The Philadelphia Energy Solutions refinery was considered the city’s biggest stationary source of air pollution and a notorious toxic emitter. On June 21st, 2019 a corroded pipe led to a fire which resulted in a massive explosion. The facility leaked hazardous chemicals into the surrounding Greys Ferry neighborhood in South Philadelphia, where many residents reported feeling sick in the coming days. Soon after, the refinery was permanently closed. Our research used publicly available data from the EPA to visualize the changes in PM2.5, SO2, and volatile organic compounds (VOCs) in the neighborhood. We created linear regression models and performed statistical analyses to determine the significance of the correlation in pollutant trends and the refinery closure. We examined pollutant trends in Camden, NJ as well to see if any pollutants experienced a short burst in concentration the night of the explosion. 

Before the refinery explosion and closure, PES accounted for 72% of Philadelphia’s toxic emissions. PES had violated the Clean Air Act’s emission limits for 9 of the 12 quarters prior to its closure. Not surprisingly, the surrounding community to the refinery in the Greys Ferry neighborhood in South Philadelphia is disproportionately black, low-income, and suffers from high rates of cancer, asthma, and other comorbidities. Residents are confident the toxic emissions in their backyard are directly or indirectly related to many of the chronic health issues in the neighborhood.

The explosion and closure of the refinery marked a turning point. The major source of pollution in the community was shuttered for good and our research began to prove that air quality would improve and toxic compounds would decrease in the community. It is crucial for current and future residents to know if they are still breathing in toxins or if their air quality has improved.

I had little experience with programming before this summer. All of the analyses required me to learn R. By the end of the summer, I became quite proficient. I picked up many data science skills as well including data cleaning and data visualization. I practiced many statistical skills in the process of making linear regression models and interpreting results. I also worked on communication and scientific writing while making my presentation to share my results. The STEER program gave me a great opportunity to explore environmental health as a future career and develop skills I will need for the rest of that career.