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Exploiting OMI NO2 satellite observations to infer fossil-fuel CO2 emissions from U.S. megacities.
Goldberg, Daniel L; Lu, Zifeng; Oda, Tomohiro; Lamsal, Lok N; Liu, Fei; Griffin, Debora; McLinden, Chris A; Krotkov, Nickolay A; Duncan, Bryan N; Streets, David G.
Afiliação
  • Goldberg DL; Energy Systems Division, Argonne National Laboratory, Lemont, IL, USA; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA. Electronic address: dgoldberg@gwu.edu.
  • Lu Z; Energy Systems Division, Argonne National Laboratory, Lemont, IL, USA; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.
  • Oda T; Goddard Earth Sciences Technology and Research (GESTAR), University Space Research Association, Columbia, MD, USA; Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Lamsal LN; Goddard Earth Sciences Technology and Research (GESTAR), University Space Research Association, Columbia, MD, USA; Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Liu F; Goddard Earth Sciences Technology and Research (GESTAR), University Space Research Association, Columbia, MD, USA; Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Griffin D; Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada.
  • McLinden CA; Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada.
  • Krotkov NA; Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Duncan BN; Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
  • Streets DG; Energy Systems Division, Argonne National Laboratory, Lemont, IL, USA; Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA.
Sci Total Environ ; 695: 133805, 2019 Dec 10.
Article em En | MEDLINE | ID: mdl-31419680
Fossil-fuel CO2 emissions and their trends in eight U.S. megacities during 2006-2017 are inferred by combining satellite-derived NOX emissions with bottom-up city-specific NOX-to-CO2 emission ratios. A statistical model is fit to a collection NO2 plumes observed from the Ozone Monitoring Instrument (OMI), and is used to calculate top-down NOX emissions. Decreases in OMI-derived NOX emissions are observed across the eight cities from 2006 to 2017 (-17% in Miami to -58% in Los Angeles), and are generally consistent with long-term trends of bottom-up inventories (-25% in Miami to -49% in Los Angeles), but there are some interannual discrepancies. City-specific NOX-to-CO2 emission ratios, used to calculate inferred CO2, are estimated through annual bottom-up inventories of NOX and CO2 emissions disaggregated to 1 × 1 km2 resolution. Over the study period, NOX-to-CO2 emission ratios have decreased by ~40% nationwide (-24% to -51% for our studied cities), which is attributed to a faster reduction in NOX when compared to CO2 due to policy regulations and fuel type shifts. Combining top-down NOX emissions and bottom-up NOX-to-CO2 emission ratios, annual fossil-fuel CO2 emissions are derived. Inferred OMI-based top-down CO2 emissions trends vary between +7% in Dallas to -31% in Phoenix. For 2017, we report annual fossil-fuel CO2 emissions to be: Los Angeles 113 ±â€¯49 Tg/yr; New York City 144 ±â€¯62 Tg/yr; and Chicago 55 ±â€¯24 Tg/yr. A study in the Los Angeles area, using independent methods, reported a 2013-2016 average CO2 emissions rate of 104 Tg/yr and 120 Tg/yr, which suggests that the CO2 emissions from our method are in good agreement with other studies' top-down estimates. We anticipate future remote sensing instruments - with better spatial and temporal resolution - will better constrain the NOX-to-CO2 ratio and reduce the uncertainty in our method.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Total Environ Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Total Environ Ano de publicação: 2019 Tipo de documento: Article