
By Greg Muttitt
The release of the World Energy Outlook (WEO) 2018 on Monday marked another missed opportunity for the International Energy Agency (IEA) to provide a roadmap to Paris success.
Governments and investors alike have been calling on the IEA to help guide them towards achievement of the Paris goals. Two years ago, the IEA itself proposed updating its climate scenario to match the ambition of the Paris goals, and also gave its updated scenarios a cameo in the WEO 2017.
The IEA has backtracked, however, removing any reference to the higher-ambition scenarios, or to the 1.5 degree Celsius (°C) goal. This comes just a month after the Intergovernmental Panel on Climate Change (IPCC) released a powerful report showing both the critical importance of limiting warming to 1.5°C, and pathways for doing so.
Following a summer of particularly devastating climate impacts, with unprecedented heat waves across much of the world, the IEA has opted for promoting the energy status quo. And 11 months after the World Bank Group decided to end financing for oil and gas extraction, the WEO 2018 instead calls for expanded investment in oil, gas and even coal.
Memories of Leadership
The IEA has proven that it can be a leader in steering energy decisions towards achievement of climate goals. When it first published its "450 Scenario" (450S) in 2008, the IEA was ahead of the curve. That scenario—designed to give a 50 percent chance of keeping warming to 2°C above pre-industrial levels—reflected the goals of the more progressive governments at the time.
But climate science has since indicated that even 2°C is dangerous—reiterated in last month's IPCC report. It was for this reason that governments decided in 2015 to increase their ambition, committing in Paris to pursue efforts to keep warming to 1.5°C, and in any case to hold warming well below 2°C.
At first, the IEA seemed to take this on board, as we explained in a recent blog. In the 2016 edition of the WEO, the IEA recognized that the 450S was not in line with the new Paris goals. It proposed developing two new scenarios, one aiming for "well below 2°C" (WB2), and one for 1.5°C.
The German government commissioned and funded a full exposition of the WB2 Scenario, published in a stand-alone report in March 2017. Many hoped then that the 2017 WEO, published in November of that year, would use this work to update its ambition to reflect the Paris goals. It was not to be.
In WEO 2017, the IEA replaced the 450S with a new "Sustainable Development Scenario" (SDS), with the welcome addition of goals on energy access and air pollution. But on climate change, the SDS maintained the pre-Copenhagen ambition level of the 450S. As the graph shows, the emissions pathways of the scenarios were identical. WEO 2017 only briefly mentioned the WB2 Scenario, and did not mention the 1.5°C Scenario at all.
Now, the new 2018 edition of the WEO omits reference to the WB2 Scenario as well, and fails to address 1.5°C at all.
Missed Goals
The WEO 2018 states that the SDS "is fully aligned with the Paris Agreement's goal of holding the increase in the global average temperature to well below 2°C." That statement omits the other half of the Paris goals, which are in full:
Holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C.
As for the "well below 2°C" part of the goals, the IEA claims that the SDS will lead to 1.7 to 1.8°C of warming. But how can a different result arise from the same emissions pathway that led to a 2°C outcome in the 450S? The answer is that the IEA has changed its assumption about what happens after 2040, beyond the scope of its own scenarios.
The IEA makes the 1.7 to 1.8°C claim by comparing the SDS with scenarios that lead to that amount of warming. As the IEA's graph shows, those scenarios depend on large-scale use of negative emissions technologies later in the century—including technologies that have been considered in theory but never tried in practice. If achieving the Paris goals is predicated on the later availability of these technologies and they do not work out, emissions to that point will be irreversible and climate limits broken.
Previous editions of the WEO have warned that negative emissions are likely not feasible at this level: WEO 2016 stated, "Such a situation is vastly removed from the realities of the current energy system, and the prospect is remote from today's perspective." WEO 2017 also cautioned that "all such technologies face severe technical, economic and resource constraints." And climate scientists have expressed growing concerns about reliance on negative emissions, as discussed in our recent blog.
In contrast, the new WEO 2018 describes negative emissions technologies as one of the "important sectors for innovation," and gives no warning about the dangers of reliance on them.
World Energy Outlook 2018 youtu.be
Misguided
All of this matters because, as the new WEO puts it, "Robust data and well-grounded projections about the future are essential foundations for today's policy choices." Scenario data and projections serve as a guide to the future, ideally to enable good decisions.
Without information about how to do it, it will be hard for governments to "pursue efforts" to keep warming to 1.5°C.
Investors too are increasingly using climate scenarios to test the robustness of their portfolios. They are vital tools for delivering the Taskforce on Climate-Related Financial Disclosures' recommendations and for the Climate Action 100+ initiative.
The new WEO states that:
Continued investment in oil and gas supply, however, remains essential even in the Sustainable Development Scenario to 2040, as decline rates at existing fields leave a substantial gap that needs to be filled with new upstream projects.
