Efforts to stem the spread of COVID-19 in China hinged on severe restrictions to human movement starting January 23rd, 2020 in Wuhan and subsequently to other provinces. Here, we quantify the ancillary impacts on air pollution and human health using inverse emissions estimates based on multiple satellite observations. We find that Chinese NOx emissions were reduced by 36% from early January to mid-February, with more than 80% of reductions occurring after their respective lockdown in most provinces. These emissions declines increased surface ozone by up to 16 ppb over northern China but decreased PM2.5 by up to 23 µgm nationwide. Air pollution appears to have substantially offset hospital admissions related to COVID-19, augmenting mitigation efforts, such as in the Hubei province with ~400 reduced admissions. Changes in human exposure are associated with about 2,100 increased ozone-related morbidity incidences and avoidance of at least 60,000 PM2.5-related morbidity incidences.

Policies to regulate severe surface ozone pollution in cities in India are challenging to develop, due to the complex dependence on precursor emissions of volatile organic compounds (VOCs) and nitrogen oxides (NOx), non-linear chemistry leading to ozone formation, and very limited spatial and temporal surface air quality monitoring. Ratios of space-based observations of formaldehyde (HCHO), an intermediate oxidation product of VOCs, and nitrogen dioxide (NO2) have been used to characterize the sensitivity of surface ozone production to precursor emissions of VOCs and NOx, but interpretation of these depends on the local oxidation regime. Here we develop an improved approach in which we discretize the data into background HCHO due to methane and other long-lived VOCs (regression intercept) and the local relationship (regression slope) between HCHO associated with reactive VOCs and NO2. We apply this to TROPOMI HCHO and NO2 tropospheric columns oversampled to higher spatial resolution than the native pixel resolution of the instrument over the ten most populous cities in India. We use GEOS-Chem to characterize the ozone production regimes and then apply this updated interpretation of the relationship between HCHO and NO2 to the oversampled TROPOMI columns to identify the most effective strategies for regulating ozone and whether these should vary seasonally and spatially.