SuperCritical Fluid Technology

Last discoveries in the field of supercritical fluids technology allowed to enlarge the range of configurations for plants working with supercritical CO2. In addition to the traditional extraction and fractionation systems, nowadays there are also continuous cycle pasteurization systems and multipurpose systems, containing all the functions listed below. In the following schemes plants having PLC control systems are described. The functioning of the manual plants is similar, but it presupposes the presence of the operator handling the valves according the necessities, and setting the temperatures on chiller and boiler. In this case pressure and temperature for every section will be recorded instruments flanking the plant.

Supercritical CO2 Extraction process (SFE=Supercritical Fluid Extraction)

Allplants realized by Separeco have in common the CO2 recirculation flow coming from the last separator. This configuration allows the recovery of the CO2 utilized during the process, in order not to loose it. Before being pumped again into the reactor, CO2 is condensed and collected in a proper tank. The plant is made of an autoclave E that can be equipped with a basket for the solid matrices treatment. The vases have a thermostatation coat which allows to set the process temperature between 20 and 85°C. On the top of the vases there is a rapid closure device, allowing a reduction in the un/loading time. The pump PCO2 sends the liquid CO2, at its maximum flow rate, into the extractor E. In the case of automatic plants, an inverter connected to a PLC pilots the pump varying the engine rounds, and so the flow rate, read by a flow meter with Coriolis effect. In this case pressure is automatically controlled by the PLC through the valve MV1. The PLC pilots the electric valves controlling the temperature in the vases, the membrane valves in control of the process pressure, the pumps flow rate, the chiller, the boiler, the temperature in every section, the alarms and every strategic component of the plant. The pressure is visualized on the plant as well, thanks to large manometers. The PLC is connected to a PC where a software named “Gerico” manages automatically the process and visualizes all the variables on the monitor, memorizing and printing graphs about each single control parameter. From the control panel the operator can change any of the process parameters. The manometers, the electronic pressure  and temperature transducers give to the operator all the process data real time. The apparatus is equipped with at least two separation stages operating in series. The first one is a gravimetric separator (S1) Most of the extract is recovered in this stage. The second one is a cyclonic separator (S2). The most volatile part is recovered at this stage. The module K gathers all the safety systems.

Supercritical CO2 separation system (SFF – Supercritical Fluid Fractionation)

The countercurrent distillation tower constitutes the core of the fractionation plant. The tower contains filling bodies structured in order to increase the exchange surface, and it is designed for 250 bar operations. The fractionation tower T is connected to the pumps PCO2 and Pliquid. The operation temperature is controlled by the fluid circulating in the coat and it can vary between 20 and 85°C. The pump Pliquid sends the liquid to be fractionated to the tower. Both volumetric pumps are piloted by an inverter for the flow rate control. The refined product is accumulated at the base of the tower and it must be cyclically discharged. The temperature inside every single section of the tower is regulated separately, while the pressure in the cycle is controlled by the membrane valve MV1 which, in the case of automatic plants, is piloted by the PLC. In this case, differently from what is made in SFE plants, two high pressure dosing pumps are necessary. The apparatus is equipped wit hat least two separation stages operating in series. The first one is a gravimetric separator (S1) Most of the extract is recovered in this stage. The second one is a cyclonic separator (S2). The most volatile part is recovered at this stage. The module K gathers all the safety systems.

Supercritical CO2 pasteurization plant (SFP – Supercritical Fluid Pasteurization)

The pasteurization plant is designed for continuous 300 bar operations. The aim of this new stage is the realization of the pasteurization process of liquids at 30-35°C. The apparatus consists in a pasteurization reactor connected to the pump PCO2 and to the pump .Pliquid through a static mixer. The pasteurization reactor is thermostated with water at 30-35°C. The process pressure is controlled by the valve MV1, positioned downstream of the pasteurization reactor. The mixture liquid-CO2 is sent to a degassing recipient, which is connected to a compressor recovering the CO2 utilized in the process and resend it to the condenser for the sequent stocking in the recipient A1. The scheme of the plant described here refers to an industrial process. In the pilot plants or lab-scale plants, CO2 is extracted through a dispersed vacuum pump. The utilization of CO2 in this process is reduced to the minimum. Upon customers' request it is possible to add some sampling points inside the reactors of pasteurization, in order to determine most precisely the ideal retention time for the pasteurization process to be complete. As for the fractionation plant, here is necessary to have two high pressure dosing pumps too. The module K gathers all the safety systems.

Extraction process

SFE is an alternative compared to the classic separation systems like fractionated distillation, steam current distillation, solvent extraction or thermal desorption. SFE can be applied to systems on a different scale: from lab-scale, analytic (from few hundreds milligrams to few grams of sample) or preparative (few hundreds grams of sample), to the pilot scale (kilograms of matrix), up to the industrial scale treating tons of raw material (e.g. in the coffee decaffeinization process).SFE can substitute many traditional extraction processes from vegetable matrices for the obtainment of dry extracts or essential oils with specific characteristics. The extraction of substances from complex mixtures, in particular, can be made highly selective modifying properly the operational temperature and pressure conditions, in order to adapt them to the solubility of the different components of interest. An example is the terpenes removal from the essential oils from citruses and other officinal plants, through which a mixture of aromatic components stable to light and temperature is obtained (generally monoterpenes are not, and sometimes they contribute in no way to the smell).On the basis of such premises, SFE progressively imposed itself as one of the elective technologies for the treatment, with different goals, of several raw materials of alimentary, pharmaceutical and cosmetic interest (active principles extraction and officinal herbs components extraction). Although theoretically there are many supercritical fluids available for the purpose, CO2 is the fittest. In fact it is non toxic, inert, non flammable, cheap, recyclable and environmentally harmless. CO2 extraction is a modern extraction technology for hydrophobic vegetable components realized according to a clean procedures without release of any residue nor solvent substances. After the extraction the operation pressure is lowered and the CO2 loses its solvent power releasing the solute substances, which are available in a concentrated and pure form. For these reasons FDA marked this process as GRAS (Generally Recognized As Safe). Natural substances, moreover, usually are not very stable at high temperatures, and need to be kept at temperatures next to the environmental one: CO2's critical temperature is 31°C, making of it particularly fit as solvent for biologic substances. Proteins, carbohydrates, inorganic salts or metals are not co-extracted in any way. CO2 extracts are microbiologically stable and do not need particular storage conditions, because given their nature they are practically sterile. Unlike conventional procedures, the extraction selectivity is specific. The method does not involve thermal stress and does not need organic solvents.

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HHO - Passivation of Stainless Steel

Many people are not aware of the need to passivate stainless steel to keep it "Stainless".

Why is it needed?

All stainless steel needs to be cleaned and passivated to protect the surface from contaminants. Stainless steel has a self protecting surface that is produced by an oxide layer. If when in manufacture and handling, the stainless comes in contact with carbon steel such as used for cutting, rolling, bending, drilling or whatever processes have been done, there is always some transfer to the stainless steel, and this needs to be removed and the oxide surface restored, that is what the passivation process does.

The process used to be done with nitric acid, which is dangerous to handle and has many drawbacks, especially environmentally.

The latest process uses Citric Acid which is much safer and easy to do and can be handled without the fear of doing damage to yourself or things around you. Citric Acid can be sent through the post because it is classified as "Non Dangerous Goods" and is also environmentally safe.

The process that we use for passivating may be a little different than those that only want to prepare a small number of plates.

The method we use can be copied easily if you have a lot to do.

First the acid powder is mixed with distilled water (one 200g satchel mixed with 2 liters of water) or 10% citric acid per volume. If you have more cells to do, just increase the number of satchels and also the amount of water.

Next the acid water is placed into a small plastic bowl and a cheap under water aquarium pump is connected to a hose that is connected to the inlet of the dry cell. If you have more than one dry cell to passivate, connect the outlet of the first cell to the inlet of the second cell and then return the outlet from that cell back to the bowl. You can chain many cells together using this method, we do as many as 12 dry cells at a time.

It is best if the acid water has a temperature of around 120°F or about 50°C. Set the pump going and leave for about 20-30 minutes, all the cells will be processed at the same time. Drain the acid water from the cells and rinse with distilled water. Blow compressed air through the cells.

The cells have now been cleaned and passivated at the same time.

If you only have some loose plates to passivate, same process only just place the plates vertically in a bowl and add the warm acid water to cover the plate. Leave for up to 1 hour and then remove. Rinse with distilled water. (wear plastic or rubber gloves to protect the plates from your oily fingers) Dry with some newspaper or air dry and assemble your cell with care so as not to contaminate the surfaces with either oily hands or by touching with other metal objects.

One 200g satchel of Citric Acid make up 2 liters of acid water.


Explore the possibilities

At Chirp, we harness the unique affordances of sound to transmit data, enabling the interconnection of millions of new types of things in a seamless, scalable, cost-effective and powerful way.

Broadcast capable

Sound is practically omnidirectional, meaning it is broadcast from a source and travels out in all directions from its origin. This makes it particularly well suited for broadcasting data in a ‘one to many’ network configuration to devices which may have no prior interaction or association.

Unlike many networking solutions, Chirp is frictionless and does not require devices to go through any prior handshake process before they can exchange data. The system can complement existing networking technologies during device onboarding by simplifying the set up process.

Works offline

Sound works completely peer-to-peer, meaning no additional connections are needed to ‘the cloud’ or other network services, so it works great in situation where there is no other network access.

Sound is everywhere around us, and billions of devices are able to make or listen for sound via their microphones and loudspeakers. Chirp can enable machine to machine transactions even in equipment without existing networking capabilities, such as legacy equipment.

Sound can take data out of the dark, transforming it into something tangible that the majority of people are familiar with. Encoding data into sound enables it to be forward shared between different platforms and devices.

Chirp acts as the Transport Layer in the networking stack, much the same way TCP does in the internet stack. Our technology gets the data from A to B but does not itself directly implement security measures - these measures are layered on top of our Transport Layer so that they are in place as the data is passed to Chirp for transmission. Importantly, this means that Chirp does not have knowledge of security strategies implemented by partners' applications and products using our technology. Partners can effectively add any type of encryption, tokenisation or other security strategy required before broadcasting.

Sign up to our newsletter to get Chirp news delivered straight to your inbox.


How To Recognize An Abusive Relationship

2018-09-07T11:15:11+00:00July 22nd, 2017|Domestic Violence/Abuse|


Photo by Andrea Booher

“Lately I’ve been feeling a bit hopeless about finding love,” writes Ask MetaFilter user seraph9, in a post called “Alternatives to Love.” “What are your most rewarding, fulfilling, amazing non-romantic experiences or undertakings?” Respondents listed enriching activities that illustrate how much more there is to life than work and romance.

