The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Long-Term Trends Worldwide in Ambient NO 2 Concentrations Inferred from Satellite Observations
Open accessAbstract
BACKGROUND: Air pollution is associated with morbidity and premature mortality. Satellite remote sensing provides globally consistent decadal-scale observations of ambient nitrogen dioxide (NO2) pollution. OBJECTIVE: We determined global population-weighted annual mean NO2 concentrations from 1996 through 2012. METHODS: We used observations of NO2 tropospheric column densities from three satellite instruments in combination with chemical transport modeling to produce a global 17-year record of ground-level NO2 at 0.1° × 0.1° resolution. We calculated linear trends in population-weighted annual mean NO2 (PWMNO2) concentrations in different regions around the world. RESULTS: We found that PWMNO2 in high-income North America (Canada and the United States) decreased more steeply than in any other region, having declined at a rate of -4.7%/year [95% confidence interval (CI): -5.3, -4.1]. PWMNO2 decreased in western Europe at a rate of -2.5%/year (95% CI: -3.0, -2.1). The highest PWMNO2 occurred in high-income Asia Pacific (predominantly Japan and South Korea) in 1996, with a subsequent decrease of -2.1%/year (95% CI: -2.7, -1.5). In contrast, PWMNO2 almost tripled in East Asia (China, North Korea, and Taiwan) at a rate of 6.7%/year (95% CI: 6.0, 7.3). The satellite-derived estimates of trends in ground-level NO2 were consistent with regional trends inferred from data obtained from ground-station monitoring networks in North America (within 0.7%/year) and Europe (within 0.3%/year). Our rankings of regional average NO2 and long-term trends differed from the satellite-derived estimates of fine particulate matter reported elsewhere, demonstrating the utility of both indicators to describe changing pollutant mixtures. CONCLUSIONS: Long-term trends in satellite-derived ambient NO2 provide new information about changing global exposure to ambient air pollution. Our estimates are publicly available at http://fizz.phys.dal.ca/~atmos/martin/?page_id=232.
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Clark, L. P., Millet, D. B., & Marshall, J. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0094431 · Cited by 463
MacIntyre, E. A., Gehring, U., Mölter, A., Fuertes, E., Klümper, C., Krämer, U., Quass, U., Hoffmann, B., Gascon, M., Brunekreef, B., et al. (2014) · Environmental Health Perspectives · doi:10.1289/ehp.1306755 · Cited by 307
Tao, Y., Huang, W., Huang, X., Zhong, L., Lu, S.-E., Li, Y., Dai, L., Zhang, Y., & Zhu, T. (2012) · Environmental Health Perspectives · doi:10.1289/ehp.1103715 · Cited by 190
Cited by
West, J. J., Cohen, A., Dentener, F., Brunekreef, B., Zhu, T., Armstrong, B., Bell, M. L., Brauer, M., Carmichael, G., Costa, D. L., et al. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.5b03827 · Cited by 390
Self-citationDi, Q., Amini, H., Shi, L., Kloog, I., Silvern, R., Kelly, J., Sabath, M. B., Choirat, C., Koutrakis, P., Lyapustin, A., et al. (2020) · Environmental Science & Technology · doi:10.1021/acs.est.9b03358 · Cited by 298
Disentangling the Impact of the COVID‐19 Lockdowns on Urban NO 2 From Natural Variability
Goldberg, D. L., Anenberg, S. C., Griffin, D., McLinden, C. A., Lu, Z., & Streets, D. G. (2020) · Geophysical Research Letters · doi:10.1029/2020gl089269 · Cited by 289
Green growth efficiency of Chinese cities and its spatio-temporal pattern
Ma, L., Long, H., Chen, K., Tu, S., Zhang, Y., & Liao, L. (2019) · Resources, Conservation and Recycling · doi:10.1016/j.resconrec.2019.03.049 · Cited by 138
Metadata
- Authors
- Geddes, J. A., Martin, R. V., Boys, B. L., & van Donkelaar, A.
- Venue
- Environmental Health Perspectives
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-03
- Volume
- 124
- Issue
- 3
- Pages
- 281-289
- ISSN
- 0091-6765 (ISSN-L)
- 1552-9924
- OpenAlex
- W2330583268
- Cited by
- 223
- References
- 3
- FWCI
- 7.10
- Type
- journal article
- Language
- en
- Open access
- gold
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