 So, we're here to discuss another aspect of fossil fuels that we haven't talked so much about yet. And it's the other impacts that are not emissions really related, right? And these questions, these broader societal questions linked to fossil extraction and the transitions away from fossil extraction. So, we're going to focus on social economic and health impacts. And we have a great panel here with us. And we'll just go through all the presentations, keep your questions, and we'll have the discussion at the end. And we will start with Ploy Achakulvisut from the Stockholm Environment Institute. Today I'm excited to share some preliminary results from a project I've been leading to quantify the health impacts and inequities of air pollution from oil and gas production and use in the United States. And, you know, we're a bit behind with the modelling, so these are very preliminary results. So please temper your expectations. And I'd like to also acknowledge all of my collaborators listed here, especially Kahn Bora, who's a post-doctoral researcher at UCL, who's led most of the modelling to date and the kind of results I'll be showing today. Okay, so there's really been two main sources of motivation for this work. The first came from actually having worked on the production gap analysis over the past three years at SEI, where we track the levels of fossil fuel production being planned by governments worldwide and those consistent with achieving the Paris Agreement. And this made me realise that actually from a pure technical climate perspective there are many different fossil fuel face down pathways that can be consistent with achieving net zero emissions. But of course this line of thinking completely ignores all the public health and environmental harms of continued oil and gas extraction that we've been hearing over the past two days as well and doesn't highlight the impacts being borne by industry workers and local frontline communities. And so I hope with this project that by being able to start assigning some concrete numbers to these impacts, we can help to compel the case for accelerating the face-out of fossil fuels in line with climate goals. So the second source of motivation really comes from my own academic background in air pollution and public health. We know we have enough evidence now to know that exposure to air pollution essentially harms every major organ system in the body. It can cause exacerbate many adverse health conditions and increase the risk of premature deaths in many, many regions of the world. And to date there have been numerous studies to quantify what we call like the burden of disease attributable to air pollution mainly from burning fossil fuels so at the end use stage. But so far there's been very limited studies focusing on the production stages of oil and gas and this is partly due to at least in the US the fact that oil and gas development sites have historically been situated in more remote and rural areas but over the past two decades advancements in horizontal drilling and hydraulic fracturing technologies have really brought unconventional oil and gas developments closer to a lot more people and it's estimated that about 18 million people, 5% of the US population now live within about a mile of at least one active oil or gas well. And we know that emissions of air fusions can occur along the whole oil and gas supply chain. So this figure kind of just lays out some of the terminology I'll be using today. So for example from the upstream stage of production you have well drilling, venting and flaring processes. In the midstream you can have leaks from transmission pipelines and storage tanks and gas compressor stations and of course oil refining into petrochemicals really significant amounts of air pollution and of course the end use of burning stage that we know releases a lot of emissions. So all these stages release what are known as criteria pollutants including fine particulate matter or PM2.5 as well as nourishing oxides and volatile organic compounds which are themselves harmful and will then further react in the atmosphere to create more PM2.5 as well as ozone that have a slew of adverse health outcomes increasing the risk of lung and heart disease, fertility problems, neurological problems, increasing the risk of premature death. And you know I think over the past few decades the scientific community is really starting to quantify and understand all of the harmful health impacts arising not just from air pollution but water, radioactive, hazardous waste, also nonchemical stressors like light and noise pollution from oil and gas production but the kind of research is I think relatively nascent and limited in terms of temporal and regional coverage and we don't really yet have enough evidence to derive the statistical relationships that are needed to perform what's called health impacts assessments in the epidemiological research to basically derive some of these numbers but I think that we can basically use the well-established relationships between certain pollutants and health outcomes like premature death from exposure to PM2.5 from all sources to begin to start to assign some numbers to the air pollution emissions arising from oil and gas production. So our research has three overarching questions. Firstly we want to understand how much do production activities contribute to local emissions of air pollution and then next we want to be able to quantify the burden of disease from three different aggregated stages of the oil and gas life cycle so the combined upstream and midstream stages, the downstream stage which is mainly aura-fining and obviously the end-use stage and we're planning on quantifying three different pollutant health outcomes PM2.5 and premature death, PM2.5 and preterm birth incidents and asthma exacerbation from NOx and finally we also want to investigate whether the exposures to these different pollutants vary between different groups based on race and income in the US and so far we've been able to conduct a pilot study focused on Texas, the largest oil and gas producing station in the US but we do plan to expand the whole analysis to the contiguous US. So yeah, today most of my results will be focused on Texas so looking at the first question we see that oil and gas production activities are a significant source of methane and non-methane volatile organic compounds leading to 65 to 90% of total anthropogenic emissions in Texas it's also a large source of NOx for PM the direct emissions are actually not so important in Texas it turns out there's a lot of dust, sea salt, aerosols and biomass burning happening in Texas but bear in mind that basically the VOCs and NOx can further react in the atmosphere to form more PM2.5 So looking at the second question so far we've been able to quantify the premature death burden attributable to PM2.5 that arises all along the oil and gas life cycle and I'm happy to go into the details of the health impacts assessments methods during the Q&A for anyone who's interested I'll just say that the kind of most resource intensive step of this calculation basically involves turning the emissions