Volunteering is the most popular suggestion. “Contributing to something greater and outside of yourself is incredibly rewarding,” says user Capt. Renault. Look for roles that let you form deep relationships with others. Many people lack the support network of reliable loved ones, so your emotional availability is just what they need.

User fairlynearlyready suggests writing to prisoners through Lifelines to Solitary. User Wilder recommends working in a hospice or other end-of-life care. “Many people are alone, or estranged from their families and have no one to help them pass away with dignity.” For more ideas, user janey47 recommends the book How Can I Help? by Ram Dass and Paul Gorman.

Friendships might feel obvious, but it takes conscious effort to prioritize them as much as people prioritize finding “the one.” Building a close group of friends gets tougher as you get older, especially as other friends start pairing off, then having kids. But approach that as just having more friends. Many couples love having single friends—they’re a nice break from other couples—and being a “friend of the family” can be a life-long fulfilling role. But be clear with them about whether or not you want to be “set up” with dates or other friends. Without guidance, couples will inevitably try to assimilate single people.

Also, seek out friendships with fellow long-term single people. You need to have friends who, like you, can think outside the relationship bubble. There’s always the risk that some day you’ll “lose them” to a romantic partner, but they’re taking that risk with you too. Try to form some close friend groups larger than two people; that’s a huge advantage you have over long-term couples, who necessarily have to center their lives on one other person.

Bring as much friend activity as you can into your home or theirs. Another joy of relationships is carving out time in private spaces, but this isn’t only a romantic activity. Get out of bars and cafés and feel the intimacy of talking to friends in your own space.

Group activities, like a dance class, a band, choir, church, book club, or even playing Dungeons & Dragons, make it easier to meet friends, as they give an immediate purpose to the shared activity. When you go to an event like a book reading, comedy show, or concert, see what more long-term options the venue or organization provides.

Find a group that meets regularly. Part of the joy of a long-term relationship, especially once you live together, is that it’s “on” by default. That removes so much stress from scheduling and uncertainty. A standing group commitment works similarly; you don’t have to worry about finding time for friendships if you’ve all made it a regular priority.

For years, my weekly D&D group worked like cruise control for our friendships. User wwax especially recommends leading a game as the dungeon master: “The feeling of telling a story with a group of other people is amazing.”

Meditation builds a foundation to make all of life more fulfilling, says user Quisp Lover. It can flip the search for non-romantic fulfillment upside-down: “Spiritual joy is not sublimated sexuality; sexuality is repressed spiritual joy.”

Owning a pet can’t substitute for human love, but it has a lot of advantages. An animal will give you unconditional love that most humans can’t. “I had never felt that kind of love coming at me before I had my baby kitty and she gave me that,” says fairlynearlyready. A pet relies on you completely, but its needs are less complicated than those of a child or partner.

Don’t write off dating around, says user late afternoon dreaming hotel. As long as you’re honest and open about it, there’s nothing inherently wrong about fulfilling more short-term needs (you know, like sex) through your dating life, while finding your long-term needs elsewhere. “Love can come second to sorting out its component pieces and, instead of looking for the end goal first, looking to meet those needs up front.”

Alternatives to Love | Metafilter


Organ Music by Costanzo Antegnati

Born: 1549

Died: 1624

Birthplace: Brescia, Italy

Costanzo Antegnati was an Italian organist, composer and organ builder; member of a famous family of organ builders. He was organist of Brescia cathedral from 1584-1619, and published volumes of Masses and psalms for double choir, motets and madrigals; also a volume of organ ricercars (1608) containing an introduction entitled L'arte organica, which discusses registration and lists the organs his family had built.


Portfolio > As far as the eye can see.

As far as the eye can see is an exhibition of works by prominent Australian printmakers investigating their local landscapes. It celebrates the breadth and depth of printmaking practice in Australia today and is a stunning reflection of Australia’s unique and varied geography. The artists express their stories and relationships to the land through a variety of print media, describing the vast scale or intimate detail of our diverse natural environment. As far as the eye can see portrays the similarities and differences of coastal, mountain, desert and island terrain all contained within our country.


1. Overview of 2nd GoGo Class: Focusing on Arms

    Thank you everyone for making last Tuesdays class such a fun and heart warming experience! It was lovely to have everyone in class, sharing, and dancing, and having a good time!!! I am so excited that we now get a chance to share this with our online class members!!!

    Last week we focused on our arms in class! We started off with a nice stretch before getting into the nitty gritty of the class!!

    Arms are a key part in GoGo dance! Our arms are what polish our dances, and take movements appropriate for the dance floor and make them big stage worthy! Arms create our space and can be used to express emotions and characters.

    When focusing on the role of our arms in GoGo dance, our first consideration should be engagement. What does it mean to have engaged arms? It means we use them with intent! If we attempt to extend an arm across our body, then we must go through the full movement before moving onto something else. If our hand is on our hip, in a rest, every part of our arm is involved in the movement, from our fingers to our elbows to our shoulders! Are your fingers engaged and pretty? Is your elbow creating a clean and beautiful line/shape for your audience? Is your shoulder back and relaxed? Generally our wrists should be relaxed, and our fingers engaged! An engaged arms is flexed where it should be flexed, relaxed where it should be relaxed, and is going for its movement with 100% commitment!

    Much of GoGo dance is really just posing! This should be our first consideration when building our freestyle dance! Take the time to look at yourself in the mirror and just pose! What poses look good to you? Why do those poses look good? The first thing they have in common is that a pretty pose creates beautiful lines. We can easily create these aesthetically pleasing lines through minding our planes!

    The planes on which we move our body are important to mind while working through a freestyle dance! If you are putting your arms out, parallel to the floor, then your arms should be parallel to the floor, with your armpit creating a 90 degree angle! Not a 78 degree angle. Not a 105 degree angle, but a 90 degree angle so that your extended arm creates a beautiful line with your body and with the floor! If we mind our planes, it will go a long way to making our dance look polished!

    Finishing your movements is the next step in mastering the perfect GoGo arm! If you begin with your hand on your hip, take a step, and extend your arm out to be parallel with the floor, then drop it after only two counts and move on to something else, you are not FINISHING your movement. A great way to practice finishing your movements is focusing on a body part or combination for at least four counts, then changing your focus to a new body part or combination. (Thinking about changing your focus, whatever that may be, on counts divisible by four is a great way to finish any movement -arms or not- and something we will focus on in the technique class).

    Drill your arms by stepping back and forth, changing your arms every two to four counts!

    Different genres of dance lend arm movements to us in GoGo dance! A lot of your long, pretty, big arm movements are rooted in modern and contemporary dance! But those long pretty movements aren’t appropriate for all types of music! We can pull inspiration and combinations from dances such as hip-hop and breakdance or even whacking and voguing! It all depends on the music and what we are trying to portray with our bodies! Take the time to research these dances, and watch videos online to pick up combinations and stylings!

    Personally I like to take a lot of my rests and holds from hip-hop! Arm rests and holds are used when you are focusing your dance on other parts of your body, such as your feet or hips! Hands on the hips, or holding yourself, even rubbing your hands through your hair or up and down your body while focusing your full highlighted dance elsewhere is a great way to keep your arms from fatiguing during your performance!

    Practice perfecting your arms by drilling poses in the mirror, by freestyling in front of a mirror or video camera while focusing on your arms, pickup combinations and styles from videos online and practice weaving them into your own dance!

    Thanks so much for joining me on this GoGo adventure! I can’t wait for the next class!!!

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        Area change of glaciers across Northern Ellesmere Island, Nunavut, between ~1999 and ~2015
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Using a variety of optical satellite scenes, this study quantifies the change in the areal extent of 1773 glaciers across Northern Ellesmere Island between ~1999 and ~2015. Our results show that the regional ice coverage decreased by 1705.3 km2 over the ~16-year period, a loss of ~5.9%. Ice shelves had the greatest losses relative to their size, of ~42.4%. Glaciers feeding into ice shelves reduced in area by 4.7%, while tidewater glaciers reduced in area by 3.3%. Marine-terminating glaciers with floating ice tongues reduced in area by 4.9%, and 19 of these 27 ice tongues disintegrated, causing these glaciers to retreat to their grounding lines. Land-terminating glaciers lost 4.9% of their 1999 area, including the complete loss of three small ice caps (<1.5 km2). Our study highlights the high sensitivity of the ice cover of Northern Ellesmere Island to recent climate warming and the continued losses that are likely to occur in the future. In particular, the ice masses most susceptible to further losses are marine-terminating glaciers with floating termini and small land-terminating ice caps at low elevations.

The Canadian Arctic Archipelago (CAA) contains ~150 000 km2 of glacier ice, making this region the most glaciated in the world outside of Greenland and Antarctica (Pfeffer and others, 2014). Based on satellite gravimetry measurements, this region has become the single largest contributor to eustatic sea-level rise outside of the major ice sheets since 2003 (Harig and Simons, 2016), during a period of rapid warming of glacier surface temperatures (Mortimer and others, 2016). The ice in this area can be separated into two groups, the southern area that spans Baffin (~36 839 km2) and Bylot (~4859 km2) islands, and the northern area (107 488 km2) that spans the Queen Elizabeth Islands, of which 27 556 km2 (all ~1960 areas) is located on Northern Ellesmere Island (Fig. 1; Andrews, 2002; Sharp and others, 2014).

Fig. 1. Queen Elizabeth Islands, Canada. The study region is shown by the dark grey area on Northern Ellesmere Island. Ice outlines (in light grey) from 1999 for Axel Heiberg, Devon, and Southern Ellesmere Island were acquired from GLIMS (

The first detailed measurements of glacier thickness and volume change across Northern Ellesmere Island were conducted by Abdalati and others (2004), who used repeat airborne altimetry measurements over the period 1995–2000 to calculate changes of −3.52 km3 a−1 (the highest rate of ice volume loss compared with all other ice caps in the CAA). Sharp and others (2014) performed measurements of the area change of glaciers (excluding ice shelves) on Northern Ellesmere Island up to the year 2000, by using ice extents from 1956 to 1961 derived from aerial photography and 2000 extents delineated using an unsupervised classification of Landsat 7 ETM+ and ASTER imagery. Their study revealed that Northern Ellesmere experienced a reduction in glaciated area of 927 km2 (3.4% of initial area) over this period, the greatest area loss of all regions measured across the CAA. The largest mean percentage area changes for Northern Ellesmere occurred from glaciers <1 km2 in area, which lost an average of 29.2% of their initial ice area. Since 2000, a few studies have been conducted on Northern Ellesmere Island to assess changes in ice shelf area (e.g., Copland and others, 2007; Mueller and others, 2017a, b) and the changes of individual ice caps (Braun and others, 2004; Serreze and others, 2017), but no detailed regional assessment of glacier changes has been conducted.

