Pollution and Race
Air pollution, encompassing the chemical, physical, and biological agents that alter atmospheric characteristics, poses significant health risks and impacts the climate and ecosystems. Despite improvements in recent years, Mecklenburg County, home to North Carolina's largest city, received a "C" grade in the American Lung Association's 2024 "State of the Air" report in both Ozone and Particulates.
Meckenburg County is home to ten of the state’s thirteen Fortune 500 companies ranging from banking to manufacturing. While jobs and transportation access allow for a diverse population, pollution from industrial activity disproportionately affects some communities more than others. This study focuses on the correlation between the locations of facilities listed in the Environmental Protection Agency’s Toxic Release Inventory (TRI) and the racial demographics of the county’s census tracts.
QGIS for data preparation, spatial analysis, and visualization.
To determine what
The population of Mecklenburg County is 55% non-white, and although several minority groups reside within the county, grouping the population into just white and non-white groups provides for easier analysis. Using Census tracts, averaging approximately 4,000 inhabitants each, are used to identify those areas that are predominantly white or non-white.
The EPA’s TRI database identified 36 facilities in Mecklenburg County releasing pollutants in 2022.
These facilities were mapped, revealing a clustering of high-polluting facilities in the southwestern and central areas of the county.
By summarizing TRI facility locations by census tract and comparing those tracts to population demographics, this analysis identified areas with high pollution and a majority non-white population. This spatial comparison highlights disparities in pollutant exposure among demographic groups.
The analysis shows a clear relationship between polluting facilities and racial demographics, with the TRI-listed facilities situated in those areas with a higher non-white population. While this result is likely expected based on the county’s majority non-white population, further investigation is necessary to identify disparities affecting specific racial groups.
While this is a good first step, it could go further. A deeper analysis has the potential to reveal more targeted information which could inform future policy decisions, ensuring all residents benefit from ongoing improvements in air quality.
Additional studies should explore individual racial groups and assess their relative exposures to determine if any one group is more impacted than another.
To mitigate data distortion caused by a few high-polluting facilities, future analyses should focus on either smaller subsets of the data or facilities with similar pollution levels. By analyzing a truncated set of facilities, it might make it easer to determine a more accurate trend.