Abstract
Comparing air pollution changes due to COVID-19-related lockdowns between areas with differing socioeconomic status
Ashley Bae1, Elizabeth Noth, PhD2, Lawrence Kang3, Jin Lee4, Ryan Choi5, Leah Kwak6, Sunjung Bok7, Yebon Lee8, Brian Kang9, Seryung Park10, Trinity Keh11, Rachel Bae12, Linsy Song13, Steven Lee7, Isaac Kim11, Hyunseo Lee14, Jason Seo7, Rachel Lee11, Claire Lim15, Joel Im16, Yechan Lee8 and Sunju Lee17
(1)Duke University, Durham, NC, (2)UC Berkeley, Berkeley, CA, (3)Homeschool, Annandale, VA, (4)Emory University, Oxford, GA, (5)Chantilly High School, Chantilly, VA, (6)La Plata High School, La Plata, MD, (7)Stuyvesant High School, New York, NY, (8)Leonia High School, Leonia, NJ, (9)Gangnam International School, Seoul, Korea, Republic of (South), (10)Tenafly High School, Tenafly, NJ, (11)Bergen County Academies, Hackensack, NJ, (12)Academy of the Holy Angels, Demarest, NJ, (13)Sewickley Academy, Sewickley, PA, (14)River Dell High School, Oradell, NJ, (15)Brigham Young University Independent Study High School, Provo, UT, (16)Brooklyn Technical High School, New York, NY, (17)Lancaster High School, Lancaster, NY
APHA 2021 Annual Meeting and Expo
Existing studies of COVID-19’s effects on ambient air pollution have not investigated the potential association between socioeconomic status and changes in air pollution. We hypothesized decreased human activity due to COVID-19 lockdowns would cause decreases in PM2.5 concentrations within major US cities. Additionally, within New York City(NYC), we expected to observe decreases in PM2.5 according to the relative socioeconomic status of the area, with larger decreases in socioeconomically disadvantaged areas. To examine this hypothesis, we adopted two approaches. First, we examined PM2.5 changes by borough, comparing the magnitude of change in concentration and the socioeconomic status of each borough. Second, changes in PM2.5 within low-income, historically red-lined areas were examined to determine whether discriminatory redlining practices affected the magnitude of air pollution changes that were present during the COVID-19 lockdown periods.
We examined city-level changes in four major US cities: NYC, NY; Houston, TX; Chicago, IL; San Francisco, CA. Statistically significant differences in average daily PM2.5 data before and during COVID-19 lockdown periods were found only in Houston, TX (p < 0.0001) and NYC (p < 0.0001). Houston observed a 15.1% decrease in average daily PM2.5 (11.28 vs. 9.58 µg/m3), while NYC saw a 19.8% decrease in its average daily PM2.5 (6.42 vs. 5.15 µg/m3). The results of our NYC analyses showed a statistically significant difference in pre-lockdown PM2.5 data between high- and low-income boroughs (p = 0.01). Within high-income boroughs, there was a statistically significant difference found between daily mean pre-lockdown and lockdown PM2.5 data (p < 0.0001; 5.23 vs. 3.88 µg/m3). Within low-income boroughs, there was an even larger difference found between mean pre-lockdown and lockdown PM2.5 data (p < 0.0001; 5.74 vs. 3.63 µg/m3). In lockdown data, air pollution levels in ‘D’ graded red-lined areas were 27.3% higher than in other areas (4.80 vs 3.49 µg/m3).
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