Impacts of Modifiable Factors on Ambient Air Pollution: A Case Study of COVID-19 Shutdowns

Abstract

Modifiable sources of air pollution such as traffic, cooking, and electricity generation emissions can be modulated either by changing activity levels or source intensity. Although air pollution regulations typically target reducing emission factors rather than altering activity, the COVID-19 related closures offered a novel opportunity to observe and quantify the impact of activity levels of modifiable factors on ambient air pollution in real-time. We use data from a network of twenty-seven low-cost Real-time Affordable Multi-Pollutant (RAMP) sensor packages deployed throughout urban and suburban Pittsburgh along with data from EPA regulatory monitors. The RAMP locations were divided into four site groups based on land use (High Traffic, Urban Residential, Suburban Residential, and Industrial). Concentrations of PM2.5, CO, and NO2 following the COVID-related closures at each site group were compared to measurements from “business as usual” periods in March 2019 and 2020. Overall, PM2.5 concentrations decreased across the domain by 3 μg/m3. Intra-day variabilities of the pollutants were computed to attribute pollutant enhancements to specific emission sources (i.e. traffic and industrial emissions). There was no significant change in the industrial related intra-day variability of PM2.5 at the Industrial sites following the COVID-related closures. The morning rush hour induced CO and NO2 concentrations at the High Traffic sites were reduced by 57% and 43%, respectively, which is consistent with the observed reduction in commuter traffic (~50%). The morning rush hour PM2.5 enhancement from traffic emissions fell from ~1.5 μg/m3 to ~0 μg/m3 across all site groups. This translates to a reduction of 0.125 μg/m3 in the daily average PM2.5 concentration. If PM2.5 National Ambient Air Quality Standards (NAAQS) are tightened these calculations shed light on to what extent reductions in traffic related emissions are able to aid in meeting more stringent regulations.

Rethinking Air Quality and Climate Change after COVID-19

“…These variations are due to the differences in upwind regions, topography, meteorological characteristics and emission characteristics, which are related to socioeconomically-driven human activities. To devise a city- or nation-specific clear air policy, the lockdown has offered an evaluation testbed of emission control policy in mitigating severe air pollution facing humankind globally [ 56 , 57 , 58 ].…”

“…Recent laboratory studies [ 59 , 60 ] revealed the presence of SAR-CoV-2 viral RNA in patients’ feces. Comparing the presence of viral RNA in respiratory swabs (16.7 days in their sampled patients), that in fecal samples lasted for a longer period (27.9 days) with respect to the first symptom onset [ 58 ]. Along with that, it has been well recognized that a toilet plume composed of virus containing bioaerosol particles could be produced during flushing [ 61 , 62 ].…”

PM2.5 and Ozone Air Pollution Levels Have Not Dropped Consistently Across the US Following Societal Covid Response

“…Our paper also adds to the existing literature exploring covid-related impacts on air pollution and related activity levels [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] . Much of the news in the popular press regarding impacts of covid on air pollution emphasizes that concentrations have improved post-covid [32][33][34][35][36][37] ; our investigation aims to test those claims using a national dataset of in-situ concentration measurements.…”

Statistical Quantification of COVID-19 Lockdown Effect on Air Quality from Ground-Based Measurements in Ontario, Canada

“…Analysis of satellite and ground-based (i.e., surface) measurements of pollutant levels pre-and post-COVID-19 closures was also reported for different cities from around the globe (see updated list of papers in reference 4 ). In the Supporting Information, we highlight a few examples from Bejing, Wuhan, and Northern China 5,6 , the City of Pittsburgh, Pennsylvania in the U.S. 7 , and over 10,000 air quality stations in 34 countries. 8 However, none of these studies has undertaken a rigorous quantification of the statistical significance associated with these findings, in that such quantification is either absent or heavily reliant upon modeling assumptions which cannot be verified.…”