Dataset Information

The impacts of human migration and city lockdowns on specific air pollutants during the COVID-19 outbreak: A spatial perspective.

ABSTRACT: The outbreak of COVID-19 continues to bring unprecedented shock to mankind's socioeconomic activities, and to the wider environment. China, as the early epicenter of the pandemic, locked down one-third of its cities in an attempt to prevent the rapid spread of the virus. Human migration patterns have subsequently been radically altered and many regions have seen perceived improvements in air quality during the lockdowns. This study empirically examines the relationship between human migration and air pollution and further evaluates the causal impacts of the lockdowns. A spatial econometric method and a spatial explicit counterfactual framework are employed in this study. The key findings are as follows: i) a considerable amount of variation in AQI, PM₁₀, PM_2.5, and NO₂ concentration can be explained by human migration but we fail to find suggestive evidence in the cases of SO₂ and CO; ii) the implementation of lockdown measures led to a significant reduction in AQI (18.1%), PM_2.5 (22.2%), NO₂ (20.5%), and PM₁₀ (10.7%), but has no meaningful impacts on SO_2, CO and O₃ levels; iii) further analysis indicates that the impacts of lockdown policies varied by control stringency and by regional heterogeneity. Our findings are of great importance for the Chinese government to create a stronger and more coherent framework in its efforts to tackle air pollution.

SUBMITTER: Zeng J

PROVIDER: S-EPMC7955165 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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The impacts of human migration and city lockdowns on specific air pollutants during the COVID-19 outbreak: A spatial perspective.

Zeng Jingjing J Bao Rui R

Journal of environmental management 20201230

The outbreak of COVID-19 continues to bring unprecedented shock to mankind's socioeconomic activities, and to the wider environment. China, as the early epicenter of the pandemic, locked down one-third of its cities in an attempt to prevent the rapid spread of the virus. Human migration patterns have subsequently been radically altered and many regions have seen perceived improvements in air quality during the lockdowns. This study empirically examines the relationship between human migration an ...[more]

PMID: 33465715

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Project description:Recent epidemiological studies have examined the associations between air pollution and birth outcomes. Regulatory air quality monitors often used in these studies, however, were spatially sparse and unable to capture relevant within-city variation in exposure during pregnancy.This study developed two-week average exposure estimates for fine particles (PM2.5) and nitrogen dioxide (NO2) during pregnancy for 274,996 New York City births in 2008-2010. The two-week average exposures were constructed by first developing land use regression (LUR) models of spatial variation in annual average PM2.5 and NO2 data from 150 locations in the New York City Community Air Survey and emissions source data near monitors. The annual average concentrations from the spatial models were adjusted to account for city-wide temporal trends using time series derived from regulatory monitors. Models were developed using Year 1 data and validated using Year 2 data. Two-week average exposures were then estimated for three buffers of maternal address and were averaged into the last six weeks, the trimesters, and the entire period of gestation. We characterized temporal variation of exposure estimates, correlation between PM2.5 and NO2, and correlation of exposures across trimesters.The LUR models of average annual concentrations explained a substantial amount of the spatial variation (R2 = 0.79 for PM2.5 and 0.80 for NO2). In the validation, predictions of Year 2 two-week average concentrations showed strong agreement with measured concentrations (R2 = 0.83 for PM2.5 and 0.79 for NO2). PM2.5 exhibited greater temporal variation than NO2. The relative contribution of temporal vs. spatial variation in the estimated exposures varied by time window. The differing seasonal cycle of these pollutants (bi-annual for PM2.5 and annual for NO2) resulted in different patterns of correlations in the estimated exposures across trimesters. The three levels of spatial buffer did not make a substantive difference in estimated exposures.The combination of spatially resolved monitoring data, LUR models and temporal adjustment using regulatory monitoring data yielded exposure estimates for PM2.5 and NO2 that performed well in validation tests. The interaction between seasonality of air pollution and exposure intervals during pregnancy needs to be considered in future studies.

Dataset Information

The impacts of human migration and city lockdowns on specific air pollutants during the COVID-19 outbreak: A spatial perspective.

Publications

The impacts of human migration and city lockdowns on specific air pollutants during the COVID-19 outbreak: A spatial perspective.

Similar Datasets

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