Here we present a comprehensive inventory of the number and extent of all glaciers on Northern Ellesmere Island, using satellite data acquired between 1999 and 2016. This is the first study to present recent area change measurements for this region and to analyze the spatial variability in glacier change in relation to terrain controls. Our data will be made available in the Global Land Ice Measurements from Space (GLIMS) database (

1.1. Study area

Ellesmere Island is the largest island in the Queen Elizabeth Islands, with an area of 196 236 km2 and a length of 830 km (Fig. 1). The island is the most mountainous in the CAA and can be separated into different ice regions from north to south that includes Northern Ellesmere Icefield, Agassiz Ice Cap, Prince of Wales Icefield, Manson Icefield and Sydkap Icefield (Fig. 1). The study area of Northern Ellesmere is separated from the rest of Ellesmere Island by the Hazen Plateau and Greely Fiord and has a maximum elevation of 2616 m at Barbeau Peak (Fig. 2). Lake Hazen is a large inland lake, with a surface area of 537.5 km2, which stretches in a southwest-northeast direction in the southeast part of Northern Ellesmere (Fig. 2). The Northern Ellesmere Icefield spans the majority of the island, while ice shelves and marine-terminating glaciers flow off the northern coastline. Smaller ice caps, such as Grant and Ad Astra, surround the main ice caps, but the majority are unnamed.

Fig. 2. Landsat OLI/TIRS mosaic (Table 1) of Northern Ellesmere Island showing the outlines classified by terminating environment in (a) 1999–2008; (b) 2015/16. Labels show the locations of the basins referred to throughout the study. Note: Northern Ellesmere Icefield is outlined with a thick black line.

The climate regime of Northern Ellesmere varies between the coastal regions, interior lowlands and highlands. The coastal waters contain a mix of first- and multi-year ice. In summer, fall and early winter (during the sea-ice consolidation period), the varying coverage of sea ice and open water leads to high frequencies of fog and low cloud over the channels and along the coastlines (Maxwell, 1981). The interior lowlands are surrounded by mountains which cause a rain shadow that results in low mean precipitation, while exposed slopes at higher elevations receive >200 mm of precipitation per year (Maxwell, 1981). At Eureka weather station, ~100 km to the southwest of the Northern Ellesmere Icefield, mean monthly precipitable water ranged from 1.8 mm in late winter to 12 mm in July between 1961 and 2007, with a 10% increase in mean annual precipitable water over this period (Fig. 1; Lesins and others, 2010). The increase in precipitable water has been dominated by increases during the spring, summer and fall, with the greatest increase occurring during summer at a rate of 0.3 mm decade−1 since 1961. Over the 54-year period, the station recorded a mean air temperature of −19.1°C.

Area changes for each glacier were determined from optical satellite imagery within the periods ~1999 (period 1) and ~2015 (period 2) (Table 1). These periods were selected to provide the broadest temporal range with the highest resolution imagery, primarily from Landsat 7 (ETM+) and Landsat 8 (OLI). The north coast of Ellesmere Island was beyond the orbit of Landsat 7 in 1999, so ASTER imagery from 2002 and 2003 was used instead, covering 5.2% of the total glaciated area. Glacier coverage for Ward Hunt Ice Shelf and for glaciers along the far north-east coast of Northern Ellesmere (comprising ~4.5% of the total glaciated area) was not available for 1999–2003, so Formosat-2 imagery from 2008 and ASTER imagery from 2009 was used in its place for period 1. Due to the lack of satellite coverage over the Markham Ice Shelf for period 1 (Fig. 2), the extent (from 2003) was obtained from Mueller and others (2017a). In the second period, Landsat 8 imagery from 2015 and 2016 provided complete coverage of the study area.

Table 1. Satellite scenes used to delineate glacier extents in this study. Landsat and ASTER images were obtained from the US Geological Survey Earth Explorer ( Formosat-2 image obtained from Planet Action ( Images used in the 2015/16 mosaic (Fig. 2; the master image against which all other imagery was georeferenced) are shown in bold

2.1. Basin boundaries

The ice cover across Northern Ellesmere Island was divided into individual drainage basins using a combination of elevation data and optical satellite imagery. Basins were delineated using a pre-release version of the ArcticDEM, a DEM with 8 m resolution constructed by the Polar Geospatial Center (University of Minnesota) from in-track, high-resolution (~0.5 m) Digital Globe imagery from 2012–15. A polygon shapefile was delineated for each drainage basin by using the Basin tool in ESRI ArcGIS 10.3.1. To create the basins, sinks were filled and an eight-direction (D8) flow model was used, which determines the flow direction of each raster cell based on the steepest path of the eight surrounding cells (Jenson and Domingue, 1988). The automated basin outlines were verified visually against the 2015/16 Landsat 8 mosaic using visible features such as flow lines, and adjusted as necessary.

2.2. Glacier outlines

An outline of the ice extent was delineated for each glacier and nunatak from orthorectified ASTER (15 m resolution) and Landsat imagery (30 m resolution enhanced with the 15 m panchromatic band) and georeferenced Formosat-2 imagery (8 m resolution) (Table 1). Images with little to no cloud cover acquired during late summer were preferentially selected due to their minimal snow cover. Pan-sharpened Landsat 8 images acquired in 2015/16 were mosaicked and used as the master image against which all other satellite images were aligned (Fig. 2; bolded scenes in Table 1). Eight ASTER images and one Formosat-2 image were georeferenced to the Landsat mosaic using 13–20 ground control points (GCPs), depending on the amount of flat and stable bedrock available in the scene. Georectification was completed using a zero-order polynomial shift in ESRI ArcGIS 10.3.1, which resulted in root mean square errors (RMSE) ranging from 15.02 to 21.80 m (Table 1). One Formosat-2 image was transformed using a first-order polynomial transformation and had an RMSE of 21.81 m. All other imagery was well-aligned and did not require modification.

During the digitization process, pan-sharpened Landsat scenes were displayed in both true colour and false colour; the false colour composites were represented with bands 4, 3 and 1 (for both Landsat 7 and Landsat 8) in the red, green and blue (RGB) channels, respectively. ASTER scenes were represented with bands 3, 2 and 1 in the RGB channels. To avoid misclassification, only glaciers >0.1 km2 in area (in 1999) were digitized in this study, although glaciers that shrank to areas <0.1 km2 during the second period of study were included for continuity of the dataset.

Once the ice extents and ice divides had been defined, nunataks were subtracted from these outlines so that each polygon represented only the area of ice and not internal rock. The image acquisition dates were used to convert measured area (in km2) of the two time periods into standardized rates of percentage change per decade. Each glacier was assigned a unique ID following the format outlined by GLIMS, which incorporates centroid coordinates of each glacier (Raup and Khalsa, 2010). The official name was included for glaciers with a name assigned in the Canadian Geographical Names Data Base of Natural Resources Canada (

2.3. Terrain parameters

In total, 11 terrain variables were derived for the glaciers (in ~2015) measured in this study to examine the influence of physiography on area losses. The coordinates of the centroid of each glacier were extracted. The minimum, maximum and mean elevation, mean slope, flow length and mean aspect for each glacier were extracted from the ArcticDEM using the Spatial Analyst extension in ArcGIS 10.3.1. The east-west and north-south scalar aspects were derived from the sine and cosine of the mean of these scalar aspects (Copland, 1998). The main terminus for each glacier was visually assessed and classified into one of five types:

  1. (a) Land-terminating glaciers refers to all outlet glaciers and ice caps that terminate on land, and in this study includes glaciers with proglacial lakes or glaciers that calve into the proglacial lakes of neighbouring glaciers.

  2. (b) Tidewater glaciers are marine-terminating ice masses that are grounded on the sea floor (Dowdeswell and Jeffries, 2017). These glaciers were distinguished by their lack of extension away from the coastline and lack of tidal cracks. This category also includes glaciers flowing into ice shelves but without visual evidence of becoming incorporated into the ice shelf. Also included are coastal ice caps that flow into the sea. Note that if any land is apparent between the terminus and the coastline, the glacier is classified as land-terminating.

  3. (c) Ice tongues are the floating extensions of single valley glaciers over the ocean (Mueller and others, 2017a, b). In this study, ice tongues are classified as floating termini that extend into a bay or fiord and include ice fragments clustered together and frozen in place by sea ice around the terminus.

  4. (d) Ice shelves comprise extensive, permanent floating landfast ice features that are >20 m thick (Dowdeswell and Jeffries, 2017). In this study, ice shelves were identifiable by their characteristic undulating surface topography and their infilling of bays and fiords along the northern coastline.

  5. (e) Ice shelf-terminating refers to glaciers that flow into ice shelves. Although these glaciers contribute directly to the ice shelves, they are separated from the ice shelf as per the GLIMS procedure (Raup and Khalsa, 2010).

2.4. Changes in accumulation area ratio (AAR)

To provide an estimate of the changes in AAR of the ice cover of Northern Ellesmere Island, the hypsometry of this region was compared with estimates of the changes in equilibrium line altitude (ELA) over the study period. The ELA across Northern Ellesmere Island at the start of period 1 was determined from digitizing the map of Wolken and others (2008), which in turn was recreated from Miller and others (1975). Wolken and others (2008) describe this map as representing the ELA in 1960, but we assume that this ELA is broadly representative of conditions at the start of period 1. This is based on mass-balance measurements on other Queen Elizabeth Islands ice caps which show generally weak trends over this period (Koerner, 2005; Thomson and others, 2017), and the observation that average glacier mass balance was five times more negative between 2005 and 2009 than 1963–2004 (Sharp and others, 2014). Since 1999, we estimate that the ELA on Northern Ellesmere has risen by ~100–300 m, based on measurements at White Glacier (Fig. 1) (mean ELA 1960–1998 = 1022 m; mean ELA 1999–2014 = 1205 m; Thomson and others, 2017) and measurements on northern Agassiz Ice Cap that indicate the 2014/15 ELA was 300 m above the 1977–2015 mean (Burgess, 2017).

2.5. Error analysis

To calculate error associated with the alignment and resolution of the satellite imagery, we used the method defined by Hall and others (2003). The uncertainty in the change of the ice extent in the linear dimension (d) between two satellite images was calculated from (after Williams and others, 1997):

(1)$$d = \sqrt {r_1^2 + \; r_2^2} + {\rm RMSE},$$

where r 1 is the cell size of the first image, r 2 is the cell size of the second image and RMSE is the error calculated during the georectification process (Table 1). The finest resolution (15 m) and the highest RMSE value (21.81 m) were used in this calculation. The linear uncertainty was converted to area uncertainty using (after Hall and others, 2003):

(2)$$a = A\left( {\displaystyle{{2d} \over x}} \right),$$

where A = x 2 and x = linear side dimension (15 m). This calculation produced an error of ±0.0013 km2.

