COVID-19 lockdowns cause global air pollution declines

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Abstract

The lockdown response to coronavirus disease 2019 (COVID-19) has caused an unprecedented reduction in global economic and transport activity. We test the hypothesis that this has reduced tropospheric and ground-level air pollution concentrations, using satellite data and a network of >10,000 air quality stations. After accounting for the effects of meteorological variability, we find declines in the population-weighted concentration of ground-level nitrogen dioxide (NO 2 : 60% with 95% CI 48 to 72%), and fine particulate matter (PM 2.5 : 31%; 95% CI: 17 to 45%), with marginal increases in ozone (O 3 : 4%; 95% CI: −2 to 10%) in 34 countries during lockdown dates up until 15 May. Except for ozone, satellite measurements of the troposphere indicate much smaller reductions, highlighting the spatial variability of pollutant anomalies attributable to complex NO x chemistry and long-distance transport of fine particulate matter with a diameter less than 2.5 µm (PM 2.5 ). By leveraging Google and Apple mobility data, we find empirical evidence for a link between global vehicle transportation declines and the reduction of ambient NO 2 exposure. While the state of global lockdown is not sustainable, these findings allude to the potential for mitigating public health risk by reducing “business as usual” air pollutant emissions from economic activities. Explore trends here: https://nina.earthengine.app/view/lockdown-pollution .

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  1. SciScore for 10.1101/2020.04.10.20060673: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations and perspectives: Making explicit links between ambient air pollution and human health burden relies on several assumptions that are difficult to verify apriori. First, using relative risk rates from select meta-analysis (17) and multi-city (n>406) short-term time-series association studies (18, 19) to make inference over entire countries rests on the assumption that city- or cohort-specific response rates are generalizable to broader populations. While this is likely to introduce uncertainty, the dearth of representative data necessities these generalizations, and this approach has been used by numerous studies at the global scale (2, 3). Further, we acknowledge that our results are affected by harvesting effects, where premature deaths attributed to air pollution might have occurred in the immediate future (20). Note that this also applies to death counts attributed to COVID-19. We also acknowledge that we do not account for indoor sources of PM2.5 pollution which are unlikely to be reduced by lockdown measures. As smoke from household stoves add substantially to population exposure for people dependent on solid fuels, accounting for ambient air pollution only could imply a misclassification of exposure and biased health burden estimates (21). Finally, the baseline mortality rates we use are from 2017 (22) and therefore may be prone to ignoring before and after COVID-19 onset differences in baseline mortality incidence. Despite these assumptions and the associat...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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