Assessing the impact of COVID-19 lockdown on fine-scale air quality across a heavy-pollution city using low-cost sensors

Abstract

COVID-19 pandemic led to restricted anthropogenic activities and drastic emission reduction, while air quality in response to strict control measures at a fine spatial scale still remained unknown. At first, we estimated the high-resolution air quality based on low-cost sensors, assimilated meteorology, and other geographical covariates. The result suggested that PM2.5, NO2, and SO2 across Handan decreased by 21%, 55%, and 12%, respectively. In contrast, the 8-h O3 level over Handan increased by 87%. Then, the random forest (RF) model was applied to remove the meteorology in order to capture the response of air quality to emission reduction at the fine spatial scale. The deweathered concentrations of some species varied greatly at different roads and points of interest (POI). The deweathered NO2 level suffered from more drastic reduction in some industrial points and roads compared with other POI, which was closely associated with the dense nitrogen oxide (NOx) emissions in these sites/roads. However, the deweathered O3 concentrations in some main lines (e.g., highway and sidewalk) showed more significant increases, which might be due to more rapid decline of NOx emission compared with volatile organic compounds (VOC) emission in a VOC-limited region.