To calculate human error that may occur during the digitization process, the same operator digitized three different glaciers from the dataset for Northern Ellesmere, of differing sizes, environments, and locations, at a consistent scale of 1: 10 000. Each glacier was digitized five times for each time period using imagery from the study. G85164W81925N, G75159W81335N and G69499W82211N were selected based on their range in size, distribution and terminal environment: G85164W81925N (5.99 km2 in 1999) is a marine-terminating glacier in the northeast, G75159W81335N (1.00 km2 in 1999) is a small ice cap in the southern region, and G69499W82211N (254.52 km2 in 1999) is a large land-terminating glacier in the western region (Fig. 2). The mean error for both time periods varied between 0.004 km2 (0.07%) for G85164W81925N, 0.004 km2 (0.69%) for G75159W81335N and 0.136 km2 (0.05%) for G69499W82211N. The largest of these errors (0.14 km2) was summed with the satellite error (0.0013 km2) to provide a total error. Based on these error calculations, glacier area changes were considered significant if they were >0.14 km2.

2.6. Climate data

To examine climate conditions since 1950, NCEP/NCAR Reanalysis monthly mean data was downloaded from the NOAA Earth System Research Laboratory website ( These data are drawn from an assimilated gridded (2.5° × 2.5° grid) dataset, based on observations from the land surface, ship, rawinsonde, piloted balloon, aircraft, satellite and other data (Kalnay and others, 1996). It should be noted that NCEP/NCAR data prior to 1979 are of a lower quality to the lack of assimilation data, although this is considered to be of minor significance as this study is primarily concerned with changes in conditions since ~1999. For this study, mean monthly surface air temperatures from 1948 to 2016 were analyzed for grid cells centered on Northern Ellesmere Island from 80.587–83.190°N to 60.678–92.296°W. This climate dataset was verified by comparing observations collected by an automatic weather station in Purple Valley (Fig. 2) over the period 2008–16 to the NCEP/NCAR data gridcell centered on this region (82.500°N, −80.999°W). The close resemblance between these datasets (Fig. 3) suggests that the reanalysis data are suitable for assessing trends in air temperature across Northern Ellesmere.

Fig. 3. Comparison of NCEP/NCAR Reanalysis and AWS mean monthly surface air temperature datasets from May 2008 to November 2016 for Purple Valley, Northern Ellesmere Island. November 2012 AWS data omitted due to sensor error.

3.1. Regional glacier inventory

For ~2015 a total of 1768 glaciers were identified, comprising 1702 land-terminating glaciers, 45 tidewater glaciers, eight marine-terminating glaciers with ice tongues, six ice shelf terminating glaciers and seven ice shelves or remnant ice shelves (Table 2; Fig. 2b and Fig. 4a). Land-terminating glaciers made up the highest proportion of the total ice area (63.4%), followed by tidewater glaciers (18.2%) (Table 2; Fig. 4a). Glaciers between 0.1 and 1 km2 in size made up 43.3% of the total number of glaciers, but only 1.2% of their total area (Fig. 4b). In contrast, the majority (40.8%) of glaciers were between 100 and 1000 km2 in size (Fig. 4b). The largest single ice mass is M'Clintock Glacier (G75759W82147N), a marine-terminating glacier with an ice tongue, measuring 1468.4 km2 in area and with a centreline flow length of ~44 km (Fig. 2). The majority of individual glaciers had a north-east facing aspect, while the majority of the total ice area had a north-facing aspect (Fig. 4c).

Fig. 4. Glacier inventory characteristics for ~2015: Total glacier area (km2) and number of glaciers in each: (a) terminus environment; (b) size class; (c) aspect class; (d) elevation class, and relationship between glacier area and (e) maximum elevation; (f) mean glacier slope. Note logarithmic scales on (e) and (f).

Table 2. Overview of glacier inventory, with details as a total area and percentage of each glacier type

Mean glacier elevation ranged from 19 m a.s.l. (M'Clintock Ice Shelf; G77428W83023N) to 1519 m a.s.l. (G73513W81780N). Turnstone Glacier (G74388W81792N) had the highest maximum elevation (2603 m a.s.l.) as it flowed from Barbeau Peak. Overall, 54.1% of glaciers had a mean elevation between 500 and 1000 m a.s.l., with <1% having a mean elevation <100 m a.s.l. (Fig. 4d). There was a fairly strong relationship (r 2 = 0.253, P = 3.23 × 10−44) between maximum elevation and glacier area (Fig. 4e), with the highest elevations concentrated from east to west along the main spine of the icefields. Glaciers with ice tongues had the highest mean difference in the highest and lowest points of elevation: 1595.0 m, compared with ice shelves with the lowest mean relief of 33.4 m. Glacier slope varied inversely with glacier area (r 2 = 0.3055, P = 5.53 × 10−19), with smaller glaciers tending to be steeper (Fig. 4f). By glacier type, ice shelves tended to have the lowest gradient (mean slope of 2.0°) which is reflected in their large flat structure. The steepest glaciers, with a mean slope of >30°, were land-terminating with areas <1 km2.

The central part of the Northern Ellesmere Icefield comprises the largest contiguous ice mass in the study region, with an area of 19 445 km2 in 2015 (outlined in black on Fig. 2) and length of up to ~300 km and width of ~160 km, located between 81°N and 83°N. It had a mean elevation of 1203 m a.s.l. This icefield contained 360 glaciers in 2015, of which 344 were land-terminating, 12 were tidewater-terminating and four were marine-terminating with ice tongues. Land-terminating glaciers made up the majority of the icefield and had a total area of 11 294 km2. All of the marine-terminating glaciers drained along the northern coast, with the exception of one tidewater glacier (Otto Glacier/G82716W81419N) flowing off the west coast (Fig. 2).

3.2. Change in glacier area, ~1999–2015

Over the study period, changes in glacier area primarily occurred due to the calving of ice shelves and ice tongues, changes in the position of land-terminating glacier termini, narrowing of glacier trunks and tributary branches, and increases in the area of nunataks. In general, there was a widespread decrease in glacier area for almost all glaciers in the study area (Table 2; Fig. 5). Out of the 1773 glaciers present in the first period, 1353 (76.3%) of them lost >0.14 km2 (the limit of uncertainty) of their area. The remaining 420 glaciers all decreased in area, but not beyond the error limits of this study, and are therefore classified as stationary. No glaciers increased in area over the period ~1999–~2015.

Fig. 5. Magnitude of area loss for each glacier basin between 1999 and 2016, overlaid on a Landsat OLI/TIRS mosaic from 2015/16 (Table 1). Basin delineations are for ~1999. Stationary results refer to glaciers with area loss within the limits of uncertainty.

3.2.1. Land-terminating glacier change

A total of 1703 land-terminating glaciers were outlined across Northern Ellesmere Island for ~1999 (Table 2). Between ~1999 and ~2015, 416 were considered stationary and 1287 shrank beyond the limits of uncertainty. Of these 1287 glaciers, their total area loss was 844.7 km2 (4.8% of their initial area), but 150 glaciers (11.7%) lost >50% of their initial area. Separated by size class, the highest mean losses occurred from glaciers that measured <1 km2 in the first time period, at a mean rate of 30.4% decade−1 (Fig. 6). With each increase in size class, the mean rate of area loss decreased, with the lowest mean area losses (0.4% decade−1) belonging to glaciers >1000 km2. The greatest total area loss of 11.9 km2 (14.3%) occurred from G89730W81726N, a medium-sized (83 km2 in 1999) ice cap on the northwest coast of Northern Ellesmere Island (Fig. 2). Relative to initial area, the greatest losses came from G74438W81359N, G76500W81203N and G76132W82570N, that all disappeared (Fig. 7). These small glaciers were all <1.5 km2 in initial area and distributed north and south of the Northern Ellesmere Icefield (Fig. 2).

Fig. 6. Mean rate of glacier loss (% decade−1) for glaciers that lost mass between ~1999 and ~2015 for each glacier type (as classified initially), separated into size classes.

Fig. 7. Outlines from 1999 of small ice caps that lost 100% of their area: (a) G74438W81359N overlaid on Landsat 8 image from 12 July 2015 (#7 on Fig. 2a); (b) G76500W81203N (eastern-most basin) overlaid on Landsat 8 image from 14 July 2015 (#13 on Fig. 2a); and (c) G76132W82570N overlaid on Landsat 8 image from 12 July 2015 (#12 on Fig. 2a).

3.2.2. Tidewater glacier change

A total of 28 glaciers were classified as tidewater in ~1999, with a total area of 1894.8 km2 (Table 2). By ~2015, 24 tidewater glaciers had shrunk and lost a total area of 61.9 km2, 3.3% of the initial ice area, at a mean rate of 8.7% decade−1. Four glaciers did not lose area beyond the limit of uncertainty and were therefore classified as stationary. According to size class, the smallest tidewater glaciers (three glaciers measuring 1–5 km2) had the greatest mean loss of 22.9% decade−1 (Fig. 6). Similar to land-terminating glaciers, as the size class increased the mean rate of ice loss decreased with the exception of tidewater glaciers between 500 and 1000 km2 that had a higher mean loss (2.7% decade−1) than glaciers 100–500 km2 (1.8% decade−1). The greatest total area loss occurred from Otto Glacier (G82716W81419N), the largest tidewater glacier on Northern Ellesmere, which lost 19.5 km2, 1.6% of its initial ice area. However, this glacier is a known surge-type glacier (Hattersley-Smith, 1969; Copland and others, 2003), which may explain some of these losses. The highest relative rate of area loss occurred from G74911W83042N and G91546W81713N which both lost ~27% decade−1. Two glaciers (Bent Glacier/G78692W81412N, and G85628W82087N) retreated to the point of becoming land-terminating.