inventory into a modelled map of concentration so we want to understand how much people are actually exposed in a given grid cell and the data and model allows us to kind of do this at the finest resolution of around 30 kilometers so far and this chemical transport model takes months and months to run so it's quite a resource intensive step Okay so this plot shows the modelled PM2.5 concentrations over Texas from the three different stages of the life cycle that I showed so a lot of the PM2.5 dust mainly come from the end use so the burning stage for oil and gas in total these three stages contributes to around 8% of PM2.5 from all sources and then when we look at the premature death attributable to this exposure we find that around 4,000 deaths per year in 2017 are attributable to PM2.5 coming from oil and gas for the whole life cycle and about 18% of this is specific to the upstream midstream downstream production stages of the oil and gas life cycle So we've also modelled the resulting nitrogen dioxide concentrations from oil and gas and we actually see that for NO2 the production stages really contribute significantly to NO2 pollution we actually see kind of the NO2 lighting up in major producing basins like the Permian and Eagleford in southern Texas there on the left and all together this combined with the end use so a lot of that is coming from cars contributes to around 62% of all the NO2 pollution occurring in Texas and the next step would be to quantify the burden of asthma exacerbation and hospitalizations resulting from NO2 and I just wanted to give a very quick teaser of a test run we did at a course model resolution for the whole of the US so you know when you have production occurring in a given state the resulting pollution can spread to neighboring states neighboring countries like Mexico and Canada as well and the resulting health burden is also going to be influenced by how close people are situated to the sources of pollution so we're seeing some potentially really interesting results for California and Pennsylvania which are also big producing states and especially for California that's where there is a lot of people residential areas and close proximity to oil and gas developments so we're excited about this and obviously the final step will also be to try to examine whether there are different differentiated exposures and environmental justice implications for this and with that I'll just thank you very much for your attention. Hi and good afternoon. I'm very excited to present some joint work that I've been doing with Florian Eagley and Tobias Schmidt from the Energy Technology and Policy Group at ETH Syrac. This is a very practically applied work so we've been talking a lot about the need for re-enupskilling for the just transition in many of today's and yesterday's sessions and this is kind of a first attempt of creating a framework with which we can actually answer re-enupskilling questions at a granular level for different industries in different regions. Short table of contents. I'll give you a brief introduction. My research questions spend some time on a conceptual framework which first tries to classify occupations based on their emission intensity and then present free days out scenarios by which we look at different stages let's say of the green transition and then a framework for understanding how similar occupations are in terms of their skill requirements and what that actually means then for transition pathways from occupation that are at risk to different other target occupations. The results will mainly focus on Germany although we will have some results ready for other European countries as well and I'll present some findings about the social demographic characteristics of green and brown jobs and then some work where we simulate moving the entire German core workforce into let's say carbon neutral or low carbon jobs and how re-enupskilling can actually enable this transition. Right, so introduction. So the background right is this policy and part also economically driven transition to carbon neutral economy in the EU we have the European Green Deal in the US recently the Inflation Reduction Act has been passed and what the rationale is that we're going to see job destruction in high emission sectors and job creation in low emission sectors, right? If you look at the modeling studies and there's work from the ILO from CDFOP also from the academic literature there's a large consensus that overall in aggregate there's going to be net job creation, right? But what's very particular about the job destruction aspect is that it's very concentrated in certain industries and regions which creates a large political backlash. We've heard in many sessions about different just transition frameworks within the European Green Deal we have the just transition mechanism within that the finance and mechanism just transition fund of 40 billion dollars in the UK context there's the UK North Sea transition deal but an important question to answer and that's what I'm alluding to with these pictures is how transferable are the skill sets of for instance people working in the offshore oil and gas industry to offshore wind be it now in the UK or from coal miners to solar PV or are they going to move to entirely different jobs? That's one of the questions we're trying to answer here in research question two and the first one is actually where in terms of regions and sectors to address workers cluster and whether the sociodemographic characteristics or how can we target actually those people the most in need of policy support. So the first part of the conceptual framework is basically an exercise where we try to take an existing inventory of occupations the European ESCO classification which provides a mapping between occupations and skills it's very granular, involves around 3,000 occupations and 13,000 skills and we use so it's kind of this buzzword thing right what's a green job, what's a brown job there are many different indicators that you can use to to gather that question we try to use indicators at the sector level at the task level and the skill level so sector level would for instance be the pollution intensity of an industry and how pertinent concentration of workers in certain occupation is within that industry there is data on on green tasks for the US for instance so imagine installing solar panels as being a green task and you can look at the fraction of green tasks in oval tasks and it gives you kind of this share of greenness at the occupation level and there's also data on skills we try to combine all of this quantitative data and match it with expert assessments so bringing in experts on labour markets and the green transition and embedding both types of knowledge to then code all of these 3,000 occupations in the ripened context as either green so emission reducing and situated in key green economy sectors brown emission enhancing situated in high emission sectors usually and neutral occupations and we validate this with an expert survey as well so that's kind of part one of the conceptual framework another part of the conceptual framework are phase out