The DOI matches its Crossref record; 218 of the 218 references it cites were found in a registry or an index.
Emissions estimation from satellite retrievals: A review of current capability
Open accessAbstract
Since the mid-1990s a new generation of Earth-observing satellites has been able to detect tropospheric air pollution at increasingly high spatial and temporal resolution. Most primary emitted species can be measured by one or more of the instruments. This review article addresses the question of how well we can relate the satellite measurements to quantification of primary emissions and what advances are needed to improve the usability of the measurements by U.S. air quality managers. Built on a comprehensive literature review and comprising input by both satellite experts and emission inventory specialists, the review identifies several targets that seem promising: large point sources of NOx and SO2, species that are difficult to measure by other means (NH3 and CH4, for example), area sources that cannot easily be quantified by traditional bottom-up methods (such as unconventional oil and gas extraction, shipping, biomass burning, and biogenic sources), and the temporal variation of emissions (seasonal, diurnal, episodic). Techniques that enhance the usefulness of current retrievals (data assimilation, oversampling, multi-species retrievals, improved vertical profiles, etc.) are discussed. Finally, we point out the value of having new geostationary satellites like GEO-CAPE and TEMPO over North America that could provide measurements at high spatial (few km) and temporal (hourly) resolution.
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Cites
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Cited by
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Self-citationUnexpected air pollution with marked emission reductions during the COVID-19 outbreak in China
Le, T., Wang, Y., Liu, L., Yang, J., Yung, Y. L., Li, G., & Seinfeld, J. H. (2020) · Science · doi:10.1126/science.abb7431 · Cited by 931
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McDuffie, E. E., Smith, S. J., O'Rourke, P., Tibrewal, K., Venkataraman, C., Marais, E. A., Zheng, B., Crippa, M., Brauer, M., & Martin, R. V. (2020) · Earth System Science Data · doi:10.5194/essd-12-3413-2020 · Cited by 714
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Metadata
- Authors
- Streets, D. G., Canty, T., Carmichael, G. R., de Foy, B., Dickerson, R. R., Duncan, B. N., Edwards, D. P., Haynes, J. A., Henze, D. K., Houyoux, M. R., Jacob, D. J., Krotkov, N. A., Lamsal, L. N., Liu, Y., Lu, Z., Martin, R. V., Pfister, G. G., Pinder, R. W., Salawitch, R. J., & Wecht, K. J.
- Venue
- Atmospheric Environment
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 77
- Pages
- 1011-1042
- ISSN
- 1352-2310 (ISSN-L)
- OpenAlex
- W2169262944
- Cited by
- 419
- References
- 218
- FWCI
- 18.82
- Type
- journal article
- Language
- en
- Open access
- green
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- Streets, D. G., Canty, T., Carmichael, G. R., de Foy, B., Dickerson, R. R., Duncan, B. N., Edwards, D. P., Haynes, J. A., Henze, D. K., Houyoux, M. R., Jacob, D. J., Krotkov, N. A., Lamsal, L. N., Liu, Y., Lu, Z., Martin, R. V., Pfister, G. G., Pinder, R. W., Salawitch, R. J., & Wecht, K. J. (2013). Emissions estimation from satellite retrievals: A review of current capability. Atmospheric Environment. https://doi.org/10.1016/j.atmosenv.2013.05.051
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
