Friday, March 29, 2019
Cleveland’s Environmental Justice Hotspots
by Tim Kovach
Last week, a coalition of partners from the City of Cleveland, Cuyahoga County, and various nonprofit and civic organizations held a press conference at City Hall to announce the “Lead Safe Cleveland Coalition,” a group committed to addressing, within the next decade, the city’s appalling child lead poisoning crisis.
The announcement is welcome, if disgracefully overdue. Over the weekend, Rachel Dissell and Brie Zeltner—the award-winning Plain Dealer journalists who arguably deserve more credit for this outcome than almost anyone else in this region (save some of the activists who have been on the front lines for years)—previewed the announcement with an article on Cleveland’s long and sordid history of failing to remedy this issue.
Unsurprisingly, given our history of segregation, lead poisoning largely falls along racial lines. In a recent post, the Scene’s Sam Allard demonstrated the strong correlation between the racial composition of K-8 schools and the share of students with elevated blood lead levels in the Cleveland Metropolitan Schools District.
But lead poisoning is hardly the only health burden which is unevenly distributed in Cleveland. Last month, Kate Warren from the Center for Community Solutions examined the stark racial disparities in Cleveland across a number of different measures of health and well-being. According to her report, the infant mortality rate for African-American babies in Cleveland is 15.2 deaths per thousand lives births, 5.8 times higher than the rate for white babies. And, due in part to this mind-boggling fact, African-Americans in Cleveland can expect to live nearly six years less, on average, than white residents (72.4 vs. 78.1 years).
This intersection of socioeconomic/demographics and public health outcomes lies at the heart of environmental justice (EJ), a concept which has been a formal part of federal environmental governance since President Clinton signed Executive Order 12898 in 1994. According to the U.S. Environmental Protection Agency (EPA), which oversees the work in this area, EJ is “the fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income with respect to the development, implementation and enforcement of environmental laws, regulations and policies.”
To help promote EJ in its work and the work of agencies and organizations which receive federal funding, EPA rolled out EJSCREEN, its Environmental Justice Screening and Mapping Tool, in 2015. This tool, which collects data on a number of indicators across the country, enables users to see which parts of a community either bear the burden of environmental harms, suffer from socioeconomic disadvantage, or both. But, as with most mapping tools of this sort, while EJSCREEN does a great job demonstrating patterns of environmental or socioeconomic disadvantage, it does not enable you to see which neighborhoods suffer from the greatest concentrated burden.
We know, for instance, that lead-poisoned children will suffer lifelong cognitive and behavioral impacts. But children who grow up in close proximity to heavily trafficked roads and are exposed to higher levels of transportation-related air pollution suffer comparable effects. In turn, children born into communities with high levels of poverty and violent crime suffer from toxic stress, a form of social pollution, which has similar consequences for their well-being.
Taken in isolation, each of these variables takes a major toll. But what about when they’re layered on top of one another? The research makes it clear that exposure to multiple environmental and socioeconomic harms is not the same as exposure to just one or two. Rather, people, particularly members of vulnerable groups like children and the elderly, who live in communities of disadvantage, suffer concentrated effects that make them susceptible to more hazards and reduce their ability to stave off effects.
There is also a complex interplay among the environmental and socioeconomic factors involved. Scholars have engaged in a long-running debate about whether companies intentionally site hazardous waste facilities in communities of color, or if minority groups move into neighborhoods with existing hazardous waste sites because they depress housing costs.
Last fall, in order to better illustrate these cumulative environmental and socioeconomic disadvantages, researchers at the Natural Resources Defense Council (NRDC) created the “Cumulative Burden of Environmental Exposures & Population Vulnerability in Chicago” map. I came across this map the other week while reading an article on it in Pacific Standard, and I was struck by the way it attempted to quantify the cumulative impacts on neighborhoods. I immediately decided to look into the methodology to determine whether or not I could replicate it for Cleveland.
Fortunately for me, the process was relatively straight forward, and the NRDC researchers provided a detailed descriptionof how they created the map. I applied the exact same methodology to block groups for both Cuyahoga County and the City of Cleveland. The only difference is that NRDC used 2017 data, while I took the updated numbers from 2018.
Unsurprisingly, the communities bearing the highest combined EJ burden scores were in the City of Cleveland. Moreover,of the 130 block groups with a score of nine, 118 (91%) are in Cleveland. The only other city with more than one block group with a score of nine or ten is East Cleveland, which has nine. While the average cumulative burden score for all block groups in the county is 5.8, the average for Cleveland’s block groups is eight. If you remove Cleveland, the average score for the County falls to 4.4.
Turning to the map for the City of Cleveland, we see that, while many of the block groups with the highest cumulative burden scores are clustered on the East Side, as expected, higher scores are spread throughout the city.
As the map and numbers suggest, the highest EJ burden appears to be distributed among the neighborhoods located in or near former industrial facilities or, to a lesser extent, interstates. The three environmental factors that seem to predict the highest cumulative burden are Proximity to Treatment Storage Disposal Facilities; Proximity to Risk Management Plan Facilities; and Lifetime Air Toxics Cancer Risk. Interestingly, the three environmental indicators with the lowest predictive power are Proximity to Superfund Sites; Summertime Average Ozone Levels; and Lead Paint Indicator (Pre-1960s Housing Stock).
Oddly, the percentage of minority populations in a Block Group has little predictive value for the cumulative burden score. Block groups in the top quintile for this indicator have an average burden score of 5.2, the fifth lowest of the Population indicators (behind just Percent Over Age 64). The two strongest predictors among the socioeconomic variables are Less than High School Education and Low Income.
Ultimately, as I noted earlier, it is less productive to try and isolate the single most “important” variable for the cumulative burden of EJ in Cleveland, as it is the layering of these various variables that creates this concentrated impact. The whole environmental justice burden on a given block group is greater than the sum of its parts.
The real takeaway from this exercise to pinpoint EJ hotspots in Cuyahoga County and the City of Cleveland is to better inform the targeting of policy interventions to redress these burdens. Hopefully these maps, and the underlying data that I used to create them can also help to empower EJ activists living and working in these neighborhoods to both resist the imposition of new environmental burdens (e.g. the siting of new hazardous waste facilities) and to demand solutions from their elected officials.
[Note: If you would like to look at the raw data for each block group (including indicator values and quintile scores for all 17 measures), I have uploaded the spreadsheet to Google Sheets. For some reason, the shapefile I used did not include block groups in Brecksville or Hunting Valley, so these are not shaded, but the data for each is available in the spreadsheet.]
A previous version of this post appeared at timkovach.com.
Tim Kovach is an independent analyst and blogger from Cleveland who researches and writes about air quality, climate change, and transportation at timkovach.com. His work has appeared on Grist, Vox, and Scientific American.
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