The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors
Open accessAbstract
Abstract An accurate fine-resolution surface of the chemical composition of fine particulate matter (PM2.5) would offer valuable information for epidemiological studies and health impact assessments. We develop geoscience-derived estimates of PM2.5 composition from a chemical transport model (GEOS-Chem) and satellite observations of aerosol optical depth, and statistically fuse these estimates with ground-based observations using a geographically weighted regression over North America to produce a spatially complete representation of sulfate, nitrate, ammonium, black carbon, organic matter, mineral dust, and sea-salt over 2000–2016. Significant long-term agreement is found with cross-validation sites over North America (R2 = 0.57─0.96), with the strongest agreement for sulfate (R2 = 0.96), nitrate (R2 = 0.90), and ammonium (R2 = 0.86). We find that North American decreases in population-weighted fine particulate matter (PM2.5) concentrations since 2000 have been most heavily influenced by regional changes in sulfate and organic matter. Regionally, the relative importance of several chemical components are found to change with PM2.5 concentration, such as higher PM2.5 concentrations having a larger proportion of nitrate and a smaller proportion of sulfate. This data set offers information for research into the health effects of PM2.5 chemical components.
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Citations
Cites
An association between air pollution and mortality in six U.S. cities
Dockery, D. W., Pope, C. A., Xu, X., Spengler, J. D., Ware, J. H., Fay, M. E., Ferris, B. G., & Speizer, F. E. (1993) · New England Journal of Medicine · doi:10.1056/nejm199312093292401 · Cited by 8,018
Cohen, A. J., Brauer, M., Burnett, R., Anderson, H. R., Frostad, J., Estep, K., Balakrishnan, K., Brunekreef, B., Dandona, L., Dandona, R., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)30505-6 · Cited by 6,583
Self-citation
Cited by
Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty
van Donkelaar, A., Hammer, M. S., Bindle, L., Brauer, M., Brook, J. R., Garay, M. J., Hsu, N. C., Kalashnikova, O. V., Kahn, R. A., Lee, C., et al. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.1c05309 · Cited by 747
Self-citationRegional and global contributions of air pollution to risk of death from COVID-19
Pozzer, A., Dominici, F., Haines, A., Witt, C., Münzel, T., & Lelieveld, J. (2020) · Cardiovascular Research · doi:10.1093/cvr/cvaa288 · Cited by 463
“The virus was zoonotic, as it originally developed in bats.9 The World Health Organization (WHO) reported that it resulted in a SARS epidemic with >8000 cases in 26 countries, mostly in south-east Asia and in Canada.8 The disease emerged in November 2002 and was contained in July 2003.”
BackgroundMethodChambliss, S. E., Pinon, C. P. R., Messier, K. P., LaFranchi, B., Upperman, C. R., Lunden, M. M., Robinson, A. L., Marshall, J. D., & Apte, J. S. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2109249118 · Cited by 156
Shi, L., Zhu, Q., Wang, Y., Hao, H., Zhang, H., Schwartz, J., Amini, H., van Donkelaar, A., Martin, R. V., Steenland, K., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2211282119 · Cited by 145
Self-citationLi, S., Oliva, P., Zhang, L., Goodrich, J. A., McConnell, R., Conti, D. V., Chatzi, L., & Aung, M. (2025) · Journal of Exposure Science & Environmental Epidemiology · doi:10.1038/s41370-024-00742-2 · Cited by 101
Metadata
- Authors
- van Donkelaar, A., Martin, R. V., Li, C., & Burnett, R. T.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-01-30
- Volume
- 53
- Issue
- 5
- Pages
- 2595-2611
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W2912034185
- Cited by
- 715
- References
- 2
- FWCI
- 34.68
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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