org | The GLM model ( 4) is generally estimable by maximum likelihood estimation methods (MLE, or alternatively Bayesian methods). However, since the results feed as inputs into the estimation of the participation model, due care is needed with respect to specification. We devote attention to two potentially important issues in section 5.1. First, our sample is clustered by location (a subject's home city, there are four possible clusters), date of study enrollment (the date a subject has participated in the first survey, there are six possible days), and date of treatment (the date a subject has participated in the second survey, there are five possible days), and each cluster may have specific effects. We will check for this by means of mixed-effects modeling, allowing for crossed random effects in the three clustering-dimensions. Second, the support of the dependent variable ∆b is limited to the interval [-1, 1]. We will check whether estimates from non-linear specifications that take account of this fact differ significantly from linear model estimates. Throughout, we will follow Occam's Razor. It turns out that a simple linear model provides decent results. We augment the participation model (1) in two ways. First, note that it can be expressed equivalently as a function of the change of belief ∆b, as defined above,
This changes the interpretation of parameter α and of the predictive margins slightly (the average participation probability if everybody would have the given value of ∆b, averaged over x), but it is easy to see that the interpretation of β and (since ∂∆b/∂b = 1) the marginal effect of beliefs is substantively preserved,
such that the meaning of hypothesis H 0 : β = 0 is still the same. 14 Yet, (5) has the advantages described above. 15 Second, using the belief updating model (4) in conjunction with (5), a control function approach can be used in which the residuals ê from the belief updating model are employed to fit
by MLE, where η ∈ R is a fixed parameter (Rivers and Vuong, 1988;Blundell and Smith, 1989). 16 We will report results including location and survey date fixed effects, and with and without bootstrap standard errors that account for clustering by location, date of study enrollment (i .e. date of first survey done), and date of treatment (i. e. date of second survey done). In the Appendix we will also report estimates from a traditional two-step approach in which the belief updating model predictions 13 The former is true if and only if θ 1 > 0, and the latter if and only if θ 1 + θ 3 < 0, which jointly implies θ 3 < -θ 1 < 0. 14 To be precise, we will report the APE based on the average structural function (Blundell and Powell, 2004). There are other approaches (Lewbell et al., 2012), but the average structural function approach has decided advantages (Lin and Wooldridge, 2015). 15 Specifically, Kendall's rank correlation coefficient between a and b is .0884, and statistically significantly different from zero (tie-corrected Kendall's score 43279 ± 10576.1, continuity corrected p = .0000). Thus, this correlation has the opposite direction of the causal effect that we uncover in Section 5. 16 In principle, parameter η is estimable and can be used to test for the endogeneity of beliefs, but since MLE estimates the parameters in the belief updating and participation models jointly, it is not actually estimated. Instead a test for zero correlation between the residuals checks for endogeneity (reported in Section 5). by Newey's efficient minimum χ 2 method (Newey, 1987). A key advantage of the control function method is that it estimates the parameters and their variances separately, whereas Newey's estimator yield variance-normalized estimates that are cumbersome to interpret and which cannot directly be compared to the MLE estimates (see Wooldridge, 2010, pp. 585-594, for a detailed discussion). We directly test the null hypothesis H 0 : β = 0 against the alternative H 1 : β = 0 by a single-parameter Wald test. The square-root of the observed Wald statistic ( W ) is under the null hypothesis equal to the ratio of the MLE estimate β and its standard error, and follows an asymptotic normal (z) distribution (Davidson and MacKinnon, 1993, p. 89). We consider the null hypothesis rejected if the observed W is outside the critical region implied by a false-positive probability threshold (level of significance) of five percent. We will report the p-value for easy evaluation under different significance thresholds. The APE estimate can also be understood within the potential outcomes framework as a so-called local average treatment effect (LATE, Imbens and Angrist, 1994;Angrist et al., 1996). This perspective clarifies that it hinges on two critical assumptions that are fundamentally untestable (because each subject is only observed under one of the two experimental conditions): the independence or valid instrument assumption, and the monotonicity assumption. In our setting the monotonicity assumption means that beliefs follow the direction of the informational stimulus, as formalized by (2), and the valid instrument assumption means that any effect of treatment on participation is fully mediated by beliefs. 17 Mourifié and Wan (2017) derived testable implications of the two assumptions in the form of two conditional moment inequalities, which can be tested by a conditional likelihood ratio test in the intersection bounds framework (Chernozhukov et al., 2013). We will apply the local method of the test to each of the "above-" and "below-groups" separately, because the monotonicity assumption goes in opposite directions. We consider our estimates as "sound", in the sense of being consistent with the valid instrument and monotonicity assumptions, if none of the tests rejects the null hypothesis that the two conditional moment inequalities are consistent with the data at a significance threshold of no less than ten percent. Figure 2 visualizes the effect of treatment on beliefs by kernel density plots of observed ∆b split by experimental condition. | 98838900-82e4-48d3-aefb-a6406b37ec9f | 5 |
0c3cdab4-eacc-487e-a8ff-949b198ab794 | https://www.gov.uk/government/publications/national-framework-for-water-resources-2025-water-for-growth-nature-and-a-resilient-future/3-how-much-additional-water-we-need-national-framework-for-water-resources-2025 | 2,025 | [
"future non - public water needs",
"supply -627.35 -627.35 -627.35 -627.35 climate change impact",
"water resource zone climate change environmental",
"demand climate change impact",
"full environmental destination planning scenario"
] | GOV.UK Environment Agency | The modelling of scenarios of population growth, climate change and environmental sustainability reductions demonstrates that without action, there could be a public water supply ( PWS ) deficit of up to 5,000 Ml/d by 2055. Additional pressure will result from other sectors of use, particularly from the energy, food and data centre sectors. Non- PWS sectors alone will account for an additional demand of 1,090 Ml/d by the 2050s. The National Framework provides a picture of water needs across the country by 2055. Figure 4 shows the forecast water needs for each regional group in England. The estimated additional public water needs are based on the Do Nothing modelled scenario. The Do Nothing scenario assumptions are explained in section 2.2. The forecasts for future non-public water needs are presented as the estimated total demand for 2055, including current demands and are based on an upper estimate scenario that considers recent actual abstraction adjusted for consumptiveness, with relevant sector-based growth factors applied. The forecasts exclude coastal, tidal and estuarine abstractions as well as abstraction related to navigation. The forecasts do not include new or emerging non- PWS demands such as low carbon energy or data centres. The non- PWS forecast approach is explained in further detail in section 3.2. Figure 4: Understanding England's future water needs by 2055 For PWS , the estimated additional water need between 2030 and 2055 includes the key drivers: increasing resilience to a 1 in 500-year drought high population growth high environmental improvement through delivery of the most ambitious reductions identified in current water company plans individual water company analysis of climate change impacts There are also other factors influencing the water supply by 2055, not captured above, which will result in both increases and decreases in total water availability across each region. We also show the upper estimate forecast of the proportion of consumptive water used by the different sectors in each region. We have shortened million litres per day to Ml/d . Water Resources West ( WRW ) The map shows the full area of WRW including parts of Wales. The values also include Welsh zones within the boundary, but the headline figures in the Framework do not. Additional PWS needs between 2030 and 2055 are 1,073 Ml/d including: drought resilience: 62 Ml/d population change: 232 Ml/d environmental improvement: 572 Ml/d climate change: 84 Ml/d Estimated total demand from other users is 416 Ml/d : 52% industry (food and drink, metal production, chemicals) 28% agriculture (spray irrigation) 13% power generation Water Resources North ( WReN ) Additional PWS needs between 2030 and 2055 are 345 Ml/d including: drought resilience: 70 Ml/d population change: 99 Ml/d environmental improvement: 109 Ml/d climate change: 60 Ml/d Estimated total demand from other users is 222 Ml/d : 27% industry (food and drink, chemicals, mineral products) 20% agriculture (spray irrigation) 51% power generation Water Resources East ( WRE ) Additional PWS needs between 2030 and 2055 are 679 Ml/d including: drought resilience: 114 Ml/d population change: 165 Ml/d environmental improvement: 415 Ml/d climate change: 26 Ml/d Estimated total demand from other users is 515 Ml/d : 12% industry (food and drink, chemicals, mineral products) 51% agriculture (spray irrigation) 27% power generation West Country Water and Environment ( WCWE ) Additional PWS needs between 2030 and 2055 are 260 Ml/d including: drought resilience: 5 Ml/d population change: 85 Ml/d environmental improvement: 182 Ml/d climate change: 20 Ml/d Estimated total demand from other users is 217 Ml/d : 61% industry (food and drink, chemicals, mineral products) 26% agriculture (spray irrigation) 1% power generation ( WRSE ) Additional PWS needs between 2030 and 2055 are 2,034 Ml/d including: drought resilience: 377 Ml/d population change: 424 Ml/d environmental improvement: 1,350 Ml/d climate change: 161 Ml/d Estimated total demand from other users is 143 Ml/d : 28% industry (food and drink, chemicals, mineral products) 37% agriculture (spray irrigation) 24% power generation 3.1 Environmental needs The quantification of changes to current and future abstraction needed to meet environmental requirements is known as the Environmental Destination for water resources. The Environmental Destination for water resources identifies where, and by how much, water abstraction needs to change to achieve and maintain a healthy water environment, both now and in the future. The Environmental Destination defines the long-term environmental outcomes to ensure abstraction from rivers, groundwater, lakes, wetlands and estuaries is environmentally sustainable, both to address current unsustainable abstraction and future pressures. It identifies where and by how much abstraction may need to reduce to meet current and future environmental requirements for nature. It considers both legal requirements and government commitments. It includes known challenges and assessments of the future potential impact of climate change and considers growth. The detailed technical approach to assessing environmental needs is contained in Appendix C: Environmental Destination technical report. This includes how we use this includes how we use environmental flow targets to identify where changes to abstraction may be required. The figures presented here are a high-level indication of need. They have been adjusted downwards to reflect the actions already included in the 2024 round of water company water resources management plans. They are based on national data sets and analysis and do not include where there may be additional local environmental requirements. They have not been adjusted to reflect any 'overriding public interest' decisions which may be made in the future. The figures may also need to be refined as the growth agenda is reflected in . They allow for better evidence to be used to refine the assessments locally and are the starting point for regional water resources groups to take the national figures and to refine them as they develop regional plans. We will provide supplementary technical guidance to advise regional groups on how to include Environmental Destination needs within their plans. Where water companies have sources within or affecting Wales (to supply England), Natural Resources Wales provides guidance on how to meet Welsh legislation Environmental Destination requirements. | 61d6982c-d194-48eb-a8ca-bb239ebdfd2d | 0 |
0c411c53-9692-4599-b0d7-a98781d00d17 | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32018R0956 | 2,017 | [
"Transport",
"Low-emissions mobility",
"Heavy-duty vehicles",
"Light-duty vehicles",
"Energy efficiency"
] | eur-lex.europa.eu | 3.5. (1) Commission Regulation (EU) No 19/2011 of 11 January 2011 concerning type-approval requirements for the manufacturer s statutory plate and for the vehicle identification number of motor vehicles and their trailers and implementing Regulation (EC) No 661/2009 of the European Parliament and of the Council concerning type-approval requirements for the general safety of motor vehicles, their trailers and systems, components and separate technical units intended therefor (OJ L 8, 12.1.2011, p. 1). | dcf8b728-01c2-4912-9703-30bf665b839c | 16 |
0c4d015b-a2bc-44ec-80de-62747fc3fc48 | 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 | A solution set can be assessed by comparing its hypervolume with that of competing algorithms or the true Pareto front, if known. Expected utility ( ↑ ) When the decision-maker’s utility function u is linear, the expected utility (EU) metric can be used to represent the expected utility over a distribution of reward weights W . GINI Index ( ↓ ) The GINI index is a measure of inequality that quantifies disparities among agents based on a specific metric, with 0 indicating perfect equality and 1 indicating maximal inequality; we employ Concept-1 GINI by Milanovic to assess international inequality, where each agent represents a region and the index reflects whether their metrics are converging. 4.2 RICE50+ Comparison
We compare our results with the default RICE50+ model, as outlined in Section 2.1. This model consists of 57 regions and integrates optimization directly within the global climate simulation. The optimization follows a single-objective approach, employing asocial welfare function asthe global objective and using a single representative agent to optimize welfare, rather than a multi-agent multi-objective framework. The results presented in the next section are obtained using standard IAM methods, specifically non-linear programming within the General Algebraic Modeling Language (GAMS) for policy optimization. Unlike our approach, RICE50+ does not perform inter-temporal optimization at each timestep. Instead, it optimizes over the entire time horizon by using asocial welfare function as a proxy for consumption per capita. Since consumption per capita is directly derived from net economic output, we extract the net economic output from RICE50+ to compare with our objectives. 5 Results
The objectives of our experiments are to verify the convergence of JUSTICE MOMARL, compare the solutions between JUSTICE and the RICE50+ model, and analyze key solutions from the Pareto set. We present results in line with these objectives. 5.1 Convergence
Figure 2 showsthat our agents converge and demonstrate consistent training over time, with both performance metrics growing and eventually stabilizing. Note that both the hypervolume and Expected Utility metrics appear large due to their exponential scaling with the number of objectives and the achievable value ranges, particularly influenced by the high values of the GEO objective. 5.2 Solutions
Figure 3 showsthe Pareto set of solutions produced by J US TICE and the single RICE50+ solution (red star). We transform the objective values for simplicity: Total Global Eco
nomic Output representsthe GEO objective, and Global Average Annual Temperature correspondsto the mean of the inverse of IGT (inverted to retrieve the temperature). Global Average Annual Temperature Rise (°C)
Figure 3: Pareto set of policies obtained by JUSTICE with the RICE50+ polict for comparison. Arrows indicate the direction of preference for the objectives. JUSTICE produces 22 solutions (policies), shown as circles in Figure 3. Among these, three are highlighted: Climate Policy (purple), Economic Policy (green), and Compromise Policy (yellow). Although the purple policy is not the most extreme in terms of climate performance, it achieves substantial economic gains with only a slightincrease in temperature compared to the extreme climate solution. Therefore, it is chosen asthe Climate Policy. This example illustrates how the multi-objective approach supports decision-making by presenting a range of trade-offs. The RICE50+ solution lies close to the JUSTICE Pareto front, roughly in the middle, indicating a balance between economy and temperature rise. However, the JUSTICE Compromise Policy dominatesthe RICE50+ solution, albeit by a small margin. Thus, JUSTICE not only offers a range of solutions but also a slightly better solution than RICE50+. 5.3 Comparison of Key Solutions We perform a comprehensive analysis of the highlighted policies in Figure 3—the three JUSTICE policies and the RICE50+ policy. To do so, we plot the key IAM outcomes from 2015 to 2300 for these policies in Figure 4. The economic output trajectories are shown in left panel of Figure 4. | 7c3e1d27-98bf-466b-a75e-da988f6e44f0 | 7 |
0c51f924-8e9b-4dbc-811e-f0fdec098dfd | 2,025 | [
"emission vehicles",
"new light commercial vehicles",
"biofuels",
"city centers",
"deliveries"
] | HF-national-climate-targets-dataset | 2.1.1.1.4 Recycled carbonaceous fuels and biofuels By 2030, at least 30% of new light commercial vehicles and vans purchased will be zero-emission vehicles. The others will be mostly low-emissions or low-carbon intensity. We promote emission-free distribution so that by 2025 only zero-emission vehicles will be circulating in city centers for deliveries | a46f0680-6c48-47e0-8878-008bc2b758b0 | 0 | |
0c52f7e3-097b-4f41-8e0f-57bcf7369a81 | http://arxiv.org/pdf/2012.14976v1 | 2,020 | [
"energy",
"carbon",
"reme",
"materials",
"cost"
] | arxiv.org | This paper describes and assesses the feasibility of a REME future and the pathway to implement it. Our REME future contains aspects of a circular economy and the circular carbon economy is a derivative of it. REME can be viewed as a Circular Carbon Economy that closes the human carbon cycle in harmony with the earths carbon cycle. 10 A conclusion of the assessment is that the HDCCRRE technologies can satisfy the scale and cost requirements needed to create an era of unprecedented global prosperity. It also concludes that the building materials we will use, if made from carbon from atmospheric CO2, provide the opportunity to sequester and monetize more carbon than necessary to meet the Paris Accord target. An important overall conclusion is that it makes sense to transition to REME, especially for its economic benefits, even if no climate threat existed. Additionally, the world's current energy and conversion technologies developed in the fossil fuel era will be useful for transitioning from a natural resource based economy to REME. In the 21 st century REME will lead to an era of unmatched welfare for humans and the rest of nature. Changes in use of energy have always driven major advances in human progress. In our past, human produced energy began with the use of wood, was followed by coal, oil, then natural gas, and now is ending in renewable energies (solar, nuclear) with fusion, which mimics the sun as the ultimate energy source. REME can be understood as a major advance in human progress enabled by low cost abundant renewable energy. ! "! The HDCCRRE approach will be successful by making its energy and materials at comparable to and in many cases even lower cost than their fossil energy natural resource based equivalents. This will be the case if we develop processes that can be implemented on a very large global scale and achieve the following performances:
1. Renewable energy produced electricity at less than 2 cts/kWh 2. Capture of CO2 from the air at under $50/tonne (For comparison a tonne of CO2 at $50 has the equivalent carbon content as $20 dollar/barrel oil.) This, in turn, will enable us to make: 4. Liquid synthetic fuels from CO2 and hydrogen for around $3/gallon, also other hydrocarbons at comparable costs to fossil-based hydrocarbons. 5. Carbon fiber based construction materials from atmospheric CO2 with cost/performance properties competitive or comparable to steel and aluminum. Concrete and the aggregate it uses can also provide sources for sequestering CO2. 11 REME makes sense even if the so-called private cost (cost paid by the consumer, based upon the cost to produce the energy and materials) is greater than the cost for producing energy and materials using fossil fuel or mineral resources. This is because of REME's social benefits compared to the social costs of fossil energy use. The social benefits of REME in providing energy security, removing conflict over resources, and preventing environmental damage and addressing the climate threat are very significant. On the other hand the fossil energy and resource extraction economy has significant negative social impacts in the same areas. Thus, a comparison of the social costs of the fossil fuel economy and REME would clearly suggest we make a transition to REME unless the private costs were very much higher. However, for our analysis we will use the highest criteria, that the REME private costs are less or comparable to the private costs of the natural resource-based economy, when REME is practiced at a global scale. Its profitability in addition to its critical social benefits is what truly ensures that REME will attract both private and public investment enabling high growth rates. This in turn will lead to global prosperity on a widespread basis, most notably by providing the increased demand and high skilled jobs needed in the developing countries. This does not mean that legislation is not needed to properly ensure that the REME social benefits are recognized and thus further increase the rate of implementing REME. REME is in harmony with other ecosystems that support us and other life forms. We also can use this ability on behalf of other life forms, thus providing the ultimate ecosystem service of preventing extinction. REME marks a transition from our species living off the land to making sure the land can support us and all life sharing the planet with us. Before addressing the feasibility of achieving each of these objectives, there are some generic properties of global technology transitions that will enable their costs to be economically viable. The learning curve methodology is useful to identify three important generic characteristics of transitions. The first is that the extremely large scale needed for global implementation of REME means that all the technologies will effectively reach their learning curve limits. Secondly, it means that the total cost from today till when global scale implementation will be achieved will be dominated by the last four to five doublings of capacity. The costs earlier on, as has been for example the case with solar, are not significant to the total cost of conversion when implemented at the global scale. So, in using the current costs, learning rates and learning curve limits, one can determine whether the cost targets will be reached well before global scale implementation (e. g. before the last four to five doublings). The final and critical characteristic of the transition to REME is the existence of socalled low hanging fruit in the early parts of the learning curve where REME costs will be high. There are many applications for renewable energy and renewable materials that can still be economically viable, while HDCCRRE technologies are low on their learning curves and thus at higher costs than their learning curve limited costs. Again, solar is a good example. Earlier applications in space and off grid power were viable at very high costs and as the costs have come down the applications and market penetration have increased dramatically. | be498d09-29d7-45e0-934c-77d10d4cd3dc | 1 |
0c5a4a99-9aa9-487b-8dcb-5aa2e992a939 | 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 | The government has set up a floating offshore wind demonstration programme to support development of state-of-the-art technologies and products in the floating Government has set an ambition to deploy 5 GWs of low carbon hydrogen production capacity in the UK by 2030, supported by a package of measures including the Net Zero Hydrogen Fund (NZHF). The NZHF will kickstart the hydrogen economy in the early 2020s by supporting projects with upfront costs, stimulating private sector investment, and developing the pipeline of projects needed to deliver hydrogen production The UK is already capitalising on opportunities from the global shift to electric vehicles, as demonstrated by recent investments made by Stellantis in Ellesmere Port, and Nissan and Envision AESC in Sunderland. Allocating a further £350 million of our up to £1 billion Automotive Transformation Fund (ATF) to support the electrification of UK vehicles and their supply chains. This will help ensure the UK maximises the benefits from the transition to a zero emission vehicle future and support tens of thousands of high-quality green jobs across the UK. Government and industry have also jointly committed around £1 billion through the Advanced Propulsion Centre for collaborative research and development in the next generation of low carbon vehicle technologies. A further £318 million of government funding has been provided to put the UK at the forefront of the design, development, and manufacturing of electric batteries through the Faraday Battery Challenge and nearly £80 million to Driving the Electric Revolution to accelerate growth in the supply chain for power electronics, Net Zero Build Back Greener
Chapter 4 – Supporting the Transition across the Economy Driving investment and jobs in the Government’s Green Recovery Challenge Fund is supporting over 150 projects across England that are tackling climate change, restoring nature, and supporting 2,500 green jobs. The Nature for Climate Fund is also contributing to net zero and creating and supporting green jobs by funding new woodland creation and peatland restoration. In addition, the £9 million Natural Environment Investment Readiness Fund is stimulating a pipeline of nature projects that can attract
9. We are working in partnership with our world-class sectors to enable them to take part in the transition, for example through the North Sea Transition Deal, which committed to focusing on supporting the transformation of the oil and gas supply chain to service the low carbon energy sector. Building on this, we have established the Energy Supply Chain Taskforce (UKESC) as a joint enterprise between industry and government to guide policy making and maximise the jobs and business opportunities from the transition in the UK. The UKESC energy sectors and regions of the UK and, building on work already underway, it will map the energy project pipeline and identify higher value segments of the supply chain to 10. The Integrated Review Security, Defence, Development and Foreign Policy committed to ‘a resilient UK able to withstand and proactively tackle the challenges of today and the future’, including a specific focus on supply chain resilience, committing to ‘using all our economic tools and our independent trade policy to create economic growth that is distributed more equitably across the UK and to diversify our supply chains in critical goods’. Similarly, the Plan for Growth outlines the importance of international markets to ensuring diverse supply sources for the goods and services we need, improving the resilience of our supply chains and benefitting prosperity. 11. The development of resilient, efficient, and competitive supply chains will be a collaborative strategic endeavour. To support this, in May 2021 we published the CCUS Supply Chain Roadmap, which sets out how government and industry can work together to harness a strong UK supply chain, and we have committed to publish a hydrogen sector development action plan in 2022, which will outline how the government will support companies to secure supply chain opportunities, skills and jobs in the sector. We will build on this by working with industry to publish further sector and supply chain development plans for those low carbon sectors where the UK has the potential to capture an economic advantage. This will include ensuring we are resilient to international changes in supply caused by external shocks, including climate-related disruption, spikes in global demand, rising commodity costs, or artificial constraints on supply. For example, we will need to ensure we have access to a diverse range of sources of chemicals, given they feed into 95% of our manufacturing base. As we move forward, where possible, government will provide more visibility around planned deployment cycles to increase the opportunity for suppliers to invest in long-term production, Net Zero Build Back Greener
Chapter 4 – Supporting the Transition across the Economy Deep Dive - Critical Minerals, The transition to Net Zero means new supply chains are becoming critical to the UK’s energy production. Critical minerals are metals and non-metals that are vital for a defined economic activity and for the well- being of the country, yet whose supply may be at risk owing to geological distribution, lack of substitutes and/or other factors. Such minerals provide materials essential for components in many of today’s rapidly growing clean energy technologies – from off- shore wind turbines to electric vehicles. The World Bank suggests that the production of minerals such as graphite, lithium and cobalt, could increase by nearly 500% by 2050 to The government is committed to working with industry and with international partners to safeguard these supply chains and our future economic resilience. We are actively supporting the adoption of transparent, ethical and responsible mining practices, reflecting environmental, social and governance (ESG) considerations, and are participating in the development of global standards through the British Standards Institution. We will establish an Expert Committee on Critical Minerals to provide independent advice to government on the scope and content of a critical minerals strategy and will publish an updated list of these minerals to guide investment decisions. | 23d06bea-fd9c-4b53-9b9a-c35258d49ad9 | 71 |
0c5df850-a927-4093-b22e-d6ab4ce84e3c | 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 | . Maximum torque conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Delete where not applicable there are cases where nothing needs to be deleted when more than one entry is applicable. a
v The specified particulars are to be given for any proposed variants. 28.7.2008
EN
Official Journal of the European Union
L 19941
4.5. 4.5.1. 4.6. Gearbox
Type manualautomaticCVT continuously variable transmission 1 . . | d3fc6859-41cb-4ee2-997b-90ebc4f9b481 | 176 |
0c619744-abc7-4def-a6de-df76ea3a0d48 | https://cdn.climatepolicyradar.org/navigator/GBR/2024/united-kingdom-biennial-transparency-report-btr1_0e77f9e4d928e6e9d64ea26cd95945e1.pdf | 2,024 | [
"climate",
"change",
"emissions",
"energy",
"government"
] | cdn.climatepolicyradar.org | The approach taken by each administration will differ, drawing on the range of policies at their disposal. As explained in Chapter 1, the UK’s ratification of the Paris Agreement has to date been extended the three Crown Dependencies, and the Overseas Territory of Gibraltar – so these are in scope of the UK’s NDC. | 2ae0b548-ef04-451f-aba3-617d0f3c41f8 | 30 |
