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Impacts of Stay-at-home Orders on Ozone in California Using an Ozone Source Apportionment Technique
YUSHENG ZHAO, Michael Kleeman, Shenglun Wu, University of California, Davis
Abstract Number: 208
Working Group: Source Apportionment
Abstract
The outbreak of the 2019 coronavirus disease (COVID-19) has posed great challenge on public safety and economics globally. However, it also brought an opportunity for researchers to study the outcome of reduced human activities.
California issued a COVID-19 shelter-in-place order asking people to stay at home between March 19 – May 8, 2020. Personal mobility decreased significantly during this period leading to generally improved air quality across the state. Several studies have found that monthly-average concentration of nitrogen dioxide (NO2) and airborne particulate matter (PM) decreased relative to levels in the previous years, but the effects on ozone (O3) are mixed. In the Los Angeles area, the 8-hr daily maximum O3 concentration increased rather than decreased.
Multiple factors could have contributed to the increased O3 concentrations during spring 2020, including NOx disbenefit and unfavorable meteorological conditions. Previous model simulations have great uncertainty when predicting the root cause because they lack direct measurements to confirm O3 response to NOx and VOC perturbations. Here we address this shortcoming by performing the first direct comparison between predicted and measured O3 response to NOx and VOC perturbations. Chemical transport model (CTM) predictions for O3 sensitivity will be compared to direct chamber measurements carried out for multiple months at Sacramento, California, during the year 2020. CTM predictions will also be compared to TROPOMI satellite measurements of HCHO/NO2 as an indirect measure of O3 sensitivity to NOx and VOC perturbations across the entire state of California. Changes to the 2020 emission inventory due to COVID-19 impacts are estimated by adjusting emissions in several sectors: on-road vehicles, air traffic, restaurants, rail and freight transport to estimate the emissions affected by the pandemic. Source apportionment algorithms built into the CTM will quantify NOx and VOC sources that contribute to O3 formation in the presence of these changes. The combined CTM predictions and direct measurements will identify the source contributions to O3 formation from different emission sectors under the altered COVID-19 conditions. The results will provide new strong guidance for future emissions control strategies to reduce O3 in California.