3.2.3. Ice tongue change

In the first period, 27 marine-terminating glaciers with ice tongues were identified along the northern coast of Ellesmere Island, covering an area of 7843.7 km2 (Table 2). All 23 glaciers shrank by the year ~2015, with a total loss of 313.98 km2, or 3.6% of their initial area at a mean rate of 6.1% decade−1. Classed by size, glaciers with ice tongues between 1 and 5 km2 had the highest mean area loss of 11.4% decade−1 (Fig. 6). Of the 23 glaciers with ice tongues measured, only eight remained by the second period: G79570W82808N, Ayles (G80489W82741N), Serson (G84958W82170N), G79117W82870N, G80481W81907N, Disraeli (G72723W82423N), Milne (G78878W82327N) and M'Clintock (G75759W82147N) glaciers. The remaining 19 retreated toward their grounding lines, causing the glaciers to lose their ice tongues and become classified as tidewater glaciers instead (Fig. 8). The greatest total area loss occurred from Disraeli Glacier, with a loss of 35.6 km2, equivalent to 2.7% of its initial area. The greatest rate of area loss, relative to its area, occurred from G80169W82886N at 15.5% decade−1.

Fig. 8. Outlines showing the loss of floating ice tongues between 1999 and 2015 from glaciers entering Yelverton Bay, Northern Ellesmere Island: (a) G81795W82368N (south; #27 on Fig. 2); and (b) G822234W82440N (north; #29 on Fig. 2), overlaid on Landsat 8 image from 12 July 2015.

3.2.4. Ice shelf change

Between 1999 and 2009, nine ice shelves and/or ice shelf remnants were identified along the northern coastline of Northern Ellesmere Island with a total area of 1028.7 km2 (Table 2). From west to east, these comprise the Serson (G86130W82356N), Wooton (G84583W82434N), Petersen (G82050W82526N), Milne (G81511W82702N), Ayles (G80719W82854N), East Ayles (G79679W82827N), M'Clintock (G77428W83023N), Ward Hunt (G74723W83074N) and Markham (G71378W83067N) ice shelves. By ~2015, the ice shelves lost 436.1 km2 of ice area, 42.4% of their original area. The greatest total area loss occurred from the Serson Ice Shelf (G86130W82356N), which lost 137.58 km2, leaving behind a small ice shelf fragment on the northeast coast of Serson Bay. The Markham (G71378W83067N; 49.1 km2) and Ayles (G80719W82854N; 75.4 km2) ice shelves lost their entire area.

3.2.5. Ice shelf terminating

In ~1999, six glaciers terminating into ice shelves occurred along the northern coast of Ellesmere Island, contributing mass to the Petersen, Milne and East Ayles ice shelves. By ~2015, these glaciers continued to flow into these ice shelves, but had lost a total area of 10.3 km2, at a mean rate of 4.2% decade−1. The greatest total area loss of 3.5 km2 occurred from G81767W82616N, a glacier flowing into the south-west region of the Milne Ice Shelf (G81511W82702N). The greatest loss relative to initial size occurred to G81776W82542N, a glacier flowing into the north-east side of Petersen Ice Shelf, which lost 15.4% at a rate of 9% decade−1.

3.3. Relationship between area changes and terrain

To better understand the potential relationships between area losses and physiography, 11 terrain variables (Section 2.3; Table 3) were acquired from the 1346 glaciers that underwent shrinkage between ~1999 and ~2015 and had coverage in the ArcticDEM. The terminus environment for each glacier was classified as 1 if it terminated off the coast and 0 if it terminated on land. Glaciers that underwent considerable change prior to the acquisition of the 2012–15 satellite imagery used to generate the ArcticDEM, such as Serson Ice Shelf, were excluded from the terrain analysis.

Table 3. Factor loadings for each significant principal component (eigenvalue >1) identified in the PCA. Bolded values indicate dominant terrain parameter(s) for each principal component

Once the terrain analysis had been completed, principal component analysis (PCA) was used to determine the relationship between terrain variables and remove collinearity between them. The PCA identified four significant components (eigenvalue >1) (Table 3). Component 1 is primarily an altitude factor that describes glaciers with high minimum, maximum and mean elevations, which tend to have steeper slopes and terminate on land. Component 2 is primarily a size factor that describes glaciers with longer flow lengths and larger areas, which also tend to reach to higher maximum and mean elevations. Component 3 is a location factor, dominated by glaciers that are located in areas that are further north and east than average. Component 4 is a north-facing aspect factor.

Over the period of study, components 2 and 3 were significantly (P < 0.0001) correlated with the % decade−1 area changes (Table 3). Component 2 was the most important factor (r = −0.461), which indicates that the biggest % decade−1 changes occurred on relatively short and small glaciers at lower elevations. Component 3 (r = 0.205) suggests that greater area losses occurred in the north-east. When the terrain factors for component 2 are plotted against area changes (Fig. 9), this reaffirms the fact that the terrain factors within component 2 are significantly correlated with area loss (P < 0.0001). The component 3 terrain factors, latitude and longitude, have a significant (P < 0.001) but the weak positive relationship with area changes; r 2 = 0.022 and r 2 = 0.007, respectively.

Fig. 9. Relationship between loss (% decade−1) and: (a) mean elevation; (b) maximum elevation; (c) flow length (note log scale on x-axis) and; (d) glacier area (note log scale on x-axis).

From these analyses, it is apparent that glacier size, elevation and flow length have been the dominant topographic controls on glacier shrinkage over the period ~1999–2015. In this case, the highest shrinkage rates occurred on small, short, low elevation glaciers. This is consistent with our results that show higher area changes from the small isolated remnant ice caps that surround the main icefields (Figs 6, 7). For example, ice masses that lost >50% decade−1 (with the exception of ice shelves) had initial areas <5.4 km2, maximum elevations <1676 m and flow lengths <4745 m.

3.4. AAR changes

In order to examine the past and future susceptibility of the glacier cover across Northern Ellesmere to melt, the ELA at the start of the study period (Fig. 10a) was used to calculate the regional size of the ablation zone, and from that the regional AAR. In 1999, 35.2% of the ice area was in the ablation zone (AAR = 0.648) (Fig. 10b, c). If this ELA rose by a conservative 100 m, the ablation zone would comprise 47.1% of the total glacier cover (AAR = 0.529). If it rose by 200 or 300 m, as seems plausible based on measurements on nearby ice caps (Burgess, 2017; Thomson and others, 2017), the ablation zone area would then comprise 60.2% (AAR = 0.398) or 72.3% (AAR = 0.277) of the overall glacier cover, respectively.

Fig. 10. (a) 1960 ELA trend surface digitized from Wolken and others (2008), assumed to represent conditions at the start of the study period, overlaid on a Landsat 8 mosaic from 2015/2016 (Table 1); (b) Total ablation area (as a proportion of total ice area) for 1960 ELA and at 100 m increments (c) Total ablation area based on the 1960 ELA zones and with a 200 m increment, overlaid on a Landsat OLI/TIRS mosaic from 2015/16 (Table 1).

3.5. Climate analysis

Mean annual surface air temperatures across Northern Ellesmere Island increased by 3.6°C (0.5°C decade−1) between 1948 and 2016 (r 2 = 0.59, P = 9.01 × 10−15; Fig. 11a). A shift seems to have occurred in the mid-1990s when temperature increases accelerated from 0.12°C decade−1 from 1948 to 1994 to 0.78°C decade−1 from 1995 to 2016. Since 1948, fall (September, October, November) has shown the greatest overall increase in mean monthly surface temperature by 0.74°C decade−1 (P = 1.45 × 10−13), followed by winter (December, January, February) at 0.65°C decade−1 (P = 7.75 × 10−10) and spring (March, April, May) at 0.46°C decade−1 (Fig. 11). Summer (June, July, August) had the weakest rate of warming at 0.24°C decade−1 (P = 3.86 × 10−05), although there has been a regime shift from mean negative to mean positive summer surface air temperatures since the year 2000. Of the 20 warmest mean annual surface air temperatures since 1946, 16 have occurred since 2000. Every summer since 2000 has exceeded the climatological summer mean temperature (−0.7°C) by 0.6–2.7°C. Compared with the climatological mean from 1981 to 2010, mean monthly temperature anomalies have been consistently above the 30-year average since 2000.

Fig. 11. Time series of (a) mean annual surface air temperatures (1948–2016). The linear trend from 1948–94 is represented in blue, while the linear trend from 1995 to 2016 is shown in red; (b–e) seasonal surface air temperatures (1949–2016). Data derived from NCEP/NCAR Reanalysis, averaged across the region 80.587–83.190°N, 60.678–92.296°W.

From the above results, it is clear that the ice cover of Northern Ellesmere Island has been undergoing widespread loss since 1999, with two trends standing out among the observations: (1) The dominance of the shrinkage of relatively small, low elevation glaciers in terms of relative area loss; (2) The substantial loss of floating ice from ice shelves and ice tongues along the northern coast. In the following analysis, we begin by comparing our inventory with others of the study region. We then examine the relationships between large area changes and small land-terminating glaciers, together with changes in the ELA and AAR. To gain a better understanding the rapid loss of floating ice termini, we then examine the influence of oceanographic factors.

4.1. Comparison against previous glacier inventories

One previous complete glacier inventory for Northern Ellesmere Island includes the outlines in the GLIMS database. These outlines were provided to GLIMS by the Randolph Glacier Inventory (RGI 6.0), a global inventory of glacier outlines ( According to the inventory metadata these outlines provide coverage for 1999 and were completed by several analysts using a semi-automated glacier classification. Our 1999 inventory differs from the GLIMS inventory in several ways, including total area values and basin delineations. According to the GLIMS database, Northern Ellesmere had an area of 27 377 km2, some 1569 km2 less than the area calculated in our study. The main reason for this difference is because the GLIMS dataset does not include all the floating termini extending from the northern coastline: ice shelves and ice tongues. For example, the area covered by ice shelves in our inventory amounts to >1050 km2. In addition, our inventory incorporates several more small ice caps (along the northern coastline) and better outlines nunataks across the region. Our basin delineations also differ from those of the GLIMS database, because our delineations were generated with the recently released, high-resolution ArcticDEM and verified manually.

A comprehensive inventory (from 1959 to 2015) of the floating portion of ice shelves and ice tongues along the northern coast of Ellesmere Island was produced by Mueller and others (2017a, b). These outlines were digitized manually using anecdotal/survey data (1906), aerial photographs/maps (1959), optical satellite imagery (1963–1992) and SAR satellite imagery (2003–2015). The outlines include only floating ice that ends at the grounding line (i.e., excluding any land ice). In contrast, our ice tongue measurements include the entire drainage basin for each glacier, making a direct comparison with our dataset difficult. However, both datasets for the ice shelves are comparable because they both only include floating ice. For 2015, the ice shelf inventory by Mueller and others (2017a, b) calculated a total area of 532.2 km2, whereas our inventory calculated a total area of 592.6 km2. The greatest difference between the two datasets is in the outlines of Ward Hunt Ice Shelf, where the discrepancy between the two datasets was 53.4 km2. Unlike the inventory by Mueller and others (2017a, b), our outlines of Ward Hunt do not exclude any of the small ice rises on the eastern half of the ice shelf. In comparing the remaining ice shelf extents, the difference in area measurements does not exceed 4.3 km2.