0c624a0b-2580-4a0c-9bb4-63edf6ca0c6a | https://www.legislation.gov.uk/ukpga/2008/27/schedule/6/paragraph/23 | 2,008 | [
"civil sanction",
"e+w+n.i.",
"relevant national authority",
"regulatory activities",
"breach"
] | legislation.gov.uk | 23 E+W+N.I. A relevant national authority may not make any provision conferring power on an administrator to impose a civil sanction in relation to a breach of regulations under this unless the authority is satisfied that the administrator will act in accordance with the principles that- (a) regulatory activities should be carried out in a way that is transparent, accountable, proportionate and consistent; (b) regulatory activities should be targeted only at cases in which action is needed. | 078df434-04e8-4935-b1e2-bbebb1fe00f0 | 0 |
0c65bdcc-7a2a-4960-a1b0-dc2dabec377e | 2,025 | [
"various regulated sectors",
"transparency",
"consistent approach",
"smarter regulation",
"due course"
] | HF-national-climate-targets-dataset | 3.18.5.1 Increasing transparency of progress 3.18.5 Demonstrating progress towards net zero government to choose how they intervene in their sectors, to allow more agile, smarter regulation. The Government would like to see a consistent approach taken across the various regulated sectors and will set out more thinking on this in due course. | 51f2a816-8f5c-4abf-b91c-88aec0e0cb61 | 0 | |
0c67e8a7-c9d5-43a6-9d0b-77d074a4adce | 2,025 | [
"annual greenhouse gas emissions",
"climate change",
"carbon dioxide",
"i.",
"tonnes"
] | HF-national-climate-targets-dataset | I. - The fight against climate change is a top priority. In this perspective, the commitment made by France to divide its greenhouse gas emissions by four between 1990 and 2050 is confirmed by reducing by 3% per year, on average, greenhouse gas emissions in the atmosphere, in order to reduce its annual greenhouse gas emissions by this deadline to a level below 140 million tonnes of carbon dioxide equivalent. | cd429e18-be5b-4ffc-9d5c-6a8a20eedf3b | 0 | |
0c7017b4-6f7c-4dab-870d-5d9c6cdc0a1b | 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 | More recently road transport use appears to be returning to pre-pandemic levels, but public transport usage is still to regain these levels. 9/3/2020 9/4/2020 9/5/2020 9/6/2020 9/7/2020 9/8/2020 9/9/2020 9/10/2020 9/11/2020 9/12/2020 9/1/2021 9/2/2021 9/3/2021 9/4/2021 9/5/2021 9/6/2021 Use % of equivalent day or week (7 day average)
Last year, we commissioned research (see Part 2) to understand the impact of COVID-19 on current and future travel choices. | 8f0273a5-decd-4a43-ab49-4f3473699e66 | 30 |
0c7560f0-7306-4e7b-9a09-8d877b3bc834 | 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 | Ambitious goals on reducing emissions should be accompanied by a promise also to increase action on adaptation, which is a key theme of the Paris Agreement and an increasingly urgent priority given the continued changes in the climate that can be expected even if the Paris Agreement goals are met. The Government must then set the Sixth Carbon Budget in law by the end of June 2021. This must be followed, as soon as is practicable, by a set of policies and proposals that demonstrably would meet the budget. We recommend that both these steps are taken without delay, in the first half of 2021. Such prompt action would demonstrate the UK’s climate credentials as President of COP26 and would give confidence to businesses looking to invest and make their own Net Zero transitions. It is necessary given the scale and speed of change We expect to report on the Government’s strategies in our next annual Progress _______________________________________________________________________________ This report represents an extensive programme of analysis, consultation and consideration by the Committee and its staff, building on the extensive evidence published last year for our Net Zero advice. This our public Call for Evidence; 10 new research projects; three expert advisory groups on health, finance and policy for Net Zero; policy roundtables on heating buildings, electricity market design and phase-out of unabated gas, digitalisation, greenhouse gas removals and low-carbon industry; detailed datasets and deep dives into the roles of local authorities and businesses. The outputs of our work are published on our website ( and explained in the five parts (10 chapters) of this report and its accompanying Policy report and Methodology report.9 • Part 1: The path to Net Zero sets out the scenarios that underpin our advice and that demonstrate how the Sixth Carbon Budget can be overall (Chapter 2), sector by sector (Chapter 3) and for Scotland, Wales and • Part 2: Impacts of the Sixth Carbon Budget sets out (in Chapter 5) our estimates of the costs, investments and potential economic impact of the budget, and (in Chapter 6) the need for a just transition, including implications for jobs, competitiveness, energy bills and the public finances. • Part 3: International Circumstances and Climate Science sets out how our recommendations represent a fair and ambitious contribution to the Paris Agreement, including consideration of the UK’s broader contribution to tackling climate change beyond UK territorial emissions, including the UK’s overseas consumption emissions (Chapter 7). Chapter 8 sets out the relevant climate science that underpins our advice. • Part 4: Recommendations sets out why our recommended pathway reduces emissions more quickly before 2035 than after 2035 (Chapter 9) and our full recommendations relating to the Sixth Carbon Budget (Chapter
33 Sixth Carbon Budget – The path to Net Zero
1 Border carbon tariffs impose a carbon tax at the border on imported products based on their embedded emissions, or carbon footprint. By matching the border carbon tariff to domestic carbon taxes imposed in the UK, a level playing field can be provided. 2 CITB (2020) Building Skills for Net Zero (draft report). 3 See Chapter 3 of this report. 4 Nicol S. et al. (2015), The cost of poor housing to the NHS. 5 Quoted emissions percentages refer to those used in this report, with adjustments from the UK’s official inventory to reflect upcoming changes for peatland emissions and Global Warming Potential (GWP) estimates. They are as a proportion of a total that includes international aviation and shipping. For some sectors (agriculture, land use, waste, F-gases, aviation and shipping) the latest available estimates are used, from 2018. Energy-from-waste emissions are reported within the waste sector. 6 The International Civil Aviation Organisation and the International Maritime Organisation. 7 BEIS = The Department for Business, Energy and Industrial Strategy. 8 CCC (2020) Policies for Net Zero and the Sixth Carbon Budget. 9 CCC (2020) The Sixth Carbon Budget – Methodology Report. 35 Sixth Carbon Budget – The path to Net Zero 2. Context – uncertain and urgent times 40 3. COP26 and international leadership 42 4. Using scenarios to identify a balanced path to Net Zero 43
37 Sixth Carbon Budget – The path to Net Zero The Sixth Carbon Budget sets the limit on allowed UK territorial greenhouse gas emissions over the period 2033 to 2037. It is our duty under the Climate Change Act to advise on it by the end of 2020, following which it must be legislated by the Our advice on the Sixth Carbon Budget builds on our Net Zero advice from May • This is the first carbon budget to be set on the path to the UK’s Net Zero target for 2050, which was placed in law in summer 2019. Whereas the Net Zero advice focused on the end point, this advice looks at the whole pathway and effectively provides the trajectory for emissions over the coming three decades on the way to Net Zero. • We have gone beyond the ‘proof of concept’ Further Ambition scenario presented in our Net Zero advice, to look at different ways of achieving Net Zero. We present five Net Zero scenarios, which explore how developments in behavioural and societal change and in technology may affect the path This advice comes at a critical juncture – the opportunity is there for the UK to provide international leadership in the run up to COP26, while also driving a resilient recovery through the low-carbon investments that will get us on track to Net Zero. We introduce our advice in five 2. Context – uncertain and urgent times 3. COP26 and international leadership 4. Our approach – using scenarios to identify a balanced path to Net Zero 5. Requirements of the Climate Change Act This advice effectively sets the
Chapter 1: Introduction and key m essages 38 In May 2019, the Committee recommended that the UK increase ambition under the Climate Change Act to require greenhouse gas emissions to reach Net Zero by 2050. | 083c769d-ace3-415a-9bbf-6c9f1540dcd7 | 10 |
0c7c3e25-f14b-4e18-b949-7f9b9e3ca952 | http://arxiv.org/pdf/1603.08961v3 | 2,016 | [
"model",
"traders",
"climate",
"market",
"prediction"
] | arxiv.org | Increasing the number of edges per trader increases the flow of information through the market, which causes traders to converge toward believing the "true" climate model. Segmented social networks reduce convergence by creating an "echo-chamber" effect, in which lack of interaction between traders with different views reduces traders' access to information that could persuade them to change their beliefs. This is apparent in Fig. 3, where the rate of convergence in highly segmented markets (seg = 0.95) is considerably slower, especially in the first three trading sequences (18 years), than for markets with low segmentation (seg = 0.05). When the true model is CO 2 -driven there is more convergence toward the true model. We believe this is because when models are fit to the historical data, the residuals from the CO 2 -driven model are considerably smaller than those from the TSI-driven model. Thus, projections of future climate change using the TSI model will exhibit significantly larger stochastic noise than the CO 2 models, and this noise makes it more difficult for traders to identify the true model when the true model is TSI. Traders with higher risk tolerance will price buy and sell orders more aggressively, so they will earn more (or lose less) on completed trades, but will have a greater risk of failing to complete trades. Among traders with the correct model of climate, those with higher risk tolerance will earn more profit on completed trades (and their counterparties will lose more). A trader's wealth is an important source of information, and we believe this is why greater risk taking enables traders to identify the correct model more quickly. Additionally, the risk of failing to complete trades adds volatility, which also puts information in play. We have observed a similar phenomenon in a very different context, where adding stochastic noise to player decisions in iterated games improves the accuracy with which machine-learning algorithms can identify the players' strategies (Nay and Gilligan 2015). What is not clear to us is why increasing the number of traders slows convergence, even if the number of edges per trader remains fixed. This is a topic for future research. We simulate two alternative climate futures: one where CO 2 is the primary driver of global temperature and one where variations in solar intensity are the primary driver. These represent the two most plausible competing views in the public discourse and our analysis is agnostic about which is "true". Market participation causes traders to converge toward believing the "true" climate model under a variety of model parameterizations in a relatively short time: In markets with low segmentation, the number of traders believing the true model rises from 50% to 75% in roughly 12 years, and even in highly segmented markets, 75% convergence is achieved in 18-24 years. Ideally, we would like to compare belief convergence with and without a prediction market but because the only source of climate belief in our current model is market interactions we cannot make this comparison. However, we do use actual temperatures for our model under historical 20th century conditions and observe convergence to the CO 2 model, whereas in the real world there is no convergence of beliefs. Both the historical and future simulation results suggest that a climate prediction market could be useful for producing broad agreement about the causes of climate change, and could have persuasive power for people who are not persuaded by the overwhelming consensus among climate researchers that greenhouse gases (and especially CO 2 ) are responsible for the majority of observed climate change (IPCC 2013). We also find that market segmentation has a large effect on the speed of convergence, so transparency and effective communication about the performance of traders with different beliefs will be important. The fact that rapid convergence to the true model occurs regardless of which model is actually "true" may persuade those who doubt the scientific consensus that the market is ideologically neutral, and that the deck is not stacked to produce a pre-determined result. All code and data for the model is available at github.com/JohnNay/predMarket. This project is a computational test-bed for public policy design: our code can be extended to test the effects of trading strategies, cognitive models, future climate scenarios, and market designs on the evolution of trader beliefs. | d54e8d90-571b-4e51-aac6-0336235f1fc4 | 4 |
0c7d218f-58b1-4695-b9e5-e2a97571ce50 | http://arxiv.org/pdf/2506.05555v1 | 2,025 | [
"Collective risk",
"Social dilemmas",
"Generative AI",
"Large Language Models",
"LLM",
"Empirical research",
"Scalability",
"Diversity",
"Institutional economics",
"Sustainability",
"Port of Mars",
"Social underpinnings",
"Human behavior",
"Game theory",
"Experimentation",
"Validation",
"Artificial intelligence",
"Risk",
"Group objective."
] | arxiv.org | In Fig. 4 we present a breakdown of the wins across the variants. On the x-axis we have the SVO angle of the leader, and on the y-axis we have the corresponding SVO angle of the player that one an experiment. For example, in the first heat map, the box 18 in the top-left corner captures the fact the -15 [◦] SVO player won 18% of the experiments when the -15 [◦] player itself was the leader. We highlight along the diagonal the outcomes for the player that is the leader. For each of the leadership variants, we note a specific finding. Firstly, for the announced leader variant we can see that the overall survival rate is comfortably the highest in comparison to the two other leadership variants. If we
Figure 6. Results of the optimal group experiments. Total system health spend is the sum over all of the players contribution throughout a full run. A lower Gini Inequality score implies more equality across the players. The dots are scaled by the average score of all the players in the experiments, with larger dots implying the average score across the players was higher. add up all of the percentages (note the total runs for each variant is the same), we find the total for the announced variant to be 414 vs. 336 (unaware) vs. 334 (vanilla), which suggests the announced variant leads to the highest survival rate overall. This aligns with findings suggesting that the mere presence of a recognised leader can be crucial for maintaining a social-ecological system. We note slightly different effects for both the unaware and vanilla leadership variants. For the unaware variant, the impact is probably as expected - a much lower overall survival rate than the announced variant, probably due to the lack of a leadership effect, and also little noticeable impact on the leaders winning performance themselves (not deviating far from their mean performance under any other leader). The vanilla variant, on the other hand, shows an interesting impact on the leaders own performance. Whereas the overall survival rate under the vanilla variant is much lower than the announced variant, the leaders individual win-rates are greatly reduced for all but one of the SVO values (consider the highlighted green boxes in comparison to the other values in the rows). This may be explained by a mixture of cheap talk which causes the leaders to take pro-self actions, whilst not gaining the recognised leader effect of. 4.5. The Optimal Group
In our final experiment, shown in Fig. 6, we aim to identify the optimal group composition based on system health, average player points and the Gini inequality (a measure of the equality across the five players). While simplistic, one could argue that optimal play balances high system health investment (to prevent port collapse), high individual points (ensuring no player’s success is compromised) and a low Gini inequality score (equality of points across players). Fig. 6 summarises the average outcomes from all our experiments. Results for SVO angles ranging from -15 [◦] to 60 [◦]
correspond to those discussed in the main figures, while an additional set of experiments with SVO angles from -30 [◦] to 60 [◦] explores scenarios with lower SVO values within the group composition. Full details of these experiments, along with those categorised as ’Other’, are provided in Appendix F. The first observation is that groups composed of lower SVO angles consistently perform worse across all of the categories than those with higher SVO angles. This aligns with earlier experiments, where lower SVO groups invested less in system health. However, their average player points are also often lower, likely due to frequent port collapses, which reduces all players points to 0. Next, consider the best runs (those in the top right corner of the plot) in terms of inequality and health spend. These are exclusively from the SVO -15 [◦] to 60 [◦] experiment set, with the majority of runs all occurring when the other players were aware a leader was present. Interestingly, there is a noticeable difference between the best runs in terms of Gini and health spend being in the ’Unaware’ leader variant and those in terms of average points and health spend being in the ’Announced’ leader variant. One explanation for this is that, in the ’Unaware’ variant, there is the general impact of the presence of a leader without the potential cheap talk aspects of a player being aware that they are, in fact, the leader. 5. Conclusion & Future Work
This work is an initial attempt to understand the behaviour of LLM agents in CRSDs. Specifically, we began by exploring two of the conditions of algorithmic fidelity within a novel CRSD, Port of Mars. We hypothesise that PoM is an ideal candidate for LLM experimentation on CRSDs, in particular due to lack of strategy contamination in the LLM training data, unlike other CRSDs. We demonstrate initial signs of algorithmic fidelity, in terms of two of the four conditions over a range of personality variables. We leverage this validation to further investigate a selection of variables that have been shown to impact social behaviour in social dilemmas, demonstrating that LLMs can simulate the results of human behaviour experiments. Future work can take two avenues for advancing our understanding of human behaviour in CRSDs - first by further validating the algorithmic fidelity of an LLM framework through more comparisons to human results, and second by exploring the impacts of other personal and social variables at a scale that is difficult to match in human experiments. | fe27d16e-0d3b-4d9d-ae39-0c07432b4202 | 19 |
0c7e1a7e-6fd4-46c4-9fa5-47e466f354d1 | https://www.gov.uk//guidance/oil-and-gas-decommissioning-of-offshore-installations-and-pipelines | 2,013 | [
"Decommissioning",
"Pipelines",
"IPR1 Form",
"IPR2 Form",
"OPRED",
"NSTA",
"Interim Pipeline Regime",
"Formal Decommissioning Programme",
"OSPAR",
"Petroleum Act 1998",
"Derogation",
"Non-Derogation",
"Cost Recovery",
"Templates"
] | gov.uk | Change of parties to the approved Programme August 2016 -
LinnhePDF,2.25 MB,66 pagesJuly 2008 Mobil North Sea LLC - - Linnhe Close Out ReportPDF,1000 KB,22 pagesNovember 2013
Indefatigable ShellPDF,11.6 MB,224 pagesMay 2007 Shell UK Limited - - Close Out ReportPDF,2.47 MB,64 pagesDecember 2014
NW Hutton decommissioning programmePDF,14.9 MB,320 pagesFebruary 2006 Amoco U.K. Exploration Company - now a subsidiary of BP plc - - Close Out ReportPDF,2.52 MB,32 pagesOctober 2014
Ardmore 2005 British American Offshore Limited - - -
Ardmore 2005 Ugland Nordic Shipping AS - - -
Ardmore 2005 Acorn Oil Gas Limited - - -
Brent Flare DPPDF,2.93 MB,122 pages2004 Shell - - Brent Flare Close out ReportPDF,2.7 MB,31 pagesMay 2025
Beatrice 2004 Talisman Energy UK Limited - - -
Forbes and Gordon 2003 BHP Billiton - - May 2005
Frigg DPPDF,10 MB,450 pagesMay 2003 Total EP Norge AS - - Frigg close out reportPDF,3.46 MB,62 pagesMay 2011
Durwood and Dauntless 2002 Amerada Hess - - -
Hutton 2002 Kerr McGee - - July 2004
Camelot CB 2001 ExxonMobil - - -
Blenheim and Bladon 2000 Talisman - - -
Durwood and Dauntless 2000 Amerada Hess - - -
Maureen and Moira 2000 Phillips - - -
Brent Spar 1998 Shell - - -
Donan 1998 BP - - -
Fulmar SALM 1998 Shell - - -
Emerald 1996 MSR - - -
Frigg FP 1996 Elf Norge TotalFinaElf Norge - -
Leman BK 1996 Shell - - -
Staffa 1996 Lasmo - - -
Viking AC, AD, AP FD 1996 Conoco - - -
Esmond CP CW 1995 BHP - - -
Gordon BW 1995 BHP - - -
Angus 1993 Amerada Hess - - -
Forbes AW 1993 Hamilton BHP - -
Argyll, Duncan and Innes 1992 Hamilton BHP - -
Blair 1992 Sun Oil AGIP - -
Crawford 1991 Hamilton Oil BHP - -
Piper Alpha 1988 Occidental Talisman - -
Notification of disused pipelines
During the course of a fields life, pipelinessections of pipelines may be taken out of use, e.g. due to corrosion, problems with reservoir pressure, damage to the pipeline, etc. When this happens, under the Petroleum Act 1998 the Secretary of State has the option of immediately calling for a full decommissioning programme. This is not always considered an appropriate option however, and so it has been agreed consideration will be given to handling suitable pipelines, under an informal decommissioning regime, thereby deferring a formal programme until the end of the fields life. If a formal decommissioning programme is not immediately deemed suitable, details of the out of use pipelines will be circulated to other government departments for comment. Following this, OPRED will decide one of the following
The Interim Pipeline Regime is intended to ensure out of use lines do not pose a risk to other users of the sea or the environment and that they are covered by an appropriate surveying and maintenance regime from the point when they are taken out of use until approval of the formal decommissioning programme, which is usually at the end of field life. It should be noted that any interim solution should not prejudice the final decommissioning options for that line, including complete removal. The department expects operators to submit details of out of use pipelinessections of a pipeline as soon as they are taken out of use. Operators are reminded that any works that are proposed on any pipelines under the Pipeline Works Authorisation regime, as per their Terms and Conditions of the PWA, must have a legal consent in place before works can commence which includes but is not exclusive to any proposed decommissioning works. Consents are issued by the North Sea Transition Authority NSTA and operators are requested to email consentsnstauthority.co.uk on any queries that they may have relating to legal consents. Further guidance can also be found on the NSTA website. Once the necessary legal consent has been issued by NSTA, Consents Authorisations Section, Operators are to email a completed
IPR1 Form MS Word Document, 63.7 KB to oduenergysecurity.gov.uk. If you are an operator, aware of any out of use pipelines that have not been referred to the department, please submit a completed IPR1 Form at your earliest convenience. Following confirmation a pipeline has been accepted under the Interim Pipeline Regime, the Offshore Decommissioning Unit will continue to monitor the condition of the pipeline by asking the Operator to confirm the status of the pipeline remains unchanged following future surveys at an agreed frequency. If you are an operator who wishes to request a change to the agreed frequency of surveys following acceptance of a pipeline into the IPR, please submit a completed
IPR2 Form MS Word Document, 53.4 KB to oduenergysecurity.gov.uk. | a27b5207-5a50-44aa-9cf6-fc657ac46f77 | 12 |
0c7fba00-18ce-4ba5-9d61-bc4d9ac0d985 | https://civitas.eu/sites/default/files/civitas_guide_for_the_urban_transport_professional.pdf | 2,001 | [
"Transport",
"Energy service demand reduction and resource efficiency",
"Energy efficiency",
"Renewables",
"Other low-carbon technologies and fuel switch"
] | civitas.eu | modes of individual transport car, motorcycle, cycle,
walking.36 Most of them relate to park ride facilities. Encouraging people to use public transport more
In the CIVITAS City of Cork this resulted, for example,
involves improving the quality of services through in-
in the first permanent park ride facility in Ireland. Be-
creased reinforcement of rules and safety and secu-
sides the introduction of physical infrastructure e.g. rity for passengers. This subject has a scope ranging
cycle infrastructure at the main stations in Venice,
from prevention of terrorism to reduction of simple acts
intermodality also involved the integration of time
of vandalism. Issues of safety and security can arise
schedules, information and ticketing. 35 EC, Equal Treatment Directive, 200078EC of 27 November 2000, Brussels. 36 EC, Green Paper Towards a new culture for urban mobility, COM 2007 551 final of 25 September 2007, Brussels. 62
CIVITAS GuI de for T he u rbA n TrAnS po rT p ro feSSIonAl
3.5 C OLL ECTIVE PASSENg ER TRANSPO RT
CIVITAS cities where collective passenger transport solutions have been implemented
In the following CIVITAS cities collective passenger transport solutions have been implemented. | a20264eb-0ca9-4fb5-983a-e64bfbff96ce | 62 |
0c7feff9-8819-4240-810b-b71fc8369eb4 | http://arxiv.org/pdf/2003.01615v2 | 2,020 | [
"climate",
"policy",
"economic",
"change",
"uncertainty"
] | arxiv.org | However,
ture.Hafstead and Williams (2020) examine the role for tax adjustment mechanisms, which automatically adjust the carbon tax rate based on the level of actual emissions relative to a legislated target, and the trade-offs of alternative designs. They show that tax adjustment mechanisms in carbon tax design can substantially reduce emissions uncertainty. ture.Hafstead and Williams (2020)
ture. find that low-carbon investments should overtake fossil investments globally by around 2025 to meet the "well below 2 °C" target of the Paris Agreement. Dietz and Fankhauser (2010) suggest that when facing an emission quantity target (e.g., determined through the Paris Agreement for keeping a globally average atmospheric temperature increase this century well below 2°C over the preindustrial level), the marginal abatement cost (i.e. the shadow price of the target constraint), rather than the SCC, will often provide more consistent and robust prices for achieving the target. Kolstad (1996) suggests that with the tension between postponing control until more is known vs acting now before irreversible climate change takes place, a temporary carbon tax may dominate a permanent one because a temporary tax may induce increased flexibility to future uncertainty. In fact, usually a time varying path would not be called a parameter. See e.g.Gillingham et al. (2018);Cai, Judd, and Lontzek (2018);Cai and Lontzek (2019) for investigations on the impact of these uncertain parameters. 7 It has other names like the pure rate of time
preference. 8 Other names include the social rate of time preference and the social discount rate. See e.g.,New and Hulme (2000),Nordhaus (2008),Ackerman, Stanton, and Bueno (2010), andAnthoff and Tol (2013). In dynamic programming models, the frequency of policy updates in the real world should also be taken into account the choice of the time step size. For example, climate policies might not update annually, while consumption decisions could be more frequent, so an IAM with annual time steps may be more suitable than those with decadal time steps or continuous time. SeeCai, Judd, and Lontzek (2012) for an example that a solution with decadal time steps is significantly different with one with annual time steps. Asset pricing theory has also been applied to estimate the SCC in the face of risks. For example,Bansal, Ochoa, and Kiku (2018) andDaniel, Litterman, and Wagner (2018) explore the implications of risk preferences for the SCC and optimal abatement policies.Bansal, Kiku, and Ochoa (2019) show that the long-run temperature elasticity of equity valuations is significantly negative and that long-run temperature
Nordhaus (1994) andNordhaus and Boyer (2000) suggest that a collapse of the thermohaline circulation might result in a 25-30% reduction in GDP. See Judd (1998) andCai (2019) for details about computational methods and error checking. There are also many reduced form IAMs (e.g.Golosov et al. 2014, Jaakkola and van der Ploeg 2019, Brock and Xepapadeas 2019), but they are mainly used for theoretical or qualitative analysis. This review focuses on quantitative analysis for climate policies. See Brock and Hansen (2018) for a review on research challenges in climate economics that focuses on three types of uncertainty: risk, ambiguity, and misspecification. | 2b5ee10e-7541-4d4d-946c-3f298c92baa3 | 9 |
0c8081e1-2515-4bbe-ac5b-cf2a52b6f274 | http://arxiv.org/pdf/2006.05845v1 | 2,020 | [
"risk",
"insurance",
"disaster",
"natural",
"management"
