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The COVID-19 containment response policies (CRPs) had a major impact on air quality (AQ). These CRPs have been time-varying and location-specific. So far, despite having numerous studies on the effect of COVID-19 lockdown on AQ, a knowledge gap remains on the association between stringency of CRPs and AQ changes across the world, regions, nations, and cities. Here, we show that globally across 1851 cities (each more than 300 000 people) in 149 countries, after controlling for the impacts of relevant covariates (e.g., meteorology), Sentinel-5P satellite-observed nitrogen dioxide (NO 2 ) levels decreased by 4.9% (95% CI: 2.2, 7.6%) during lockdowns following stringent CRPs compared to pre-CRPs. The NO 2 levels did not change significantly during moderate CRPs and even increased during mild CRPs by 2.3% (95% CI: 0.7, 4.0%), which was 6.8% (95% CI: 2.0, 12.0%) across Europe and Central Asia, possibly due to population avoidance of public transportation in favor of private transportation. Among 1768 cities implementing stringent CRPs, we observed the most NO 2 reduction in more populated and polluted cities. Our results demonstrate that AQ improved when and where stringent COVID-19 CRPs were implemented, changed less under moderate CRPs, and even deteriorated under mild CRPs. These changes were location-, region-, and CRP-specific.

Background: Health impact assessment (HIA) of exposure to air pollution is commonly based on city level (fine) particle concentration and may underestimate health consequences of changing local traffic. Exposure to traffic-related air pollution can be assessed at a high resolution by modelling levels of nitrogen dioxide (NO 2 ), which together with ultrafine particles mainly originate from diesel-powered vehicles in urban areas. The purpose of this study was to estimate the health benefits of reduced exposure to vehicle emissions assessed as NO 2 at the residence among the citizens of Copenhagen Municipality, Denmark., Methods: We utilized residential NO 2 concentrations modelled by use of chemistry transport models to calculate contributions from emission sources to air pollution. The DYNAMO-HIA model was applied to the population of Copenhagen Municipality by using NO 2 concentration estimates combined with demographic data and data from nationwide registers on incidence and prevalence of selected diseases, cause specific mortality, and total mortality of the population of Copenhagen. We used exposure-response functions linking NO 2 concentration estimates at the residential address with the risk of diabetes, cardiovascular diseases, and respiratory diseases derived from a large Danish cohort study with the majority of subjects residing in Copenhagen between 1971 and 2010. Different scenarios were modelled to estimate the dynamic impact of NO 2 exposure on related diseases and the potential health benefits of lowering the NO 2 level in the Copenhagen Municipality., Results: The annual mean NO 2 concentration was 19.6 μg/m 3 and for 70% of the population the range of exposure was between 15 and 21 μg/m 3 . If NO 2 exposure was reduced to the annual mean rural level of 6 μg/m 3 , life expectancy in 2040 would increase by one year. The greatest gain in disease-free life expectancy would be lifetime without ischemic heart disease (1.4 years), chronic obstructive pulmonary disease (1.5 years for men and 1.6 years for women), and asthma (1.3 years for men and 1.5 years for women). Lowering NO 2 exposure by 20% would increase disease-free life expectancy for the different diseases by 0.3-0.5 years. Using gender specific relative risks affected the results., Conclusions: Reducing the NO 2 exposure by controlling traffic-related air pollution reduces the occurrence of some of the most prevalent chronic diseases and increases life expectancy. Such health benefits can be quantified by DYNAMO-HIA in a high resolution exposure modelling. This paper demonstrates how traffic planners can assess health benefits from reduced levels of traffic-related air pollution., (Copyright © 2018 Elsevier Ltd. All rights reserved.)