An inventory describing the distribution of surge-type glaciers across the Canadian High Arctic was generated by Copland and others (2003), and included Northern Ellesmere. Copland and others (2003) used 1959/60 aerial photographs and 1999–2000 Landsat 7 imagery to visually identify potential surging glaciers based on the presence of surface features (e.g. looped medial moraines, intense folding, heavy crevassing and rapid advance) consistent with surge activity. The findings identified eight possible surge-type glaciers across Northern Ellesmere, four likely surge-type glaciers and one observed surge. The observed surge was from Otto Glacier (G82716W81419N), a glacier that was reported to have surged between 1950 and 1959 (by Hattersley-Smith, 1969) and continued to surge or surge again by 1999 (Copland and others, 2003). An active surge was also reported for the Milne Glacier from 1966 to 1983, when the glacier advanced by 4.25 km at a rate of 250 m a−1 (Jeffries, 1984). Based on the recent surge activity of the Otto and Milne Glaciers, it is possible that the losses reported in our study (22.54 and 19.48 km2, respectively) may be linked to the quiescent phase of their surge cycles. If all 13 of the glaciers identified by Copland and others (2003) as being surge-type retreated solely as a result of surge behaviour, then this would account for 10.9% of the area changes determined across Northern Ellesmere in our study. However, the actual area changes attributable to surging are likely much less than this as only Otto and Chapman glaciers are known to have surged during the period 1999–2015 (Van Wychen and others, 2016).

4.2. Loss of small ice caps

Based on the terrain analysis presented in Section 3.3, the largest area changes occurred from small, low elevation glaciers. Separated by size class, the largest area changes occurred from land-terminating glaciers that were <1 km2, with a mean loss of 30.4% decade−1 (Fig. 6). Based on the results from Sharp and others (2014), this trend was also apparent on Northern Ellesmere between ~1960 and ~2000, when 218 glaciers <1 km2 and 1–5 km2 in size had the highest mean losses of 29.2% (0.73% decade−1) and 25.6% (0.64% decade−1), respectively. For the other size classes described by Sharp and others (2014), losses ranged from 22.2% for glaciers 5–10 km2 in area, decreasing to 2% for glaciers >10 000 km2. Sharp and others (2014) also noted this trend on Agassiz Ice Cap, Prince of Wales Icefield, South Ellesmere Island, Axel Heiberg Island and Devon Island. Similarly, Thomson and others (2011) described a trend of significant retreat of small independent ice masses on Axel Heiberg Island, which included ice caps <25 km2, along with the complete disappearance of 90% of ice masses smaller than 0.2 km2 over the period 1958–2000.

Braun and others (2004) examined the mass balance and area fluctuations of four ice caps on the Hazen Plateau of Northern Ellesmere from 1959 to 2002, including the St. Patrick Bay (also in our study; Fig. 2), Murray and Simmons Ice Caps. In their study, the substantial loss observed from these small ice caps was attributed to low winter snow accumulation, the absence of ice flow and small vertical relief. Braun and others (2004) described these small ice masses as relicts of the Little Ice Age, no longer sustainable in the current climate as the ELA rises above their summits (>1103 m). Rising ELAs have also been observed in the mass-balance records of White Glacier, Axel Heiberg Island, the nearest long-term mass-balance monitoring site to Northern Ellesmere (Fig. 1). If the ELA at the start of our study period in ~1999 ascended as much as the ~200 m rise in ELA recorded at White Glacier since 1999 (Thomson and others, 2017), then 60.2% of the regional glacier cover across Northern Ellesmere would be in the ablation zone (AAR = 0.398), and 589 (33.3%) glaciers would be completely below the ELA. According to Dyurgerov and others (2009) most glaciers with balanced regimes will have an AAR of ~0.40 to 0.80, which would suggest that Northern Ellesmere is out of balance with the current climate. If the ELA were to rise 300 m, 940 (53.2%) glaciers would be completely below the ELA and the regional AAR would only be 0.277 (Fig. 10).

Serreze and others (2017) described the continued loss of the Hazen Plateau ice caps up to 2016, and revealed that the St. Patrick Bay Ice Caps only had 5% of their 1959 area remaining (10.42 km2 in 1959 vs 0.50 km2 in 2016). The authors noted that the ice caps even shrank noticeably between 2014 and 2015, in direct response to the particularly warm summer of 2015. The rapid loss of these ice caps was also attributed to the more pronounced appearance of dirt layers on the ice surface, leading to a decrease in summer surface albedo. In 2016 the Murray and Simmons ice caps still had 39% and 25% of their 1959 ice areas remaining, respectively, which was linked to their higher mean elevations (up to ~290 m higher), thus providing relatively cooler summer conditions.

4.3. Loss of floating glacier termini

Between 1999 and 2015, there was a marked loss in floating glacier termini, including the loss of 18 ice tongues, the complete loss of the Ayles and Markham ice shelves, and substantial decreases in the Serson and Ward Hunt ice shelves. Unlike land-terminating glaciers that typically shrink gradually under atmospheric forcing, marine-terminating glaciers and ice shelves are subject to oceanographic forcing and can lose mass rapidly through calving.

Detailed studies have been conducted on several Arctic ice shelves, including the Petersen and Ayles, that document the events leading up to calving events (Copland and others, 2017). In the study by White and others (2015), the Petersen Ice Shelf is shown to have undergone a series of calving events between 2005 and 2012, during record high summer temperatures, that resulted in a ~61% loss in ice area. The calving events were initiated by the loss of >50-year-old multi-year landfast sea ice (MLSI) that fringed the ice shelf front in 2005, and by open water events in 2008, 2011 and 2012. White and others (2015) also reported that in situ thinning and pre-existing fractures in the ice shelf would have weakened it, thus allowing ice islands to separate from the ice shelf during open water events and drift away. Copland and others (2007) described the conditions leading to the complete collapse of the Ayles Ice Shelf in August 2005 that resulted in it calving within the space of a few hours and producing an 87.1 km2 ice island. Similar to the Petersen, Copland and others (2007, 2017) reported that this collapse was initiated by record high summer temperatures in 2005, and by the loss of landfast sea ice that had previously fringed the ice shelf. Copland and others (2007) also reported that high offshore winds occurred during the event.

For marine-terminating glaciers with floating termini, the presence of ice mélange and sea ice provides a seasonally dependent stabilizing mechanism that allows the termini to remain intact and possibly advance (Reeh and others, 2001; Pimentel and others, 2017). This has been evident with ice tongues composed of agglomerated ice blocks such as at the front of Jakobshavn Isbrae, Greenland (Amundsen and others, 2010). During winter, sea ice forms and binds the ice mélange and prevents glacier calving, while the retreat of sea ice in spring causes the mélange to weaken and calving to recommence. Todd and Christoffersen (2014) examined the calving dynamics of Store Glacier in West Greenland and found that the presence of ice mélange was principally responsible for the observed seasonal advance of the terminus.

These factors may have also played an important role in the loss of the floating ice tongues observed in this study, particularly in Yelverton Inlet and Bay where several ice tongues disappeared over the study period. According to Pope and others (2012), 932.6 km2 of MLSI occupied Yelverton Inlet and Bay, including Kulutingwak Fiord in 1959. By August 2005, ~330 km2 of MLSI broke away from Yelverton Bay and was soon followed by the fragmentation of 690 km2 of older MLSI from Yelverton Inlet. In summer 2008 fragments of MLSI in Yelverton Bay and Kulutingwak Fiord broke apart and drifted away. In summer 2010 the last remaining plug of MLSI in Yelverton Inlet broke away, along with sections of MLSI from Kulutingwak Fiord. The loss of MLSI from this region means that the glaciers flowing into this system would then be exposed to an entirely new environment consisting of open water and young, thinner sea ice. It is likely that the loss of the floating ice tongues was a direct response to the loss of the back pressure previously provided by the thick and semi-permanent MLSI cover.

According to our observations between ~1999 and ~2015, regional ice coverage has decreased by 5.89% (3.68% decade−1) over the 16-year study period. This equates to an area loss of 822 km2 decade−1. From 1948–2016, the highest rate of warming occurred during fall and winter at 0.74 and 0.65°C decade−1, respectively. Although summer showed the lowest rate of temperature increase (0.24°C decade−1), the change in the mean summer temperature over time has resulted in a change from mean negative temperatures to mean positive temperatures since 2007 (with the exception of 2014). There is evidence for a small increase in precipitation over time on Ellesmere Island at Eureka (~10% between 1961 and 2007; Lesins and others, 2010), but this is insufficient to compensate for the rapid recent increase in air temperatures.

Recent area losses from some glaciers, such as the Milne (G78878W82327N) and Otto (G82716W81419N), could be explained by retreat during quiescent periods after potential surge-type behaviour observed over past decades (Hattersley-Smith, 1969; Jeffries, 1984; Copland and others, 2003), but this is likely much <10% of the regional total. Two main trends for the remaining glaciers include the rapid loss of small, low elevation land-terminating glaciers and the loss of floating glacier termini in the form of ice tongues and ice shelves. The loss of small glaciers is a trend that has continued since the 1950s, and has been observed in other regions across the CAA as well (Braun and others, 2004; Thomson and others, 2011; Sharp and others, 2014; Serreze and others, 2017). Our analysis also revealed the complete loss of three small ice caps. The increased loss of small ice caps on Northern Ellesmere can be attributed to their increased sensitivity to the accelerated warming in the region, and the decrease in their surface albedo due to the accumulation of surface debris (Serreze and others, 2017). Small glaciers with relatively higher mean elevation are slightly less sensitive due to their cooler summer temperatures at high altitudes (Serreze and others, 2017). This is apparent in our study, where for land-terminating glaciers <10 km2, glaciers with mean elevations <700 m had a mean loss of 25.7% decade−1 whereas glaciers with mean elevations >700 m had a mean loss of 16.0% decade−1.

Over our 16-year study period, there was a substantial change in the amount of floating ice. Ice shelves lost ~42.4% of their initial ice area, including the complete loss of the Ayles Ice Shelf (−83.5 km2) and nearly the complete loss of the Serson Ice Shelf (−184.0 km2). Our inventory also identified the loss of 18 floating ice tongues, causing these marine-terminating glaciers to retreat to their grounding lines. Past studies have linked the loss of ice shelves to warmer summer temperatures, offshore winds and the loss of the protective barrier created by MLSI (Copland and others, 2007, 2017; White and others, 2015). These factors may have also played an important role in the loss of floating ice tongues observed in this study, particularly in Yelverton Inlet and Bay where several ice tongues have disappeared since the loss of MLSI in this region in summers 2008 and 2009 (Pope and others, 2012).