] | arxiv.org | 4 In order to protect the national financial stability, the Sendai Frame-3 Main market failures in disaster risk management relate to the insurability of risks, information asymmetry, adverse selection, consumer behavior, moral hazard and charity hazard. As far as insurability concerns, spatial correlation among insured assets constitutes a central issue for disaster management because generates the potential for enormous losses to the insurers (Glauber, 2004). For example, a series of hurricanes in the US during the 1990s led to a consistent number of insolvencies (Matthews et al., 1999;Mills et al., 2001). As a consequence, insurance included higher risk-load in premium rating for high-risk areas (Feldblum, 1990;Kreps, 1990;Meyers, 1996;Mango, 1997Mango, , 1998;;Kreps, 1998), that often do not meet the demand from rational purchaser (Kousky and Cooke, 2012). Along with behavioural bias (Kunreuther, 1996), climate change further complicates the development of financial and insurance market. The Geneva Association (2013) warns that return periods and correlation among claims for several high-loss extreme events are "ambiguous rather than simply uncertain", and raises concerns about the future sustainability of insurance business on natural risks. Failures in capital markets have been explored by Froot (2001), that found that securitization is not always the lowest-cost way to transfer risk due to supply restrictions associated with capital market imperfections and market power exerted by traditional reinsurers. 4 Losses that the government may incur can be both explicit or implicit: the expenses that could derive from the reconstruction of public goods and infrastructures or other financial commitments following a disaster are explicit; on the contrary, expenses that do not reflect any type of commitment or liability, but which can still occur due to a perceived obligation work claims that the government, while guaranteeing social assistance, should share responsibilities with private stakeholders and therefore private initiatives in prevention and financial protection should be encouraged. As emphasized by the OECD (2015), improving public awareness reduces the human-induced factors that make a major contribution to the cost of disasters and alleviates losses on public finances. However, educating and informing the society is usually not enough. Hence, if some degree of government involvement is necessary to protect the most vulnerable layers of the society and the market, how can authorities balance public and private initiatives? According to Jaffee and Russell (2013), public initiatives should only complement private activities and the role that the government should assume depends on the relationship between objective and subjective probabilities of loss. In case of perfectly rational individuals with objective perception of risk, an active role of government is necessary during emergency response only; if individuals underestimate their risk, investments in public awareness are needed or, alternatively, mandatory insurance purchase might be introduced. Whether other differences between objective and subjective probabilities are not generated from behavioural biases, the government should identify and implement the solution that addresses the specific market failure in the most efficient way. Unfortunately, identifying market failures is complicated. To make matters worse, "with increasing complexity and interaction of human, economic and political systems within ecological systems, risk becomes increasingly systemic" (UNDRR, 2019), and responsibilities increasingly blurred. In increasingly uncertain and complex contexts, cooperation between all the subjects involvedindividuals, businesses, authorities -is essential to build the community's resilience. Although most countries are still not adequately prepared to deal with the consequences of possible future disasters 5 , some have already implemented sophisticated risk management plans which envisage a public-private partnership with the insurance sector. Almost all of these few virtuous countries have intervened in the insurance sector, becoming insurers, reinsurers or, in the poorest economies, by activating micro-insurances. These partnerships are then supported and strengthened by governments through a series of legislative provisions and investments, which make each strategy unique. Although it is not possible to replicate any of these strategies in other countries, some useful lesson can still be drawn from them. In the next section the main public-private partnerships currently in force are analyzed. The benefits of these partnerships are widely recognized, but some important weaknesses have also emerged, which we discuss in section 3. Among these, risk understanding and government's attitude toward natural risks are today the two major limits in disaster risk management. Many of these weaknesses can be overcome by adopting an even are implicit. 5 According to the report by Wilkinson et al. (2017), a number of disaster risk management activities were conducted during the past decades (most of which were relatively low cost), but, however, they were not as effective as they could and disaster losses increased during the Hyogo Framework of Action. more inclusive approach, which involves a greater number of subjects and therefore allows to monitor the risk on the whole society. For these reasons, UNDRR (2019) argues that countries should move towards a community-based approach to risk management, and section 4 deals with this. To conclude, section 5 discuss the next challenges in disaster risk management. There is a widespread agreement on the benefits of public-private partnerships for the management of natural disasters (Kunreuther, 2006b;World Bank, 2012b;Shukla et al., 2019) and in particular, public intervention in the insurance sector is increasingly proving to be effective, especially in the poorest countries. Government-supported initiatives are in fact able to distribute risks and losses over the entire population and over time (Kunreuther and Pauly, 2006), and are much more flexible than private solutions as they are not tied to profit objectives (Penning-Rowsell, 2015). When insurance schemes are properly designed and supported, they communicate risk to the population, foster adaptive responses and risk reduction and above all improve economic stability and protect the well-being of the community (Kunreuther and Pauly, 2006;Lotze-Campen and Popp, 2012;Hudson et al., 2016;Kunreuther and Lyster, 2016;Kousky et al., 2018;Linnerooth-Bayer et al., 2019). As argued by Bruggeman et al. (2010), however, public intervention are beneficial only if they solve a specific market failure that the private sector is not able to cope with on its own. Otherwise, the State's entry into the insurance (or reinsurance) market might play a distorting effect. | 2ad4d6c1-208e-43c6-a808-86d49e99d8bd | 1 |
0c80e6e1-0376-4658-b86d-2f4578c56e10 | http://arxiv.org/abs/2209.02292v1 | 2,022 | [
"average ln t.",
"different time scales",
"complex climate system",
"dr. xiaojie chen",
"stronger baroclinic disturbances"
] | ArXiv | The plot shows that extreme day-to-day temperature differences are more common before the summertime, followed by high-temperature days from June to August (the summertime of the Northern Hemisphere and the sites in the South Hemisphere fol-lows similar seasonal trends, see Fig. S1 in SI). This is related to the well-known stronger weather variability in winter versus summer, associated with the presence of stronger baroclinic conversion processes [44]. To investigate the approach to the limiting behaviour in the statistics of temperature differences defined by extreme value theory, we apply the Peaks Over Threshold methods [43] to the normalised temperature positive and negative differences for all sites separately. We show the dependence of the estimates of the shape parameter and of the modified scale parameter on the threshold value for sites on land and ocean in Fig. S2 in SI. The distribution of the estimates of shape parameters is broader over the oceans, which means the asymptotic behaviours are less accurately established for ocean sites. However, most of the shape parameters of oceans and lands fall within a reasonably small range of [0.1, 0], and the asymptotic regime is established for quantiles as low as (60%, 67.5%) because the estimates of the scale parameters and of the modified scale parameter become stable as we consider higher quantiles [43,47]. This regime is considerably lower than what is usually found when looking at temperature extremes, see, e.g. [48], which is encouraging in terms of applicability of extreme value theory for day-to-day temperature variability also in conditions where data availability is limited. We consider all sites on the entire Earth together. With this consideration, we have lost the structure in space and in the magnitude scale; nonetheless, the change in the process properties with q within the extreme regime will allow us to recover some information. A positive extreme event set E + i (q) is defined when the value CV exceeds a chosen threshold associated with a quantile q. Then, we define the magnitude of the positive extreme temperature difference as the normalised value of the event, that is m + ev = CV ev + CV ev + , ev E + i , where CV ev + is the standard deviation of the extreme part, CV ev + for site i. Similarly, a negative extreme event set E i (q) is defined when the value CV is smaller than a chosen quantile q. Then, for simplicity, we define the magnitude of the negative extreme temperature difference as the minus normalised value of the event, that is After taking the minus of the values, the m ev will be positive, which is comparable to the m + ev . Likewise, we define for the absolute values, m abs ev = |CV| ev abs CV abs ev , ev E abs i . The waiting time i T i of the extreme events in E i is the number of days between two consecutive events [49]. Therefore, we can define four types of waiting times: + ( , abs ) is the waiting time between positive (negative, absolute) extreme temperature difference, i.e. the waiting time in E + (E , E abs ). The fourth type + ( + interchangeable) is the number of days between extreme positive and extreme negative change events (or extreme negative and extreme positive), Here, we focus on the distributions of the dimensionless magnitudes m + ev and m ev for all sites on the Earth, that is, the positive and negative extreme parts of CV. We choose q = 90%, 92.5%, 95% and 97% as threshold quantiles within the extreme regime. The normalised PDF for m + ev and m ev , p(m + ev ; q) and p(m ev ; q) are shown in Figs. 2a and c, respectively. The PDF satisfies a single peak distribution and depends on our chosen threshold quantiles q. The distributions of m + ev and m ev are expected to take the following scaling forms, and where f + and f are two universal scaling functions, m + ev ( m ev ) and (q) is the mean value and standard deviation associated with quantile q. We then define two rescaled parameters and . Combining the proposed scaling forms, Eqs. ( 1) and (2), with computing values (q) of different q, yields collapse onto the respective universal scaling functions, as shown in Figs. 2b and d. In particular, we find that both f + and f are well described by the Gumbel extreme function, and where ) is the location parameter (the mode) and + ( ) is the scale parameter. The physical mechanism underlying our above conjecture is based on the Generalised Extreme Value (GEV) theory, see Eq. ( 9). When we fit our rescaled collapsed data with the GEV distributions (see Methods for the fitting process), we find that the shape parameter is very close to zero (see Tab. I). The GEV functions with a small (Eq. ( 9)) and Gumbel function (Eqs. ( 3) and ( 4)) are complemented in Figs. 2b, d and f. They are hardly distinguishable, which indicates that the f + (f ) can be well approximated by a Gumbel distribution. We analyse the cumulative distribution function (CDF), and the data are also collapsed together. The results are consistent with the PDF's, see Fig. S4 in SI. The waiting time for extreme events is also crucial for understanding the risk management of systems. As we mentioned before, for a given site and quantile q, we introduced four types of waiting time + , , + ( + ) and abs . We first consider their PDFs: D( + ; q), D( ; q), D( + ; q) and D( abs ; q). Since the multiple time scales are involved from days to many years, we work with the logarithm of . | 68528c78-10ea-4ae5-b39a-78198a775182 | 1 |
0c8887ce-ff54-4603-94c9-51b38c1e1b7f | http://arxiv.org/pdf/2309.16186v2 | 2,023 | [
"cost",
"abatement",
"model",
"time",
"damage"
] | arxiv.org | Thus, with A(t ) being the productivity and γ the elasticity of substitution between capital and labor,
Here, productivity A(t ) is modelled as
, where initial productivity growth rate ga = 0.076 and productivity growth decreases by deltaA = 0.005. Population L(t ) is assumed to follow a deterministic path described by
, using L(∞) = 11500 and g = 0.134/5, such that the unit of population is [mil persons]. We propose modifications to integrated assessment models to investigate the effect of stochastic interest rates, funding, and non-linear financing cost 35 . These may be also incorporated into more complex IAMs. We use the simple DICE model to illustrate potential effects. Our choice to make interest rates stochastic is only exemplary. The interest rate is an important factor in linking present abatement cost to the avoided future damage cost. While one may introduce stochasticity in many other state variables, the use of an abatement policy adapted to the economic factors (interest rates) will already lead to all other state variables becoming stochastic. The classical way in which interest rates are modelled in an IAM is via a discount factor. A time-t value V (t) is derived in the model, then discounted and aggregated to a final value forming the objective function
We model stochastic interest rates r . Our implementation allows to use a general discrete forward rate model (LIBOR Market Model). The experiments in Section 5 were conducted with a classical Hull-White model. The model provides the stochastic numeráire N (and thus discount factor) as well as the stochastic forward rate FR. If interest rates are stochastic but the function V (t) remains deterministic, adding stochastic interest rates does not change the interaction with the IAM since
. Thus, in a classical IAM the discount factor can be interpreted as an expectation. Due to the lack of a feedback that allows to adjust the abatement path and resulting damages, adding stochastic interest rates does not introduce changes in the model dynamics. As interest rate levels and term-structure have a strong impact on the optimal abatement policy, it is natural to introduce a stochastic abatement policy, i.e., µ will become stochastic. This reflects the possibility that the abatement policy can be adjusted to the interest rate scenarios. Thus abatement policy t → µ(t ) becomes a stochastic process that adapts to the changes in interest rates. A simple example for a stochastic abatement model is a parametric one, where the abatement speed is a (linear) function of the interest rate level r , e.g.,
Moving to a stochastic abatement model, all model quantities become stochastic. This then introduces stochastic cost, and hence a notion of risk. The geophysical part of the model produces damages. Future damages may be reduced by performing abatement. Both, abatement and damage are associated with costs. The abatement costs and the damage costs are compensated instantaneously. This is modelled by reducing the time t i GDP by the time t i costs. The remainder is then available for consumption or investment. Investment adds to the capital which determines the GDP of the next time t i+1 . We introduce the ability of funding of cost, especially for abatement cost. As abatement is a planned process of societal relevance, it is reasonable to assume that abatement cost are covered by a loan for which interest rate corresponds to the current discount rate. 4 We define C µ (t) as the instantaneous abatement costs in time t, which might be funded for a period ∆T A . Thus abatement costs of C µ (t) are accrued with the forward rate FR(t, t + ∆T A ; t ) observed in t, such that the realized abatement cost C A at time t + ∆T A are
For the case of no funding, i.e. In a standard model for risk-neutral valuation, this change would have no effect, as the accruing is compensated by the discounting. However, the change might introduce an effect in the DICE model, due to the way how abatement and damage cost are associated and due to the time-preference included in the utility function. Since damages occur instantaneously, we do not consider funding of these and thus total cost is given by C(t ) := C A (t) + C D (t). For an unsecured financial cash-flow its present value is defined by a discount factor times the cash-flow. If the future cash-flow is subject to default, the discount factor is lower, reflecting the additional value reduction due to the risk of (partial) default. As default is not an option for future damage cost, it appears as if the risk-free discount factor should apply. However, since no hedging strategy exists, a risk free funding is not possible. Thus additional cost may occur to secure the unsecured funding 35 . Since damage cost may become very large -much larger than funds provided by standard financial markets -it is reasonable to assume that these additional funding cost become (over-proportionally) large for larger cost. We model this by optionally adding non-linear financing cost using a non-linear funding model 35 . This model 35 allows, that the discount factor may depend on the magnitude of the cash-flow. Thus the funding of larger cash-flows requires a premium to compensate for a larger default risk or other frictions. For our application, this means that larger cost get a larger weight. Our model modification is now a modification of the damage cost. Let C • D (t) denote the damage cost of the classical model, i.e. We then define the effective damage costs as
where DC(C • D (t); t ) is the default compensation factor. It is somewhat similar to the inverse of a discount factor, describing the over-proportional cost to fund large projects. As C • D (t) represents a time-value, it is natural that the default compensation factor depends on a renormalised value only. | 83e1583e-1852-4565-9eb1-c6bb6660a24a | 2 |
0c8c67c6-9d78-47f2-bfb9-e6db095a27c4 | http://arxiv.org/pdf/2503.12331v2 | 2,025 | [
"Canada",
"boreal forest",
"afforestation",
"climate change mitigation",
"carbon removal",
"carbon sequestration",
"Monte Carlo",
"carbon budget model",
"satellite inventory",
"fire regime",
"ecosystem carbon",
"greenhouse gas emissions",
"net-zero",
"Taiga Shield",
"permafrost",
"surface albedo",
"forest migration",
"planting mortality",
"land classes",
"climate variables",
"ecosystem modeling",
"2025-2100",
"spatial modeling",
"ecological forecasting."
] | arxiv.org | A similar relationship can be drawn for site quality. 9) Fire events are assigned by sampling fire return intervals (FRIs) from a weibull distribution. The weibull distribution parameter scale is sampled according to eco-zone specific mapping based on the eco-zone of the cell. The weibull shape parameter is randomly sampled from a range. The scale parameter represents a measure of the characteristic time scale of afire regime, whereas the shape parameter connects the “hazard of burning” with stand age, with shape - 1 denoting an increase in hazard of burning with stand age. No fire events are assigned for the first 3 years after afforestation, after which fires are assigned every year according to a binomial probability of afire event happening in the current year given the previous fire event and difference between the years. The base probability of fire happening on any given year is set to 1/FRI. Equation 1: Weibull distribution with shape parameter k and scale parameter λ. 10) The fire fraction is set to the historical fire fraction of the cell. The fire regions are assigned for successive years by starting from the bottom of the inventory region and assigning non-overlapping regions with lat range = fire fraction*lat range of inventory region. | e05d25b6-82b4-4c40-bf8b-a5bd61ef0f97 | 18 |
0c8e08c5-0ff7-4759-94b3-42743328740d | https://assets.publishing.service.gov.uk/media/6424b2d760a35e000c0cb135/carbon-budget-delivery-plan.pdf | 2,023 | [
"carbon",
"delivery",
"additional",
"plan"
] | www.gov.uk | We envisage the certification scheme will use the methodology set out in the Low Carbon Hydrogen Standard, which sets a maximum threshold for the amount of greenhouse gas emissions allowed in the production process for hydrogen to be considered ‘low carbon hydrogen’. Creating a trusted, transparent certification scheme will help producers and consumers to demonstrate the environmental credentials of the hydrogen they create and use. It will also help to deliver carbon savings in end use sectors by boosting the growth of the low carbon hydrogen market and helping consumers choose low carbon hydrogen. Hydrogen production and certification alone will not generate carbon savings, but we expect it to enable carbon savings in several sectors including industry, power, transport and potentially buildings, by replacing high-carbon fuels used
No. Sector Policy name and description How the policy supports delivery/ 39 Fuel Supply Net Zero Hydrogen The £240m Net Zero Hydrogen Fund (NZHF) aims to support the commercial deployment of new low carbon hydrogen production projects during the 2020s. The NZHF will provide capital grant co-funding to give projects a financial boost for construction to begin. It will also provide development support to stimulate a diverse pipeline of This funding will kickstart the production of low carbon hydrogen during the 2020s, which is crucial in displacing fossil fuels and meeting our ambitions for hydrogen It will also help to deliver carbon savings in end use sectors by boosting the growth of the low carbon hydrogen market. Hydrogen production alone will not generate carbon savings, but we expect it to enable carbon savings in several sectors including industry, power, transport and potentially buildings, by replacing high-carbon fuels used today. 40 Fuel Supply Hydrogen Production Business A government subsidy which provides revenue support to hydrogen producers to overcome the operating cost gap between low carbon hydrogen and high The intervention will support the deployment of low carbon hydrogen projects that will support government's ambition of reaching up to 10GW of hydrogen production capacity by 2030, with at least half of this from electrolytic hydrogen. It will also help to deliver carbon savings in end use sectors by boosting the growth of the low carbon hydrogen market. Hydrogen production alone will not generate carbon savings, but we expect it to enable carbon savings in several sectors including industry, power, transport and potentially buildings, by replacing high-carbon fuels used today. No. Sector Policy name and description How the policy supports delivery/ 41 Fuel Supply Industrial Decarbonisation and Hydrogen Revenue Support (IDHRS) scheme and Hydrogen Production Business Model (HPBM) will initially be taxpayer funded via the Industrial Decarbonisation and Revenue Support (IDHRS) scheme. Through the Energy Bill, we have introduced hydrogen spending powers and provisions for a hydrogen levy which is intended to fund revenue support payments made through the HPBM. Government will provide funding for successful projects from the first electrolytic hydrogen allocation round until the hydrogen levy is in place. It is intended to give long term certainty to investors and projects and enable the first commercial scale deployment of low carbon hydrogen production. It will also help to deliver carbon savings in end use sectors by boosting the growth of the low carbon hydrogen market. Hydrogen production alone will not generate carbon savings, but we expect it to enable carbon savings in several sectors including industry, power, transport and potentially buildings, by replacing high-carbon fuels used today. 42 Fuel Supply Hydrogen Transport and Storage Business This is a proposal to design new business models for hydrogen transport and storage infrastructure by 2025. A consultation government response is expected in Q2 2023. Legislative measures will be crucial to delivering these new business models. The business models will support hydrogen transport and storage infrastructure which is needed to enable our 10GW production capacity ambition and lead to potential carbon It will also help to deliver carbon savings in end use sectors by boosting the growth of the low carbon hydrogen market. Hydrogen production alone will not generate carbon savings, but we expect it to enable carbon savings in several sectors including industry, power, transport and potentially buildings, by replacing high-carbon fuels used today. No. Sector Policy name and description How the policy supports delivery/ 43 Fuel Supply Reducing Methane Leakage through the Distribution Network (Ofgem) The Gas Distribution Networks have been given a financial incentive in the RIIO-2 price control to reduce leakage levels by means of lowering system pressures and improved gas conditioning levels. Reducing methane leakage means lower The Gas Distribution Networks have been given a financial incentive in the RIIO-2 price control to reduce leakage levels by means of lowering system pressures and improved gas conditioning levels. Reducing methane leakage means lower 44 Industry Climate Change Agreements (existing Agreements scheme exists to ensure that the businesses, for whom energy makes up a larger proportion of their operating costs, are supported to make changes to their processes to increase their energy efficiency. Support through Climate Change Agreements is available to 2,600 eligible businesses in over 50 industrial sectors who meet negotiated energy efficiency or carbon reduction targets. The current scheme began in 2013 and will run until the 31 March 2025. CB 4 Climate Change agreements support energy efficiency improvements and associated carbon savings for eligible
No. Sector Policy name and description How the policy supports delivery/ 45 Industry Climate Change Agreements (from 2025): The government is extending the Climate Change Agreements (CCA) scheme by two years to cover 2025-26 and 2026-27 as announced in the March 2023 Budget. This will allow continued support to energy-intensive businesses across the UK in return for them meeting energy efficiency targets. The terms of the extended scheme are set out in a consultation document published by the Department for Energy Security and Net Zero, published alongside the Budget. | 15a3290f-77f0-4f00-b9be-47c5b73d4f14 | 31 |
0c90eb1c-5d34-4580-a471-99e7b7ff5c99 | https://www.gov.scot/binaries/content/documents/govscot/publications/strategy-plan/2017/12/scottish-energy-strategy-future-energy-scotland-9781788515276/documents/00529523-pdf/00529523-pdf/govscot%3Adocument/00529523.pdf | 2,017 | [
"energy",
"scotland",
"scottish",
"government",
"carbon"
] | www.gov.scot | It will also mean our energy companies retaining the capabilities that will help them take advantage of future supply chain opportunities at home and allow further internationalisation As the North Sea is a relatively mature basin, decommissioning on a significant scale will commence earlier than other basins – meaning that Scottish supply chain companies have the opportunity to build on their success and develop expertise which can then be exported. The latest forecasts suggest that decommissioning in the UK Continental Shelf could be worth around £60 billion over the coming decades, with a forecast spend of nearly £17 billion in the next 8 years alone Nuclear decommissioning also represents huge opportunity for Scotland. There are more than 400 civil nuclear reactors across the world due to 37 UKCS Decommissioning – 2017 Cost Estimate decommissioning-cost-report-2.pdf
Scottish Energy Strategy 78/79 Our businesses have developed real strengths across the whole supply chain – in project development, civil engineering, and operation and maintenance. Campbeltown is also currently home to the UK’s only wind turbine Scotland’s capabilities in architecture and design provide a natural advantage in the low carbon buildings sector. Scotland’s Energy Efficiency Programme offers a huge opportunity for construction and energy systems technologies companies, with low carbon building technology sales in Scotland forecast to be worth £1.9 billion 41 Construction – Low Carbon Opportunities in insight/construction-low-carbon-opportunities-in-scotland Scotland’s outstanding natural resources, and our decades of offshore engineering experience, make us a hugely attractive prospect for marine renewables. The Scottish Government has done more than any other nation to support the development of these technologies. Orkney hosts not only the world’s first grid- connected wave and tidal test centre (the European Marine Energy Centre) but also the world’s largest tidal turbine (ScotRenewables), whilst the Pentland Firth is home to the world’s largest planned tidal stream array (MeyGen). Onshore wind is another key component of the big industrial opportunity that renewables create for Scotland. The sector supports an estimated 7,500 jobs in Scotland, generating more than £3 billion in turnover in 2015 40 ONS Low carbon and renewable energy economy survey 2015: energyeconomysurvey2015? :uri=releases/lowcarbonand renewableenergyeconomysurvey2015 Workers in front of an AR1500 turbine, used in the world’s flagship tidal stream project, MeyGen, in Scotland’s Pentland Firth (Credit: Highlands and Islands Enterprise)
The areas explored above constitute a huge prize for Scotland. But there are other opportunities which we are well placed to exploit. Our economic development agencies have several programmes and partnerships in place to support energy innovation. These have led to major investments, designed to support key infrastructure projects and companies, and to help Scotland exploit these emerging opportunities. Energy System Technologies supporting Innovative Local Energy Systems Energy System Technologies (ESTs) span the management, transfer, storage and transformation of energy. Global spend on ESTs could amount to around £70 billion between 2018 and 2020, with about half occurring in Europe, presenting opportunities for Scottish companies to gain a foothold in this market. Scotland has strengths in knowledge provision, digital platforms, sensors, controls and security, engineering services and power electronics. We also host facilities such as the Power Networks Demonstration Centre (PNDC) – a world-class establishment, designed to accelerate the adoption of new, smart technologies within The shift to smart, flexible networks, already underway, will also demand and depend upon the continuing development of systems and technologies which can store power and help to manage increasingly decentralised Scotland is already developing local energy solutions, in line with the Scottish Government’s place-based approach to inclusive growth. These are mainly in Island communities and other rural areas, with innovative methods of energy storage helping to manage grid constraints. Surf ‘n’ Turf hydrogen electrolyser, Orkney (Credit: Colin Keldie) Aberdeen hydrogen bus project (Credit: Transport Scotland) The DART® simulation suite at Robert Gordon University
Scottish Energy Strategy 80/81 There are also opportunities to develop niche transport applications in Scotland’s rural and island communities – given Scotland’s existing bus and ferry manufacturing capability, hydrogen’s compatibility as a fuel for these heavy duty cycle vehicles, and because the refuelling infrastructure is greatly simplified as the vehicles operate constrained routes. Digital technologies and skills will continue to transform and disrupt markets, with new, data- driven business models and platforms based on a better-improved understanding of customer and market behaviour. The growth of innovative local energy systems presents an opportunity for Scottish businesses to develop new ways to trade energy. Scotland has rich potential in these areas, with a growing digital economy and particular capabilities in areas such as data science and informatics. We have around 150 businesses delivering value from data and employing over We believe that Scottish technology developers and businesses are well equipped to deliver the software, systems and innovations that smarter homes, appliances, vehicles and networks will demand. All these innovations have significant Our Low Carbon Infrastructure Transition Programme can help demonstrate and improve innovative local energy systems, creating an opportunity for Scotland to lead in developing, deploying and exporting these solutions. Scotland’s development agencies will continue to support companies working and innovating in Carbon Capture and Storage and Carbon Carbon capture and storage (CCS) in depleted North Sea oil and gas reservoirs could be hugely important to our energy future, with opportunities to repurpose infrastructure and draw on Scotland’s extensive expertise in the Carbon capture and utilisation (CCU) refers to processes or power generation to create premium chemical products. This has been identified as an increasingly important market for Scotland’s chemical industry. When coupled with green hydrogen, this could include the manufacture of renewable transport fuels. Both opportunities would use existing Scottish supply chain strengths in chemicals and oil The turnover for Scottish companies involved in the transport sector is around £2 billion per 42 . Our target to phase out the need for new petrol and diesel vehicles by 2032 creates a raft of new opportunities for these companies. | 679d47a0-85c7-43df-8c6e-b43d114f552a | 23 |
0c91340c-97e1-4bbe-964a-8c47223dc21f | 2,025 | [
"afforestation",
"semi - arid regions",
"sink areas",
"sub - legislation",
"resistant tree species"
] | HF-national-climate-targets-dataset | 3 > Soil Conservation and Land Law will be implemented effectively and sub-legislation envisaged for this will be prepared; Legal regulations enacted for the protection and development of meadows and pastures will be implemented and monitored effectively. > 2.3 million hectares of land will be afforested and rehabilitated between 2008-2012 within the scope of the National Afforestation Campaign. In this way, in addition to the carbon captured by our existing sink areas, a total of 181.4 million tons of carbon will be captured by our forest areas in 12 years until 2020. Especially in arid and semi-arid regions, drought-resistant tree species will be determined and afforestation will be carried out in these species; Planting will be done in areas where afforestation is difficult and costly. | e9502be1-ccf5-4be9-840b-add78b65b9ca | 0 | |
0c926998-9fdb-4ca5-8f9b-db35a50ca52c | http://arxiv.org/pdf/2507.21147v1 | 2,025 | [
"Wildfires",
"Ecosystems",
"Biodiversity",
"Climate Change",
"Risk Management",
"Technology",
"Deep Learning",
"Spatio-temporal data",
"Weather data",
"Prediction",
"Contrastive learning",
"Latent representations",
"Morphology",
"Curriculum learning",
"Patch sizes",
"Experimental analysis",
"Mediterranean",
"Hydrological risks",
"Toxic emissions."
