Disbanded Air Pollution Panel Finds EPA Standards Don’t Protect Public Health

By Gretchen Goldman
The Independent Particulate Matter Review Panel has released their consensus recommendations to the EPA administrator on the National Ambient Air Quality Standards for Particulate Matter. The group of 20 independent experts, that were disbanded by Administrator Wheeler last October and reconvened last week, hosted by the Union of Concerned Scientists, has now made clear that the current particulate pollution standards don't protect public health and welfare.
The Clean Air Scientific Advisory Committee (CASAC) — the remaining seven-person committee that is providing science advice to the EPA on the particulate matter standards — meets this week to discuss their recommendations on whether the current standards are adequate. The letter from the Independent Panel will be the elephant in the room.
The Elephant in the CASAC Meeting
CASAC has already acknowledged that they don't have the expertise to conduct the review but you know who does? The Independent Panel. The Panel has more than double the experts of CASAC, and importantly, it has multiple experts in each of the necessary scientific disciplines critical to ensure a comprehensive, robust review of the science supporting the standards.
As a result, we should watch whether or not CASAC aligns with the panel in their recommendations on the standards. If CASAC doesn't decide this week to make a similar recommendation as the Independent Panel, they'll have to explain why they disagreed with a larger, more experienced, and more diverse set of experts on the topic. In any event, the administrator will have access to both CASAC and the Independent Panel's recommendations when he ultimately makes the decision of where to set particulate pollution standards. The panel's recommendations should hold the administrator's feet to the fire.
The Fine Particulate Matter Standards Don’t Protect Public Health
The standards of greatest interest are the primary PM2.5 standards. These are the standards for particulate matter less than 2.5 micrometers (fine particulate matter) that are designed to protect public health. The panel supported the preliminary conclusions of a Draft EPA Policy Assessment that the current standards aren't requisite to protect public health.
The letter cited new and consistent epidemiological findings, supported by human and animal studies and other studies with natural experiments, as providing "clear and compelling scientific evidence" for tighter standards. Since the last particulate matter review, several new large-scale epidemiological studies provide powerful evidence that particulate matter is causing adverse health outcomes (such as early death, heart attacks, and respiratory stress) at locations and during time periods with concentrations at or below the level of the current standards.
They write, "New and compelling evidence that health effects are occurring in areas that already meet or are well below the current standards." Notably, this evidence cuts across different locations with different study populations, different study designs, and different statistical approaches.
Given the weight of the evidence from new studies across scientific disciplines and consistent with the decision-making process that EPA and its science advisers have used for many years, the panel recommends a particulate matter standard between 8 µg/m3 and 10 µg/m3 for the annual PM2.5 standard (compared to the current standard of 12 µg/m3) and between 25 µg/m3 and 30 µg/m3 for the 24-hour standard (compared to the current standard of 35 µg/m3) to protect public health. These ranges are tighter than those recommended in EPA's Draft Policy Assessment.
Keeping the Current Fine Particulate Matter Standards Ignores the Science
The Independent Panel rejected a potential argument for maintaining the current primary PM2.5 standards. The Draft Policy Assessment offered up an alternative rationale that might be used if the agency were to reject the draft assessment's recommendation to strengthen the standards and maintain the current standards. This alternative rationale explains that such a move would require the administrator to be arbitrarily selective in choosing which new studies to accept and which to toss and to disregard new epidemiologic evidence showing effects at lower levels.
The panel roundly rejected this justification, noting that, "Arguments offered in the draft Policy Assessment for retaining the current standards are not scientifically justified and are specious." This is important because if the administrator fails to strengthen the standards, he'll have to explain (both in court and in the court of public opinion) why he feels such a decision is science-based, as required under the Clean Air Act. And one proposed argument he could use has just been debunked by this expert Panel.
Otherwise, the EPA’s Draft Policy Assessment Is Scientifically Sound
While the Independent Panel critiqued some details of the EPA's Draft Policy Assessment, the panel agreed that the draft science and policy assessments were cohesive and robust and the panel commended the "good faith effort" involved in the policy assessment. Specifically, the panel affirmed the use of EPA's causality framework used in the Integrated Science Assessment they reviewed last year and the Policy Assessment's new use of a hybrid modeling technique that allows for better assessment of risk from particulate matter exposure across the country especially in rural areas.
This diverges from what the seven-member CASAC has said and done around the EPA's assessment of the science and policy. In December, they concluded that the agency's draft science assessment was not a scientific document (it is) and CASAC Chair Dr. Tony Cox has been critical of the agency's causality framework that has been developed with dozens of experts over more than a decade. This view is not shared by the scientific community, and now, not shared by the Independent Panel either.
Other Particulate Pollution Standards Also May Need Revamping
The Independent Panel decided other particulate standards were also inadequate. On PM10, particulate matter less than 10 micrometers, the panel recommended revising this standard downward given that the PM2.5 component would also be tightened and noted several research and monitoring areas that need further work. On the secondary standards, i.e. the standards designed to protect welfare effects, such as visibility, the panel concluded that the standards should be tightened in order to be more protective.
The Panel Condemns the EPA’s Broken Process
The Independent Panel's deliberations, demands for further research, and unanswered questions highlight how broken the EPA process is. In a normal review cycle, the panel would have had the opportunity to talk with agency scientists directly. The EPA staff would then have considered their comments and revised the Integrated Science Assessment in response to the committee and panel's suggestions. But because the administrator disbanded the panel and abbreviated the process, there was no opportunity for such dialogue and refinement of the agency's science assessment before policy decisions were discussed. But alas, the panel had to make do with what was available to them and CASAC does too.
Fortunately for CASAC, an Independent Panel has already done their job, and they are free (and encouraged) to run with it, especially given the long list of ways that EPA Administrator Wheeler has damaged the ambient air pollution review process.
Listen and watch this week as CASAC discusses the same questions that the Independent Panel did last week. If CASAC comes to different conclusions than the larger, more experienced, and more diverse Independent Panel, we should ask why.
You can raise these questions yourself and demand that the administrator follow the panel's recommendations, by providing written or oral public comments at a future CASAC meeting and commenting on the docket for the particulate matter rule-making. I'll be providing public comments this afternoon urging CASAC to follow the advice of the Independent Panel and commenting on the EPA's problematic process and drawing attention to that elephant in the room.
Gretchen Goldman is the research director at the Center for Science and Democracy.
Reposted with permission from our media associate Union of Concerned Scientists.
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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.
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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.