This study demonstrates that the icescape of Northern Ellesmere is changing and, if current temperatures persist or continue to increase, small ice caps will be the first to vanish and coastal zones will become free of floating glacier termini and ice shelves. If the ELA has risen by 300 m since 1960 levels, which seems possible given the rapid recent changes recorded by mass-balance programs on other nearby ice caps, then >50% of glaciers are currently completely in the ablation zone. It is important that regional inventories such as this one continue to be created and updated to monitor changing glacial landscapes in a warming climate.

This work was funded by grants from the Natural Sciences and Engineering Research Council (NSERC) of Canada, Canada Foundation for Innovation, University of Ottawa, Polar Continental Shelf Program, the Royal Canadian Geographic Society and ArcticNet, a Network of Centres of Excellence of Canada. We would like to acknowledge the Polar Geospatial Center (University of Minnesota) for providing early access to the ArcticDEM. Adrienne White was supported by graduate scholarships from NSERC, the Ontario Graduate Scholarship, the Association of Canadian Universities for Northern Studies, the Garfield Weston Foundation and awards from the Northern Scientific Training Program.

Abdalati, W and 9 others (2004) Elevation changes of ice caps in the Canadian Arctic Archipelago. J. Geophys. Res., 109(F04007) (doi: 10.1029/2003JF000045)
Amundsen, JM and 5 others (2010) Ice mélange dynamics and implications for terminus stability, Jakobshavn Isbrae, Greenland. J. Geophys. Res., 115(F1) (doi: 10.1029/2009JF001405)
Andrews, JT (2002) Glaciers of Baffin Island. In Williams, RS Jr and Ferrigno, JG eds. Satellite Image Atlas of the World, U.S. Geological Survey Professional Paper, 1386-J-1, J165J195. United States Government Printing Office, Washington
Braun, C, Hardy, DR and Bradley, RS (2004) Mass balance and area changes of four High Arctic plateau ice caps. Geogr. Ann., 86A(1), 4352 (doi: 10.1111/j.0435-3676.2004.00212.x)
Burgess, DO (2017) Mass balance of ice caps in the Queen Elizabeth Islands, Arctic Canada: 2014–2015. Geol. Survey Canada, Open File 8223, 38 p. (doi: 10.4095/300231)
Copland, L (1998) The use of terrain analysis in the evaluation of snow cover over an alpine glacier, In Lane, SN, Richards, KS and Chandler, JH, eds. Landform Monitoring, Modelling and Analysis. John Wiley & Sons, Chichester, 385404
Copland, L, Sharp, M and Dowdeswell, J (2003) The distribution and flow characteristics of surge-type glaciers in the Canadian High Arctic. Ann. Glaciol., 36, 7381
Copland, L, Mueller, DR and Weir, L (2007) Rapid loss of the Ayles Ice Shelf, Ellesmere Island, Canada. Geophys. Res. Lett., 34(21), L21501 (doi: 10.1029/2007GL031809)
Copland, L, Mortimer, C, White, A, Richer McCallum, M and Mueller, DR (2017) Factors contributing to recent Arctic ice shelf losses. In Copland, L and Mueller, D, eds. Arctic Ice Shelves and Ice Islands, Springer, Dordrecht, 263286
Dowdeswell, JA and Jeffries, MO (2017) Arctic ice shelves: an introduction. In Copland, L and Mueller, DR, eds. Arctic Ice Shelves and Ice Islands, Springer, Dordrecht, 321
Dyurgerov, M, Meier, MF and Bahr, DB (2009) A new index of glacier area change: a tool for glacier monitoring. J. Glaciol., 55(192), 710716
Hall, DK, Baa, KJ, Schöner, W, Bindschadler, RA and Chien, JYL (2003) Consideration of the errors inherent in mapping historical glacier positions in Austria from the ground and space (1893–2001). Remote Sens. Environ., 86, 566577
Harig, C and Simons, FJ (2016) Ice mass loss in Greenland, the Gulf of Alaska, and the Canadian Archipelago: seasonal cycles and decadal trends. Geophys. Res. Lett., 43(7), 31503159 (doi: 10.1002/2016GL067759)
Hattersley-Smith, G (1969) Recent observations on the surging Otto Glacier, Ellesmere Island. Can. J. Earth Sci., 6(4), Part 2, 883889
Jeffries, MO (1984) Milne Glacier, Northern Ellesmere Island, N.W.T., Canada: a surging glacier? J. Glaciol., 30(105), 251253
Jenson, SK and Domingue, JO (1988) Extracting topographic structure from digital elevation data for geographic information analysis. Photogramm. Eng. Remote Sens., 54(11), 15931600
Kalnay, E and 21 others (1996) The NCEP/NCAR Reanalysis 40-year project. B. Am. Meteorol. Soc., 77(3), 437471
Koerner, RM (2005) Mass balance of glaciers in the Queen Elizabeth Islands, Nunavut, Canada. Ann. Glaciol., 42, 417423
Lesins, G, Duck, TJ and Drummond, JR (2010) Climate trends at Eureka in the Canadian high Arctic. Atmos. Ocean, 48(2), 5980 (doi: 10.3137/AO1103.2010)
Maxwell, JB (1981) Climatic regions of the Canadian Arctic islands. Arctic, 34(3), 225240
Miller, GH, Bradley, RS and Andrews, JT (1975) The glaciation level and lowest equilibrium line altitude in the high Canadian Arctic: maps and climatic interpretations. Arct. Alpine Res., 7(2), 155168 (doi: 10.2307/1550318)
Mortimer, CA, Sharp, M and Wouters, B (2016) Glacier surface temperatures in the Canadian High Arctic, 2000–15. J. Glaciol., 62(235), 963975 (doi: 10.1017/jog.2016.80)
Mueller, DR, Copland, L and Jeffries, MO (2017a) Northern Ellesmere Island ice shelf and ice tongue extents, v. 1.0 (1906–2015). Nordicana, D28 (doi: 10.5885/45455XD-24C73A8A736446CC)
Mueller, DR, Copland, L and Jeffries, MO (2017b) Changes in Canadian Arctic ice shelf extent since 1906. In Copland, L and Mueller, DR, eds. Arctic Ice Shelves and Ice Islands, Springer, Dordrecht, 109148
Pfeffer, WT and 18 others and the Randolph Consortium (2014) The Randolph Glacier Inventory: a globally complete inventory of glaciers. J. Glaciol., 60(221) (doi: 10.3189/2014JoG13J176)
Pimentel, S and 7 others (2017) Modelling intra-annual dynamics of a major marine-terminating Arctic glacier. Ann. Glaciol., 58(74), 118130 (doi: 10.1017/aog.2017.23)
Pope, S, Copland, L and Mueller, D (2012) Loss of multiyear landfast sea ice from Yelverton Bay, Ellesmere Island, Nunavut, Canada. Arct. Antarct. Alp. Res., 44(2), 210221 (doi: 10.1657/1938-4246-44.2.210)
Raup, B and Khalsa, SJS (2010) GLIMS analysis tutorial. National Snow and Ice Data Center, Boulder, CO,
Reeh, N, Thomsen, HH, Higgins, AK and Weidick, A (2001) Sea ice and the stability of north and northeast Greenland floating glaciers. Ann. Glaciol., 33(1), 474480 (doi: 10.3189/172756401781818554)
Serreze, MC, Raup, B, Braun, C, Hardy, DR and Bradley, RS (2017) Rapid wastage of the Hazen Plateau ice caps, northeastern Ellesmere Island, Nunavut, Canada. Cryosphere, 11, 169177 (doi: 10.5194/tc-11-169-2017)
Sharp, M and 12 others (2014) Remote sensing of recent glacier changes in the Canadian Arctic. In Kargel, JS, Bishop, MP, Kaab, A, Raup, BH and Leonard, G, eds. Global Land Ice Measurements from Space: Satellite Multispectral Imaging of Glaciers. Springer-Praxis. Springer-Verlag, Berlin, Heidelberg, 205228 (doi: 10.1007/978-3-540-79818-7_9)
Thomson, LI, Osinski, GR and Ommanney, SL (2011) Glacier change on Axel Heiberg Island, Nunavut, Canada. J. Glaciol., 57(206), 10791086 (doi: 10.3189/002214311798843287)
Thomson, LI, Zemp, M, Copland, L, Cogley, JG and Ecclestone, MA (2017) Comparison of geodetic and glaciological mass budgets for White Glacier, Axel Heiberg Island, Canada. J. Glaciol., 63(237), 5566 (doi: 10.1017/jog.2016.112)
Todd, J and Christoffersen, P (2014) Are seasonal calving dynamics forced by buttressing from ice mélange or undercutting by melting? Outcomes from full-Stokes simulations of Store Glacier, West Greenland. Cryosphere, 8, 23532365 (doi: 10.5194/tc-8-2353-2014)
Van Wychen, W and 6 others (2016) Characterizing interannual variability of glacier dynamics and dynamic discharge (1999–2015) for the ice masses of Ellesmere and Axel Heiberg Islands, Nunavut, Canada. J. Geophys. Res.-Earth, 121(1), 3963 (doi: 10.1002/2015JF003708)
White, A, Copland, L, Mueller, D and Van Wychen, W (2015) Assessment of historical changes (1959–2012) and the cause of recent break-ups of the Petersen Ice Shelf, Nunavut, Canada. Ann. Glaciol., 56(69), 6576 (doi: 10.3189/2015AoG69A687)
Williams, RS, Hall, DK, Sigurđsson, O and Chien, JYL (1997) Comparison of satellite-derived with ground-based measurements of the fluctuations of the margins of Vatnajökull, Iceland, 1973–92. Ann. Glaciol., 24, 7280
Wolken, GJ, England, JH and Dyke, AS (2008) Changes in late-neoglacial perennial snow/ice extent and equilibrium-line altitudes in the Queen Elizabeth Islands, Arctic Canada. Holocene, 18(4), 615627 (doi: 10.1177/0959683608089215)


Invited Lecture (JGES)
November 3 (Thu.), 14:00–14:40, Room 7 (Portopia Hotel Main Building Kairaku 1)
Invited Lecture-5

Functional disorder of the proximal gastrointestinal tract

J. Tack
Functional gastrointestinal disorders (FGIDs), although highly common, are relatively poorly understood and difficult to manage in clinical practice. The Rome consensus has classified these disorders into organ regions (i.e., esophageal, gastroduodenal, bowel, biliary, anorectal), presuming that there are unifying features underlying diagnosis and management that relate to these organ locations. Individual disorders are diagnosed based on symptom groupings. The link between symptoms and organ location is mainly based on expert consensus. The previous Rome I-III consensus documents generated authorative criteria for diagnosing, studying and treating FGIDS. The latest iteration of this process is the Rome IV consensus on diagnostic criteria for FGIDS, just presented last May 2016. As a general important innovation, thresholds for frequency of symptoms in Rome IV now have a scientific basis: the Rome foundation conducted a Normative Symptom Study to allow the development of thresholds for symptoms based on evidence.