] | arxiv.org | However, this flexibility comes at a cost: transformers typically demand significantly higher computational resources for training compared to CNNs. The CNN model utilized, for instance, has approximately 414 k parameters, while TimeSformer has around 1 . 16 M, and the Swin Transformer is the most extensive with 1 . 8 M parameters. This trade-off between flexibility and computational efficiency is an important factor when considering transformer models for forecasting tasks, especially in resourceconstrained environments. All experiments were carried out using a single node with 96 CPUs, 512 GB RAM, and an NVIDIA V100 GPU with 16 GB VRAM. | ad90efd0-8172-4fc8-a270-0d29dbf3a921 | 14 |
0c932095-ed99-41ce-b9ea-27342c2be57e | 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 | Commodities and
EN
30
EN
products from high-risk countries or parts thereof should be subject to enhanced
scrutiny by the competent authorities. 47 For this reason, the Commission should assess the deforestation and forest degradation
risk at a level of a country or parts thereof based on a range of criteria that reflect both
quantitative, objective and internationally recognised data, and indications that the
countries are actively engaged in fighting deforestation and forest degradation. This
benchmarking information should make it easier for operators in the Union to exercise
due diligence and for competent authorities to monitor and enforce compliance, while
also providing an incentive for producer countries to increase the sustainability of their
agricultural production systems and reduce their deforestation impact. This should
help making supply chains more transparent and sustainable. This benchmarking
system should be based on a three-tier classification of countries to be regarded as
low, standard or high risk. In order to ensure appropriate transparency and clarity, the
Commission should in particular make publicly available the data being used for
benchmarking, the reasons for the proposed change of classification and the reply of
the country concerned. For relevant commodities and products from low risk countries
or parts of countries identified as low-risk, operators should be allowed to apply a
simplified due diligence, whilst competent authorities should be required to apply
enhanced scrutiny on relevant commodities and products from high risk countries or
parts of countries identified as high-risk. The Commission should be empowered to
adopt implementing measures to establish the countries or parts thereof that present a
low or high risk of producing relevant commodities and products that are not
compliant with this Regulation. 48 Competent authorities should carry out checks at regular intervals on operators and
traders to verify that they effectively fulfil the obligations laid down in this
Regulation. Moreover, competent authorities should carry out checks when in
possession of and based on relevant information, including substantiated concerns
submitted by third parties. For a comprehensive coverage of the relevant commodities
and products, the respective operators and traders and the volumes of their share of
commodities and products, a twofold approach should apply. Competent authorities
should thus be required to check on a certain percentage of operators and traders,
whilst also covering a specific percentage of relevant commodities and products. Such
percentages should be higher for relevant commodities and products from high-risk
countries or parts thereof. 49 The checks of operators and traders by competent authorities should cover the due
diligence systems and the compliance of the relevant commodities and products with
the provisions of this Regulation. The checks should be based on a risk-based plan of
checks. The plan should contain risk criteria that enable competent authorities to carry
out a risk analysis of the due diligence statements submitted by operators and traders. The risk criteria should take into account the risk of deforestation associated to
relevant commodities and products in the country of production, the history of
compliance of operators and traders with the obligations of this Regulation and any
other relevant information available to competent authorities. The risk analysis of due
diligence statements should allow competent authorities the identification of operators,
traders and relevant commodities and products to be checked, and should be carried
out using electronic data processing techniques in the information system which
collects the due diligence statements. 50
In case the risk analysis of the due diligence statements reveals a high risk of non-
compliance of specific relevant commodities and products, the competent authorities
EN
31
EN
should be able to take immediate interim measures to prevent their placing or making
available on the Union market. In case such relevant commodities and products were
entering or leaving the Union market, the competent authorities should request from
customs authorities the suspension of the release for free circulation or the export to
enable competent authorities to carry out the necessary checks. Such request should be
communicated by means of the interface system between customs and competent
authorities. Suspension of the placing or making available on the Union market, of the
release for free circulation or of export should be limited to three working days except
where the competent authorities require additional time to assess the compliance of the
relevant commodities and products with this Regulation. | fdc8afd5-2a2d-4946-a4da-be36ebf11749 | 45 |
0c990fc7-64d5-4760-8849-ad312d209f2b | 2,025 | [
"sustainable mobility",
"efficient renovation",
"green transition",
"electric charging stations",
"railway infrastructure"
] | HF-national-climate-targets-dataset | Key measures for the green transition The plan supports the green transition through investments of over €1 billion in the energy-efficient renovation of buildings, including social housing. Furthermore, €1.3 billion will be invested in sustainable mobility, notably by improving railway infrastructure, financing green public buses, deploying electric charging stations, developing urban public transport and creating or refurbishing cycling pathways. In addition, an important reform promotes electric road transport by limiting preferential tax treatment of company cars to zero-emission vehicles by 2026. The plan supports the decarbonisation of the energy sector by promoting the use of hydrogen as an energy source, with an investment of €540 million and an accompanying reform that should contribute to making it happen. On biodiversity and climate change adaptation €400 million will be invested for reconnecting ecosystems, enhancing protected natural areas, forests and wetlands and for structural measures to sustainably manage water availability thereby increasing climate change resilience. Example project: Electric charging stations | 8567e9ee-762e-49c0-b6f1-61ffd768b1c1 | 0 | |
0c99f837-ad52-4511-b882-a81ea77bf2df | https://www.gov.uk/guidance/energy-technology-list | 2,017 | [
"energy",
"technology",
"list",
"products",
"updated"
] | www.gov.uk | Energy Technology List (ETL) - GOV.UK
We use some essential cookies to make this website work. We’d like to set additional cookies to understand how you use GOV.UK, remember your settings and improve government services. We also use cookies set by other sites to help us deliver content from their services. You have accepted additional cookies. You can
at any time. You have rejected additional cookies. You can
at any time. Accept additional cookies
Reject additional cookies
Hide this message
Guidance
The ETL is a government-backed scheme featuring over 8,000 independently verified and accredited energy efficient products. From:
Published
15 May 2015
Last updated
10 July 2024
—
Print this page
The Energy Technology List (
ETL
) is a scheme featuring over 8,000 independently verified and accredited energy efficient products across 62 sub-technology groups, backed by the Department for Energy Security and Net Zero (
DESNZ
). The
ETL
helps contribute to net zero goals by increasing access to stringently tested products. It provides free, impartial support and information, enabling purchasers to easily compare product features and performance across suppliers so that UK businesses and the public sector can make greener energy choices. All products listed, ranging from boilers and electric motors to refrigeration, have met a robust set of criteria and are placed in the top 25% of the market for energy efficiency in their class. For purchasers, the
ETL
provides an easy-to-use procurement tool, while manufacturers can have their energy efficient products listed for free (subject to meeting energy performance criteria). The list is updated monthly and the Department for Energy Security and Net Zero annually reviews the technologies and products that qualify for inclusion. ICF manages delivery of the scheme, including marketing and communications. Ricardo delivers the technical assessments of product applications and operates the annual Research Programme. boiler equipment
boiler retrofit equipment
combined heat and power
compressed air equipment
energy monitoring
hand dryers
heat pumps
heat recovery ventilation units
HVAC Equipment
lighting
motor drives and fans
pipework insulation
professional foodservice equipment
radiant and warm air heaters
refrigeration equipment
solar thermal collectors
uninterruptible power supply
waste heat to electricity conversion equipment
wastewater heat recovery systems
For more details, please visit the
. To suggest a new technology category, please see the
. Purchasers can use the
ETL
to source and compare independently verified and accredited energy-saving equipment:
Manufacturers and suppliers of energy-saving technology can apply to have their products listed on the
ETL
for free:
At the request of users and purchasers from the Energy Technology List (
ETL
), we have worked with NBS to map the 140
ETL
product categories against the UNICLASS codes:
This development delivers closer integration for users of the
ETL
, enabling users to seamlessly select verified energy efficiency products for use within their existing procurement and designing systems. At
DESNZ
we’re committed to protecting the personal data we hold and to being transparent about the information we are collecting about you and what we do with it. GDPR
gives individuals (whether these be customers, contractors or members of staff) more control over the ways in which businesses process personal data. To reflect the newest changes in data protection law, and our commitment to transparency, we have updated our privacy policy for the
ETL
scheme:
Published 15 May 2015
Last updated 10 July 2024
10 July 2024
Links updated to point to new Energy Technology List website. 1 April 2020
Details on the future of the ETL published in light of the Enhanced Capital Allowance (ECA) for energy and water efficient plant and machinery ending in April 2020. 6 March 2019
Publication of changes to the Energy Technology List. 25 May 2018
Added details of updated privacy policy. 6 March 2018
Latest Product and Criteria lists published. Note added on changes to the technologies supported under the ETL as a result of the 2017 Budget
19 September 2016
Energy Technology List – Updated Technology Criteria and Product Eligibility Lists for Enhanced Capital Allowances
8 September 2016
Energy Technology List 2016 criteria and product lists update
17 July 2015
updated content
15 May 2015
First published. Print this page
Yes
this page is useful
No
this page is not useful
Report a problem with this page
To help us improve GOV.UK, we’d like to know more about your visit today. . Cancel | f452e845-af2b-4894-a937-376b40b95ab7 | 0 |
0c9def3f-0b7e-4fc9-8213-45e02f50d955 | 2,025 | [
"anthropogenic risk remediation",
"national emission ceilings",
"gross final energy consumption",
"soil",
"settlements"
] | HF-national-climate-targets-dataset | Limiting and controlling the contamination and other degradation of soil and rocks caused by human activities Reducing greenhouse gas emissions within the EU ETS by 21% and limiting the increase in emissions outside the EU ETS to 9% by 2020 compared with the 2005 level Implementing the national emission ceilings for sulphur dioxide (SO2), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH) and fine suspended particles (P2.5) Securing 13% share of energy from renewable sources in the gross final energy consumption by the year 2020 Ensuring a 10% share of energy from renewable sources in transport by the year 2020, while reducing emissions of NOx, VOC and PM5 from transportation Implementing the commitment to increase energy efficiency by 2020 Maintaining and strengthening the non-productive functions of the agricultural landscape and forests Halting the decline of native species and natural habitats Limiting the negative impact of invasive species and taking effective measures to regulate them Strengthening the regeneration of brownfields with a positive impact on the quality of the environment in settlements Improving the management of rainwater in settlements Preventing the sources of anthropogenic risk Remediation of contaminated sites, including old environmental burdens, and repair of onui ironments m | 2eb8512c-6df5-47e2-882c-d25161aee2e4 | 0 | |
0ca21984-b01c-4a68-bb07-5659480f0ce9 | http://arxiv.org/pdf/2108.03722v2 | 2,021 | [
"adaptation",
"technologies",
"patents",
"mitigation",
"climate"
] | arxiv.org | We find that adaptation technologies, as reflected by patents, can be grouped into two clusters: (i) science-intensive technologies (agriculture, health, and indirect adaptation); and (ii) engineering-based technologies (coastal, water, and infrastructure). We measure the scientificness of adaptation technologies by the share of patent citations to science over the sum of citations to other patents plus citations to science. | e7c5ec21-08e6-4ef3-84cf-6a259e7f7c53 | 30 |
0ca2d713-8b51-4473-92f8-d83867159acf | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_8122f7d823bf366105239091fb57ffd2.pdf | 2,023 | [
"data",
"energy",
"emissions",
"inventory",
"environment"
] | cdn.climatepolicyradar.org | The EEMS data per installation are only available back to 1998. The UK inventory estimates for the 1990 -1997 period are based on industry surveys and analysis that were submitted to UK Government by the trade association, UKOOA; these data are more aggregated, per source but aggregated across all installations during 1995 to 1997, and aggregated across sources for 1990-1994. | 9ce0b96e-2800-424e-bffb-cd8ba36e0902 | 173 |
0ca2f484-7ab8-4109-b6af-a99aa65c0084 | 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 | 6289
ELI httpdata.europa.euelireg20241781oj
OJ L, 28.6.2024
EN
2. The CE marking shall be affixed before the product is placed on the market or put into service. For a product in the production control phase in which a notified body participates, the CE marking shall be followed
3. by the identification number of that notified body. The identification number of the notified body shall be affixed by the body itself or, under its instructions, by the
manufacturer or its authorised representative. The CE marking and, where applicable, the identification number of the notified body may be followed by
4. a pictogram or other marking indicating a special risk or use. 5. Member States shall build upon existing mechanisms to ensure correct application of the regime governing the CE
marking and take appropriate action in the event of improper use of the CE marking. | a753c674-997e-439a-b7e9-1f2dc3546402 | 91 |
0ca94abd-c4ab-4e32-9850-04e39ae92075 | https://cdn.climatepolicyradar.org/navigator/GBR/2021/decarbonising-transport-a-better-greener-britain_23f5c97decfa20f90e61d607b564fc76.pdf | 2,021 | [
"Transport",
"Co-benefits",
"Cycling",
"Climate Finance",
"Public Transport",
"Freight",
"EVs",
"Shipping",
"Aviation",
"Walking",
"emissions",
"transport",
"government",
"zero",
"emission"
] | cdn.climatepolicyradar.org | Train emissions are based on an average for diesel and electric trains; if a route is fully electrified, emissions would be lower than
1. Greenhouse gas emissions and transport 15 1.13 The choices people make about whether to travel or transport goods using different modes of transport determine the environmental impact of that journey. The amount of GHG emissions associated with transport will depend on various factors such as the type and size of vehicle, the type of fuel used, fuel efficiency, route choices and the 1.14 At present, there are official statistics on total GHG emissions from different transport modes, but no official advice to help individuals understand the GHG emissions for specific journey and modal options. If individuals are able to access clear, transparent information about the emissions associated with their journeys, then this will enable more informed decisions about how individuals and goods travel. 1.15 Several organisations, such as the Energy Saving Trust, have made comparisons using publicly available conversion factors for the amount of emissions per unit of transport assumptions and can result in a wide range of estimates for the same journey. For have an impact, as would including different numbers of passengers within the cars. An electric bus operating on London’s 507 bus route
16 Decarbonising Part 1 – Setting the Challenge
2. Moving emissions by mode 2.1 In this chapter, the current position of each transport mode used to move people is summarised against their historical emissions along with the current targets for each mode and the policies in place to deliver them. Future work already in place or planned for each mode is also presented. 2.2 The majority of the trips we make annually are for leisure, including trips to visit friends, attend sports events, for holidays and day trips, followed by commuting and journeys for work or business purposes. Cars are the most common mode of transport regardless of the journey type. 94% of these car journeys are under 25 miles, with 58% under five 16. 87% of car users in England are of the view that their current lifestyle means they need to own a car17. Modal Share, England 2018 Trips by journey length, England 2018 National Travel Survey 2018, NTS030318 National Travel Survey 2018, NTS030818 Commuting/Business Education/escort education Shopping Other escort Personal business Leisure National Travel Survey 2018, NTS040318
18 D ecarbonising Setting the Challenge Travel is an important aspect of our everyday activities and our daily habits are often dependent on the transport available to us, whether we are aware of it, or not. Whether it is through the purchase of a new type of vehicle, moving to greater sharing of transport to increase utilisation, or switching modes, behaviour change will be an important aspect of the decarbonisation of transport. Whilst an understanding of what will prompt behaviour change does exist, a greater understanding of this at a transport-system level will help to support people to change to On 11 February, the Prime Minister announced £5 billion funding for investment in local buses and cycling and walking infrastructure. It includes funding at least 4,000 zero emission buses to make greener travel the convenient option, driving forward the UK’s progress on its net zero ambitions; and measures to improve modal shift onto the bus, such as high frequency services, more ‘turn up and go’ routes, new priority schemes, and more affordable fares. This is also part of the creation of a long term cycling and walking programme and budget that will enable delivery of the Government's aim to double cycling and increase walking by 2025, including through the £350 million Cycle Infrastructure Fund announced in the Conservative Party manifesto. Further details and allocations will be confirmed later in 2020. 2. M oving emissions by mode 19 Current position of the sector versus historical emissions 2.3 Cars today have lower emissions, with the average car in 2018 emitting just over 20% less CO2e for the same mileage than the average car in 199019. However, total fleet GHG emissions from cars have fallen just 11% since 2001 to 68MtCO2e20. 2.4 Motorists are making the switch to electric vehicles (EVs) and there are record numbers of them on UK roads. In 2019, the UK was the third largest market for ultra low emission vehicles (ULEVs) in Europe and is a global leader in their development 21. There are over 240,000 battery electric and plug in hybrid vehicles registered in the UK, nearly 230,000 of which are ultra low emission cars, up from just over 1,300 ultra low emission cars in 201022. 2.5 The UK is one of the largest markets in the world for the automotive sector. The number of battery electric car models on the global market is around 30, compared to over 350 for conventional vehicles. Supply is starting to increase and we expect to see around 20 new models available in the UK in 2020. Battery prices, a large part of the current total cost of EVs, have fallen almost 80% since 2010 costs have largely been offset by an increase in the battery size used in vehicles, 2.6 As we move to the mass adoption of ULEVs, more infrastructure will be needed alongside improvements to the consumer experience of using it. Whilst many EV drivers are likely to choose to charge their vehicles at home, or at their workplace, 20 to 30% of motorists do not have off-street parking24. More than a third of households in England do not have access to off-street parking, and this proportion increases in
20 D ecarbonising Setting the Challenge urban areas where air quality concerns are most acute. Not everyone without offstreet parking has a vehicle, but there are indications that around 25% of cars are parked on Current government aims and targets 2.7 The Government’s aim is to put the UK at the forefront of the design and manufacturing of zero emission vehicles26. | fc31b289-cdf5-490a-8570-5131d0d7e616 | 3 |
0caef2aa-a512-4c7d-9475-5034d28d7927 | https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32021R2116 | 2,013 | [
"Agriculture and forestry",
"Non-energy use"
] | eur-lex.europa.eu | CHAPTER II
Governance bodies
Article 8
Competent authority
1. Each Member State shall designate a competent authority at ministerial level responsible for:
(a)
the issuing, reviewing and withdrawing of accreditation of paying agencies referred to in Article 9(2);
(b)
the designation and the issuing, reviewing and withdrawing of the accreditation of the coordinating body referred to in Article 10;
(c)
designating and withdrawing the designation of a certification body as referred to in Article 12, and ensuring that there is always a certification body designated;
(d)
carrying out the tasks assigned to the competent authority under this Chapter. 2. On the basis of an examination of the minimum conditions to be adopted by the Commission in accordance with Article 11(1), point (a), the competent authority shall, by way of a formal act, decide on the issuing or, following a review, the withdrawal of the accreditation of the paying agency and on the designation and accreditation and the withdrawal of the accreditation of the coordinating body. 3. The competent authority shall, by way of a formal act, decide on the designation, and the withdrawal of the designation, of the certification body, while ensuring that there is always a certification body designated. 4. The competent authority shall inform the Commission without delay of all accreditations and withdrawals of accreditation of the paying agency and of the designation and accreditation and withdrawal of accreditation of the coordinating body, as well as of the designation, and the withdrawal of the designation, of the certification body. Article 9
Paying agencies
1. Paying agencies shall be departments or bodies of the Member States and, where applicable, of their regions responsible for the management and control of expenditure referred to in Article 5(2) and Article 6. With the exception of making payment, paying agencies may delegate performance of the tasks referred to in the first subparagraph. 2. Member States shall accredit, as paying agencies, departments or bodies which have an administrative organisation and a system of internal control which provide sufficient guarantees that payments are legal, regular and properly accounted for. To that end, paying agencies shall comply with minimum conditions for the accreditation with regard to the internal environment, control activities, information and communication and monitoring laid down by the Commission pursuant to Article 11(1), point (a). Each Member State shall, taking into account its constitutional provisions, restrict the number of its accredited paying agencies:
(a)
to a single paying agency at national level or, where applicable, one per region; and
(b)
to a single paying agency for the management of both EAGF and EAFRD expenditure where paying agencies exist only at national level. Where paying agencies are established at regional level, Member States shall, in addition, either accredit a paying agency at national level for aid schemes which, by their nature, have to be managed at national level, or confer the management of those schemes on their regional paying agencies. By way of derogation from the second subparagraph of this paragraph, Member States may maintain the paying agencies which have been accredited before 15 October 2020, provided that the competent authority, by means of the decision referred to in Article 8(2), confirms that they comply with the minimum conditions for accreditation referred to in the first subparagraph of this paragraph. Paying agencies which have not managed EAGF or EAFRD expenditure for at least three years shall have their accreditation withdrawn. Member States shall not accredit any new additional paying agency after 7 December 2021, except for cases referred to in the second subparagraph, point (a), where, taking into account the constitutional provisions, additional regional paying agencies may be necessary. | 8f9bf1c1-a150-4ba5-bf0e-b248d1eace93 | 31 |
0cb31ce2-87f4-497b-83a3-26bf5d7ac2de | 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 | (2004); EMEP/EEA (2019); IPCC (1997); IPCC (2006) An accompanying spreads heet “Energy_background_data_uk_2023.xlsx” lists all emission factors used in the energy sector, including a full list of references 49. In addit ion, Annex 3 EMEP/EEA Guidebook aircraft categories. UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 172 Estimates are based on IPCC Tier 3 method, and use the number of aircraft movements broken down by aircraft type at each UK airport together with UK energy statistics. The methods used to estimate emissions from aviation require the following activity • Aircraft movements and distances travelled Detailed activity data has been provided by the UK Civil Aviation Auth ority (CAA). These data include aircraft movements broken down airport; aircraft type; whether the flight is international or domestic; and, the next/last POC (port of call) from which sector lengths (great circle) have been calculated. The data covered all Air Transport Movements (ATMs) excluding air-taxi. The CAA also compiles summary statistics at reporting airports, which include air-taxi and non-ATMs. • Inland Deliveries of Aviation Turbine Fuel and Aviation Spirit Total inland deliveries of aviation spirit and aviation turbine fuel to air transport are given in DUKES (BEIS , 2022a ). This is the best approximation of aviation bunker fuel consumption available and is assumed to cover international, domestic and military use. • Consumption of Aviation Turbine Fuel and Aviation Spirit by the Military These data are supplied by the Ministry of Defence (MoD). Military aviation estimates are included in MS 15 . The data for total fuel use for military aviation is used in the normalisation to the DUKES total. Calendar year activity data are derived from the data sources described above. International Flights from UK Airports, 1990-2018
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 173 Estimated emissions from aviation are based on data provided by the CAA and, for overseas territories, the DfT. Gm flown calculated from total flight distances for departures from UK and overseas territories airports. A combination of national airport specific LTO factors (derived from local airport studies) and EMEP/EEA Eurocontrol cruise factors for generic aircraft are used. An accompanying spreadsheet “Energy_background_data_uk_2023.xlsx” lists all emission factors used in the energy sector, including aviation, and associated references. Carbon emission factors are country specific, whereas defaults are used for other gases. The basic approach to estimating emissions from the LTO cycle is as follows. The contribution to aircraft exhaust emissions (in kg) arising from a given mode of aircraft operation (see list below) is given by the product of the duration (seconds) of the operation, the engine fuel flow rate at the appropriate thrust setting (kg fuel per second) and the emission factor for the pollutant of interest (kg pollutant per kg fuel). The annual emissions total for each mode (kg per year) is obtained by summing contributions over all engines for all aircraft movements in the year. The time in each mode of operation for each type of airport and aircraft has been taken from individual airport studies. The time in mode is multiplied by an emission rate (the produ ct of fuel flow rate and emission factor) at the appropriate engine thrust setting in order to estimate emissions for phase of the aircraft flight. The sum of the emissions from all the modes provides the total emissions for a particular aircraft journey. The modes considered • Take-off Roll (start of roll to wheels-off); • Initial-climb (wheels-off to 450 m altitude); • Climb-out (450 m to 1000 m altitude); • Approach (from 1000 m altitude); • Auxiliary Power Unit (APU) use after arrival; and Departure movements comprise the following LTO taxi -out, hold, take-off roll, initial- climb, climb-out and APU use prior to departure. Arrivals approach, landing-roll, taxi-in and APU use after arrival. Aircraft often take-off at reduced thrust (i.e. less than 100% thrust). Thrust setting for Take-off roll; Initial-climb; and Climb-out depend on airport and aircraft type and are derived from local airport studies. Thrust setting during Approach are 15% for the initial phase (above 600 ft) and 30% for the final phase (below 600 ft). Depending on airport and aircraft type, the Landing -roll often includes periods or reverse thrust at either at idle or 30%, the remainder of the time is at idle thrust setting. Other modes (Taxi and Hold) are at idle thrust. UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 174 Idle thrust is nominally 7%, however an adjustment is made to the idle fuel flow to account for The approaches to estimating emissions in the cruise are su mmarised below. Cruise emissions are only calculated for aircraft departures from UK airports (emissions therefore associated with the departure airport), which gives a total fuel consumption compatible with recorded deliveries of aviation fuel to the UK. This procedure prevents double counting of emissions allocated to international aviation. The EMEP/EEA Emission Inventory Guidebook ( EMEP/EEA, 2019) provides fuel consumption and emission data for non -GHGs (NOx, HC and CO) for a number of aircraft cruise modes (climb cruise and descent). The data are given for a selection of generic aircraft type and for a number of standard flight distances. The breakdown of the CAA movement by aircraft type contains a more detailed list of aircraft types than in the EMEP/EEA Emission Inventory Guidebook. Therefore, each specific aircraft type in the CAA data has been assigned to a generic type in the Guidebook. | 70afacf8-8641-4466-819d-f4db8cad9d69 | 276 |