scenarios so how many of these brown jobs that we coded are affected at which time and we have basically a low end, mid end and the high end scenario so the low end scenario is a coal phase out where we assume that all of those occupations that we coded as brown pertaining to the coal mining and coal-fired power production sectors are at risk and need to transition into other occupations the mid point scenario says well oil and gas also needs to phase out now in addition to coal but we have technological change allowing for the substitution of high fossil fuel input fuels and end of pipe solutions within a reasonable time frame and the last kind of high end scenario says that these technological options are not going to be viable in a reasonable time frame and then the last part of the conceptual framework pertains to this question of skills transferability so what you see here is for all of these 3000 occupations you see the number of overlapping skills for all of the possible combination of transitions between occupations so it makes sense that along the diagonal it's quite blue and we do see clusters along the diagonal but we also see clusters far off the diagonal so in between very different occupation groups and that's the last piece of information that we kind of need to get to answering this question of occupation transition pathways and skills transferability right and so what you can do with this matrix then is identify occupation transition pathways that are viable and we can also answer and try to answer the question of what effect does reenup skilling so if we add or if we have workers learning new skills this will change the let's say the blueness of these matrix right and how does this then change translate into the transition pathway question. On to the results so these are some results for Germany based on very granular survey data micro sensor survey data and one of the inequality questions that we have not really talked about in the sessions that I have attended so far is the divide along the gender dimension so what you can see here is that in neutral job categories primary the tertiary sector service sector is a very even distribution between males and females once we move to the green sector we see well it's mainly male a few more female workers in the brown sectors so we see there's a huge story there also in terms of promoting green jobs and making sure that this is equally attractive for both men and women a second piece of information here about the educational divide for neutral green and brown occupations so we see that there seems to be higher education requirements in green occupations in Germany so the share of workers with a bachelor's degree is twice the share in the brown sector and in a master's degree even three times the share and we see but that's also very pertaining to the German education system a large share has been trained in vocational education and training in the German lehren what you can see on the right these are some results at the EU level and basically it's a bit small but the box plots are spent by the share of brown jobs in each country and sector and we rank the kind of different sectors by the median share and we see the mining and quarrying sector coming out at the top followed by manufacturing so that kind of makes sense we see that there's a large spread between different European countries I'm going to go into the details there but we see there are on different trajectories towards within the green transition the second set of results is on transition options so what you can see on this map is basically the number of transition options out of brown jobs for at-risk workers in the co-phase out scenario that find jobs in green or neutral jobs that are similar enough to their existing skillset and we have workers choose among different options to move into the occupation that retains most of their wage with minimal wage loss the bluer the easier to transition and in this red part of Germany there are very few options and we see that there are differences depending on the industry from which workers transition out of so in the mining and quarrying sector this is much harder so we have on average one transition option that's viable per worker whereas in the electricity supply sector they have many more options sorry how does this translate into earnings losses so on this map shows the aggregated change in annual earnings in the year 2019 for workers moving out of coal into other jobs the thing in Germany is that there is a large wage premium on coal mining and jobs and large unionization rates so the question of how do you provide a similar income is very important here and again we see that there is difference between different regions pertaining to the economic structure and for different sectors as well we have now simulated the dissimulation where every worker was re-in-up-skilled with the skill that in this transition option space creates most additional pathways and what we see is that the map gets a lot bluer so retraining and rescaling workers in this sense tripled the amount of transition pathways out of brown jobs in our simulations and we see that now mining and quarrying workers are actually transition options on average and pertaining to earnings losses we also see that now it's a lot less red and some parts of it are blue so actually on aggregate in some regions there's more money being created and more taxes being paid and again we see that there's differences along the industry dimension let me close with the key message that we think that navigating the green transition really requires a granular understanding of impacts and we need to move beyond just knowing which sectors are affected by how many percent towards understanding changes at the occupation and scale levels and understanding them between different regions and sectors so we try to devise a classification of environmental impact dimension of occupations for the European context we find that the socio-demographic characteristics are largely in parallel to research findings that are out so far and we see this method of simulating transition pathways rescaling options merely as a tool I'm not saying that the numbers are spot on here it's really just a tool to think about different options recommendations for policy makers well, targets, policy support to those spotlight regions where we have not a lot of transition pathways and what we mean by skill smart we in upscaling is moving from industry to the scale level no coding courses for coal minus and Appalachia and the same goes for skill smart industry education thanks for your attention and I'll leave you with this check out our latest publication on this stream of work where we look into some conceptual thoughts thanks a lot thank you everybody it's a pleasure to be here at this fantastic conference so far my name is Tim Donagy I am the research manager for Greenpeace USA and I wanted to present on a report that we put out last year with some colleagues at the Gulf Coast Center for Law and Policy which has now rebranded themselves as Taproot Earth and the Movement for Black Lives and this is a report we did on