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      COVID-19 pandemic reveals persistent disparities in nitrogen dioxide pollution

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          Significance

          We leverage the unparalleled changes in human activity during COVID-19 and the unmatched capabilities of the TROPOspheric Monitoring Instrument to understand how lockdowns impact ambient nitrogen dioxide ( N O 2 ) pollution disparities in the United States. The least White communities experienced the largest N O 2 reductions during lockdowns; however, disparities between the least and most White communities are so large that the least White communities still faced higher N O 2 levels during lockdowns than the most White communities experienced prior to lockdowns, despite a 50% reduction in passenger vehicle traffic. Similar findings hold for ethnic, income, and educational attainment population subgroups. Future strategies to reduce N O 2 disparities will need to target emissions from heavy-duty vehicles.

          Abstract

          The unequal spatial distribution of ambient nitrogen dioxide ( N O 2 ), an air pollutant related to traffic, leads to higher exposure for minority and low socioeconomic status communities. We exploit the unprecedented drop in urban activity during the COVID-19 pandemic and use high-resolution, remotely sensed N O 2 observations to investigate disparities in N O 2 levels across different demographic subgroups in the United States. We show that, prior to the pandemic, satellite-observed N O 2 levels in the least White census tracts of the United States were nearly triple the N O 2 levels in the most White tracts. During the pandemic, the largest lockdown-related N O 2 reductions occurred in urban neighborhoods that have 2.0 times more non-White residents and 2.1 times more Hispanic residents than neighborhoods with the smallest reductions. N O 2 reductions were likely driven by the greater density of highways and interstates in these racially and ethnically diverse areas. Although the largest reductions occurred in marginalized areas, the effect of lockdowns on racial, ethnic, and socioeconomic N O 2 disparities was mixed and, for many cities, nonsignificant. For example, the least White tracts still experienced 1.5 times higher N O 2 levels during the lockdowns than the most White tracts experienced prior to the pandemic. Future policies aimed at eliminating pollution disparities will need to look beyond reducing emissions from only passenger traffic and also consider other collocated sources of emissions such as heavy-duty vehicles.

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          Most cited references58

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          The Lancet Commission on pollution and health

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            Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement

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              Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study

              Summary Background Within 4 months of COVID-19 first being reported in the USA, it spread to every state and to more than 90% of all counties. During this period, the US COVID-19 response was highly decentralised, with stay-at-home directives issued by state and local officials, subject to varying levels of enforcement. The absence of a centralised policy and timeline combined with the complex dynamics of human mobility and the variable intensity of local outbreaks makes assessing the effect of large-scale social distancing on COVID-19 transmission in the USA a challenge. Methods We used daily mobility data derived from aggregated and anonymised cell (mobile) phone data, provided by Teralytics (Zürich, Switzerland) from Jan 1 to April 20, 2020, to capture real-time trends in movement patterns for each US county, and used these data to generate a social distancing metric. We used epidemiological data to compute the COVID-19 growth rate ratio for a given county on a given day. Using these metrics, we evaluated how social distancing, measured by the relative change in mobility, affected the rate of new infections in the 25 counties in the USA with the highest number of confirmed cases on April 16, 2020, by fitting a statistical model for each county. Findings Our analysis revealed that mobility patterns are strongly correlated with decreased COVID-19 case growth rates for the most affected counties in the USA, with Pearson correlation coefficients above 0·7 for 20 of the 25 counties evaluated. Additionally, the effect of changes in mobility patterns, which dropped by 35–63% relative to the normal conditions, on COVID-19 transmission are not likely to be perceptible for 9–12 days, and potentially up to 3 weeks, which is consistent with the incubation time of severe acute respiratory syndrome coronavirus 2 plus additional time for reporting. We also show evidence that behavioural changes were already underway in many US counties days to weeks before state-level or local-level stay-at-home policies were implemented, implying that individuals anticipated public health directives where social distancing was adopted, despite a mixed political message. Interpretation This study strongly supports a role of social distancing as an effective way to mitigate COVID-19 transmission in the USA. Until a COVID-19 vaccine is widely available, social distancing will remain one of the primary measures to combat disease spread, and these findings should serve to support more timely policy making around social distancing in the USA in the future. Funding None.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                27 July 2021
                19 July 2021
                19 July 2021
                : 118
                : 30
                : e2022409118
                Affiliations
                [1] aDepartment of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University , Washington, DC 20052;
                [2] bEnergy Systems Division, Argonne National Laboratory , Lemont, IL 60439
                Author notes
                1To whom correspondence may be addressed. Email: gaigekerr@ 123456gwu.edu .

                Edited by Susan Solomon, Massachusetts Institute of Technology, Cambridge, MA, and approved June 11, 2021 (received for review October 26, 2020)

                Author contributions: G.H.K., D.L.G., and S.C.A. designed research; G.H.K. and D.L.G. performed research; G.H.K. and D.L.G. analyzed data; and G.H.K., D.L.G., and S.C.A. wrote the paper.

                Author information
                http://orcid.org/0000-0001-8869-0752
                http://orcid.org/0000-0003-0784-3986
                http://orcid.org/0000-0002-9668-603X
                Article
                202022409
                10.1073/pnas.2022409118
                8325165
                34285070
                b7050746-a6d4-4aaa-b8c2-955dd3ade72b
                Copyright © 2021 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                History
                Page count
                Pages: 9
                Funding
                Funded by: National Aeronautics and Space Administration (NASA) 100000104
                Award ID: 80NSSC20K1122
                Award Recipient : Daniel L Goldberg Award Recipient : Susan Anenberg
                Funded by: National Aeronautics and Space Administration (NASA) 100000104
                Award ID: 80NSSC19K0193
                Award Recipient : Daniel L Goldberg Award Recipient : Susan Anenberg
                Categories
                413
                434
                9
                Physical Sciences
                Earth, Atmospheric, and Planetary Sciences
                Social Sciences
                Sustainability Science

                nitrogen dioxide,air pollution,environmental justice,covid-19,tropomi

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