Lockdowns implemented in response to COVID-19 have caused an unprecedented reduction in global economic and transport activity. In this study, variation in the concentration of health-threatening air pollutants (PM 2.5 , NO 2 , and O 3 ) pre- and post-lockdown was investigated at global, continental, and national scales. We analyzed ground-based data from >10,000 monitoring stations in 380 cities across the globe. Global-scale results during lockdown (March to May 2020) showed that concentrations of PM 2.5 and NO 2 decreased by 16.1% and 45.8%, respectively, compared to the baseline period (2015–2019). However, O 3 concentration increased by 5.4%. At the continental scale, concentrations of PM 2.5 and NO 2 substantially dropped in 2020 across all continents during lockdown compared to the baseline, with a maximum reduction of 20.4% for PM 2.5 in East Asia and 42.5% for NO 2 in Europe. The maximum reduction in O 3 was observed in North America (7.8%), followed by Asia (0.7%), while small increases were found in other continents. At the national scale, PM 2.5 and NO 2 concentrations decreased significantly during lockdown, but O 3 concentration showed varying patterns among countries. We found maximum reductions of 50.8% for PM 2.5 in India and 103.5% for NO 2 in Spain. The maximum reduction in O 3 (22.5%) was found in India. Improvements in air quality were temporary as pollution levels increased in cities since lockdowns were lifted. We posit that these unprecedented changes in air pollutants were mainly attributable to reductions in traffic and industrial activities. Column reductions could also be explained by meteorological variability and a decline in emissions caused by environmental policy regulations. Our results have implications for the continued implementation of strict air quality policies and emission control strategies to improve environmental and human health.

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Mitigating high air temperatures and heat waves is vital for decreasing air pollution and protecting public health. To improve understanding of microscale urban air temperature variation, this paper performed measurements of air temperature and relative humidity in a field of Wuhan City in the afternoon of hot summer days, and used path analysis and genetic support vector regression (SVR) to quantify the independent influences of land cover and humidity on air temperature variation. The path analysis shows that most effect of the land cover is mediated through relative humidity difference, more than four times as much as the direct effect, and that the direct effect of relative humidity difference is nearly six times that of land cover, even larger than the total effect of the land cover. The SVR simulation illustrates that land cover and relative humidity independently contribute 16.3% and 83.7%, on average, to the rise of the air temperature over the land without vegetation in the study site. An alternative strategy of increasing the humidity artificially is proposed to reduce high air temperatures in urban areas. The study would provide scientific support for the regulation of the microclimate and the mitigation of the high air temperature in urban areas.