what we call fossil fuel racism and you can find it online on our website and I just wanted to shout out some of my collaborators who helped put this together yeah, and to start off I just wanted to kind of dive in and say what do we mean when we talk about fossil fuel racism and I wanted to put this up here to say as Ploy was saying in her excellent presentation there's actually going to be a lot of overlap I think between what you were talking about and this each stage of the life cycles of oil gas and coal generates toxic air and water pollution so in addition to the greenhouse gases and at each stage approximately the public health hazards of this pollution disproportionately impact Black, Brown, Indigenous and poor communities and this is something that seems from the literature we've reviewed to be generally true there's of course some exceptions but as a good rule of thumb in the context of the United States this is sort of what's going on and you know for communities that live for folks to live in these communities they might look at this and say yeah, no duh you know like this is pretty obvious and I think you know the environmental justice movement I really want to shout out because they have been saying this for decades and they have been really instrumental in bringing the concept of environmental justice into the conversation around climate change and the science communities were finally catching up which is great and so obviously environmental justice is a very broad topic so it talks about some of the earlier fights for around incinerators and toxic waste dumps you can talk about access to nature in an environmental justice context so fossil fuel racism is sort of narrowing a little bit into the fossil fuel part of that because that gives us an overlap with climate policy so I kind of wanted to give a little bit of a taste of what we have in the report and what are the bigger questions about what does this mean for climate policy and what are the questions we should keep in mind as we're designing climate policies so just to go through a real quick cartoon version of fossil fuel life cycles we have basically three stages extraction, processing and transport thinking about oil refineries or natural gas processing and then finally combustion where the fossil fuels get burnt and that happens in a lot of different places and you can sort of see that this is obviously but pollution comes off from each of these stages in different ways and so from the combustion end we have sort of the carbon dioxide which is obviously what's driving the climate crisis and what a lot of the focus of climate policy is on and rightfully so but of course there's other greenhouse gases that are getting more attention including methane which comes from different parts of the fossil fuel life cycle and as Ploy was talking about we have criteria air pollutants including fine particulate matter one of the main ones of concern and one of the ones that's best studied but there's also something under the Clean Air Act in the US they call hazardous air pollutants and these often come from extraction sites or processing and transport sites and these include volatile organic compounds, VOCs, but also like the B-tex chemicals benzene toluene, eplobenzene and xylene are components of oil and gas and so they're sort of inevitably there when you have oil and gas happening and benzene is of course a carcinogen and so there's definitely like the potential for our health hazard from this and so our report we kind of go stage by stage and kind of look at what the literature says so for example as I'm going to go skip through this really quickly because Ploy already basically went through this in a lot more depth but the combustion in terms of criteria pollutants including fine particulate matter it's associated very strongly with a lot of health problems I think the connection with premature mortality is becoming close to being fairly well established epidemiologically and you know this is it's a big number when you look globally 4.5 to 8.7 million premature deaths in 2018 that's sort of pandemic level public health problem and in the context of the United States it's also clear that there's disproportionate impact a lot of studies have looked at PM2.5 and found that Black, Asian, Hispanic or Latino and low income populations have an elevated burden of exposure to fine particulate matter and this is this pattern is sort of consistent across different sources so if you're looking at coal-fired power plants if you're looking at you know exposure to freeways with traffic pollution you're seeing basically that there's a disproportionate impact among certain populations and in the context of the United States you know the Clean Air Act has been successful over the last decades which means that overall air pollution has gone down but the disparities have remained and just one statistic that I found fairly shocking was that the Black 65 and older population so African Americans who are elderly has a three times higher PM2.5 attribute old death rate so this is sort of you know very concrete harms that we're seeing due to largely due to the combustion of fossil fuels I want to dip in real quickly to another part of the fossil fuel life cycle looking at petroleum refining and as we saw you know this is you know there's definitely criteria air pollutants associated with oil refineries but often in many cases it's different pollutants that are associated with these and proximity to refineries leads to health risks both from normal operations but also oil refineries tend to have accidents and explosions there was a case in the Chevron refinery in Richmond, California about 10 years ago had an accident that sent about 10,000 people to the emergency room and some recent monitoring of EPA data shows that nearly half of all US refineries had benzene emissions at levels that could pose long-term health threats for surrounding communities I think you know the epidemiology around benzene emissions is not as well established as for fine particulate matter but you know this is a known carcinogen that's sort of being emitted into our communities seems like something we should look into and there's actually an interesting study of kind of a controlled experiment looking at a closure of a refinery where they were actually able to measure this in the community after the refinery closed down and just wanted to talk a little bit about some research we included in our report looking at the disproportionate impact of refineries so this scatterplot over here on the left is all 120 oil refineries in the US and the size of the dot is the size of the pollution essentially of toxic release inventory reported pollution so the bigger the dot the more polluting it is the next axis is how much that pollution impacts people of color minorities and the y-axis is how much it impacts poor people so you can see that there's a big cluster of US refineries that are in the sort of upper right-hand quadrant meaning that their you know their toxic pollution is disproportionately impacting both people of color and disproportionately impacting poor people and so and looking