0cb754ab-cea2-4234-a3de-df03c07e7ae0 | https://assets.publishing.service.gov.uk/media/644a2dfdc33b460012f5e2fb/uk-net-zero-research-innovation-framework-delivery-plan-2022-2025.pdf | -1 | [
"government",
"zero",
"research",
"innovation"
] | www.gov.uk | Additional net zero research will be undertaken to support minimisation of methane emissions from landfills and the UKRI Strategic Priorities Fund National Interdisciplinary Circular Economy Research (NICER) Programme of circular economy centres aims to reduce waste. See also UKRI’s ISCF Smart Sustainable Plastic Packaging Challenge, Challenges 5.1 & 9.10. UK Net Zero Research and Innovation Delivery Plan | 87 Challenge Current Programme Summary Food Loss and waste makes a significant contribution to GHG emissions, with food waste accounting for about 10% of global emissions. UKRI is developing a research programme to address this challenge, building on the Horticulture Crop Quality and Food Loss Prevention Network, £0.5m SR22-25. Internationally, the Ayrton Fund / ODA-funded Transforming Energy Access Programme (TEA) is supporting innovations in reducing and managing electronic waste in Africa. The water industry has launched their route map to net zero by 2030. Water companies will be making investments in reaching net zero, regulated by Ofwat, with funding raised through water bills. Evidence assessments of measures to reduce Greenhouse Gas Emissions from the wastewater treatment sector will be UKRI alongside Defra are investing £6.9m SR22-25 (£8.4m overall) into understanding changes in the quality of UK freshwaters that will support reduced water treatment costs including reduced emissions through better planning for improving water quality. Work on this is being undertaken as part of policy appraisal in the review of the F-gas Regulation. This includes exploring alternative technology options through engagement with industry. Internationally, work is mainly aimed at the identification and filling of gaps in, and enhancement of current global monitoring of ozone
88 | UK Net Zero Research and Innovation Delivery Plan Taking a systems approach requires research to understand the interrelated nature of different sectors, the interaction of new technologies and how these impact consumers’ green choices and business models, as well as their potential impacts on health. Cross-cutting themes and systems research questions include understanding the optimum use of scarce resources; integration of digital solutions; the need for broad public support of new technologies; as well as the development of viable markets, regulatory arrangements and supply chains. The characteristics of the net zero challenge requires action by multiple parties across the public and private sectors, delivery at pace and management of uncertainty. Taking a systems approach to policy will help to navigate this complexity. We must consider the environment, society and economy as parts of an interconnected system, where changes to one area can directly or indirectly impact others. This will help to ensure we design policy to maximise benefits, account for dependencies, mitigate conflicting interests and take account of learning as we go. It reduces the risk of unintended consequences, ensuring individual decisions designed to help achieve net zero do not end up hindering it or other important objectives. UK Net Zero Research and Innovation Delivery Plan | 89 Challenge Current Programme Summary The UKRI Changing the Environment Programme, £24m SR22-25, (£40m overall) – aims to stimulate new collaborations across disciplines, to help realise the full potential of the UK’s contribution to environmental challenges such as energy decarbonisation, creating a circular economy, reversing biodiversity decline, sustainable supply chains and cleaner air. In addition, the UK FIRES Research Programme, £2m SR22-25, (£5.2m overall) – aims to reveal and stimulate industrial growth in the UK compatible with a rapid transition to zero emissions. The Strategic Priority Fund UK Climate Resilience Programme, £2.1m SR22-25, (£18.7m overall) – funded by UKRI and the Met Office, focusses on drawing together climate research and expertise to provide robust, multi and interdisciplinary climate risk and adaptation solutions research, required to ensure the UK is resilient to climate variability and able to exploit adaptation and green UKRI’s Geoenergy Observatories (UKGEOS), £12.4m SR22-25, (£31m overall) – is developing two subsurface observatories in Glasgow and Cheshire. This network of UK observatories will deliver essential new data to understand how geothermal energy, hydrogen, carbon capture and storage, and storage solutions for wind, solar and tidal energy can reduce our carbon emissions. Air pollution and climate are interlinked, with many air pollutants being ‘climatically active’, such that improving air quality also contributes to mitigation against climate change. The UKRI Strategic Priority Fund Clean Air Programme, £15.5m SR22-25, (£42.5m for wave 1 and wave 2 overall) – adopts an integrated approach to develop innovative solutions which could have co-benefits for both air quality and climate change. Internationally, the Climate Compatible Growth (CCG) Programme, £38m, part of the Ayrton Fund, is helping developing countries with economic strategies, plans and policies to attract investment into low-carbon growth opportunities. 90 | UK Net Zero Research and Innovation Delivery Plan Challenge Current Programme Summary UKRI’s the Future Design the Green Transition Net Zero Programme, £25m, supports design, research, innovation and public engagement on societal change and green choices. This includes a national engagement centre, up to 50 hyperlocal, place- based engagement projects and 4 large-scale regional clusters, as well as embedding highly qualified design researchers in public, private and third sector organisations. UKRI’s Centre for Climate Change and Social Transformations (CAST), £2m SR22-25, (£5m overall) – supports research on green choices in four areas of everyday life with potential climate change consumption of goods and physical products, food and diet, travel, and heating / cooling. UKRI’s Advancing Capacity for Climate and Environment Social Science (ACCESS), £2m SR22-25, (£5m overall) – aims to provide leadership to the social science contribution to tackling and solving environmental problems, by providing insights and new solutions to support the transition to a sustainable and biodiverse environment UKRI supported research programme, the Economics of Biodiversity, £5.7m SR22-25, (£6.4m overall) – will address how biodiversity and ecosystems connect to wider societal factors, such as achieving net zero, by advancing our understanding of the economic value, benefits and costs that society associates with, and Internationally, the Ayrton Fund supports the Modern Energy Cooking Services (MECS) Programme – £27.4m, which aims to transition from biomass to clean cooking in developing countries, delivering major health and environmental benefits. | bdc9cb31-994d-41fe-82b1-774692453063 | 20 |
0cbdd53d-6dca-4067-ba43-fb524cd35b40 | http://arxiv.org/pdf/2209.05767v1 | 2,022 | [
"model",
"data",
"bayesian",
"time",
"iams"
] | arxiv.org | In fact we have computed the full posterior distribution of the IAMs output mean given by SSPs specific input. This has enormous advantages in terms of interpretation of the estimates, since we can give true probabilistic interpretation of these estimates. | fb2cf143-cc5e-4887-aa4d-e7c043bedeb3 | 8 |
0cc58625-6782-47be-a313-40f689a83519 | 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 | 8. relevant commodity or product, except where the due diligence statement is lodged
pursuant to Article 262. Upon receipt of a customs declaration for release for free circulation or export of a
relevant commodity or product entering or leaving the Union market, customs
authorities shall verify the status of the due diligence statement using the electronic
interface referred to in Article 261. Any change of status in the Information System
referred to in Article 31, which takes place before the release for free circulation or
export of that relevant commodity or product, shall be notified automatically to the
customs authorities supervising that relevant commodity or product. Where following the risk analysis under Article 144 the status of the corresponding
due diligence statement indicates in the information system established under
Article 31 that a relevant commodity or product requires to be checked before placed
or made available on the EU market or exported, customs authorities shall suspend
the release for free circulation or export of that relevant commodity or product. Where all other requirements and formalities under Union or national law relating to
the release for free circulation or export have been fulfilled, customs authorities shall
allow a relevant commodity or product to be released for free circulation or exported
in any of the following circumstances
a Following the risk analysis under Article 144, competent authorities have not
indicated in the information system established under Article 31 that relevant
commodity or product as requiring the suspension of release for free
circulation or of the export pursuant to paragraph 6
b Where the release for free circulation or export has been suspended in
accordance with paragraph 6, the competent authorities have not requested,
within the 3 working days indicated in Article 147, the need to maintain the
suspension of the release for free circulation or export of that relevant
commodity or product
c Where competent authorities have notified customs authorities through the
information system established under Article 31 that the suspension of the
release for free circulation or export of the relevant commodities and products
can be lifted. The release for free circulation or export shall not be deemed proof of compliance
with Union law and, in particular, with this Regulation. the customs authorities accordingly
Where the competent authorities conclude that a relevant commodity or product
entering or leaving the Union market is not compliant with this Regulation, they shall
notify
information system
established under Article 31. Competent authorities may also indicate in the
information system that they object to placing the relevant commodity or product
under other specific customs procedures. through
the
Upon notification of that status, customs authorities shall not allow the release for
free circulation or export of that relevant commodity or product. They shall also
include the following notice in the customs data-processing system and, where
possible, on the commercial invoice accompanying the relevant commodity or
product and on any other relevant accompanying document Non-compliant
commodity or product release for free circulationexport not authorised
Regulation EU 2021XXXX. OP to indicate reference of this Regulation
EN
49
EN
Where the relevant commodity or product is subsequently declared for other customs
procedures and provided that the competent authorities did not object to such
placement, the notice shall be included by operator in the customs declarations and
registered, under the same conditions, in the customs data-processing system and,
where possible, on the accompanying documents used in connection with any such
procedures. Notifications and requests under paragraphs 5 to 8 of this Article shall take place by
means of the electronic interface referred to in Article 261. Paragraphs 5 to 8 shall
apply once the electronic interface referred to in Article 261 is in place. Customs authorities may destroy a non-compliant relevant commodity or product
upon the request of the competent authorities or where they deem it necessary and
proportionate. The cost of such measure shall be borne by the natural or legal person
holding the relevant commodity or product. Articles 197 and 198 of Regulation EU
No 9522013 shall apply accordingly. Upon request of competent authorities, non-
compliant relevant commodities and products may alternatively be confiscated and
placed by customs at the disposal of the competent authorities. Article 25
Exchange of information and cooperation among authorities
To enable the risk-based approach referred to in Article 143 for relevant
commodities and products entering or leaving the Union market and to ensure that
checks are effective and performed in accordance with the requirements of this
Regulation, the Commission, competent authorities and customs authorities shall
cooperate closely and exchange information. Customs authorities and competent authorities shall cooperate in accordance with
Article 472 of Regulation EU No 9522013 and exchange information necessary
for the fulfilment of their functions under this Regulation, including via electronic
means. 9. | fdc8afd5-2a2d-4946-a4da-be36ebf11749 | 65 |
0ccecc5d-2227-4fee-907a-7a20a8763b03 | https://www.gov.scot/binaries/content/documents/govscot/publications/strategy-plan/2020/12/securing-green-recovery-path-net-zero-update-climate-change-plan-20182032/documents/update-climate-change-plan-2018-2032-securing-green-recovery-path-net-zero/update-climate-change-plan-2018-2032-securing-green-recovery-path-net-zero/govscot%3Adocument/update-climate-change-plan-2018-2032-securing-green-recovery-path-net-zero.pdf | 2,019 | [
"scotland",
"climate",
"change",
"plan",
"emissions"
] | www.gov.scot | This will include a comprehensive set of significantly scale up deployment energy efficiency in Scotland. This Climate Change Plan update provides a summary of the policies and actions that will be set out Buildings Strategy. During 2021 we will set out the key elements of how the housing sector will drive towards net zero emissions in the context of the 20 year Housing to 3.2.26 Our early actions to 2025 will focus on increasing deployment rates of zero and low emissions 3.2.27 Principles for action a) taking a whole systems view; ensuring a just transition, including towards meeting our targets on c) working closely with citizens, 53 Energy Efficient route d) driving innovation to secure efficiency improvements and cost e) exploring innovative finance and f) using tax based incentives to Ħ creating the conditions to secure Ħ Local Heat & Energy Efficiency Strategies for all of Scotland by the end of 2023 to ensure a 3.2.29 These key actions, principles are outlined below. The Heat in Buildings Strategy will set out in more detail how we will achieve 3.2.30 The Heat in Buildings Strategy will update the Energy Efficient standards and regulation for heat it is within legal competence, to ensure that all buildings are energy efficient by 2035 and use zero emission heating and cooling 3.2.31 We will ensure the alignment and coherence of wider policies and regulations so that these support the reduction of emissions from 3.2.32 As far as is within our legislative competence, we will put in place a new, appropriate framework by
Update to the Climate Change Plan | Buildings 101 3.2.33 Our initial focus for action before introducing a standard requiring all domestic private rented sector; 3. introducing regulations for all buildings to achieve a good level of 4. establishing a new net zero carbon standard for new public 5. taking steps to facilitate common 3.2.34 We will also work with social landlords to bring forward the Efficiency Standard for Social to strengthening and realigning 3.2.35 The forthcoming Heat in Buildings Strategy will set out the steps we will take to develop proposals for a future regulatory framework for zero emissions heating, to be put in place to drive very significant accelerated market growth from 2025, subject to the limits of the 3.2.36 We will invest £1.6 billion54 in heat and energy efficiency over the next Parliament. This will leverage additional UK Government funding and private household financing to deliver against our ambition to 54 Announced in 2020-2021 Programme for Government see, as a minimum, the rate of zero emissions heat installations in new and existing homes and buildings double every year out to 2025. 3.2.37 The investment will deliver against 1. Supporting those least able to pay, for example through increased Scotland and continuation of the within the successor to the Low Carbon Infrastructure Transition costs for zero emissions systems can in some instances be higher than current fossil fuel equivalents, priority funding theme in the LCITP successor programme, supporting communities to decarbonise their buildings (through schemes such as CARES, including dedicated support for islands and our most remote adoption by providing support for decarbonisation of the public sector estate, maximising spend through domestic and small and medium- sized business cashback schemes, programme for the self-funded. 4. Innovation and we will promote learning by doing, support technology and business
102 Update to the Climate Change Plan | Buildings as a priority theme within the and hybrid systems, and in the decarbonisation such as multi- 3.2.38 Investment commitments Funding Invitation to support low carbon and zero emissions heat projects in Scotland (already in efficiency of the public estate; 3. £25 million to support zero carbon energy infrastructure and heat networks for residential and commercial premises in the Clyde 4. up to £4.5 million over the next six months in a cashback scheme cashback for zero emissions heating efficiency measures, with a total of £13,500 available per home; 5. boosted and strengthened Energy Efficient Scotland delivery schemes to stimulate even greater take up buildings56 and a new commitment to increase zero emissions heating 6. continued support for affordable install zero emissions heating supply 55 Announced in the 2020-2021 Programme for Government, with further commitments included in this Climate Change Plan 56 Boosted both in the 2019-2020 Programme for Government, and in the 2020-2021 Programme for Government ahead of regulatory requirements in 2024, through our Affordable 3.2.39 We will use our investment investment and target deployment at no and low regret priorities in order to grow the customer base, emissions heat projects through Ħ publish a Local Energy Policy that has people at its centre, supported by strong partnership working and collaboration at a Protecting consumers and ensuring 3.2.41 We will establish clear principles no one being left behind, ensuring our approach neither increases the fuel poverty rate nor increases the depth of existing fuel poverty. | 9e89f3e7-5608-4a69-bc95-89195cd33085 | 28 |
0ccfad1d-ae08-460b-8fa6-9b54e2806fb2 | https://www.odyssee-mure.eu/publications/archives/MURE-Overall-Policy-Brochure.pdf | 2,001 | [
"Buildings",
"Energy efficiency"
] | www.odyssee-mure.eu | httpwww.isi.fraunhofer.deisi-dexprojektebmwi_weisse-zertifikate_31-517-6_sm.php
Seefeldt et al. Seefeldt, F. Struwe, J. Ragwitz, M. Steinbach, J. Jacobshagen, U. Kachel,
M. Brandt, E. Nast, M. Simon, S. Bürger, V. 2012 Fachliche und juristische
Konzeption eines haushaltsunabhängigen
für erneuerbare Wärme
Zwischenbericht unpublished
Instruments
Staniaszek, D. Lees, E. 2012 Determining Energy Savings for Energy Efficiency
Obligation Schemes. Report commissioned by RAP and eceee. April 2012. httpwww.eceee.orgEED
UK Department of Energy Climate Change 2012 Annual Report on Fuel Poverty
Statistics 2012. httpwww.decc.gov.ukencontentcmsstatisticsfuelpov_statsfuelpov_stats.aspx
Transport
ACE, 2011. National energy efficiency and energy saving targets further detail on Member
States, 24 May 2011 Dr Joanne Wade, and Pedro Guertler, Darryl Croft and Louise
Sunderland, from the Association for the Conservation of Energy
ADEME 2012 Energy Efficiency Trends in the Transport Sector in the EU Lessons from the
ODYSSEE MURE project, March 2012
AEA and TEPR, 2011. Report on the implementation of Directive 199994EC relating to the
availability of consumer information on fuel economy and CO2 emissions in respect of
the marketing of new passenger cars. Report for DG Clima Action, European
Commission
Álvarez, E 2008. Type approval requirements for the general safety of motor vehicles, Report
for the Department Economic and Scientific Policy European Parliament
73
Energy Efficiency Policies in the European Union
ARUP 2008 Investigation into the scope for the transport sector to switch to electric
vehicles and plug-in hybrid vehicles Department for Business Enterprise Regulatory
Reform Department for Transport. httpwww.bis.gov.ukfilesfile48653.pdf
BMWi Federal Ministry of Economics and Technology 2011 2nd. National Energy
Efficiency Action Plan NEEAP of the Federal Republic of Germany - Methodological
Accompanying Document -in accordance with the EU Directive on Energy End-use
Efficiency and Energy Services 200632EC and the Act on Energy Services and
other Energy Efficiency Measures Energiedienstleistungsgesetz, EDL-G. July 2011
httpec.europa.euenergyefficiencyenduse_en.htm
DG TREN 2009 Energy Savings Potentials in EU Member States, Candidate Countries
and EEA Countries
EC 2009. Moving forward together on saving energy Synthesis of the complete
assessment of all 27 National Energy Efficiency Action Plans as required by Directive
200632EC on energy end-use efficiency and energy services. SEC2009889 final
EC 2011. White Paper Roadmap to a Single European Transport Area Towards a
competitive and resource efficient transport system COM2011 144 final
Ecolane
2011
Ultra-low
carbon
vehicles
in
the UK. RAC Foundation. httpdesign.open.ac.ukdocumentsMarket_delivery_of_ULCVs_in_the_UK-
Ecolane.pdf
EEA 2010 Towards a resource-efficient transport system TERM 2009 indicators tracking
transport and environment in the European Union, EEA Report No 22010
Element Energy 2009 Strategies for the uptake of electric vehicles and associated
Change. Committee
Climate
on
implications. infrastructure
httphmccc.s3.amazonaws.comElement_Energy_-
_EV_infrastructure_report_for_CCC_2009_final.pdf
ETC 2009 Environmental impacts and impact on the electricity market of a large scale
introduction of electric cars in Europe. European Topic Centre on Air and Climate
Change. httpacm.eionet.europa.eudocsETCACC_TP_2009_4_electromobility.pdf
FIA 2011 Towards e-mobility and the challenges ahead. Federation Internationale de
LAutomobile httpwww.lowcvp.org.ukassetsreportsemobility_full_text_fia.pdf
httpwww.eceee.orgPolicyTargetsTargets_Country_Specific_Information.pdf
IDEA, 2006. Guia para la implementacion de Planes de Movilidad Urbana Sostenible
PMUS, Madrid. | 122a6704-bce7-4e62-9bc9-5e1516956bc0 | 98 |
0cd228e8-b124-42ed-b070-7a8dd096bbe0 | https://www.odyssee-mure.eu/publications/archives/MURE-Overall-Policy-Brochure.pdf | 2,000 | [
"Industry",
"Energy efficiency"
] | www.odyssee-mure.eu | Another example would be the
ECoWILL project32 focusing on reducing carbon emissions by 8Mt by 2015 through
implementing more fuel efficient driving across Europe. 30 httpwww.eea.europa.euthemestransportspeed-limits
31 httpsuite101.comarticleconfusion-over-spain-speed-limit-u-turn-a377305
32 httpwww.ecodrive.orgenhomeecowill_the_project
48
Energy Efficiency Policies in the European Union
4.5.1 Optimised logistics
Freight logistics
Another approach taken by countries to improving the overall fuel efficiency of freight
transport is through fleet managementfleet logistics, such as voluntary agreements which
are already covered in section 0. An example is the management of road transport fleets in
Spain As part of the basket of measures on More Efficient Use of the Means in the
Transport Sector within the Action Plan 2011-2020, Spain introduced a measure to improve
the management of the road transport fleet in order to achieve a reduction in the specific
consumption per ton or transported passenger. | 0a44b68e-44b8-4fcc-b398-2ce2c8fbc626 | 65 |
0cd816f2-c068-4454-a093-842fac44b344 | 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 | In the construction and heating sectors, up to 230,000 skilled trades people could be required in 2030 to deliver the retrofitting of houses125and to meet our ambition of installing 600,000 heat pumps a year by 2028, we will need to rapidly increase the number of qualified installers from around 3,000 to 35,000 within the next 7 years.126 As the automotive manufacturing sector transforms to producing electric vehicles, as many as 50,000 workers in the UK’s automotive manufacturing sector could need reskilling by 2025.127 In forestry and its supporting sectors, industry estimates point to projected labour demand of approximately 2,000 jobs over the next five years.128 As well as specialists in these sectors, employers will also need workers with wider cross- cutting skills to deliver net zero, including digital and data skills, project management, communications and change management.129 There will also be increased need to work in a multidisciplinary way due to the way work will change in some sectors. For example, whole house retrofitting will need knowledge of multiple technologies. The impact of the transition on the labour market will not be evenly spread across the UK, reflecting the geographical distribution of where existing industries will need to adapt and others new ones will flourish.130 However, there are opportunities for workers in transitioning sectors, such as oil and gas, to utilise their specialist skills in key important green sectors, 125 ITB (2021), ‘Building Skills for Net Zero’, reports/search-our-construction-industry-research-reports/building-skills-for-net-zero/ 126 Heat Pump Association (2020), ‘Building the Installer Base for Net Zero Heating’, org.uk/wp-content/uploads/2020/06/Building-the-Installer-Base-for-Net-Zero-Heating_02.06.pdf 127 BEIS (2021), ‘Green Jobs Taskforce Report’, 128 Forestry Skills Forum (2021) ‘Forestry Workforce Research’, forestry-workforce-research-final-report-august-2021.pdf 129 BEIS (2021), ‘Green Jobs Taskforce report’, 130 BEIS (2021), ‘Green Jobs Taskforce report’,
Chapter 3 Policies and Measures 241 sectors such as hydrogen and CCUS with these two sectors expected to grow from the orking with industry and key partners to support good green jobs and skills Industry and government will need to take action to ensure the UK has the skilled workforce to deliver net zero and that workers, industries and places are supported on the transition. This will be particularly important given the pace and scale of the change, and the specific challenges faced by smaller companies in some sectors and supply chains. To drive this forward, we have announced a Green Jobs Delivery Group to include representatives from industry, the skills sector and other key stakeholders to support the development and delivery of the Government’s plans for green jobs and skills. The Green Jobs Delivery Group met for the first time on 11 May 2022, and will be the central forum through which government, industry and other key stakeholders work together to ensure that the UK has the workforce needed to deliver a green industrial revolution. The Group includes Ministerial representation from BEIS, Defra, DWP and DfE and will be co-chaired by an industry representative. The Group will be active for the duration of this Parliament and will aim to drive forward industry ensuring we have the skilled workfor ce to deliver net zero and wider environmental goals in line with the UK’s levelling up agenda; 2. ensuring workers and communities in high carbon sectors are supported with the transition in the wider context of the UK’s levelling up agenda; essing barriers to recruitment, retention and 5. building on the work of the Gr een Jobs Taskforce to develop a clearer understanding of the green economy and how to define and measure it. To support this work, and monitor our progress, it is vital that we continue to develop the evidence on how net zero will impact jobs and skills. The Office for National Statistics will seek to refine our understanding and measurement of the green economy as the UK transitions to net zero, including looking at such issues as quality of work and diversity within Join up between local bodies, employers and local communities will be key to ensuring an effective transition. Building on the measures set out in the Local Climate Action chapter in the Net Zero Strategy, and our skills system reforms, we will assess how local areas are working to support workers and communities with the net zero transition across England. We want to see continuous improvement in the quality of jobs in the UK, both in the creation of new high-quality jobs which support Government priorities such as net zero, and through While skills policy is a devolved matter, the Government also welcomes close engagement with the devolved administrations, Mayoral Combined Authorities and the Greater London Authority, on this agenda, to ensure everyone across the UK has access to green We are driving forward reforms to put employers at the heart of the skills system and ensure colleges are responsive to the needs of local economies. As demand for green skills
242 8th National Communication continues to grow across the UK, employers in the green economy must prioritise investment in the retraining and upskilling of their workforce, and actively take the opportunity to engage with education providers to shape local provision. Central to our strategic reforms are the plans set out in the Skills for Jobs White Paper, which will enable local employers to set out their green skills needs to drive provision in local colleges. The programme is made up of two local skills improvement plans and the First, the Trailblazers for local skills improvement plans, led by employer representative bodies will identify and articulate unmet and future local skills needs and work with further education providers to adapt their technical training offer so that it becomes more responsive to employers’ needs. | e6994b55-18ee-49c8-92db-2261135aea96 | 101 |
0cda15e0-a14b-472f-86b5-fb761cac2c70 | https://www.legislation.gov.uk/ukpga/2008/27/schedule/2/paragraph/23 | 2,008 | [
"allowances",
"certificates",
"trading scheme",
"united kingdom",
"following- u.k."