In a first part, the major changes with Rome IV will be highlighted. The functional esophageal disorders were thoroughly revised taking into account new diagnostic entities that need to be excluded (eosinophilic esophagitis) and new technological developments to detect other diseases (high resolution manometry and esophageal pH impedance monitoring). In addition, in Rome III, "Functional Heartburn" defined heartburn symptoms in the absence of evidence that the symptom is associated with gastroesophageal reflux. However, there are also patients who have normal acid reflux levels, but who are sensitive to this physiological reflux and so develop heartburn. For Rome IV, "Reflux Hypersensitivity" characterizes this entity and is to be differentiated from functional heartburn and from classic non-erosive reflux disease with pathological acid exposure. Since the Rome III consensus, FD was subdivided into epigastric pain syndrome (EPS) and postprandial distress syndrome (PDS). PDS is characterized by postprandial fullness and early satiation) while EPS is characterized by epigastric pain and burning. The Rome IV subdivision has used the same principles for defining EPS and PDS, but aimed at decreasing the overlap by taking into account postprandial occurrence of EPS symptoms and nausea. Current evidence shows that this has a favorable impact on the overlap issue. For Rome IV the new diagnosis "Chronic Nausea Vomiting Syndrome" combines the previous Rome III entities "Chronic Idiopathic Nausea" and "Functional Vomiting." The rationale for combining the two diagnoses relates to the paucity of data delineating differences in diagnostic approach and management of nausea compared to vomiting, and the clinical observation that these symptoms are commonly associated.

In the second part, clinical application in diagnostic-therapeutic algorithms will be illustrated for several of these disorders.
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Ice Nine Kills

East Coast Collective presents

Ice Nine Kills

The Plot in You, Dayseeker, Carousel Kings, Basilisk, Awake At Last

Tue 11/28

5:30 pm

$13.60 - $18.00

This event is 16 and over

Ice Nine Kills
Ice Nine Kills

The Plot in You
The Plot in You

Carousel Kings
Awake At Last
Every day presents us with a choice; to keep our passions as mere dreams, or to chase after those dreams until they become a reality. For the Dover, Delaware rock band, Awake At Last. that decision has always come with a cost, but, is one they are willing to pay. The band was formed with the purpose of leaving a positive imprint in a dark world. Every time they take the stage, they are answering the call to live out their dreams, all while encouraging others to do the same. ”Our goal is to inspire people to live fulfilling lives”, vocalist, Vincent Torres, explains, “so many people get caught up in how our society says they should be perceived, but I think our real purpose is to do what actually fuels our soul.“ No stranger to the road, the band relentlessly toured behind King Of The World, playing over 200 shows in support of the release. This gained them the reputation of being a hard working, highly energetic live band and also built up a significant social media following for the band. During this time the band was named one of the “7 Underground Bands You Need To Hear” by Alternative Press magazine and began writing Life/Death/Rebirth.
Venue Information:
Revolution Bar and Music Hall
140 Merrick Road
Amityville, NY, 11701


Targeted Therapies A Sustainable

Business Model

Erik Tambuyzer,  Senior Vice President Corporate Affairs Europe and International Genzyme Corporation Belgium

Personalised medicine breaks the cycle of trial and error medicine and helps ineffectiveness rates of medicines to decrease dramatically. Orphan drugs, targeted therapies for rare diseases, with their innovative nature and improved efficacy, make it a precursor for personalised medicine therapies and can offer a viable business model to expand from. Society should develop consensus for such new models in multi-stakeholder partnerships which will also make it sustainable.

For many rare diseases, there is as yet no satisfactory treatment. Rare diseases are defined as life-threatening and / or serious and chronic diseases, according to the European Orphan Medicinal Products regulation. These diseases represent a high unmet medical need. Rare diseases, with their genetic origin and because of small number of patients to be treated, require effective diagnosis linked to treatment. So, orphan drugs, with their targeted nature, are of immense use and could pave the way for future developments in healthcare

Since 70 to 80 per cent of rare diseases are genetic in origin, the right diagnosis before treatment is of high importance to ensure that the patient not only gets the right treatment but also does not suffer from side effects. The rarity and severity of the diseases not only mean lesser patients are treated but also result in a high compliance because the medicines work. Rarity also leads to higher costs, but orphan drugs also have a higher innovative nature and a higher benefit than average drugs through their better clinical efficacy and effectiveness. In the European definition, orphan drugs are unique treatments, meaning there are no alternatives available. This is the case for about one-third of the orphan drugs approved in Europe) or make a better therapy over (an) existing one(s), which is the case for the other two-thirds of approved orphan drugs in Europe. Not only economic factors but social benefits also need to be taken into account as well: many patients affected by rare diseases had no therapy available before and such therapy is often a first in human history.

Innovation, rarity and complexities caused

The current debate in society is about the value of innovation in healthcare: our society supports such beneficial or valuable innovation to the benefit of patients, including those in the case of orphan drugs. Even in difficult economic times, such beneficial innovation must be encouraged and the resulting products must be reimbursed when they have measurable and demonstrable value. However, given the rarity of the diseases studied, sufficient time to gather data to show such value must be granted.

In order to understand the concept of rarity, Figures 1 and 2 provide the number of patients treated in the US in 2006 for a number of non-rare disease and, from Gleevec (Glivec TM) downwards, for rare diseases.

The application of models used in health economics introduces further challenges to the development of orphan medicines and to the discussion about their reimbursement.

Cost-Effectiveness = Cost / Effectiveness, where cost is raised by rarity, but data to calculate effectiveness are limited by rarity. Therefore, rarity is affecting both the factors of the equation making the outcome much more uncertain as it grows.

Based on this, it has to be clear that cost-effectiveness cannot be the only decisive factor. Current definitions of health technology assessment, therefore, include other factors such as equity, fairness, ethics and social values. Politicians need to take responsibility to reward innovations in this field to allow them to happen and to continue.

As shown by the consultancy company Alcimed in a report for the European commission in 2004, pricing is a function of the rarity of the treated disease. Therefore, the prices of orphan drugs, given that their development cost is not necessarily lower than the cost to develop a medicine for a common disease, will be higher than the prices of drugs for treating a (more) common disease. As such, prices largely depend on the patient population to be treated. As a consequence, the application of the same rules of cost-effectiveness for orphan drugs, and especially for drugs for very rare diseases, will not be appropriate, as this would result in orphan drugs and even more clearly the so-called ultra-orphan drugs being excluded from reimbursement since they often do not reach the required Quality Adjusted Life Year (QALY) limit.

The future of personalised medicine
Further, drawing the analogy with personalised medicine, a future with more compliance and far less side effects would be the goal. This will ultimately result in costs going down, as only the right medicine would reach the right patient and minimise side effects. In order to do that, the following series of questions need to be answered:

  • Which medicine should I use?
  • How much of the medicine do I need?
  • Is the medicine working?
  • Is my disease controlled or gone?

The old paradigm of trial and error medicine, based on the sequence of an observation with an action followed by an observable response is only successful when it leads to innovation and improved standard of care. But it fails when we settle for “trial and error” medicine as the standard of care. The new paradigm of personalised medicine links diagnostic tests to action and therapy. This happens by having an observation confirmed by a test and have it followed by appropriate physician actions which will result in a predictable response, that breaks the cycle of trial and error medicine and helps the patient. Personalised medicine leads to the right drug for the right patient. It results in providing benefits without toxicity. It saves patients from the treatment that would have the benefits but with the toxicity of the medicine if any. Also, it excludes them from the treatments that would have no benefits and no toxicity, and, of course, also from those without any benefits but with toxicity.

As shown in Figure 3, the current ineffectiveness rate of medicines is ranging from 40 to 75 per cent, but this percentage will dramatically decrease with the venue of personalised medicine.

No future without challenges
The current evolution in evidence-based medicine also comes with challenges:

  •  Physicians are being overwhelmed by the volume of the available data, so, they need more tools to identify and track test / drug combinations, as well as need more education on diagnostics and genomics. They also need more treatment guidelines and are organising themselves into expert centres. They may carry an increased liability risk confronted with patients who are more vocal, informed and organised.
  • Diagnostic testing laboratories perform intense data acquisition, with high manipulation and storage requirements, while they face complex reimbursement challenges with new technologies coming into routine practice. They also face issues based on expanded intellectual property portfolios and enjoy an increased focus and scrutiny from all parts of the healthcare community.
  • Payers face difficulties to follow the rapid evolution of the diagnostics / genetics field, but, demand evidence-based medicine. They also want to make payment conditional on drug effectiveness, but face challenges as we have discussed above. Payers fund their own databases on patient outcomes, which they usually don’t share with other stakeholders. In demanding tests for evidence-based medicine, they require the providers to prove the relevance of such tests to the patient and the physician.
  • Regulators face increased concerns about safety of medicines, and need to remain up-to-date on the new technologies. Such new technologies may bring along the need for adaptive clinical trials as many new insights are gained while the trials progress.
  • Industry is facing vastly increasing costs driven by the increased demand for data and ever more complex clinical trials, while at the same time facing downward pressure on prices and a more complex reimbursement negotiation process.

The only solution to such complex societal problems and in order to build new healthcare systems for the future is to be found by the creation of multi-stakeholder partnerships to develop consensus on the way forward. This should result in a wheel of sustainability: life-saving treatments provide a better patient outcome, which warrants reimbursement, and as a consequence, rewards risk-taking and provides return on investment, which in turn leads to more investment in risky projects, resulting in more effective treatments coming onto the market. Clearly, having a market for personalised medicines is in the society’s best interest. We must all work on making it happen!

As the public image of the pharmaceutical industry is challenging, better and clearer communication is needed to explain the contributions it makes to society. And while no company on its own can change the sector’s image, industry must work together. Personalised medicine represents a great opportunity to change public image of the industry for the better!

Author Bio

Erik Tambuyzer

Erik Tambuyzer is Senior Vice President of Corporate Affairs Europe and International at Genzyme Corporation. He is a founding Board member and past Chairman of EuropaBio, the European Association for Bioindustries, and founder of its Ethics Working Group, as well as the Chair of the EBE / EuropaBio Rare Diseases and Orphan Drugs Task Force.