EPA Accused of Violating Clean Water Act Through Approval of Corexit in BP Gulf Oil Cleanup

DeSmogBlog
Oil Spill Eater International (OSEI), through the Gulf Oil Spill Remediation Conference group, issued a press release this week saying that the U.S. Environmental Protection Agency (EPA) effectively blocked or otherwise delayed scientific advancement in the cleanup of the 2010 Gulf of Mexico oil disaster by refusing to acknowledge the toxicity of the oil dispersant Corexit.
According to OSEI, the EPA is guilty of violations to the Clean Water Act because they knowingly used the toxic dispersant instead of opting for cleaner, less toxic methods of oil spill cleanup.
OSEI is actually not off base with their accusations. Reports from late 2012 revealed that using oil dispersants like Corexit make oil spills less visible, but when combined with the oil, create a mixture that is 52 times more toxic than the oil itself. The studies revealed that even in small amounts, the combination of oil and Corexit reduced the number of egg hatchings in small marine invertebrates by 50 percent. These are small creatures like krill, shrimp and other crustaceans that form the bottom of the oceanic food pyramid.
Those results were just from small doses of the mixture. And as I wrote in 2011, the amount of Corexit dumped into the Gulf was anything but “small":
An estimated 1.8 million gallons of Corexit were dumped into the Gulf of Mexico in an attempt to displace the 206 million gallons of oil that spewed from a broken wellhead on the Gulf floor. And while the dispersant itself was ruled to be less toxic than the oil, the study suggests that the combination mixture of crude oil and dispersant poses a significantly greater threat to both the environment and marine life than either substance on its own. The EPA says that studies have been done on some of the 57 chemical agents found in dispersants, but they also acknowledge that no long-term studies have been conducted on the exposure to these chemicals in quantities as large as were poured into the Gulf.
As for the EPA’s role and knowledge of the dangers of Corexit, that was also known as far back as 2011:
BP knew that Corexit was not the best choice in oil dispersants, but chose to use that chemical anyway. Studies by the EPA showed that Corexit was far less effective on the type of crude oil that was leaking from BP’s broken well, and there were in fact at least 12 other dispersants that would have worked better. Those same studies also showed that the other 12 more effective dispersants were also less toxic than Corexit.
Think Progress points out that the choice to use Corexit instead of more effective, less toxic competitors could easily stem from the fact that the company that produced Corexit, Nalco, was formerly owned by Exxon and the leadership for the company includes executives from both Exxon and BP. The EPA had originally ordered BP to use a different dispersant, but backed off their order due to insistence from the company.
So from the start, it was glaringly obvious that both the EPA and BP knew that Corexit was the wrong choice, but chose to go with it anyway because it could make BP a little extra cash on the side.
Less than one year ago, the EPA told us that they had concluded that Corexit was “practically non-toxic,” in spite of all evidence to the contrary:
EPA official turned whistleblower Hugh Kaufman told Democracy Now! two years ago that the agency was hiding the real dangers of Corexit from the public:
Corexit is one of a number of dispersants, that are toxic, that are used to atomize the oil and force it down the water column so that it’s invisible to the eye.
In this case, these dispersants were used in massive quantities, almost two million gallons so far, to hide the magnitude of the spill and save BP money.
And the government—both EPA, NOAA, etc.—have been sock puppets for BP in this cover-up.
Now, by hiding the amount of spill, BP is saving hundreds of millions, if not billions, of dollars in fines, and so, from day one, there was tremendous economic incentive to use these dispersants to hide the magnitude of the gusher that’s been going on for almost three months.
… People who work near [Corexit] are hemorrhaging internally [but the] EPA now is taking the position that they really don’t know how dangerous it is, even though if you read the label, it tells you how dangerous it is.
… for example, in the Exxon Valdez case, people who worked with dispersants, most of them are dead now.
The average death age is around fifty.
It’s very dangerous, and it’s an economic—it’s an economic protector of BP, not an environmental protector of the public.
So not only was the EPA well aware of the dangers of Corexit, but they were actively involved in covering up the dangers of Corexit.
The toxic results of Corexit have already been seen in Gulf waters, as marine wildlife are being discovered with abnormal mutations that fishermen and scientists say they have “never seen” in their lives, and are attributing to Corexit exposure.
Given what we know about both the EPA’s actions and the scientific reports on Corexit’s toxicity, OSEI is not out of bounds saying that the regulatory agency violated the Clean Water Act.
Unfortunately, as the group that enforces the Clean Water Act, the accusations are about as far as the case will go.
Visit EcoWatch’s GULF OIL SPILL and OFFSHORE OIL DRILLING pages for more related news on this topic.
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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.