] | legislation.gov.uk | 23 (1) The regulations may provide for the creation and maintenance of a register or registers of information relating to a trading scheme and, in particular, for the register or registers to keep track of any of the following- U.K. (a) the participants in a trading scheme; (b) any limits on or obligations applying to the participants' activities under the scheme; (c) any allocation of allowances among the participants; (d) the allowances, credits, certificates or other units held by the participants or others; (e) trading in allowances, credits, certificates or other units; (f) the use by the participants or others of allowances, credits, certificates or other units for the purposes of the scheme; (g) the cancellation of allowances, credits, certificates or other units; (h) permits held by the participants, and any conditions attached to those permits. (2) The regulations may, in particular, provide for the establishment and maintenance of accounts in which allowances, credits, certificates or other units may be held by the participants, the administrator or others and between which they may be transferred. (3) The regulations may provide for the same register to operate in relation to more than one trading scheme. (4) The regulations may make provision for the disclosure of information held in or derived from a register relating to a trading scheme- (a) for the purposes of the administration of another trading scheme for which provision is made by regulations under this Part of this Act, or (b) for the purposes of the administration of any other trading scheme (at United Kingdom, European or international level) relating to greenhouse gas emissions. | 23ecf4ec-6f48-45f2-bd98-078e5df2b653 | 0 |
0cdcdc54-4198-4f96-a7d2-cf37a1d08f32 | https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32013D1386&from=EN | 2,013 | [
"General",
"Energy efficiency",
"Renewables",
"Non-energy use"
] | eur-lex.europa.eu | Priority objective 2 To turn the Union into a resource-efficient, green and competitive low-carbon economy
29. The Europe 2020 Strategy seeks to promote sustainable growth by developing a more competitive low-carbon
economy that makes efficient, sustainable use of resources. Its Resource-efficient Europe Flagship Initiative aims to
support the shift towards an economy that is efficient in the way it uses all resources, absolutely decouples
economic growth from resource and energy use and its environmental impacts, reduces GHG emissions,
enhances competitiveness through efficiency and innovation and promotes greater energy and resource security,
including through reduced overall resource use. The Roadmap to a Resource Efficient Europe and the Roadmap for
moving to a competitive low-carbon economy 1 are key building blocks of the Flagship Initiative, setting out the
framework for future actions to deliver on those objectives, and should be supported by the exchange of best
practice between Member States. Furthermore, a partnership between the Union, its Member States and industry,
under the Unions integrated industrial policy will provide a means of stepping up investment and innovation in six
green economy-related growth markets 2 . 30. Innovation to improve resource efficiency is required throughout the economy to improve competitiveness in the
context of rising resource prices, scarcity, raw material supply constraints and dependency on imports. The business
sector is the primary driver of innovation, including eco-innovation. However, markets alone will not yield the
desired results, and in order to improve their environmental performance, small and medium-sized enterprises
SMEs, in particular, require specific assistance with the uptake of new technologies, including through research and
innovation partnerships on waste 3 . Government action, at Union and Member State level, is essential to provide
the right framework conditions for investment and eco-innovation, stimulating the development of sustainable
business or technological solutions to environmental challenges and promoting sustainable patterns of resource
use 4 . 31. This key requirement for meeting environmental challenges also has important socioeconomic benefits and can
stimulate competitiveness. Potential job growth brought about by the transformation to a low carbon, resource-
efficient, safe and sustainable economy is central to the fulfilment of the Europe 2020 employment objectives 5 . Employment in environmental technologies and service sectors in the Union has been growing by around 3
annually over recent years 6 . The global market for eco-industries is estimated to be worth at least one trillion
EUR 7 , and is forecast to almost double over the next 10 years. European companies already have a global lead in
recycling and energy efficiency and should be encouraged to benefit from this growth in global demand, supported
by the Eco-innovation Action Plan 8 . For example, the European renewables sector alone is expected to generate
more than 400 000 new jobs by 2020 9 . A sustainable bioeconomy can also contribute to intelligent and green
growth in Europe, and, at the same time, it will benefit from improved resource efficiency. 32. Fully implementing the Union Climate and Energy Package is essential to reaching the milestones identified for
2020 and for building a competitive, safe and sustainable low-carbon economy by 2050. Whereas the Union is
currently on track to reduce domestic GHG emissions 20 below 1990 levels by 2020, meeting the 20 energy
efficiency target will require far more rapid efficiency improvements and behavioural change. | 2b3f86a5-3e9b-443e-ad77-adb974811b8a | 19 |
0cddd914-3937-41ac-8137-b7bc5dd705a4 | http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:52005DC0628 | 2,005 | [
"Transport",
"Electricity and heat",
"Renewables"
] | eur-lex.europa.eu | 3.2. EBA
So far, exports of bioethanol from countries benefiting from the special arrangement for the least developed countries (the EBA initiative) under the GSP (EC) Regulation 980/2005 to the EU have been negligible and have primarily come from one country - the Democratic Republic of Congo - which already qualified for duty-free access as an ACP country. At the moment, the Democratic Republic of Congo is the only LDC with sizeable, though erratic, exports of alcohol to the EU under code 22 07 since 1999. In 2004 exports totalled 18 956 hl after peaking at 86 246 hl the year before. It is fair to recognise, however, that EBA dates back to only 2001 and that some of the countries which did not have duty-free access under other earlier regimes (notably Bangladesh, Laos, Cambodia, Afghanistan and Nepal) might find new ways of access to the EU in the medium or longer term. New opportunities might emerge in these countries - which generally do not produce (or are not very competitive at producing) sugar cane or any other raw material for bioethanol production from their own resources in the form of processing molasses imported from their competitive, sugar-producing neighbours. This might be the case with Cambodia which could use raw material from Thailand, or with Bangladesh and Nepal which might process raw material from India. At the moment it is difficult to quantify future potential production from these countries but investments are known to have been made in some of them, like Bangladesh. In this respect it is important to stress that under Council Regulation (EC) 2501/2001, imports are subject to the GSP rules of origin plus regional cumulation. The Commission is currently examining a proposal for a new regulation which would introduce the principle of determination of the preferential rules of origin based on the value-added method. Distillation should continue to be considered an operation with sufficient added value to confer origin on the finished product. | 4d97d3b3-afe5-45f2-8123-6e37d1fdc0fe | 67 |
0ce00ceb-17d6-4c15-8108-b4fad7175801 | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_8122f7d823bf366105239091fb57ffd2.pdf | 2,023 | [
"data",
"energy",
"emissions",
"inventory",
"environment"
] | cdn.climatepolicyradar.org | 2A2 non-fuel combustion 10.00% 5.00% (a) 5.00% High level of reporting in EU ETS for recent years and EF reflects small range of data for carbonates used in lime production. AD uncertainty higher in earlier years. | 9ce0b96e-2800-424e-bffb-cd8ba36e0902 | 78 |
0ce2af2c-675c-4d68-949b-c806891eb375 | 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 | We want to continue to deepen devolution across England in the future, as new Strategic Authorities grow in capacity and coverage. So, we will regularly review the Devolution Framework in collaboration with Strategic Authorities. As a first step, we will work with areas that have mayoral devolution agreements and priority areas for new mayoral devolution in the coming months to include them in conversations to evaluate the new framework Established Mayoral Strategic Authorities will be able to propose, individually or with others, additional functions to be added to the statutory Devolution Framework, or piloted locally, in order to deliver their areas of competence. The mechanism of requesting further powers is intended to drive innovation and testing to ensure we continue to trailblaze. This will be an annual process ahead of fiscal events. Proposals will be discussed at the Mayoral Council and then Established Mayoral Strategic Authorities will be invited to submit a written proposal formally, to which the government will have a duty to respond. Successful pilots will be considered for addition to The government will therefore take the power to add to, but not remove from, the statutory Devolution Framework by statutory instrument, subject to consultation with Mayoral Strategic Authorities. 2.2 Widening and deepening devolution in England We want to see all of England benefit from devolution, with full devolution coverage across the country, at least to the level of Foundation Strategic Authorities, with an ambition to move to a mayoral model. By completing the map and working towards all areas having a Mayor, the government will rebalance power. The government will consider future devolution agreements against the criteria set out below on geography and governance arrangements. Ahead of the English Devolution Bill, we will bring forward areas ready to move quickly through a new Devolution Priority Programme. When agreeing geographies the government will consider the following principles. It will not be possible to meet all the principles in all situations and the government will work with areas to find an optimal Strategic Authorities should be of comparable size to existing institutions. The default assumption is for them to have a combined
4/10/25, 5:12 PM English Devolution White Paper - GOV.UK 25/101 population of 1.5 million or above, but we accept that in some places, smaller authorities may be necessary. Strategic Authorities must cover sensible economic geographies with a particular focus on functional economic areas, reflecting current and potential travel-to-work patterns and local labour markets. It is likely that where travel to work areas are small and fragmented, Strategic Authorities will cover multiple travel to work areas. Any proposed geography must be contiguous across its constituent councils (either now or with a clear plan to ensure contiguity in the future through agreed local government reorganisation). No ‘devolution islands’: Geographies must not create devolution ‘islands’ by leaving areas which are too small to go it alone or which do Geographies should ensure the effective delivery of key functions including Spatial Development Strategies, Local Transport Plans and Get Britain Working Plans. The government will seek to promote alignment between devolution boundaries and other public sector boundaries. A vital element of successful devolution is the ability for local residents to engage with and hold their devolved institutions to account – and local identity plays a key role in this. Given Mayors are the government’s strong preference, the deepest powers will only be available at the Mayoral level and higher. Mayors should have a unique role in an institution which allows them to focus fully on their devolved responsibilities, while council leaders must continue to focus on leading their place and delivering vital services. Conflating these two responsibilities into the same individual and institution, as is the case if an individual local authority had a mayoral model of devolution, would risk the optimal delivery of both. We will therefore discontinue the individual Local Authority devolution model in its mayoral form. To provide consistency across the country, we will remove the ability of Strategic Authorities to call Mayors by another name, in common with local government councillors and UK MPs, regardless of the ward or constituency Non-Mayoral devolution (Foundation level) The government will also consider proposals for local authorities to work in partnership through the establishment of a Combined Authority or Combined County Authority, as a platform to consider mayoral devolution in the future. By exception, the government will consider non-mayoral
4/10/25, 5:12 PM English Devolution White Paper - GOV.UK 26/101 devolution arrangements for single local authorities, where the criteria above are met, but only as a stepping-stone towards forming a Mayoral Combined Authority or Mayoral Combined County Authority. In areas with two tiers of local government, before moving to a single tier, the government will establish Combined County Authorities but not Combined Authorities. In those cases, while districts will not be constituent members, the government expects effective levels of collaboration to be demonstrated between constituent members and district councils, especially where the district council covers the primary city or economy in that county. 4/10/25, 5:12 PM English Devolution White Paper - GOV.UK 27/101 Devolution in North East Child Poverty Reduction Unit In the North East the Mayor is driving forward proactive and practical solutions to support prevention of child poverty. This year, the Mayor launched the Child Poverty Reduction Unit. The aim of the Unit is to
4/10/25, 5:12 PM English Devolution White Paper - GOV.UK 28/101 build a strategic, long-term and collaborative approach to reducing child poverty, building on the initiatives already underway. One of the first outputs will be a Mayor’s Childcare Grant, which will help parents find or return to work and keep more of their earnings. This year, the Combined Authority is delivering a programme of work across all seven constituent authorities. More than 220 schools will be supported to mitigate the symptoms and causes of child poverty. Advisors have supported families and households by bringing welfare rights advice and support into schools. | 969ae9d8-79fb-416b-8702-ba47c750f97a | 8 |
0ce76fe6-62e5-4dfb-9107-0bdb05ff0737 | 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 | There is a separate folder for each inventory year and at the end of an inventory cycle the final versions of all datasets remain unchanged for back reference if r equired. In addition to this , the model code used within UKCEH for inventory compilation is stored in a subversion repository to ensure a clear record of all amendments and iterations. | 70afacf8-8641-4466-819d-f4db8cad9d69 | 101 |
0cf7158f-281f-4540-b161-e9da5c8c564b | 2,025 | [
"different jurisdictions",
"country breakdown",
"data availability",
"disclosures",
"period"
] | HF-national-climate-targets-dataset | These disclosures are expected to improve data availability and quality and help develop common robust methodologies. The EBA envisages a phase-in period until June 2024 for these disclosures. S The EBA simplified the template in question by removing the country breakdown. In addition, the e template has been amended to increase the t e comparability of the information disclosed across a different jurisdictions. | ca244b81-0eaa-40d6-80f0-7bd56f4bad67 | 0 | |
0cfa32ec-474e-49ad-85db-30c83fbf75f6 | 2,025 | [
"uk water industry research",
"non - hazardous waste",
"landfill emissions estimation",
"carbon accounting workbook",
"routemap"
] | HF-national-climate-targets-dataset | Net Zero Strategy: Build Back Greener Resources and Waste: For municipal wastewater, water companies use the Carbon Accounting Workbook developed by UK Water Industry Research to estimate operational GHG emissions across the industry. The workbook has been in place since 2004 and is updated annually to reflect the needs of the industry, including changes in carbon accounting practices with updated emission factors to align with the latest UK and international data. There are no internal models for private or industrial emissions and there are still significant gaps in our understanding of the magnitude and main sources of these. The Water UK Routemap to 2030 sets out industry plans to achieve net zero by 2030.113 This routemap has been used as the basis for Defra to develop net zero consistent policies, for example, using assumptions from industry on cost and feasibility of policy deployment. For landfill emissions estimation, the Landfill Environmental and Financial (LEAF) model has been used. This was developed by Resource and Waste Solutions, and more detail can be found in their report.114 This is a high-level and strategic model of non-hazardous waste flows in England. LEAF allows the different scenarios to be described numerically and their effects on landfill emissions and costs of landfill to be calculated. The model considers the impacts of changes on landfill gas, leachate and void space consumption. The model is England only, but to provide an indication of Devolved Administration potential, emission savings are scaled to a UK level using relative emissions shares between England and the Devolved Administrations. It is assumed that there is a linear increase in diversion from landfill after 2021. | 236d69b2-e54c-46c2-8bce-1278195c3e8d | 0 | |
0cfc7b9f-6355-41eb-9a7d-5529ce908e39 | http://arxiv.org/pdf/2312.07614v3 | 2,023 | [
"model",
"abatement",
"cost",
"stochastic",
"interest"
] | arxiv.org | ∆T A = 0, we recover the classical model with
In a standard risk-neutral valuation, this change would have no effect, as the accruing is compensated by the discounting. However, the change might introduce an effect in the DICE model, due to the way how abatement and damage cost are associated as well as due to the time-preference included in the utility function. Since damages occur instantaneously, we do not consider funding of these. The total cost is given by C(t ) := C A (t) + C D (t). For an unsecured financial cash-flow its present value is defined by a discount factor times the cash-flow. If the future cash-flow is subject to default, the discount factor is lower, reflecting the additional value reduction due to the risk of (partial) default. As default is not an option for future damage cost, it appears as if the risk-free discount factor should apply. However, since no hedging strategy exists, a risk free funding is not possible. Thus additional cost may occur to secure the unsecured funding [42]. Since damage cost may become very large -much larger than funds provided by standard financial markets -it is reasonable to assume that these additional funding cost become (over-proportionally) large for larger damages. We model this by optionally adding non-linear financing cost using a non-linear funding model [42]. This model allows, that the discount factor may depend on the magnitude of the cash-flow. Thus the funding of larger cash-flows requires a premium to compensate for a larger default risk or other frictions. For our application, this means that larger damages get a larger weight. Our model modification is now a modification of the damage cost. Let C • D (t) denote the damage cost of the classical model, i.e. the quantity that was formerly denoted by C D (t). We then re-define the effective damage costs as
where DC(C
The latter approach allows us to penalize damages that exceed a certain percentage of the GDP. The factor DC * (x ) depends on the size of x. For small x we have DC * (x ) = 1, but for large x we may have factors > 1. Obviously, this will penalize large spikes in the costs. In our numerical experiments the funding period was set to 20 years and the non-linear discounting was set to increase the default compensator significantly for damage cost over 3% of the GDP (black). The parameter choice is exemplary, other experiments with similar results can be reproduced in the published source code. As the abatement cost are usually smaller and part of a more planned process, we do not consider a default compensation factor for the abatement cost. To measure the burden born by a generation, we consider the relative total damage and abatement cost per GDP. Putting nominal values relative to the GDP is a common measure, e.g., to assess national debt [57]. Here, it reflects that a more wealthy generation can carry a greater burden, mimicking an effort sharing scheme and also considering the greater capacity of future generations under the expected baseline growth in DICE. In our numerical experiments we measure the instantaneous cost-per-GDP C(s)/GDP(s) as well as the lifetime-average cost-per-GDP C(s)/GDP(s). To allow for a netting within a generation one may consider the (discounted) average value over a generation lifetime. For a given time s let T L (s) denote the expected lifetime of a generation. We then consider the lifetime average cost and GDP. Our numerical analysis shows that a continuous adaptation of the abatement strategy may increase the risk and expectation of intergenerational inequality measures as cost-per-GDP. The expected emissions/damage/cost are higher than the emissions/damage/cost calculated for the expected interest rate level. Such an effect may come as a surprise. However, it is well known from mathematical finance, known under the name convexity. The effect corresponds to Jensen's inequality, that the expectation of a convex function of a random variable is higher than the convex function applies to the expectation of the random variable. Here, the random variable is the exogenous given discount rate, or stochastic process of the interest rates, and the integrated assessment model acts as a convex function. In other words: DICE has convexity in the interest rates once the abatement strategy depends on the interest rate level. D (t); t ) = DC N (C • D (t); t ) := DC * ( D (t); t ) = DC Y (C • D (t); t ) := DC * ( C • D (t) Y (t)). D (t); t ) = DC N (C • D (t); t ) := DC * ( D (t); t ) = DC Y (C • D (t); t ) := DC * ( C • D (t) Y (t)
In[7] the letter C was used for consumption, which we do not reference here. Our choice to make interest rates stochastic through uncertain time preference rates is only exemplary. The interest rate is an important factor in linking present abatement cost to the avoided future damage cost. While one may introduce stochasticity in many other state variables, the use of an abatement policy adapted to the economic factors (interest rates) will already lead to all other state variables becoming stochastic. | e59ed0c8-6982-42f6-b202-fc77233fe026 | 5 |
0cfda04b-d24e-4256-916e-55192ecd3b9a | 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 | Where the car remains attractive for longer journeys, it will face competition from high-speed decarbonised rail and zero emission coaches offering affordable alternatives. Embracing new ways of sustainable travel, such as e-cycles and other emerging technologies, will create opportunities for more people to travel this way and foster new alternatives for journeys too time consuming, or too long, to previously walk or cycle. | b1244f11-6485-47b2-ba2a-c8a54f51cd77 | 76 |
0cfe4cf2-01f2-4cab-b7bb-090b645209e6 | 2,025 | [
"10.2.2020",
"motor vehicle tax",
"energy markets",
"law",
"waste management"
] | HF-national-climate-targets-dataset | Climate change and energy
o Energy Law (2018) (Official Gazette of the RM no. 96, 28.5.2018)
Climate change and energy balances
0 Rulebook on energy balances and energy statistics
Climate change and energy markets
Rulebook on the manner and procedure for monitoring the functioning of energy
markets
Climate change and energy efficiency
o Law on Energy Efficiency (2020) (Official Gazette of the RNM no. 32, 10.2.2020)
Rulebook on Marking Energy Consumption and Other Resources for Energy
Products (2016)
Climate change and renewable energy
O Rulebook on Renewable Energy Sources (2019) (Official Gazette of the RNM no. 112, 3.6.2019)
Decree on the measures for support of the electricity generation from renewable
energy sources (2019) (Official Gazette of the RM no. 29, 5.2.2019)
Decision on the total installed capacity of the preferential producers of electricity
(2019) (Official Gazette of the RM no. 29, 5.2.2019)
0
0
Decision on the national mandatory goals for the share of energy generated from
renewable sources in the gross final energy consumption and for the share of
energy generated from renewable sources in the final energy consumption in
transport (2019) (Official Gazette of the RM no. 29, 5.2.2019)
Climate change and waste
Law on Waste Management (Consultation document 2020)
O
Climate change and transportation
Law on Vehicles (2016) (Official Gazette of the RM no. 140/08, 53/11, 123/12,
70/13, 164/13, 138/14, 154/15, 192/15, 39/16)
Law on Motor Vehicle Tax (2019) (Official Gazette of the RNM no. 261/2019)
Law on Excises (Official Gazette of the RNM no. 108/19, 143/19, 225/19 and
275/19) | 16f90d59-df38-4c15-9b3e-9499d237268e | 0 | |
0d01f8c7-263c-4b17-ae1e-d955816aa27e | http://arxiv.org/pdf/2410.20982v2 | 2,024 | [
"policy",
"voters",
"climate",
"change",
"equilibrium"
] | arxiv.org | (3)
To see how a voter optimally chooses her motivated belief μ, take the derivative of AU (s, p, μ)
with respect to μ:
, then this is equal to zero, independent of s. If ∆ > 1, then κ > 1, and because κ is a belief, it must be true that κ < κ, implying that the sign of (4) is independent of κ. In particular, if this is the case, then AU (s, p, μ) decreases in μ if s > 0, and it increases in μ if s < 0. Otherwise, that is, if ∆ ≤ 1, then whether or not AU (s, p, μ) increases in μ depends on both s and the belief κ. Note that for each voter κ can be interpreted as a measure of trust in government. κ is the distribution of beliefs about the policies that will be enacted. If a voter believes that the government will always enact the policy that matches the true state, then κ = π(s, p, μ). If, however, there is little trust in government regarding policy choices, then κ ̸ = π(s, p, μ), and if trust is very low, we have κ ∈ {0, 1}. We can now derive the optimally distorted complexity of the issue climate change:
κ < κ, or s > 0 and κ > κ, and (ii) μ * = 0, if either s < 0 and κ > κ, or s > 0 and κ < κ. The lemma provides us with an important intermediate result, the optimal distortions of µ for different voters. We see that beliefs about policy only matter if severe climate change causes only moderate baseline welfare losses. Otherwise, if severe climate change leads to catastrophical welfare losses, then any signal indicating that ω = 1 will be interpreted as pure noise and hence completely ignored. To the contrary, any signal indicating ω = 0 will be accepted as a perfect indication that climate change is indeed mild, independent of the signal's strength. Finally, a voter with a signal s = 0 or a voter with κ = κ has no incentive to distort her signal's precision and hence updates her belief about ω like a perfect Bayesian. What does this imply for the beliefs about ω the voters hold? Clearly, if μ = 0, then beliefs do not change at all, and π(s, p, 0) = q. The same is true for a voter receiving a signal s = 0, which is not informative about ω. Moreover, if μ = ∞, then any signal that contains only the slightest bit of information will completely move beliefs to the extremes, and hence π(s, p, ∞) ∈ {0, 1}. Only if s ̸ = 0 and κ = κ will the belief be a non-constant continuous function of s and it equals π(s, p, µ):
We now know the beliefs of all voters as functions of their signals and of their policy belief κ. Corollary 1 shows that if ∆ > 1, and hence severe climate change has catastrophic consequences, then the equilibrium has a simple structure, and κ actually plays no roll. Voters have two different beliefs, π(s, p, μ) = 0 and π(s, p, μ) = π. What does this imply for voters' decisions at the ballot? Recall that voters vote sincerely for the alternative that they believe maximizes (1). The expected utility from policy 1 is u(p = 1) = -π(s, p, μ)∆ -(1π(s, p, μ)), while from policy 0 she gets u(p = 0) = -π(s, p, μ)(∆ + β). Hence, the voter cast her ballot for policy 1 iff
If the reverse is true, then policy 0 is strictly preferred, and if π(s, p, μ) = π, then a voter is indifferent. Clearly, 1 > π > 0. Note that by Assumption 1 we have π > q. If ∆ > 1, then voters hold two different beliefs, either π(s, p, μ) = 0 or π(s, p, μ) = π. A voter with the former belief always votes for policy 0, while the decision at the ballot of the other voter depends on q, β, as well as on the politicians' strategies ρ 0 and ρ 1 . If π > π, then these voters vote for policy 1, and as a consequence all voters vote informatively, i.e., they vote according to their signals. This means that in each state ω the policy that matches this state is chosen. If, however, π ≤ π, then a majority of voters always supports policy 0, implying it wins independent of the state. Things are slightly different when ∆ ≤ 1. On the one hand, the equilibrium just described continues to exist also when severe climate change decreases baseline welfare only moderately. In particular, this is the case if π ≤ π and κ < κ for sufficiently many s. To the contrary, if π ≥ π and κ > κ for sufficiently many s, then policy 1 wins independent of the state. Hence, when severe climate change is not catastrophic, then there might exist an equilibrium in which politicians always campaign on the policy tailored for severe climate change, independent of the true state. It follows that we cannot yet exclude that, when ∆ ≤ 1, a second inefficient equilibrium may exist. What about the efficient equilibrium, in which candidates choose the optimal policies given ω? Assume each voters wants to believe her signal and thus has κ < κ when s < 0 and κ > κ when s > 0. Then every voter votes informatively, and therefore the policy matching the state wins for all π ∈ (0, 1). Hence, if even severe climate change decreases baseline welfare only moderately, then there always may exist an equilibrium in which voters vote informatively, and hence the correct policy is chosen with probability 1. We summarize the results of this section in our next proposition:
1. | f0bf0dd6-329f-4bb1-8f1e-9d81ea8f4129 | 3 |
0d06ed99-e330-430e-af4d-c49acd51d22e | 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 | . 3.2.7.3.2.2. Types
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.7.3.3. Drive ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.8. Intake system
3.2.8.1. Pressure charger yesno 1
3.2.8.1.1. Makes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . | d3fc6859-41cb-4ee2-997b-90ebc4f9b481 | 118 |
0d0e65d3-64ed-4071-986a-fcfbb894d139 | http://eur-lex.europa.eu/legal-content/en/TXT/?uri=CELEX:31991L0676 | 1,991 | [
"Agriculture and forestry",
"Agricultural N2O",
"Energy service demand reduction and resource efficiency",
"Non-energy use"
] | eur-lex.europa.eu | 8. 1977, p. 1. (2)OJ N° L 265, 12. 9. 1989, p. 30. (3)OJ N° L 334, 24. 12. 1977, p. 29. (4)OJ N° L 335, 28. 11. 1986, p. 44. ANNEX V INFORMATION TO BE CONTAINED IN REPORTS TO IN ARTICLE 10 1. A statement of the preventive action taken pursuant to Article 4. 2. A map showing the following: (a) waters identified in accordance with Article 3 (1) and Annex I indicating for each water which of the criteria in Annex I was used for the purpose of identification; (b) the location of the designed vulnerable zones, distinguishing between existing zones and zones designated since the previous report. 3. A summary of the monitoring results obtained pursuant to Article 6, including a statement of the considerations which led to the designation of each vulnerable zone and to any revision of or addition to designations of vulnerable zones. 4. | 3bfb3caf-f010-48ac-a6b2-affa1aa11973 | 8 |
0d13ca43-1062-4b82-baab-c6fca01ffc23 | 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. MASSES AND DIMENSIONS c in kg and mm
Refer to drawing where applicable
1 Delete where not applicable there are cases where nothing needs to be deleted when more than one entry is applicable. a
If the means of identification of type contains characters not relevant to describe the vehicle, component or separate technical unit types
covered by this information document, such characters shall be represented in the documentation by the symbol.?. e.g. ABC??123??. b Classified according to the definitions listed in Annex II, Section A. c
e Where there is one version with a normal cab and another with a sleeper cab, both sets of masses and dimensions are to be stated. 28.7.2008
EN
Official Journal of the European Union
L 19929
2.6. | d3fc6859-41cb-4ee2-997b-90ebc4f9b481 | 82 |
0d1d2784-22fb-4133-8263-0c76c29d1e12 | 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 | . 3.2.8.2.1. Type air-airair-water 1
3.2.8.3. Intake depression at rated engine speed and at 100 load compression ignition engines only
Minimum allowable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . kPa
Maximum allowable
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . | d3fc6859-41cb-4ee2-997b-90ebc4f9b481 | 424 |
0d2aef34-1d01-4c85-955c-2cd808f319d9 | https://www.legislation.gov.uk/ukpga/2008/27/schedule/6/paragraph/21 | 2,008 | [
"that- e+w+n.i.",
"non - compliance",
"civil sanction",
"discretionary requirement",
"discounts"
] | legislation.gov.uk | 21 (1) Where power is conferred on an administrator by the regulations to impose a civil sanction in relation to a breach of regulations under this , the provision conferring the power must secure that- E+W+N.I. (a) the administrator must publish guidance about the administrator's use of the civil sanction, (b) the guidance must contain the relevant information, (c) the administrator must revise the guidance where appropriate, (d) the administrator must consult such persons as the provision may specify before publishing any guidance or revised guidance, and (e) the administrator must have regard to the guidance or revised guidance in exercising the administrator's functions. (2) In the case of guidance relating to a fixed monetary penalty, the relevant information referred to in sub-paragraph (1)(b) is information as to- (a) the circumstances in which the penalty is likely to be imposed, (b) the circumstances in which it may not be imposed, (c) the amount of the penalty, (d) how liability for the penalty may be discharged and the effect of discharge, and (e) rights to make representations and objections and rights of appeal. (3) In the case of guidance relating to a discretionary requirement, the relevant information referred to in sub-paragraph (1)(b) is information as to- (a) the circumstances in which the requirement is likely to be imposed, (b) the circumstances in which it may not be imposed, (c) in the case of a variable monetary penalty, the matters likely to be taken into account by the administrator in determining the amount of the penalty (including, where relevant, any discounts for voluntary reporting of non-compliance), and (d) rights to make representations and objections and rights of appeal. | 836fb353-965c-4045-94bd-66a08bc3fad2 | 0 |
0d2b4d63-c6e1-48ac-9be7-5c32336e5237 | https://cdn.climatepolicyradar.org/navigator/GBR/2024/anti-greenwashing-rule_4a7a8d8a322d714e3d698e9ab7b4a7b0.pdf | 2,024 | [
"Economy-wide",
"Greenwashing",
"Disclosure",
"sustainability",
"product",
"firms",
"must",
"label"
] | cdn.climatepolicyradar.org | • Firms must specify a robust method for measuring and demonstrating the positive impact of both the assets the product invests in and the firms’ • As with all labels, firms must have and carry out an escalation plan in cases where assets are not demonstrating sufficient progress towards the sustainability
7.1 This chapter summarises the feedback received on the naming and marketing rules which apply to products made available to retail investors that do not use one of the labels. We proposed that these products would be restricted from using any sustainability-related terms in their product names and marketing. The requirements would not apply for the purposes of disclosing factual information in the pre-contractual disclosures, consumer -facing disclosures, or any other disclosure requirements the firm Do you agree with our proposed product naming rule and prohibited terms we have identified? If not, what alternative Do you agree with the proposed marketing rule? If not, what alternative do you suggest and why? Are there additional approaches to marketing not covered by our proposals that could lead to greenwashing if 7. 3 A small minority of stakeholders – including consumer groups – agreed with our proposed approach to naming and marketing. They considered it to be a clear approach that would help consumers navigate the complex landscape and protect them from greenwashing. However, many stakeholders considered the approach to marketing in particular to be too constraining. We summarise the feedback and our response below. proposals Stakeholder feedback and our response General feedback Some stakeholders agreed with our proposals for both naming and marketing, or naming alone, as they considered it would lead to a clear investment product landscape for consumers. Some stakeholders considered the anti-greenwashing rule, Consumer Duty, existing COLL rules and the Guiding Principles as sufficient requirements for firms to accurately name and market their products and did not agree with our proposals. Those stakeholders considered the proposals could hinder consumers’ ability to differentiate between products and restrict consumer choice in products without a label. They were also concerned that firms may be discouraged from adopting sustainability-related investment approaches, firms could create other terms to describe their approaches, or that the proposals could lead to so called ’greenhushing’ (where organisations hide their ESG credentials to avoid scrutiny and regulatory requirements). They were also concerned that there may be a disconnect between regulatory disclosures (which may include those terms if integral to the investment approach) and marketing, as well as a mismatch between disclosures for retail and institutional investors, and Some stakeholders also asked us to consider the costs and timelines for updating existing products to meet our proposed requirements. We recognise the strength of this feedback. It is important that consumers can navigate the market and find the products that meet their needs and preferences. This includes products that may not qualify for or use a label, but nevertheless have some sustainability characteristics. However, firms must accurately describe the sustainability characteristics of those products. Our final naming and marketing rules and guidance aim to strike the right balance. We have made some amendments so that firms can continue to use sustainability-related terms in product names and marketing (i.e. financial promotions) if they use a label or if they meet the product name, disclosure and statement conditions outlined in the summary below, Annex 2, and Appendix 1.