at the industry as a whole 56% whether toxic burden is born by minorities and 19% by poor people whereas in the US generally the red line shows sort of the national average where 39% of the US population is minorities so you can sort of see that each refinery is a little bit different but in general the industry is sort of weighted towards a disproportionate impact and then to talk a little bit about some of the context for you know why this happens for folks who are not from the US one of the things that we have in our history is the history of redlining and this has to do with going back to the 1930s and the new deal the federal government guaranteed housing loans for people basically to support them in buying a home but for certain neighborhoods you couldn't get a loan and this is a map of my hometown of Fresno California and you can see that the neighborhoods that are marked red here you know it was basically impossible to get a home loan and as a result it's sort of reinforced housing segregation and you can still see like someone from Fresno would be able to look at this map and be like yeah it's the same pattern today basically those same sort of demographic patterns have persisted for almost a century now and there's been a lot of really interesting studies looking at redlined areas and what what is the environmental consequences for pollution today so like generally speaking across the US an area that used to be redlined has more pavement, fewer trees it's about 2.6 degrees hotter due to the urban heat island effect 2.4 times higher rate of asthma emergencies and nearly twice the density of oil wells so there's sort of a dynamic going on here that's sort of concentrating or keeping pollution concentrated in these neighborhoods and then I just wanted to sort of close out with a couple questions about sort of what does this mean for climate policy and I think you know obviously addressing the climate crisis in general means using less fossil fuels so there's a huge opportunity here to reduce air pollution health risks and partly redress the sort of decades of environmental justice so we should see this as like a really positive thing you know like doing a good job on climate policy is going to help solve this problem a little bit but I want us to keep in mind some of these questions you know as we are doing this climate policy have we maximized public health gains as we reduce carbon emissions so you know because the scale of these harms is so big you know it's it's a good idea to make sure we're really trying to squeeze every last drop we can of public health benefit out of our climate policy and have we reduced sort of long-standing pollution disparities or are there hot spots that remain even as the sort of overall pollution levels go down I think in my mind I think about in the United States there's a place called Cancer Alley and I think you could imagine a situation where we stop using quite so much fossil fuels but that area remains polluted you know it's sort of as we you know phase out a little bit that remains a hot spot and the communities there remain suffering under sort of these public health harms so that's something to keep in mind you know is the transition going to be equitable when it comes to these health pollution impacts and then a question for us as a research community you know we have all these really great metrics around carbon you know the social cost of carbon many of these interesting studies we've heard about today around fossil fuel supply what research products are needed to better integrate these issues into policymaking so what do we need to know about air pollution to make sure it's in the front of the minds of our policy makers as they're making these decisions I'm really excited the work you're doing very very cool you know and I think as environmental justice advocates have pointed out many times there's a lot of climate solutions that get thrown out there and some of the ones that are kind of designed to sort of you know give a little bit of a lifeline to fossil fuels let them continue on for a little bit longer also have really potentially not great impacts on local air pollution so things like carbon offsets so it doesn't really do very much for the local community that might be suffering from this sort of air pollution impact carbon capture for enhanced oil recoveries another one there's you know sometimes you hear hype around carbon neutral oil but you know that oil is not going to be asthma neutral or cancer neutral necessarily and that's something that we should try to keep in mind as well yeah so and then just putting it together you know obviously this is a complicated you know policy question with lots of moving parts so this is sort of the prescription we have at Greenpeace you know in fossil fuel racism phase out fossil fuel production ensure no worker communities left behind an active green deal in order to do all this we need to protect and expand our democracy so thank you very much well good afternoon and my name is Marti Orta-Martinez from the University of Barcelona and today I'm going to present the work we've we've been doing on mapping creating an atlas of which specific in particular oil reserves we need to live and tap this work we've we've been doing it with some colleagues from the International Institute of Social Studies and the University of Barcelona but I want to mention that still I'm presenting today both Lorenzo Pellegrini and myself have contributed equally to this work said that let me start with some figures that you all know but I think it's important we keep in mind so we all know that the carbon budget estimated from the very beginning of 2020 onwards for the target of 1.5 Celsius degrees was 440 giga tons of CO2 we are meeting 40 around 42 giga tons of CO2 per year that's why the carbon budget could be completely exhausted by the end of this decade and well the disparity between this carbon budget and the CO2 emissions embedded in the global fossil fuels is the reason for which we are all here and it's because basically the emissions embedded in the global fossil fuel reserves and the global fossil fuel resources are much higher than the carbon budget we have so that's why we cannot explore for further reserves and we cannot use all the resources we know we all know that so what we need to do now well to manage the phase out of fossil fuels a rational approach to do it would be to select to prioritize which reserves which resources we need to live and tap in the ground and basically this is the work Christoph and Paul did in their seminal paper from 2015 and also the work Dan and James and Steve and Paul did in their more recent paper from last year where they basically produce these maps showing us where we need to live higher portions of the reserves and resources and tap all this work they've done is considering basically economic criteria and considering the cost of the opportunity of the different types of fossil fuel reserves also including refining and transportation costs but basically with this they came up with these figures I'm going to talk just about oil so I'm going to focus on this and for