As Oil Change International's research has shown, investment in new oil and gas fields—beyond those that are already in operation—is not consistent with the Paris goals. The IEA is able to make the contrary claim for the SDS only because the SDS falls short of the Paris goals.
This is a crucial omission. Based on such projections, governments may continue licensing new oil and gas, locking in their future emissions, while failing to plan for an orderly just transition for workers. Investors may understate the risks associated with the energy transition, leading to future economic disruption.
More Fossil Fuels
The vast majority of WEO 2018, like in previous editions, is focused on the "New Policies Scenario" (NPS), which would lead to around 3°C of warming. By comparison, the SDS gets only one paragraph in the six-page summary.
The IEA has said before (in WEO 2017), if the future turns out like the NPS, "this will not be a sign of success," adding that, "Success for the WEO is about helping countries to achieve the long-term energy and related goals that they have chosen."
But since the NPS is so centrally promoted, it is the NPS that decision makers use as the default guide. As we showed in our Off Track report, the NPS' demand projections have been used by governments and investors to support damaging projects from Australian coal mines to Arctic oil drilling. This is why Oil Change International calls for the goals-based scenario—which the IEA says is the one it wants—to be made the central one in the WEO.
Furthermore, in the new WEO, the IEA repeatedly advocates for fossil fuel investment in line with the NPS. This investment will help create that very future that the IEA says it does not want. On oil:
Today's flow of new upstream projects appears to be geared to the possibility of an imminent slowdown in fossil fuel demand, but in the New Policies Scenario this could well lead to a shortfall in supply.
We estimate that around 16 billion barrels of new conventional crude oil resources would need to be approved each year between now and 2025 to avoid any potential "mismatch" between supply and demand. However, the average annual level of new resources approved in the three years since the oil price fall in 2014 was around 8 billion barrels. … The level of conventional crude oil approvals therefore needs to double if there is to be a smooth matching between supply and demand.
Much of today's media coverage can be expected to focus on the IEA's projection that (in the NPS) oil demand will not peak until after 2040. This narrative of ongoing future demand will also drive ongoing investment in more oil.
The same is true of gas: The WEO states that "building up infrastructure … requires conscious choices in favour of natural gas." It urges governments and companies "to ensure that adequate and cost-effective investment in new supply keeps gas as competitive as possible with other fuels," in other words reinforcing gas against competition from renewables.
Oil Change International research has found that there is no room for new gas development while achieving the Paris goals: Gas cannot be considered a "bridge fuel," as some claim.
Remarkably, the WEO also calls for increased investment in coal mining, especially in China and India, with $1 trillion of investment in new mining capacity over the period to 2040, as worldwide coal demand increases in the NPS until at least 2040: "Capital expenditures are needed along the value chain to sustain existing and to establish new mining operations, as well as to build railway and port infrastructure to connect new or expanding mining regions to coal importers."
Time to Change
Oil Change International believes the IEA has a significant opportunity for leadership, an opportunity that it regrettably missed in WEO 2018. It would in fact be easy for the IEA to become a climate champion by updating the SDS to match the Paris goals and by making that the central scenario in the WEO.
Decision makers—political and financial alike—are demanding the tools to implement their policy commitments and plan for success in a rapidly changing energy landscape. It is an opportunity that can't be ignored and, as the IEA faces increasing public pressure in 2019, calls for this increased ambition will only grow.
With time to spare to incorporate the IPCC Special Report, the mounting political and investor concerns, and the moral imperative of action on the heels of a year of devastating climate impacts, the 2019 WEO must step up high-profile ambition or risk becoming irrelevant in a world urgently demanding pathways to success.
Global Carbon Emissions Rise for First Time Since 2014 https://t.co/Oi1UefIhFr @Connect4Climate @350— EcoWatch (@EcoWatch)1521764107.0
A rare yellow penguin has been photographed for what is believed to be the first time.
- World-Renowned Photographer Documents Most Remote ... ›
- This Penguin Colony Has Fallen by 77% on Antarctic Islands ... ›
EcoWatch Daily Newsletter
By Stuart Braun
We spend 90% of our time in the buildings where we live and work, shop and conduct business, in the structures that keep us warm in winter and cool in summer.
But immense energy is required to source and manufacture building materials, to power construction sites, to maintain and renew the built environment. In 2019, building operations and construction activities together accounted for 38% of global energy-related CO2 emissions, the highest level ever recorded.
- Could IKEA's New Tiny House Help Fight the Climate Crisis ... ›
- Los Angeles City-Owned Buildings to Go 100% Carbon Free ... ›
- New Jersey Will Be First State to Require Building Permits to ... ›
Trending
By Eric Tate and Christopher Emrich
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Mapping Social Vulnerability
<p>Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6237.8402002" target="_blank"><em>Cutter et al.</em></a> [2003]. Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.</p>Fig. 1. (a) Social vulnerability across the United States at the census tract scale is mapped here following the Social Vulnerability Index (SoVI). Red and pink hues indicate high social vulnerability. (b) This bivariate map depicts social vulnerability (blue hues) and annualized per capita hazard losses (pink hues) for U.S. counties from 2010 to 2019.