proposals Stakeholder feedback and our response Naming Many stakeholders suggested that we continue to restrict the use of sustainability-related terms in product names but not marketing. Some stakeholders suggested that the terms ‘sustainable’ and ‘impact’ should be protected as they are used for labels, but that terms used to describe investment approaches like ‘responsible’ and ‘exclusions’ should not be restricted. Some asked whether terms like ‘ethical’, ‘Socially Responsible Investing (SRI)’, ‘forestry’ or synonyms to terms in our proposed list can be used. Others wanted a more comprehensive list including, for example, ‘earth’ and ‘nature’. Some also said that passive funds need to be able to use index provider’s product name in their own product, which may include The name of a product is very important. We have made some amendments that enable firms to continue using sustainability- related terms in their names if certain conditions are met. These include producing certain disclosures and a statement to clarify that the product does not use a label and why (see the summary below, We have retained the non-exhaustive list of sustainability-related terms in the Handbook as a starting point. The list includes ‘any other term which implies that a product has sustainability characteristics’. The naming rules are consistent with our Guiding Principles and anti- greenwashing rule. They specify that products using sustainability- related terms in their names must have sustainability characteristics and the name must accurately reflect those characteristics. We clarify in guidance that those characteristics should be material to the product ie, at least 70% of the product’s assets. We continue to restrict the use of ‘sustainable’, ‘sustainability’ and ‘impact’ to In the case of passive funds, fund managers could choose not to name their product after the index it tracks if it does not meet our requirements, or should satisfy itself that the index name meets the We recognise that ‘ethical investing’ is a common approach, and we want consumers to be able to identify all products that meet their needs and preferences, including where those needs and preferences may be to invest in line with their individual ethics and values. In our consultation, we clarified that values-based investing is different to investing with an aim to achieve positive environmental and/or social outcomes. However, where an ‘ethical’ investment product has and markets sustainability (environmental and/or social) characteristics, it would be in scope of our naming and marketing
proposals Stakeholder feedback and our response Marketing Many stakeholders asked for the rules to allow factual and proportionate use of sustainability-related terms in marketing. | 015f55a6-a111-41c8-aa1e-5b87f091464d | 12 |
0d30dec2-24ce-46c0-8b82-1b348f2e3921 | http://eur-lex.europa.eu/legal-content/AUTO/?uri=CELEX:32004D0280&qid=1448884592942&rid=8 | 2,004 | [
"General",
"Energy service demand reduction and resource efficiency",
"Energy efficiency",
"Renewables",
"Other low-carbon technologies and fuel switch",
"Non-energy use"
] | eur-lex.europa.eu | Important legal notice
32004D0280
Decision No 280/2004/EC of the European Parliament and of the Council of 11 February 2004 concerning a mechanism for monitoring Community greenhouse gas emissions and for implementing the Kyoto Protocol
Official Journal L 049 , 19/02/2004 P. 0001 - 0008
Decision No 280/2004/EC of the European Parliament and of the Councilof 11 February 2004concerning a mechanism for monitoring Community greenhouse gas emissions and for implementing the Kyoto ProtocolTHE EUROPEAN PARLIAMENT AND THE COUNCIL OF THE EUROPEAN UNION,Having regard to the Treaty establishing the European Community, and in particular Article 175(1) thereof,Having regard to the proposal from the Commission,Having regard to the opinion of the European Economic and Social Committee(1),After consulting the Committee of the Regions,Acting in accordance with the procedure laid down in Article 251 of the Treaty(2),Whereas:(1) Council Decision 93/389/EEC of 24 June 1993 for a monitoring mechanism of Community CO2 and other greenhouse gas emissions(3) established a mechanism for monitoring anthropogenic greenhouse gas emissions and evaluating progress towards meeting commitments in respect of these emissions. In order to take into account developments on the international level and on the grounds of clarity, it is appropriate for that Decision to be replaced.(2) The ultimate objective of the United Nations Framework Convention on Climate Change (UNFCCC), which was approved by Council Decision 94/69/EC(4), is to achieve stabilisation of greenhouse gas concentrations in the atmosphere at a level which prevents dangerous anthropogenic interference with the climate system.(3) The UNFCCC commits the Community and its Member States to develop, periodically update, publish and report to the Conference of the Parties national inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by the Montreal Protocol on substances that deplete the ozone layer (hereinafter greenhouse gases), using comparable methodologies agreed upon by the Conference of the Parties.(4) There is a need for thorough monitoring and regular assessment of Community greenhouse gas emissions. The measures taken by the Community and its Member States in the field of climate change policy also need to be analysed in good time.(5) Accurate reporting under this Decision at an early stage would allow early determination of emissions levels pursuant to Council Decision 2002/358/EC of 25 April 2002 concerning the approval, on behalf of the European Community, of the Kyoto Protocol to the United Nations Framework Convention on Climate Change and the joint fulfilment of commitments thereunder(5), and thereby enable early establishment of eligibility to participate in the Kyoto Protocol's flexible mechanisms.(6) The UNFCCC commits all Parties to formulate, implement, publish and regularly update national, and where appropriate, regional programmes containing measures to mitigate climate change by addressing anthropogenic emissions by sources and removals by sinks of all greenhouse gases.(7) The Kyoto Protocol to the UNFCCC was approved by Decision 2002/358/EC. Article 3(2) of the Kyoto Protocol requires Parties to the Protocol included in Annex I to the UNFCCC to have made demonstrable progress in achieving their commitments under the Protocol by 2005.(8) In accordance with part II, section A, of the Annex to Decision 19/CP.7 of the Conference of the Parties, each Party to the Kyoto Protocol included in Annex I to the UNFCCC is required to establish and maintain a national registry in order to ensure the accurate accounting of the issue, holding, transfer, cancellation and withdrawal of emission reduction units, certified emission reductions, assigned amount units and removal units.(9) In accordance with Decision 19/CP.7, each emission reduction unit, certified emission reduction, assigned amount unit and removal unit should be held only in one account at any given time.(10) The Community's registry may be used to hold emission reduction units and certified emission reductions generated by projects funded by the Community, thereby providing a stimulus for Community action in third countries to address climate change more widely, and may be maintained in a consolidated system together with Member States' registries.(11) The purchase and use of emission reduction units and certified emission reductions by the Community should be subject to further provisions to be adopted by the European Parliament and by the Council on a proposal from the Commission.(12) The Community and the Member States have the obligation, under Decision 2002/358/EC, to take the necessary measures to comply with their emission levels determined pursuant to that Decision. | c952e7f6-3fa4-4f03-a106-1c4a6f890d47 | 0 |
0d311930-14d7-489d-8f1f-89a8b5b2999c | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_8122f7d823bf366105239091fb57ffd2.pdf | 2,023 | [
"data",
"energy",
"emissions",
"inventory",
"environment"
] | cdn.climatepolicyradar.org | 50% (a) 47.15% HFCs 2F1 10.00% 10.00% 10.00% 10.00% Good UK data on refrigerant supply is used to tune the model of emissions for this sector, which means that there is a high confidence in the overall estimates of an activity for this sector. Good activity data helps mitigate the uncertainty in emissions, as leakage and disposal is directly HFCs 2F2 (a) 15.00% (a) 15.00% HFCs 2F3 (a) 25.00% (a) 25.00% HFCs 2F4a 5.00% 10.00% 5.00% 10.00% HFCs 2F4b (a) 10.00% (a) 10.00% HFCs 2F5 (a) 25.50% (a) 25.50% HFCs 2F6 (a) 51.00% (a) 42.00% PFCs 2B9 (a) 15.00% (a) 10.00% PFCs 2C3 (a) 20.00% (a) 20.00% PFCs 2F3 (a) 25.00% (a) 25.00% PFCs 2G2e (a) 44.50% (a) 47.15%
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 737 SF6 2G2a (a) 50.00% (a) 50.00% SF6 2G2b (a) 17.50% (a) 15.50% SF6 2G2e (a) 40.00% (a) 10.00%
UK NIR 2023 (Issue 1) Ricardo Energy & Environment Page 738 A 2.3.2 General Considerations The uncertainty parameters presented above are based primarily on expert judgment, but where • The uncertainty range presented for data (for example the confidence interval in the 2006 IPCC guidelines for default factors) • Monte Carlo Analysis of some of the more sophisticated models, most notably for agriculture, LULUCF and F-gases In some cases, the individual uncertainties for the activity data and the emission factor are difficult to separate, but the uncertainty on the total emission can more easily be estimated. | 9ce0b96e-2800-424e-bffb-cd8ba36e0902 | 119 |
0d37e3b8-c305-4b3b-873f-e6ab26474bac | http://arxiv.org/abs/2205.00133v2 | 2,022 | [
"Great Filter",
"Climate Change",
"Earth",
"Humanity"
] | ArXiv | Differentiated from BECCS, CO2 sequestered into geologic reservoirs is usually "pressurized until it becomes a liquid, and then...injected into porous rock formations in geologic basins", and this process of carbon storage, also known as tertiary recovery, plays an important part in enhanced oil recovery [53]. Other methods of storing fully oxidized carbon involve the transformation of CO2, such as "dissolving CO2 in underground water or reservoir oil", "adsorption trapping", "decomposing CO2 into its ionic components", and chemically combining and attaching these captured carbons with other underground substances by "locking CO2 into a stable mineral precipitate" [55]. Large volumes of these types of formations can be found in the U.S.'s coastal plains regions (e.g., "The coastal basin from Texas to Georgia. ...accounts for 2,000 metric gigatons, or 65[%], of the storage potential" [56], and the abundance of carbon storage capacity in geologic reservoirs can also be observed in Table 7, where the global capacity of carbon storage ranges from 5,000GtCO2 to 25,000GtCO2. Therefore, it is crucial for organizations to pinpoint the most optimal locations for such implementation, such as "mature oil and natural gas reservoirs [,] oil and gas-rich organic shale [,] uneconomic coalbeds [,] deep aquifers saturated with brackish water or brine (saline) [,] salt caverns [, and] basalt formations," [55] can help to ensure the process proceeds smoothly. One of the most obvious benefits of geologic reservoir sequestration is the improvement in atmospheric concentrations of CO2. By trapping the CO2 before it reaches the atmosphere, CO2 loading will be reduced therefore slowing down the growth rate of greenhouse gasses. This process, however, may generate a larger consumption of fossil fuels if no cleaner energy sources are broadly adopted, which leads to one of the main concerns regarding geologic reservoir sequestration -the location and transportation of CO2 as it affects the overall balance of energy and CO2. Due to the locations of most "oil sands and coal-burning electrical plants" being situated away from the suitable geological areas for carbon injection, CO2 must be transported through pipes or on trucks over long distances to be stored underground [55]. The transportation process entails extra costs and energy, and if not done carefully can emit a considerable amount of CO2 itself which undermines the strategy's intent. To put in perspective, approximately $88.90 is required to transport 1 million tonnes per annum of CO2 (MtpaCO2) over 500 miles and "assumes extra monitoring requirements for CO2 storage" [57]. In addition, an increase in energy and resource consumption can be observed through the construction and operation of such facilities, bringing further concerns both economically and environmentally to the surface. The number of carbon injections is ultimately limited to prevent increasing the probability of natural disasters such as earthquakes. Current EPA underground injection control programs, such as the (MASIP), establish regulations for carbon injections based on "calculated, testable, and well documented" pressure requirements that will prevent unintended formation fracturing which may arise during the process of injections. Other substantive risks include fracking which would potentially lead to brine water leakage and result in freshwater contamination. This, in turn, may also affect how the strategy is perceived by the government and the public [58]. As a contemporary of BECCS, geologic reservoir sequestration has been implemented in only a few instances and is still largely in its developmental stage. Some examples where geological sequestration is used include "offshore natural gas production" and to "boost production from oil fields by displacing trapped oil and gas". Similar uses of this strategy can be further adopted as the technology more fully develops (e.g., carbon transportation, pipe leakage prevention, injection methods/architectures, etc. ), increasing its carbon capture potential and reducing the costs and landmass requirements, as shown in Table 7 [59]. Geological sequestration is largely interconnected with many other mitigation technologies, so the increased implementation of others is likely to lead to an expansion of this practice as well. Throughout human history most anthropogenic soil alterations usually resulted in a degradation of up to 50% to 70% of soil carbon storage and decreased more than 840 GtCO2 of soil carbon. For example, forests were converted into farms or croplands, and farms were replaced by industrial factories or cities, etc. Therefore, soil carbon sequestration serves as a reversal process of these and other carbon-depleting practices, restoring the soil using plants best suited to the land, transforming infertile soil back to its initial generative states and re-introduces "the chemicals that inhibit the mycorrhizal and microbial interactions that store carbon" [60]. "Launched by France on December 1 st , 2015, at the COP 21," the 4 per 1000 initiative is one of the many soil carbon sequestration organizations and initiatives [61]. Intending to increase plant and soil (top 30 -40 cm) carbon absorption and storage by 4% every year through afforestation and other agroecological practices, the initiative not only hopes to improve soil carbon storage but also food security and agricultural adaptation under climate change. Other practices such as changes in agricultural methods and restoration of forests, grasslands, and wetlands can all yield increases in soil carbon storage. The main benefits brought through soil carbon sequestration are that a healthier soil obtains a stronger defense against challenges brought by climate change such as drought, flood, and heavy rainfall, and by requiring fewer fertilizers to be used, is economically, ecologically, and environmentally less of a burden, where indicated in Table 8, it demands a minimal amount of cost (cost of technique does not exceed $100/tCO2 while it is able to cost as low as $0/tCO2) and soil while capable of storing a significant amount of carbon dioxide in the soil (soil carbon storage is able to increase to as high as 130GtCO2 globally by 2100) In addition, by improving and restoring the health of the soil, afforestation and reforestation can encourage an increase in agricultural productivity. | d25fea62-8af9-4da1-a686-b2c4ae9b1f46 | 10 |
0d393734-6387-42f7-9a30-dd54d7f0ceb1 | http://arxiv.org/pdf/2506.19102v1 | 2,025 | [
"intermodal transportation",
"resilience",
"robustness",
"disruptions",
"network science",
"freight transport",
"infrastructure failure",
"climate change",
"Earth System Models",
"topology",
"tonnage",
"node removal",
"operational efficiency",
"risk management",
"logistics",
"vulnerability",
"system response",
"policy",
"sustainability",
"modeling",
"interdependencies",
"transportation networks."
] | arxiv.org | The color bar range is kept constant for comparison. Robustnessand Resilience Analysis The resilience of the transportation system is assessed by evaluating its response to various disruption scenarios. Using the FTOT dataset, we analyzed the robustness of the rail and water networks, focusing primarily on visualizing the loss of critical functionality based on closeness, betweenness centrality, degree, climate change, and random disruption, as depicted in Figure 3. TF was determined to be 84 nodes for the rail network and 47 for the water network. We quantified the robustness of our rail and water networks as they react to random and targeted disruptions. Our analysis revealed that the SCF, calculated as the ratio FF/TF, varied significantly depending on the type and severity of the disruptions. In scenarios where disruptions caused the collapse of several nodes, the SCF was notably reduced, indicating a significant impact on network connectivity and functionality. The network’s ability to reroute and maintain operations was crucial in mitigating the effects of these disruptions. We observe that node removal based on degree and dynamic centrality measures can lead to a more rapid network collapse. This is demonstrated by the targeted closeness, targeted betweenness, and targeted degree plots, which show a faster decline compared to the random and targeted hot days scenarios at Figure 3. As shown in Figure 3 (a), we assume that a loss of functionality up to 90% constitutes a complete collapse for our rail and water networks. For the rail network with a total of 84 nodes, complete collapse occurs when we lose 46% of nodes under the targeted degree scenario, 52% under targeted betweenness degree removal, 56% under targeted closeness degree removaland 87% under random removal. Similarly, for the water network), a complete collapse happens with the loss of 23% of nodes under targeted degree removal, 32% under targeted betweenness degree removal, 40% under targeted closeness degree removal and 87% under random removal of nodes. Robustness Analysis under the LOCA-Down-scaled Climate-Model Ensemble Across the eight LOCA-2 models, the qualitative ordering of disruption severity is unchanged. For the rail network, collapse to an SCF ≤ 10% occurs after 45% ± 4% of nodes are removed in the targeted sequence, with ACCESS-ESM1-5 yielding the earliest collapse and GFDL-ESM4 the latest). The water network remains more brittle: fragmentation is reached after 24% ± 3% removals). Robustness of the rail and water network to hot days based disruption is much higher and comparable to random or stochastic disruptions. | d2391652-4d7b-448b-9767-9c27112817ca | 15 |
0d3e0cfd-de9b-4cba-b719-0b8b1f511edc | https://cdn.climatepolicyradar.org/navigator/GBR/2023/united-kingdom-national-inventory-report-nir-2023_8122f7d823bf366105239091fb57ffd2.pdf | 2,023 | [
"data",
"energy",
"emissions",
"inventory",
"environment"
] | cdn.climatepolicyradar.org | This integrated approach e nsures that where better data or information (e.g. regarding local farm practices, uptake of mitigation measures) becomes available, the subsequent improvement in method accuracy to better -reflect local circumstances also ripples through all of the sub -national to This wide range of reporting and policy evidence requirements has informed the design and scope of the UK agriculture model, and indeed continues to shape the evolution of the UK agriculture model, through improvements to refine inventory data and methods in order to address ever - increasing demands for more detailed, accurate GHG and ammonia (NH3) data, at a higher level of resolution (e.g. | 9ce0b96e-2800-424e-bffb-cd8ba36e0902 | 263 |
0d414ad2-76e6-4e91-a120-b288cf809f8b | https://committees.parliament.uk/publications/30507/documents/175976/default/ | 2,022 | [
"climate",
"government",
"national",
"resilience",
"change"
] | parliament.uk | When we launched this inquiry, climate adaptation had been described as the ‘Cinderella’ of climate change, compared with climate mitigation and the path to net zero. Approaching the vital COP26 summit, we saw much-needed discussion about actions to decarbonise the UK economy and cut greenhouse emissions for the future, but little attention was paid to the effects of climate change already incurred. During the course of our inquiry, however, the UK experienced major weather events such as Storm Arwen, including extensive power outages and a knock-on effect on communications. We concluded our inquiry in the midst of an unprecedented heatwave, taking evidence from Government Ministers and officials while the country faced significant rail disruptions, flight delays and power cuts. These events have moved climate adaptation more firmly into the public eye and demonstrated that poor adaptation poses a threat to UK national security, but they have also shone a light on an alarming lack of Government action in this vital area. Readiness for storms ahead? Critical national infrastructure in an age of climate change 12 interdependencies and information- 20. On 26–27 November 2021, winds of up to 98mph battered the UK, causing significant damage and disruption. The unusual northerly winds contributed to the felling of thousands of trees, bringing down power lines in North East England and Scotland.38 Almost a million customers lost power, with nearly 4,000 suffering outages for over a week;39 twelve days after the storm, dozens of homes were reportedly still affected.40 The impact was felt in more than one CNI BT’s ongoing transition to digital phone lines, which are reliant on electricity, meant that some customers were left without access to communication, even for calls to the emergency services (see Box 3). Almost 300 military personnel were deployed to support the local response.41 21. Storm Arwen was a stark illustration of some of the dominant themes emerging from this the strong interdependencies between different CNI sectors; the cascading risks generated by extreme weather events and other effects of climate change; and the lack of anticipation by key actors (for wind coming from an unanticipated direction, for example). This chapter considers some of those issues, including the current state of collaboration, cooperation and information-sharing between different CNI sectors. Key interdependencies between CNI sectors 22. In its Third Independent Assessment, the Adaptation Committee noted that extreme weather events can create “cascading risks” that spread across sectors, “with impacts an order of magnitude higher than impacts that occur within a single sector”, and it emphasised the particular dependence of other sectors on energy supply.42 A number of witnesses also gave examples of major interdependencies between CNI sectors, highlighting the risks of cascading failures. For • The Scottish Government commented that infrastructure systems “do not operate in isolation”, 43 and highlighted the dependence on energy supply of water and wastewater treatment systems, IT infrastructure, and signalling for roads and rail.44 In turn, bridges may support cables and pipes carrying energy 38 Met Office briefing, Storm Arwen, 26 to 27 November 2021 , 2 December 2021 39 Ofgem press release, Ofgem publishes full report following six-month review into networks’ response to Storm 40 BBC News, Storm Power cut compensation posted to victims , 17 December 2021 41 Answer to UIN 125099, 1 March 2022 42 Climate Change Committee, Independent Assessment of UK Climate Risk : Advice to Government for the UK’s third Climate Change Risk Assessment (CCRA3), June 2021 43 Scottish Government written evidence ( NIC0018), point 5 44 Scottish Government written evidence ( NIC0018), point 5 45 Scottish Government written evidence ( NIC0018), point 5
13 Readiness for storms ahead? Critical national infrastructure in an age of climate change • Anglian Water noted that the water sector depends on sectors such as chemicals, communications, energy and transport for their service delivery, whilst food sectors, energy producers (such as nuclear power stations) and oil refineries depend heavily on the water sector for production, processing and cooling.46 • The UK Energy Research Centre pointed out that, as well as an increasing reliance on electricity among other CNI sectors, any disruption to telecoms could impact on other CNI sectors (including energy), because operators increasingly use mobile or internet-based means to communicate with their staff.47 In addition, energy, water and IT infrastructure are often co-located, meaning that weather- related power cuts can affect multiple sectors simultaneously.48 23. Professor Jim Hall, Professor of Climate and Environmental Risks at the University of Oxford, told us that individual operators understand their own networks “pretty well”, but have a “less clear picture” of the networks upon which they depend.49 In Box 3, we outline the impact of Storm Arwen on BT’s ‘Digital Voice’ programme, which caused major communication disruptions for customers. Our survey respondents also described a number of recent near-misses and interdependencies. For • A power station told us that it relies on water abstracted from a local canal, which fell below the required water level in 2021, reducing operations for two to • A water company reported that Storm Arwen led to power being lost from 140 wastewater sites, along with water treatment assets serving 17,500 properties, which were left without water. • An energy company reported that the ‘Beast from the East’ in 2018 caused significant travel disruption, meaning that its engineers had trouble visiting gas sites to deal with technical faults. 24. Some interdependencies are less obvious, and thus more difficult to predict. Perhaps the most alarming ‘near miss’ that we encountered during this inquiry was the near- flooding of the National Blood Bank, which was highlighted by Network “[…] there is a limit to what individual organisations or sectors can do to manage more strategic risks. For example, the recent failure of one of our drainage systems nearly caused the National Blood Bank to flood . | 43237e88-37c1-47c7-8205-9b4d15852705 | 5 |
0d416e09-a846-4190-bec1-abf44bf228a2 | http://arxiv.org/pdf/2111.00987v1 | 2,021 | [
"electricity",
"model",
"market",
"energy",
"learning"
] | arxiv.org | In addition, what would the effect be of a market cap on such electricity markets? Would a market cap reduce the ability for Generation Companies (GenCos) to inflate electricity prices artificially? Chapter 6 investigates this issue. We find that if a generator company, or group of colluding generator companies own over 11% of the total generation capacity, electricity prices start to increase. However, the impact of this market power can be limited through the setting of a market cap. In the case of the UK, a market cap of £190/MWh suffices. Through these questions we not only answer whether AI and ML methods can be used with electricity market agent-based models, but also what is the wider impact of the behaviours on the market. Primarily, in this work, simulation is used as a tool to better understand and make projections for electricity markets. Specifically, in this thesis, the agent-based modelling paradigm is used. This enables us to model generator companies as individual agents, with heterogeneous strategies and characteristics. These agents have access to imperfect information and imperfect foresight. This methodology differentiates this work from the traditional centralised optimisation approach. Agent-based models are critical to model the behaviour of individual actors within an electricity system. Without this distinction, the system must be modelled as a homogenous system, which does not accurately reflect the real world. Through this approach, we hope to learn that it is possible to accurately model the UK's national electricity system with an agent-based approach. Machine learning and statistical techniques are used to make short-term forecasts of electricity demand. We use both deep learning, offline learning and online learning to further improve our methods. Online learning is a machine learning approach which utilises new data to update model weights, and does not require the model to be completely retrained, which is the case for offline learning. In comparison, deep learning utilises neural networks with many different layers. We utilise these methods due to their data-driven approach and strong ability to forecast time-series data. Online learning is used as over the time-periods with which we are forecasting, the underlying time-series changes in structure. Online learning is able to continually use new data points to retrain the model. Deep learning, on the other hand, uses many layers to learn more complex patterns from the training set. Through taking this approach, we hope to learn that it is possible to improve predictions for energy demand data when compared to the traditional machine learning methods. Once our simulation model is built, we are able to answer different questions using several approaches. For example, we perturb the exogenous electricity demand by the error distribution generated by the aforementioned electricity demand forecasting methods. This provides an insight into how small errors can have large impacts on long-term electricity markets in terms of both investments made and generator utilisation. This approach was taken due to its ability to mimic the behaviour of generator companies in a simple manner. We hope to learn what the impact of short-term decisions are on the long-term market. Multi-objective genetic algorithms are used to explore carbon tax policies which will reduce both carbon emissions and average electricity price. We find that we are able to achieve both of these goals by setting a median carbon tax of ∼£200 per tonne of carbon dioxide. This methodology is chosen due to the genetic algorithm's distributed nature. We are able to run the algorithm in parallel and reduce training time significantly. From this, we hope to learn that there is an automatic method to reduce the search space for policy makers when coming up with complex policy in a high parameter space. Finally, we explore the ability for deep reinforcement learning (DRL) to make strategic bidding decisions within a day-ahead electricity market. This work enables us to see the proportion of capacity that must be controlled to artificially inflate the electricity price in the market using market power. Deep reinforcement learning was chosen due to its ability to quickly form a policy on the expected environment. The bidding environment with multiple competing agents is highly complex and difficult to solve through a rule-based approach, and so DRL is chosen to simplify the approach of forming a policy. Through this, we hope to learn the parameters which allow for the manipulation of the market, such as the size of generator companies and total capacity controlled, and how to reduce this impact of it occurs. The work in this thesis makes a number of key contributions:
1. Development of the open-source, generalised long-term agent-based model for decentralised electricity markets, ElecSim [129]. This can be accessed at: https://github.com/ alexanderkell/elecsim. This model is parametrised to the UK electricity market, and contains the major pertinent features to model this market. This answers research question 1 by modelling an electricity market over the long-term. 2. Validation of the aforementioned model through the use of cross-validation through five years and comparison with the established UK Government model until 2035 [134]. Through this validation we are able to answer research questions 2 and 3 by modelling the inter-year variability and verify the outputs of the model. 3. Forecasting of electricity demand using machine learning models and exploration of the impact of the prediction errors on the long-term electricity market [131]. This contribution answers research question 4 by showing that short-term errors do have a large impact on the final electricity mix. 4. Optimisation of a carbon tax policy to reduce electricity cost and carbon emissions for the UK electricity market using a multi-objective genetic algorithm, from the perspective of a benevolent government [135]. This answers research question 5 by showing that it is possible to come up with an optimal strategy for setting a carbon price to reduce carbon emissions and electricity price. 5. Exploration of the long-term impact of strategic bidding and collusion on decentralised electricity markets [133]. This answers research question 6 by showing that if generator companies control a large part of the market, market power occurs. | d602c796-019d-4603-b326-d7f62c6a33dd | 1 |
0d47e8f2-8f66-4048-87d9-827e8e8176e8 | http://arxiv.org/abs/2403.06025v3 | 2,024 | [
"similar deep learning problem",
"deep brine aquifers",
"important emissions reduction technology",
"fluid flux q = /p",
"prof. ronaldo borja"