the different regions of the world for the different continents they gave us different amounts of giga barrels and percentages of the reserves that should be left and tapped making up to this global of the percentage of the oil that should be unbornable similar for gas the 59% or the coal the 89% yeah so also with this seminal paper from just two years ago from Steve Pie other criteria have been discussed on how to select how to prioritize which reserves we need to live and tap and coming from ethical considerations for instance historical responsibility in the accumulated emissions has been suggested as another criteria to allocate these right of extraction but also the capability to be at the cost of the transition and the adaptation to it but as we have seen in this previous presentations but also many others during these two days there are let me see if this video works so there are many severe social environmental impacts of oil extraction but also from gas extraction and also from coal extraction local social environmental impacts that obviously if we take them into account could generate additional sustainability benefits while we reduce the extraction of fossil fuels by the way this is from a resin oil spill in the northern Peruvian Amazon in the Hvar territory and actually this idea of taking these social environmental impacts into account was at the very beginning of the idea to leave the oil in the soil from oil watch in the Niger Delta but also with the Yasuniai did proposal in Ecuador so nothing new I'm skipping this so basically what we were suggesting was to Yasuniai the world and use this social environmental data spatial data to identify which resources we should live and tap to do so we have used data from the US geological survey with all the different giga barrels we have in the different sedimentary basins of the world and we have used the data from this is from Welsby et al 2021 that was basically telling us that we need to live and burn 81% of the oil resources of the world this is 3300 giga barrels of oil meaning that we can burn the remaining 19% that is 780 giga barrels of oil so to allocate this we have used the first thing we did was to basically identify the top priority social environmental areas and to assess the amount of reserves and resources of oil that are there basically what we did was to study how many reserves were in the biodiversity hotspots but also since the biodiversity hotspots are circumscribed to terrestrial areas we also used other schemes to prioritize to identify the global biodiversity conservation priorities for instance the rich centers of endemic species both terrestrial and marine or also the global system of natural protected areas we also used other criteria for instance we calculated the amount of oil that is in urban areas considering a buffer of 10 km and also in the territories of indigenous people involuntary isolation surprisingly and this is the amount of giga barrels we have in each of these different so for instance for the biodiversity hotspots we have 142 giga barrels of oil or for the richness centers of endemic species we have a total of 130 giga barrels of oil while in the global protected areas of the world we have 140, exactly the same here and here we have for the social criteria territories of indigenous people involuntary isolation or urban areas and then adding the different kinds of criteria we came up with this 457 giga barrels of oil and that is far less than what we need to live and tap why we consider these areas that actually have a total surface of more than 12 million square kilometers we consider them exclusion zones where oil should not be by no means be extracted and basically these are the maps so due to the time I just put all the layers here but we have the protected areas of the world in this light green the biodiversity hotspots in this red the territories for indigenous people living in involuntary isolation or the richness centers for endemic species and in purple the exclusion zones that basically are concentrated in some hotspots like the one in the Caribbean or the American coastal plains or indigenous centers of endemic species like in southeast Asia so basically all these exclusion zones are concentrated in these areas more surprisingly and contrary to the concept of the carbon bombs well 60% of this oil in the exclusion areas are concentrated in just 10% of the exclusion areas basically in the Arabian peninsula in the Iranian Zagros mountains in Venezuela, in the Niger delta and in Siberia meaning that in the 90% of these exclusion zones there are really really minor quantities of oil that for sure makes no sense to continue to extract further so well what else we've done basically since we need to find additional reserves to add to these 450 57 gigabytes of oil we use continuous special data to identify those we basically use for instance special data on rural human populations densities so basically considering these health effects of oil extraction we also use continuous data on the richness not the richness centers but the richness of terrestrial endemic species and of marine endemic species and these are the results so we have the purple areas that are the exclusion zones and the green areas would be the additional areas for the different criteria in this case for the rural taking into account the rural population the human rural population densities or the terrestrial endemic richness with some extra areas added here in this as unburnable or for the marine endemic species with these extra areas basically located in obviously these biodiversity hotspots so to finish basically we believe that the implementation of these would maximize the collateral social environmental benefits of climate policies while these exclusion zones only overlap with as I said 460 gigabytes of oil that are insufficient to meet the climate policy targets so the case for declaring them unburnable is very strong at least to our opinion and basically this could be used with additional criteria for instance the presence of indigenous people we haven't done use it because they have the right to free prior and inform consent so they have the right also to say yes to extraction or also considering environmental conflicts for instance data from the environmental justice but anyway we consider these could help a lot corporations also to minimize the risk of stranded assets because for us these are really the priorities for the unburnable oil reserves thank you very much thank you very much for the presentations I had a question for by the way I'm Steve Pye from UCL I just wondered in terms of the zones that you were looking at for exclusion purposes how many of them have licensing already happening in those zones just because it would potentially make it more problematic to develop that kind of concept you know in reality yeah thanks we'll just take a few at once Himena Hello, Himena Warners from the Ford Foundation also a question for Marty I know that you just mentioned really quickly about the criteria why you weren't using or that you could use also more social environmental data I'm curious to understand why you only