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dc.contributor.authordeSouza, Priyanka N.
dc.contributor.authorChaudhary, Ekta
dc.contributor.authorDey, Sagnk
dc.contributor.authorKo, Soohyeon
dc.contributor.authorNémeth, Jeremy
dc.contributor.authorGuttikunda, Sarath
dc.contributor.authorChowdhury, Sourangsu
dc.contributor.authorKinney, Patrick
dc.contributor.authorSubramanian, S.V.
dc.contributor.authorBell, Michelle L.
dc.contributor.authorKim, Rockli
dc.coverage.spatialIndiaen_US
dc.date.accessioned2024-03-06T13:51:40Z
dc.date.available2024-03-06T13:51:40Z
dc.date.created2023-11-07T11:20:54Z
dc.date.issued2023
dc.identifier.citationScientific Reports. 2023, 13 (1), .en_US
dc.identifier.issn2045-2322
dc.identifier.urihttps://hdl.handle.net/11250/3121314
dc.description.abstractDue to the lack of timely data on socioeconomic factors (SES), little research has evaluated if socially disadvantaged populations are disproportionately exposed to higher PM2.5 concentrations in India. We fill this gap by creating a rich dataset of SES parameters for 28,081 clusters (villages in rural India and census-blocks in urban India) from the National Family and Health Survey (NFHS-4) using a precision-weighted methodology that accounts for survey-design. We then evaluated associations between total, anthropogenic and source-specific PM2.5 exposures and SES variables using fully-adjusted multilevel models. We observed that SES factors such as caste, religion, poverty, education, and access to various household amenities are important risk factors for PM2.5 exposures. For example, we noted that a unit standard deviation increase in the cluster-prevalence of Scheduled Caste and Other Backward Class households was significantly associated with an increase in total-PM2.5 levels corresponding to 0.127 μg/m3 (95% CI 0.062 μg/m3, 0.192 μg/m3) and 0.199 μg/m3 (95% CI 0.116 μg/m3, 0.283 μg/m3, respectively. We noted substantial differences when evaluating such associations in urban/rural locations, and when considering source-specific PM2.5 exposures, pointing to the need for the conceptualization of a nuanced EJ framework for India that can account for these empirical differences. We also evaluated emerging axes of inequality in India, by reporting associations between recent changes in PM2.5 levels and different SES parameters.en_US
dc.language.isoengen_US
dc.publisherSpringer Nature ltden_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAn environmental justice analysis of air pollution in Indiaen_US
dc.title.alternativeAn environmental justice analysis of air pollution in Indiaen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber0en_US
dc.source.volume13en_US
dc.source.journalScientific Reportsen_US
dc.source.issue1en_US
dc.identifier.doi10.1038/s41598-023-43628-3
dc.identifier.cristin2193155
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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