<p>Many current indexes in the United States and abroad are direct or conceptual offshoots of SoVI, which has been widely replicated [e.g., <a href="https://link.springer.com/article/10.1007/s13753-016-0090-9" target="_blank"><em>de Loyola Hummell et al.</em></a>, 2016]. The U.S. Centers for Disease Control and Prevention (CDC) <a href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html" target="_blank">has also developed</a> a commonly used social vulnerability index intended to help local officials identify communities that may need support before, during, and after disasters.</p><p>The first modeling and mapping efforts, starting around the mid-2000s, largely focused on describing spatial distributions of social vulnerability at varying geographic scales. Over time, research in this area came to emphasize spatial comparisons between social vulnerability and physical hazards [<a href="https://doi.org/10.1007/s11069-009-9376-1" target="_blank"><em>Wood et al.</em></a>, 2010], modeling population dynamics following disasters [<a href="https://link.springer.com/article/10.1007%2Fs11111-008-0072-y" target="_blank" rel="noopener noreferrer"><em>Myers et al.</em></a>, 2008], and quantifying the robustness of social vulnerability measures [<a href="https://doi.org/10.1007/s11069-012-0152-2" target="_blank" rel="noopener noreferrer"><em>Tate</em></a>, 2012].</p><p>More recent work is beginning to dissolve barriers between social vulnerability and environmental justice scholarship [<a href="https://doi.org/10.2105/AJPH.2018.304846" target="_blank" rel="noopener noreferrer"><em>Chakraborty et al.</em></a>, 2019], which has traditionally focused on root causes of exposure to pollution hazards. Another prominent new research direction involves deeper interrogation of social vulnerability drivers in specific hazard contexts and disaster phases (e.g., before, during, after). Such work has revealed that interactions among drivers are important, but existing case studies are ill suited to guiding development of new indicators [<a href="https://doi.org/10.1016/j.ijdrr.2015.09.013" target="_blank" rel="noopener noreferrer"><em>Rufat et al.</em></a>, 2015].</p><p>Advances in geostatistical analyses have enabled researchers to characterize interactions more accurately among social vulnerability and hazard outcomes. Figure 1b depicts social vulnerability and annualized per capita hazard losses for U.S. counties from 2010 to 2019, facilitating visualization of the spatial coincidence of pre‑event susceptibilities and hazard impacts. Places ranked high in both dimensions may be priority locations for management interventions. Further, such analysis provides invaluable comparisons between places as well as information summarizing state and regional conditions.</p><p>In Figure 2, we take the analysis of interactions a step further, dividing counties into two categories: those experiencing annual per capita losses above or below the national average from 2010 to 2019. The differences among individual race, ethnicity, and poverty variables between the two county groups are small. But expressing race together with poverty (poverty attenuated by race) produces quite different results: Counties with high hazard losses have higher percentages of both impoverished Black populations and impoverished white populations than counties with low hazard losses. These county differences are most pronounced for impoverished Black populations.</p>Fig. 2. Differences in population percentages between counties experiencing annual per capita losses above or below the national average from 2010 to 2019 for individual and compound social vulnerability indicators (race and poverty).