chose Indigenous people living in in voluntary isolation and not all Indigenous territories where they potentially would be overlapping with oil and it'd be interesting to see also taking that former question which Indigenous is where there are reserves and where there's already existing projects Thanks Yeah, Miquel Thanks, Miquel Muñoz SCI a question on the jobs when we talk about the quality of the jobs and the salaries how much do you think that's a construct of the sector itself versus a construct of a modern industry versus a legacy industry so if renewals were happening 50 years ago we would have a few new jobs today or how does it compare to the technology sector or other modern sectors so if you could elaborate on that, thank you and then on the racism I was very intrigued by the Ontario one that was measured and I was wondering did they measure other things like did the property price go up or was there gentrification so is there any potential drawback so if we look for success on that, thank you Very good question I'm going to throw in one, two for ploy so we do a full round so when we open up the discussion beyond emissions what political opportunities come up like what type of actors can we bring in the discussion that can help move things forward maybe we start with the do one more with Felix and we'll go back Thanks for your question what I can say is that what's interesting is that these brown jobs that we're looking at they're highly unionized for the green jobs that's not the case right so really the the coalition around providing decent jobs and quality jobs around in the green economy sectors are not there yet and that's one potential pitfall I'd say because the earnings that focus for instance the coal industry are used to it just not we're not just not able to provide them in green economy sectors I think the government in that sense will probably have to step in over some part of the way to fill in this gap and then I think I think there will or there should be coalition building around good quality good earning green jobs happening and could you repeat the the drawback that you were yeah that's a great question I don't know if anybody's looked at that there's a lot of there's a lot of there's a lot of there's a lot of I don't know if anybody's looked at that there are a handful of studies looking at the do the sort of natural experiment of looking at what happens after you close down that one was refinery but there are others that look at power plants and generally find measurable health benefits and yeah I get you know gentrification is one of those things that certainly happens in some places in the US but not everywhere you know and so I think it would probably depend you know on the geography and demographics of where the closure happened so but and also interesting to look at what happens with jobs you know we have costs and benefits all inter-tangled together and the very often the communities that are suffering from the health arms often have workers in that community as well so it's complicated yeah I see if you want to elaborate on the criteria sure so thanks for the questions so basically the first answer is yeah this is an ongoing work so we started with data with the USGS that was really available there but it's really all data not updated at all and actually we know that there are plenty of limitations the the scale is also not enough for this selection but this was like the initial work we're not working with the risk database and then with this data we will have well we will have the opportunity to really yeah focus on what's already being developed and yeah with much better scale to conduct the analysis because actually what we did now was basically to split the reserves of the sedimentary basins on the pixels that we had for the other rasters of information so yeah and yeah regarding the indigenous people actually this was an internal discussion we had and yeah one option would have been to include it just to account for the number of to quantify the amount of reserves that are located in indigenous territories just in an informative way but yeah we haven't done it because yeah we thought if they have the right to say yes and to say no let's not put this as an exclusion zone because yeah we are not going to decide that they don't want oil in their territories so that's why we only include indigenous territories so people are living in in isolation yeah Thanks Claudio yeah I think that's a really good question and when we expand the conversation beyond green house gas emissions we have this opportunity to bring in so many actors from building the movement we're seeing recently the World Health Organization and 200 other health organizations endorsing the fossil fuel non-proliferation treaty we've seen work being done by the Lancet Countdown to highlight the health impacts of climate change all the way to the biodiversity crisis being highlighted by others so I think there's kind of really opportunity to broaden the movement all the way to bringing in the academic research communities and yeah also policymakers and stakeholders from a policy perspective the US has quite robust pollution regulations under the Clean Air Act and so it's kind of opportunities for using other regulatory levers to limit fossil fuel production as well I'm so wondering in terms of these like main concerns that you can mobilize around health is so close to us I mean it's people's health, we always say health is the most important thing right so I think there is a lot of mobilization potential in that field, it's very interesting and potentially powerful work you're doing there were some more questions the lady in the middle Thank you, hi I'm Michelle Postumonte with NRDC my question was also for Poi so sorry I was a little slow getting in for the first round I love the work that you're doing and I'm really excited to buy it, I was a little surprised originally that for the life cycle impacts you were looking within a particular geographic region even if it's an oil that's being extracted in Texas isn't necessarily being used in Texas but I think it allows you to get data and actually provide results which is amazing, I wondered if you thought about or are interested in looking at pre-decision tracing where that oil goes and where the health impacts maybe a future oil production would be, did that make sense those were rambling questions do you mean where the oil ends up being used or for example you're considering developing a new oil and gas extraction in Texas and you want to consider the health impacts downstream where those might happen is that something that you've considered maybe building a cross geographic health life cycle assessment or if so what do you think about that kind of an approach Karl, I think you had a question yes yes, Karl Spelling from Albury University, Denmark I have a short question to Ploy and one to Felix Ploy did you, I saw you cut off sort of at the onshore oil extraction, what about offshore and also did you how does this compare to other energy sources, biomass, coal potentially geothermal and these things do you have any insights on that and to