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dc.contributor.authorMartin, RV
dc.contributor.authorBrauer, M
dc.contributor.authorvan Donkelaar, A
dc.contributor.authorShaddick, G
dc.contributor.authorNarain, U
dc.contributor.authorDey, S
dc.date.accessioned2019-09-30T11:08:52Z
dc.date.issued2019-05-24
dc.description.abstractExposure to ambient fine particulate matter (PM2.5) is the leading global environmental risk factor for mortality and disease burden, with associated annual global welfare costs of trillions of dollars. Examined within is the ability of current data to answer a basic question about PM2.5, namely the location of the city with the highest PM2.5 concentration. The ability to answer this basic question serves as an indicator of scientific progress to assess global human exposure to air pollution and as an important component of efforts to reduce its impacts. Despite the importance of PM2.5, we find that insufficient monitoring data exist to answer this basic question about the spatial pattern of PM2.5 at the global scale. Only 24 of 234 countries have more than 3 monitors per million inhabitants, while density is an order of magnitude lower in the vast majority of the world's countries, with 141 having no regular PM2.5 monitoring at all. The global mean population distance to nearest PM2.5 monitor is 220 km, too large for exposure assessment. Efforts to fill in monitoring gaps with estimates from satellite remote sensing, chemical transport modeling, and statistical models have biases at individual monitor locations that can exceed 50 μg m−3. Progress in advancing knowledge about the global distribution of PM2.5 will require a harmonized network that integrates different types of monitoring equipment (regulatory networks, low-cost monitors, satellite remote sensing, and research-grade instrumentation) with atmospheric and statistical models. Realization of such an integrated framework will facilitate accurate identification of the location of the city with the highest PM2.5 concentration and play a key role in tracking the progress of efforts to reduce the global impacts of air pollution.en_GB
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canadaen_GB
dc.description.sponsorshipDepartment of Biotechnology on ‘Air Pollution and Human Health’en_GB
dc.identifier.citationVol. 3: 100040en_GB
dc.identifier.doi10.1016/j.aeaoa.2019.100040
dc.identifier.grantnumberBT/IN/UK/APHH/41/KB/2016–17en_GB
dc.identifier.urihttp://hdl.handle.net/10871/38962
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.rights© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND licenseen_GB
dc.subjectFine particulate matteren_GB
dc.subjectPM2.5en_GB
dc.subjectAir qualityen_GB
dc.titleNo one knows which city has the highest concentration of fine particulate matteren_GB
dc.typeArticleen_GB
dc.date.available2019-09-30T11:08:52Z
dc.identifier.issn2590-1621
dc.descriptionThis is the final version. Available from the publisher via the DOI in this record.en_GB
dc.identifier.journalAtmospheric Environment: Xen_GB
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_GB
dcterms.dateAccepted2019-06-14
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2019-06-24
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-09-30T11:05:02Z
refterms.versionFCDVoR
refterms.dateFOA2019-09-30T11:08:55Z
refterms.panelBen_GB
refterms.depositExceptionpublishedGoldOA
refterms.depositExceptionExplanationhttps://doi.org/10.1016/j.aeaoa.2019.100040


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© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
Except where otherwise noted, this item's licence is described as © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license