<p>Our current work focuses on social vulnerability to floods using geostatistical modeling and mapping. The research directions are twofold. The first is to develop hazard-specific indicators of social vulnerability to aid in mitigation planning [<a href="https://doi.org/10.1007/s11069-020-04470-2" target="_blank" rel="noopener noreferrer"><em>Tate et al.</em></a>, 2021]. Because natural hazards differ in their innate characteristics (e.g., rate of onset, spatial extent), causal processes (e.g., urbanization, meteorology), and programmatic responses by government, manifestations of social vulnerability vary across hazards.</p><p>The second is to assess the degree to which socially vulnerable populations benefit from the leading disaster recovery programs [<a href="https://doi.org/10.1080/17477891.2019.1675578" target="_blank" rel="noopener noreferrer"><em>Emrich et al.</em></a>, 2020], such as the Federal Emergency Management Agency's (FEMA) <a href="https://www.fema.gov/individual-disaster-assistance" target="_blank" rel="noopener noreferrer">Individual Assistance</a> program and the U.S. Department of Housing and Urban Development's Community Development Block Grant (CDBG) <a href="https://www.hudexchange.info/programs/cdbg-dr/" target="_blank" rel="noopener noreferrer">Disaster Recovery</a> program. Both research directions posit social vulnerability indicators as potential measures of social equity.</p>Social Vulnerability as a Measure of Equity
<p>Given their focus on social marginalization and economic barriers, social vulnerability indicators are attracting growing scientific interest as measures of inequity resulting from disasters. Indeed, social vulnerability and inequity are related concepts. Social vulnerability research explores the differential susceptibilities and capacities of disaster-affected populations, whereas social equity analyses tend to focus on population disparities in the allocation of resources for hazard mitigation and disaster recovery. Interventions with an equity focus emphasize full and equal resource access for all people with unmet disaster needs.</p><p>Yet newer studies of inequity in disaster programs have documented troubling disparities in income, race, and home ownership among those who <a href="https://eos.org/articles/equity-concerns-raised-in-federal-flood-property-buyouts" target="_blank">participate in flood buyout programs</a>, are <a href="https://www.eenews.net/stories/1063477407" target="_blank" rel="noopener noreferrer">eligible for postdisaster loans</a>, receive short-term recovery assistance [<a href="https://doi.org/10.1016/j.ijdrr.2020.102010" target="_blank" rel="noopener noreferrer"><em>Drakes et al.</em></a>, 2021], and have <a href="https://www.texastribune.org/2020/08/25/texas-natural-disasters--mental-health/" target="_blank" rel="noopener noreferrer">access to mental health services</a>. For example, a recent analysis of federal flood buyouts found racial privilege to be infused at multiple program stages and geographic scales, resulting in resources that disproportionately benefit whiter and more urban counties and neighborhoods [<a href="https://doi.org/10.1177/2378023120905439" target="_blank" rel="noopener noreferrer"><em>Elliott et al.</em></a>, 2020].</p><p>Investments in disaster risk reduction are largely prioritized on the basis of hazard modeling, historical impacts, and economic risk. Social equity, meanwhile, has been far less integrated into the considerations of public agencies for hazard and disaster management. But this situation may be beginning to shift. Following the adage of "what gets measured gets managed," social equity metrics are increasingly being inserted into disaster management.</p><p>At the national level, FEMA has <a href="https://www.fema.gov/news-release/20200220/fema-releases-affordability-framework-national-flood-insurance-program" target="_blank">developed options</a> to increase the affordability of flood insurance [Federal Emergency Management Agency, 2018]. At the subnational scale, Puerto Rico has integrated social vulnerability into its CDBG Mitigation Action Plan, expanding its considerations of risk beyond only economic factors. At the local level, Harris County, Texas, has begun using social vulnerability indicators alongside traditional measures of flood risk to introduce equity into the prioritization of flood mitigation projects [<a href="https://www.hcfcd.org/Portals/62/Resilience/Bond-Program/Prioritization-Framework/final_prioritization-framework-report_20190827.pdf?ver=2019-09-19-092535-743" target="_blank" rel="noopener noreferrer"><em>Harris County Flood Control District</em></a>, 2019].</p><p>Unfortunately, many existing measures of disaster equity fall short. They may be unidimensional, using single indicators such as income in places where underlying vulnerability processes suggest that a multidimensional measure like racialized poverty (Figure 2) would be more valid. And criteria presumed to be objective and neutral for determining resource allocation, such as economic loss and cost-benefit ratios, prioritize asset value over social equity. For example, following the <a href="http://www.cedar-rapids.org/discover_cedar_rapids/flood_of_2008/2008_flood_facts.php" target="_blank" rel="noopener noreferrer">2008 flooding</a> in Cedar Rapids, Iowa, cost-benefit criteria supported new flood protections for the city's central business district on the east side of the Cedar River but not for vulnerable populations and workforce housing on the west side.</p><p>Furthermore, many equity measures are aspatial or ahistorical, even though the roots of marginalization may lie in systemic and spatially explicit processes that originated long ago like redlining and urban renewal. More research is thus needed to understand which measures are most suitable for which social equity analyses.</p>Challenges for Disaster Equity Analysis
<p>Across studies that quantify, map, and analyze social vulnerability to natural hazards, modelers have faced recurrent measurement challenges, many of which also apply in measuring disaster equity (Table 1). The first is clearly establishing the purpose of an equity analysis by defining characteristics such as the end user and intended use, the type of hazard, and the disaster stage (i.e., mitigation, response, or recovery). Analyses using generalized indicators like the CDC Social Vulnerability Index may be appropriate for identifying broad areas of concern, whereas more detailed analyses are ideal for high-stakes decisions about budget allocations and project prioritization.</p>Wisconsin will end its controversial wolf hunt early after hunters and trappers killed almost 70 percent of the state's quota in the hunt's first 48 hours.
By Jessica Corbett
Sen. Bernie Sanders on Tuesday was the lone progressive to vote against Tom Vilsack reprising his role as secretary of agriculture, citing concerns that progressive advocacy groups have been raising since even before President Joe Biden officially nominated the former Obama administration appointee.