Felix I saw you excluded CCS in your greenest scenario as the end of pipe solution and I'm wondering because CCS can be applied as end of pipe solution but also more proactively not from fossil fuels but from biomass and other sources to do green fuel production so I wonder what does this mean in terms of skill set and work force if you make that distinction thank you we had a question towards the front this is a question maybe for everyone but I don't know but maybe Felix can address this first, again follow up on the jobs do you think that there are limits to wages even if they were comparable, even if the legacy industry and the new renewable industries were comparable in terms of unionization are there other intrinsic things about the differences in these industries that might create an upper limit on the profitability and hence also the wages in these sectors or maybe they could also be different governance structures that could affect the wages so maybe not corporate but cooperatively owned and so on thank you we'll take it but it has to be very snappy and concise thank you Manal Shahabi, University of Oxford question to the first speaker I apologize I didn't catch your name I think if I got it correctly the majority of the emissions was at like 86% or something were in use of the fossil fuels so it's a little bit related to the question from the lady in front of me and my thinking was why are in you're looking at the effect of that will be really long term it's not immediately sought so I think you're looking at impacts of people was it race and income why not look at for example intergenerational things like the old who would probably be the most impacted health wise but also the babies who are really probably really relevant across all socioeconomic aspects because you know I think one of the reasons of the difficulty connecting health issues with climate change and fossil fuel use is that fact is not immediate it takes a long time so just wondering why not look at these maybe most harmed groups in general that would be across all incomes and racial distributions and my second question I think was for Felix about similar to the CCS question if it's a fossil fuel industry but then they do have CCS would that be blue or not blue brown great neutral what's the classification of that job thanks thank you you want to go first the first question was am I considering oil being produced in one state and being burned elsewhere and I think to some extent we're going to capture that in the end-use stage so modelling the health impacts of end-use we're not really tracing it to where that oil is produced although that is like a concept from greenhouse gas emissions where we account for extraction based emissions so yeah that might be one component we could add although the main novelty of this work is really being able to quantify the health impacts from the production stages which are much more local there was a question about are we considering offshore emissions we are to the extent that the data is available from the EPA emissions inventory of pollution emissions from oil and gas the effect is likely going to be small given you know there's not really populations living close to the offshore oil and gas strailing rigs yeah so yeah to the extent that the data is available we are including that and in terms of comparison to other sources so from the preliminary results we're seeing that from the full oil and gas life cycle across the US the PM 2.5 attributable burden might be about 90,000 if we compare that to the coal life cycle it's about 250,000 so coal is still the dirtiest source in terms of the resulting air pollution but again there's just so little evidence out there for oil and gas and that's maybe the next frontier as well the conversations around gas as a bridge fuel gas lock in so we kind of want to just hone in on oil and gas production and then there was a final question looking at health impacts which I didn't quite understand so we are quantifying the health impacts across all age groups from children to the elderly that is accounted for and we can we can also look I think if I got your question right maybe the environmental justice implications in terms of age that's certainly yeah great suggestion and I mean air pollution effects are immediate right I mean it's sort of you have effects from short term exposure like even hourly, daily but also the long term exposure and these are immediate as compared to the longer term impacts of greenhouse gas emissions so sorry I didn't quite understand the question but yeah thank you thanks Felix you're going to start with the last question on fossil fossil fuel biogeneration let's say and CCS would that be blue and neutral that's a very interesting question I think it kind of eludes to this discussion of what do we focus on do we just focus on do we have a carbon tunnel vision and say in our project we have a bit of a carbon tunnel vision we focus mainly on CO2 emissions I think it's fair to say that this is not the only way you could look at this and that including other impacts such as health would be worth considering in our framework at the moment it would be neutral in that sense regarding CCS in other sectors your question Carl this is something that like due to the that's super interesting due to the data structure that we're using we cannot really accommodate that so we can only really accommodate CCS in fossil fuel intensive jobs I'm happy to talk about that later it's a bit too nitty gritty I think to answer now and regarding the question on wages I'm also not quite sure if I got this right I mean one thing that I think is very different when we look at these legacy industries and the green industries is which parts of the supply chains are located in the countries and what we see for green technologies right is that large parts of the supply chains that are generating a lot of value are not within the countries and not within Germany there are in China and other countries so I think this is something to consider if we then look at let's say operation there will be more jobs in operation maintenance solar panels will be installed and then the work that happens after maybe provides less full-time equivalence these are considerations I think where there will be differences I hope that's part of it very well I will take my facilitation privilege to just highlight a few points I thought were really interesting and that we can maybe take away with us the first one is the potential of this the political potential of these these approaches right and also the opportunity they give us to go much more precise in scale and provide much better policy input into the policy process I think the visualization visualization component is also very strong in this session and also brings us back to the map that Nemonte talked about yesterday and the power of visual ways to show what's happening and especially in that case the potential to highlight special racial gender inequalities and therefore once we identify them do something about it on this I'll end the session and I think our great panel and everybody for your participation in the discussion