] | ArXiv | The dataset includes two parts as the static model and the transient model. The input dataset are 2D geometries of geological layers , which consists of two heterogeneous materials as the hard rock with high permeability and soft shale with low permeability; and the label is surface displacement contour under specific loading. The geometries are sampled according to the real underground stratum. The size of the domain (length and width of the rectangle), the thickness, and the depth of shale layer is fixed, while the variable is the dip angle of shale layer. The data of surface displacement field is generated from simulation results in FEniCS (an open-source computational platform using Finite element Method (FEM)) [2]. The model setting used in the problem is depicted in The geometries are generated as the input of machine learning model by PIL.draw modulus, and are depicted in the Fig. 1, labeled as input image. The material characteristics of the shale and rock are distinct, thus different layout of the material will yield different results. We generate 10000 groups of data by sampling the dip angles from 0 to 45 uniformly for the training purpose. Different dip angles correspond to specific geometries, which impact the result of displacement.We split the entire dataset with 95% for training and 5% for validation. Next, we generated 5% of new samples for testing. We consider vertical displacement u y as the label, which is defined on each vertices of the finite element mesh [10], and can be considered as the displacement at points uniformly sampled over the domain. The vertical displacement (u y ) corresponds to the upheaval of the stratum. The FEniCS program provides the following API: Layout of problem = u y across the domain (1) As for the labels (ground truth), we use a numpy 1D array to store the vertical displacement of 1250 points from a uniform 50 x 25 points sampled over the domain. The dataset is demonstrated in Tab. 1. For the mathematical interpretation, refer to the Appendix A. Based on the static model, the next problem we deal with is the coupled hydro-mechanical simulation, which takes the pressure of fluid into account to better simulate the real situation. The coupled hydro-mechanical simulation is widely applied in the industry, and is well-known for dealing with consolidation case, which is a transient (time-dependent) problems. We use the same kind of geometry as what we generated for the static case, but employ another set of equations to simulate the physics process. The mathematical interpretation can be found in Appendix A. In the static case, we calculate one step of displacement across the domain, given one input geometry. However, the transient simulation will yield multiple images at different time steps given one single geometry. In addition, we focus on the vertical displacement on the ground, which is the interest in industry. In this project, we sample 40 points on the ground surface, and capture their vertical displacement. The dataset is illustrated in Tab. 2. To further prepare the data for the time series prediction model, we conduct the min-max scaling for the data by Also, we create the data sequence for the transformer and LSTM model later by using continuous five data points to predict the next data point, like where each u y,t represents a 1D array with size of 40. We adopt sliding windows to generate the sequence, thus generating 89400 pieces of displacement sequence. Similarly, we split the dataset with 95% for training, 5% for validation, and generate new samples (5%) for testing. In this project, we deal with two different computational problems, the static mechanics and the transient mechanics. We developed three models, which includes a well-designed combination of ResNet and UNet model to predict the static displacement, and the LSTM and transformer model that base on the pretrained ResNetUNet model. We are motivated to start from CNN models by literature [18], and further test ResNet and UNet from a similar deep learning problem to handle heterogeneity in input images [8]. The CNN and ResNet network reduces the dimension of images layer by layer. It loses information while collecting important features from input. Meanwhile, the deep neural network constructed by the ResNet can be utilized to decode the physical Eq. 6, which is a complicated procedure. Additionally, the heterogeneous distribution of material impacts the final result considerably. Inspired by the segmentation in computer vision [19], we use UNet to capture the heterogeneous distribution of the pixel/material. As the baseline model, we use the most basic CNN model, using continuous layers of convolution blocks which comprises a conv2d, BatchNorm2d and relu. Finally, we flatten the convolution to get a fully connected layer with 1250 dimensions for output. For the other baseline model, ResNet, we use the resnet18 model in Pytorch and modify the last layer to have the convolution with width, height and channel as 50 x 25 x 1, which will be flattened as the fully connected layer afterwords. ResNetUNet is the model designed by ourselves to solve the current problem. Compared to the conventional UNet [19], we modify the encoder part by using the ResNet for downsampling the image to better capture the physical equations. The upsampling is the same as the traditional UNet [34]. The architecture of the ResNetUNet is illustrated in the where m is the number of examples. Note that we use the MSE for the loss function, but use both MSE and maximum absolute error (MAE) for the evaluation metrics. In this part, we use both the LSTM and transformer to predict the evolution of vertical displacement, the interest in industry, given the specified material distribution as an image. We adopt two models, LSTM and transformer, to perform the task, which is similar to an image caption work [24,16], except that we use the displacement as the sequence rather than the words embedding. The combination of CNN and LSTM have been proved effective for the image caption work [24]. | 2fb7bf7b-1cc7-41eb-b10a-8e8e89307c34 | 1 |
0d4a1be9-c81c-4bab-bd93-4f6093285873 | 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 | The effect of annual temperatures can produce large inter-annual variations. Fuel consumption data since 1990 indicates a general trend in fuel switching in these sectors, away from more carbon-intensive fuels such as coal, coke, fuel oil and gas oil, towards natural gas. | 95866fde-5b53-4214-b279-97a1078c466c | 233 |
0d53550e-732a-4c6a-9cb8-98175eb62f58 | 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 | 3.6.3. A vehicle family, as defined in point 3.6.1, may be approved with CO2 emission and fuel consumption data that
are common to all members of the family. The technical service shall select for testing the member of the family
which the service considers to have the highest CO2 emission. The measurements shall be performed as described
in Annex XII, and the results according to the method described in section 5.5 of UNECE Regulation No 101 shall
be used as type-approval values that are common to all members of the family. Vehicles that are grouped in a family as defined in point 3.6.1 may be approved with individual CO2 emission and
fuel consumption data for each of the family members. The technical service shall select for testing the two vehicles,
which the service considers to have the highest and the lowest CO2 emissions respectively. The measurements shall
be performed as described in Annex XII. If the manufacturers data for these two vehicles falls within the tolerance
limits described in section 5.5 of UNECE Regulation No 101, the CO2 emissions declared by the manufacturer for
all members of the vehicle family can be used as type-approval values. If the manufacturers data do not fall within
the tolerance limits, the results according to the method described in section 5.5 of UNECE Regulation No 101
shall be used as type-approval values and the technical service shall select an appropriate number of other family
members for additional tests. 4. CONFORMITY OF PRODUCTION
4.1. | d3fc6859-41cb-4ee2-997b-90ebc4f9b481 | 58 |
0d579414-5e06-4aa9-bcb9-3923759c4c53 | http://arxiv.org/pdf/1912.10774v4 | 2,019 | [
"model",
"arctic",
"climate",
"models",
"statistical"
] | arxiv.org | In section 2, we introduce a linear statistical trend model and use it to produce long-range sea ice point forecasts. In section 3, we introduce the "shadow ice" concept to account for the zero-ice lower bound. In section 4, we generalize to a nonlinear (quadratic) statistical model and to interval forecasts that incorporate several forms of uncertainty. In section 5, we compare our statistical model forecasts to global climate model forecasts with particular attention to hard versus soft landings at zero ice. In section 6, we make probabilistic assessments of several sea ice scenarios. We conclude in section 7. Arctic sea ice has been continuously monitored since 1978 using satellite-based passive microwave sensing, which is unaffected by cloud cover or a lack of sunlight. For a polar region divided into a grid of individual cells, the satellite data provide cell-by-cell brightness readings, which can be converted into fractional ice surface coverage estimates for each cell. Sea ice extent, SIE -a very commonly-used measure of total ice area -is the total area of all cells with at least 15 percent ice surface coverage. That is, SIE rounds down cells with measured coverage of less than 15 percent to zero and rounds up cells that pass the 15 percent threshold to full coverage. The up-rounding in SIE is effectively a useful bias correction, as melting pools on summer ice surfaces can be mistaken for ice-free open water. For this reason, we follow common practice and use monthly average SIE data from November 1978 through October 2019 from the National Snow and Ice Data Center (NSIDC). 3 The NSIDC data use the NASA team algorithm to convert the satellite microwave brightness readings into measured ice coverage (Fetterer et al., 2017). 4,5 Figure 1 plots the time series of Arctic SIE -each monthly average observation is a dot -with an overall estimated linear trend superimposed. The clear downward trend is accompanied by obvious seasonality. A more subtle feature is the possible time variation in the seasonal effects, which may be trending at different rates and possibly nonlinearly. These effects turn out to be of interest in a complete statistical representation of sea-ice dynamics. A simple initial representation to capture this variation is a linear statistical model with twelve intercepts, one for each month, each of which may be differently trending, and potentially serially correlated stochastic shocks:
where the D i 's are monthly dummy variables (D it =1 in month i and 0 otherwise, i=1, ..., 12) and T IM E is a time dummy (T IM E t =t). 6,7 We estimate model (1) -and other versions below -by maximizing the Gaussian likelihood. Detailed regression results for model (1) are in column (6) of Table A1 in Appendix A. Figure 2 shows the resulting linear trends for all twelve months, highlighting March in blue and September in red. All of the monthly trends slope downward -an indication of a warming climate -and are highly significant. The slopes of the linear trends also differ across months (Serreze and Meier, 2019;Cavalieri and Parkinson, 2012). In particular, the seasonally lowice months of July through October have notably steeper downward sloping trends than the seasonally high-ice months of December through May. The estimated September trend, for example, is twice as steep as the March trend, and the difference is highly statistically significant. These linear trends are also extrapolated out of sample (shaded gray) through the end of the century. For example, September sea ice extent is projected to reach zero just after 2072. Such linear point forecasts are a useful first step, but they can be improved by allowing for nonlinearity in the trends and by quantifying forecast uncertainty -as described in section 4. First, however, we elucidate a "shadow ice" modeling approach that takes into account the fact that the measured amount of sea ice is bounded below by zero. One consideration for downward trending statistical models for Arctic sea ice is that the measured amount of sea ice will always be non-negative. By contrast, extrapolations of simple trend models will eventually push into negative territory. There are various functional forms that can be used to model such bounded time series, and the appropriate representation depends very much on the details of the real-world phenomenon under examination. 8 Some bounds act like reflecting barriers, so the variable of interest spends very little time at the constraint. Other bounds are absorbing states, and once reached, they may be sustained for some time. With positive amounts of sea ice, fluctuations in SIE can serve as a rough approximation for changes in the amount of thermal energy in the Arctic; that is, hotter and colder ocean surface temperatures are reflected in less or more ice, respectively. 9 However, this connection 8 One modeling approach is to rescale the bounded time series data to the real line using, say, a log-ratio transformation (Wallis, 1987). Alternatively, a time series can be modeled in the original bounded sample space using, for example, the beta autoregressive model of Rocha and Cribari-Neto (2008). By contrast, some physical science analyses simply terminate model simulations when zero ice conditions are reached, as in Obryk et al. (2019). 9 The amount of sea ice depends on a variety of factors including ocean and air temperature, ocean salinity, cloud cover, and wind, current, and wave action. However, several studies have identified ocean heat content as a major driver of sea ice coverage, notably, Arthun et al. (2012), Schlichtholz (2011), andSelyuzhenok et al. (2020). breaks down when the ice disappears: While SIE is fixed at zero, the surface temperature of the Arctic ocean can continue to warm. Furthermore, the warmer the ocean becomes, the less likely there will be a quick return of sea ice, which is indicative of a partially-absorbing state. 10To account for this effect, the negative values of sea ice produced by a statistical model can be viewed as a rough expression of ocean temperature. | 73022bbb-9f75-4f9b-ad93-5cc4d613aaf4 | 1 |
0d57ef58-ab7b-4875-8d50-645050e74b69 | 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 | And emissions from car and van use is the largest component of total transport emissions. Depending on progress in the sector at some points this may require additional targeted action (such as steps to reduce use of the most polluting cars and tackle urban congestion) to enable these targets to be met. | 8f0273a5-decd-4a43-ab49-4f3473699e66 | 213 |
0d5a6818-0524-48a4-b825-f80392a6fed2 | https://www.gov.uk//guidance/the-energy-labelling-of-products | 2,014 | [
"Energy labels",
"UK",
"Great Britain",
"Northern Ireland",
"EU",
"Energy Information Regulations 2011",
"Energy efficiency",
"Product compliance",
"Suppliers",
"Dealers",
"Eco-design regulations",
"Re-scaled energy labels",
"A-G energy rating",
"Light sources",
"Product marketing",
"Market surveillance",
"OPSS",
"Advertising Standards Authority",
"Non-compliance",
"Energy usage",
"Consumer information",
"Packaging",
"Distance selling",
"EPREL database",
"Enforcement policy",
"Guidance",
"Compliance",
"Product safety",
"Energy efficiency class",
"Retailers",
"Imports",
"Marketing."
] | gov.uk | Further requirements
If, at the point of sale, a product model is only displayed in the packaging not taken out of the packaging for display the dealer must ensure visibility of the label for the consumer. Requirements for all energy labels
The energy label is common across the UK, with variations according to GB or NI placement on market, and must include
From 1 January 2021 the energy label, for products placed on the GB market, must also include
GB energy labels can be accessed using the Create an energy label service. To help you comply with the regulations there is a UK Energy Label Generator. This covers all the products listed under the What is Covered section. From 1 January 2021, the energy label, for products placed on the NI market, must include
Suppliers placing products on the NI market can create their own energy labels using the EPREL database. The role of the Office for Product Safety and Standards OPSS
OPSS is the appointed Market Surveillance Authority in Great Britain and Northern Ireland for suppliers. Local authorities are responsible for enforcing the regulations in relation to dealers. The Advertising Standards Authority ASA is responsible for enforcing the marketing of products with energy efficiency information. Our approach to addressing non-compliance by those we regulate is set out in our Enforcement Policy, which should be read alongside guidance on the specific enforcement actions available to us under the regulations, and associated rights to make representations or appeal. Read our Enforcement Policy
Read our guidance on enforcement actions and associated rights
Where to find out more
If placing products on the market or making products available on the market in Great Britain
This gives guidance for dealers
Guidance on how to describe a products energy efficiency class ASA
If placing products on the market or making products available on the market in Northern Ireland
Contact us
If you have a specific enquiry about compliance or wish to contact us regarding suspected non-compliance please email OPSS.enquiriesbusinessandtrade.gov.uk. | d18197e6-eed0-4a40-b5f5-839cf81e4741 | 1 |
0d5fb60a-aa19-4678-a01a-00a8aaa9f10b | http://arxiv.org/pdf/2503.18433v1 | 2,025 | [
"West Nile Disease",
"WND",
"Risk Assessment",
"Probabilistic Approach",
"Spillovers",
"Compartmental Model",
"Differential Equations",
"Pathogen Spillovers",
"Forecasting",
"Long-term Forecasts",
"Short-term Forecasts",
"California",
"Orange County",
"Los Angeles County",
"Kern County",
"California Department of Public Health",
"2022-2024",
"Prediction Accuracy",
"Logarithmic Scoring",
"Predictive Models",
"Global Warming",
"High-risk Days",
"Epidemic Severity",
"Disease Transmission",
"Data Analysis",
"Model Validation",
"Effectiveness"
] | arxiv.org | Lastly, the method is applied to explore the impact of global warming on spillover risk, revealing an increasing trend in the number of high-risk days and a shift toward a greater proportion of these days over time for the onset of the disease. 1 Introduction
The first recorded case of WND in the United States was observed in 1999 in New York. Over time, disease became a major public health issue in many states in the United States, causing both health risks and economic losses. The increasing prevalence of the disease led to increased investment in mosquito control programs and the implementation of widespread public health campaigns to mitigate its impact. Consequently, since 1999, authorities in the United States have mainly been concerned with assessing the various aspects of the risk of WND to the human population. The West Nile virus is transmitted primarily by mosquitoes, the main vector species belonging to the Culex family. The disease’s mechanism of spread relies on interactions between mosquitoes and birds, with occasional transmission to humans as spillover cases. Mosquitoes and birds can mutually infect each other, while mosquitoes serve as the only agents that transmit the infection to mammals. In particular, mammals cannot infect mosquitoes and act as dead ends of the A PREPRINT - MARCH 25, 2025
Significant work has been done on the risk assessment of West Nile disease, focusing on various aspects and parameters. For example, focused on various types of mosquitoes to determine which species significantly affect the transmission of WND to the human population. This work proposed a measure based on the abundance, prevalence of infection, vector competence, and bite behavior of vectors. assessed the effect of climate and climate change on the risk of spreading of WND using a comprehensive set of species distribution models. For this work, CDC information on the West Nile virus (WNV) about vectors, birds, and humans, along with climate data, have been used to predict the future of the disease in different climate scenarios. used a localized Knox test to identify areas of high risk for WND in New York City. used a mean random forest (RF) model to assess the influence of climate parameters on the geographical pattern of (WNV) in the USA. In addition, used two risk models, one environmental and the other spatial-environmental with fuzzy logic, to assess the risk and concluded that the spatial-environmental model is the most useful for predicting the location of the outbreak. For network base works, Das et al. proposed a model to simulate and predict spillover dynamics across interconnected networks, emphasizing the level of interconnection as a critical factor. Using the FastGEMF framework, developed by Samaei et al., for efficient simulation of mechanistic models over multilayer networks, they explored the spillover as a function of the connections between human and animal networks. Their findings demonstrated how these interconnections influence transmission processes, providing valuable insight into the dynamics of networked systems. However, these insights are most beneficial when detailed information about reservoir and host networks is readily available. | 414fcd1c-22ea-4154-8429-039e9228171c | 1 |
0d62cab7-4ed1-4bba-991b-78101eb41f66 | 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 U K g overnment is committed to fostering growth in these markets in
a way that is high-integrity, unlocks truly additional finance for net zero, and takes advantage of the synergies between carbon and other ecosystem services, such as biodiversity, water or flood mitigation, to unlock additional investment in nature. 3.4.1 Voluntary carbon markets 90. Voluntary carbon markets (V C M s) enable carbon credits to be purchased, usually by organisations, for use against voluntary climate commitments, as opposed to legally binding emissions reduction obligations. V C M s have grown rapidly in recent years from around $300 million in 2019 to $2 billion in 2021174, fuelled by an increase in net zero commitments made by non-state actors. Further progress was made at COP 2 6, including through agreement on the framework and rules for international carbon trading under Article 6 of the Paris Agreement. 91. Financial institutions and other stakeholders have highlighted a number of challenges that could prevent V C M s from reaching their potential. These include the need for clarity on what constitutes a good quality credit, how credits should be used when claiming the achievement of private sector net zero targets, relevant disclosure and assurance processes, the need for common international standards and principles, and the need for clarity on a range of regulatory matters. Whilst it is important that the market is able to innovate, there is a clear appetite for U K g overnment action to ensure the market grows in a manner that provides assurance on integrity. This includes considering targeted regulatory interventions where these will help the market play a greater role in the transition to net zero and ensure companies are not incentivised to use credits as an alternative to taking action on their own 92. More is needed to build international consensus on V C M s, including their interactions with Article 6. The Voluntary Carbon Markets Initiative (V C M I ) and the Integrity Council on Voluntary Carbon Markets (V C M I ), created through international multistakeholder processes during the U K ’s COP 2 6 Presidency, are striving to tackle many of these challenges by providing greater clarity on the definition of high-integrity V C M s. Both initiatives will publish their guidance this year; the U K g overnment will consider the potential for their outputs to serve as a basis for international best practice on market integrity, and the extent to which they could be incorporated within relevant regulatory regimes, including through the consultation set out in section 3.4.3. The U K g overnment has confirmed its intention to position the U K a s a global hub for trading in voluntary carbon markets, and is grateful for the work of the U K V C M F orum and its chair, Dame Clara Furse, to this end. 93. Nature markets enable farmers and natural resource managers to sell carbon and other ecosystem services – the benefits provided by nature – through sustainable management and nature restoration projects. Nature markets may be voluntary or driven by regulatory obligations. They include V C M s such as the U K W oodland Carbon Code and U K P eatland Code, and other emerging nature markets such as Biodiversity Net Gain in England. Further opportunities exist in markets still in development such as
94. Nature markets need to grow rapidly to attract investment at the scale required to achieve our net zero and environmental targets. The U K g overnment is committed to supporting the development of markets for carbon and other ecosystem services in the U K , guiding, and stimulating demand while also ensuring that they build trust 95. We are supporting market participants to develop and converge around common, trusted standards and processes which will ensure integrity. With the right policy guardrails, the growth of nature markets can represent a triple delivering for the climate and the environment; providing vital revenue streams to finance farm businesses and nature recovery; and enabling responsible firms to meet their net zero and environmental obligations and commitments transparently and efficiently. 96. As announced at Budget 2023, the U K g overnment is exploring elements of the tax treatment of ecosystem service markets and environmental land management. This includes a call for evidence published on the 15 March 2023 on the tax treatment of the production and sale of ecosystem service units. The aim is to understand the commercial operations and the areas of uncertainty in respect of taxation. The Peatland Code and U K S altmarsh Code are voluntary certification standards for U K p eatland restoration projects, providing a consistent approach for projects wishing to attract carbon finance. We recently funded the International Union for Conservation of Nature (I U C N ), U K C entre for Ecology & Hydrology (U K CEH) and the James Hutton Institute to expand the Code to a significantly larger area of England’s peat. This will help facilitate more private investment into peatland restoration. 97. We are also supporting innovation to develop and pilot new nature markets. Our Natural Environment Investment Readiness Fund (N E I R F ) is supporting the development of 86 nature projects across England to generate revenue from nature markets and operate on repayable private sector investment. Projects will either monetise the benefits of nature or develop tools or standards to help others to do so. We will consider options for continuing our investment readiness support for nature projects beyond the current iteration of the N E I R F , drawing on the results of an independent evaluation of the programme. Box 29: Supporting farmers to participate in nature markets As custodians of over 70% of U K l and, farmers will be key to the success of nature markets, and we are committed to ensuring they can access these markets. | 56ee4d88-2ab4-4059-810e-e3d833392a95 | 42 |
0d6b8c67-9ed8-4aa9-b882-38a486d83f53 | 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 | Forest land - 13,992.50 - 13,992.50 - 14,533.82 - 15,009.88 - 15,406.14 - 15,394.24 - 15,494.45 - 15,968.62 - 16,091.74 - 16,547.76 - 16,667.49 - 16,873.56 - 17,360.36 - 17,659.70 - 17,835.42 - 18,253.24 - 18,528.70 - 18,830.18 - 18,915.42 - 19,522.03 - 19,706.04 - 19,583.74 - 19,354.46 - 18,430.17 - 18,593.20 - 18,742.79 - 18,182.76 - 18,386.03 - 18,413.32 - 18,205.86 - 17,942.70 - 17,933.72 28.17
8th National Communication Annex 2: Common Tabular Format Tables (CTF) supporting the UK’s fifth biennial report to the UNFCCC 486 Base yeara 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Change from B. Cropland 15,947.46 15,947.46 15,942.08 15,912.08 16,059.05 16,041.26 16,235.51 16,111.18 16,076.21 16,024.66 15,963.97 15,833.29 15,676.94 15,590.81 15,465.00 15,330.79 15,153.66 15,125.10 14,920.31 14,733.19 14,954.89 14,882.77 14,804.09 14,811.55 14,650.40 14,570.75 14,456.89 14,514.05 14,472.92 14,389.97 14,375.78 14,403.93 - 9.68 C. Grassland 114.65 114.65 41.31 - 82.47 - 241.94 - 417.87 - 440.78 - 625.75 - 745.56 - 847.94 - 306.12 204.27 223.66 47.38 12.45 - 323.73 - 357.00 - 449.83 - 402.12 - 534.75 - 621.62 - 694.66 - 1,095.53 - 1,105.57 - 1,206.80 - 1,139.01 - 1,589.96 - 1,404.16 - 1,572.71 - 1,746.08 - 2,003.48 - 1,873.95 - 1,734.43 D. Wetlands 571.12 571.12 601.05 555.25 539.46 648.48 736.77 622.71 551.07 421.80 548.40 613.72 654.30 457.19 709.44 554.41 626.38 662.69 551.85 539.74 579.08 621.10 588.08 565.51 658.55 505.07 1,201.97 567.46 546.93 920.67 1,297.05 605.99 6.10 E. Settlements 5,427.63 5,427.63 5,324.15 5,222.83 5,128.42 5,041.20 4,959.40 4,821.80 4,806.37 4,681.85 4,590.99 4,350.47 4,174.74 4,096.21 4,132.54 4,195.18 4,158.48 3,923.65 4,056.09 3,900.74 3,787.08 3,906.49 3,804.24 3,740.48 3,668.31 3,561.44 3,580.55 3,966.16 3,829.33 3,968.26 3,984.85 4,032.04 - 25.71 F. Other land NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO 0 - 2,087.72 - 2,087.72 - 1,889.00 - 1,926.34 - 1,973.33 - 2,215.95 - 2,276.69 - 2,217.53 - 2,395.28 - 2,288.00 - 2,522.19 - 2,776.41 - 2,622.44 - 2,580.97 - 2,707.28 - 2,502.47 - 2,408.54 - 2,150.57 - 2,270.64 - 1,969.48 - 1,891.70 - 2,095.05 - 2,316.17 - 2,920.79 - 2,569.69 - 2,480.93 - 2,906.63 - 2,591.27 - 2,381.63 - 2,238.40 - 2,300.94 - 2,128.72 1.96 H. Other NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE NO, IE 0 5. Waste 1,360.37 1,360.37 1,329.20 1,324.70 1,275.35 1,082.40 1,050.80 1,056.30 649.22 654.09 604.63 631.27 567.14 552.43 536.98 519.27 465.53 313.42 386.60 334.24 304.14 290.03 266.07 263.86 263.38 270.01 245.63 263.83 258.10 241.11 243.14 248.95 - 81.70 A. Solid waste disposal NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE 0 1,360.37 1,360.37 1,329.20 1,324.70 1,275.35 1,082.40 1,050.80 1,056.30 649.22 654.09 604.63 631.27 567.14 552.43 536.98 519.27 465.53 313.42 386.60 334.24 304.14 290.03 266.07 263.86 263.38 270.01 245.63 263.83 258.10 241.11 243.14 248.95 - 81.70 E. Other NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO 0 International bunkers 24,271.88 24,271.88 23,987.36 25,817.51 26,756.47 26,912.98 28,631.21 30,721.38 32,971.80 36,130.45 36,080.40 38,126.52 37,985.43 36,536.46 36,957.92 40,906.76 43,570.54 45,004.79 44,967.76 47,693.09 45,671.34 43,009.11 45,320.48 43,027.91 43,312.38 44,117.70 43,749.72 44,595.87 46,669.25 46,704.01 46,190.59 22,817.39 - 5.99 Aviation 15,392.61258 15,392.61258 15,151.13816 16,769.70702 17,961.11181 18,758.25802 19,963.32607 21,122.58417 22,466.32019 25,009.11215 27,170.22041 29,980.48 29,198.49 28,660.43 29,358.69 32,180.37 34,747.24 35,275.46 35,103.77 34,330.90 32,523.26 31,451.57 32,930.19 32,071.32 32,354.06 32,592.05 33,098.22 33,323.04 35,882.01 36,264.49 36,444.45 14,343.23 - 6.82 Navigation 8,879.26932 8,879.26932 8,836.22043 9,047.80088 8,795.36195 8,154.72492 8,667.88309 9,598.79686 10,505.47796 11,121.33823 8,910.18072 8,146.05 8,786.94 7,876.03 7,599.23 8,726.39 8,823.31 9,729.32 9,863.99 13,362.19 13,148.08 11,557.54 12,390.30 10,956.59 10,958.32 11,525.65 10,651.50 11,272.83 10,787.24 10,439.52 9,746.14 8,474.16 - 4.56 Multilateral operations NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE NE 0 3,849.142767 3,849.142767 3,930.250609 4,251.634337 4,369.654477 6,161.591412 6,553.476469 6,701.947266 6,070.029874 6,786.437896 7,006.623875 6,830.16 7,131.89 7,754.54 8,812.42 10,137.71 11,702.42 12,404.83 12,331.96 14,568.70 16,130.08 18,298.02 18,902.84 19,474.32 23,108.75 27,599.46 32,830.32 34,606.10 36,788.06 42,024.79 45,640.49 47,197.54 1,126.18 CO2 captured NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO NO 0 Indirect CO2 (3) NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE NO, NE 0 602,652.0784 602,652.0784 610,098.9537 594,499.0571 580,276.8227 574,683.2411 566,852.1959 587,450.9062 563,386.5771 569,237.7831 562,344.3012 569,744.21 578,698.60 561,014.63 572,373.66 574,200.86 571,126.89 568,698.07 560,512.74 545,791.87 494,923.49 512,736.34 470,509.12 488,176.36 478,311.00 439,505.39 423,162.94 400,145.84 388,085.92 380,444.86 365,468.41 326,920.69 - 45.75 608,632.7334 608,632.7334 615,584.7222 599,170.5329 584,382.3463 578,386.1324 570,571.9546 590,194.6904 565,587.6523 570,682.3944 563,951.8619 571,096.00 579,445.43 560,965.55 572,150.41 573,201.81 569,771.16 566,978.93 558,452.81 542,939.28 492,025.18 509,773.26 466,939.37 484,837.39 474,918.56 435,779.91 419,723.00 396,812.05 384,567.42 377,533.41 362,878.95 324,026.26 - 46.76 CRF = common reporting format, LULUCF = land use, land-use change and forestry. | e6994b55-18ee-49c8-92db-2261135aea96 | 215 |
0d7c76d8-d3bc-41c1-a194-c789d00eac89 | 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 | It shall not affect the validity of
any delegated acts already in force. Before adopting a delegated act, the Commission shall consult experts designated by
each Member State
the
in accordance with
Interinstitutional Agreement of 13 April 2016 on Better Law-Making. the principles
laid down
in
As soon as it adopts a delegated act, the Commission shall notify it simultaneously to
the European Parliament and to the Council. A delegated act adopted pursuant to Articles 93, 108 and 324 shall enter into
force only if no objection has been expressed either by the European Parliament or
by the Council within a period of two months of notification of that act to the
European Parliament and the Council or if, before the expiry of that period, the
European Parliament and the Council have both informed the Commission that they
will not object. That period shall be extended by two months at the initiative of the
European Parliament or of the Council. 1. | fdc8afd5-2a2d-4946-a4da-be36ebf11749 | 73 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.