The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO2, O3, and PM2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO2 concentrations and increases in O3 were observed in almost all cities. However, the decline in NO2 concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O3 increased by 2 to 30% (except for London), the total gaseous oxidant (Ox = NO2 + O3) showed limited change, and PM2.5 concentrations decreased in most cities studied but increased in London and Paris. Our results demonstrate the need for a sophisticated analysis to quantify air quality impacts of interventions and indicate that true air quality improvements were notably more limited than some earlier reports or observational data suggested.

Black carbon (BC) not only warms the atmosphere but also affects human health. The nationwide lockdown due to the Coronavirus Disease 2019 (COVID-19) pandemic led to a major reduction in human activity during the past 30 years. Here, the concentration of BC in the urban, urban-industry, suburb, and rural areas of a megacity Hangzhou were monitored using a multiwavelength Aethalometer to estimate the impact of the COVID-19 lockdown on BC emissions. The citywide BC decreased by 44% from 2.30 to 1.29 μg/m 3 following the COVID-19 lockdown period. The source apportionment based on the Aethalometer model shows that vehicle emission reduction responded to BC decline in the urban area and biomass burning in rural areas around the megacity had a regional contribution of BC. We highlight that the emission controls of vehicles in urban areas and biomass burning in rural areas should be more efficient in reducing BC in the megacity Hangzhou. As the first country reporting and fighting Coronavirus Disease 2019 (COVID-19), China has implemented a series of effective measures to prevent the spread of COVID-19, including stay-at-home orders, travel bans, shutting down nonessential commercial activities, and a national lockdown (Tian et al., 2020). These nationwide restrictions have led to the lowest human activity in modern China in the past 30 years, resulting in the

Atmospheric particulate matter (PM) exerts significant impacts on air quality, climate change, and public health (IPCC, 2013; West et al., 2016). The megacities in developing countries, such as China and India, are facing severe air pollution, especially the fine particle (PM 2.5) problem because of their fast-growing economy and urbanization in past decades (Fu & Chen, 2017; Gurjar et al., 2016). To mitigate air pollution, the Chinese State Council implemented the "Air Pollution Prevention and Control Action Plan" in 2013 (Chinese State Council, 2013). As a consequence, anthropogenic emissions of major air pollutants decreased largely (e.g., 59% for SO 2 , 21% for NO x , and 33% for primary PM 2.5) in China during 2013-2017 (Q. Zhang & Geng, 2019). However, despite large reductions in primary emissions, heavy haze episodes still occur in

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