Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data
We estimate methane emissions from North America with high spatial resolution by inversion of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite observations using the Goddard Earth Observing System Chemistry (GEOSâ€Chem) chemical transport model and its adjo...
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ftcaltechauth:oai:authors.library.caltech.edu:57kha-ag836 2024-06-23T07:53:34+00:00 Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data Wecht, Kevin J. Jacob, Daniel J. Frankenberg, Christian Jiang, Zhe Blake, Donald R. 2014-06-27 https://doi.org/10.1002/2014jd021551 unknown American Geophysical Union https://doi.org/10.1002/2014jd021551 oai:authors.library.caltech.edu:57kha-ag836 eprintid:91253 resolverid:CaltechAUTHORS:20181127-155643512 info:eu-repo/semantics/openAccess Other Journal of Geophysical Research. Atmospheres, 119(12), 7741-7756, (2014-06-27) methane inversion emissions satellite info:eu-repo/semantics/article 2014 ftcaltechauth https://doi.org/10.1002/2014jd021551 2024-06-12T05:26:08Z We estimate methane emissions from North America with high spatial resolution by inversion of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite observations using the Goddard Earth Observing System Chemistry (GEOSâ€Chem) chemical transport model and its adjoint. The inversion focuses on summer 2004 when data from the Intercontinental Chemical Transport Experimentâ€North America (INTEXâ€A) aircraft campaign over the eastern U.S. are available to validate the SCIAMACHY retrievals and evaluate the inversion. From the INTEXâ€A data we identify and correct a water vaporâ€dependent bias in the SCIAMACHY data. We conduct an initial inversion of emissions on the horizontal grid of GEOSâ€Chem (1/2° × 2/3°) to identify correction tendencies relative to the Emission Database for Global Atmospheric Research (EDGAR) v4.2 emission inventory used as a priori. We then cluster these grid cells with a hierarchical algorithm to extract the maximum information from the SCIAMACHY observations. A 1000 cluster ensemble can be adequately constrained, providing ~100 km resolution across North America. Analysis of results indicates that the Hudson Bay Lowland wetlands source is 2.1 Tg a^(−1), lower than the a priori but consistent with other recent estimates. Anthropogenic U.S. emissions are 30.1 ± 1.3 Tg a^(−1), compared to 25.8 Tg a^(−1) and 28.3 Tg a^(−1) in the EDGAR v4.2 and Environmental Protection Agency (EPA) inventories, respectively. We find that U.S. livestock emissions are 40% greater than in these two inventories. No such discrepancy is apparent for overall U.S. oil and gas emissions, although this may reflect some compensation between overestimate of emissions from storage/distribution and underestimate from production. We find that U.S. livestock emissions are 70% greater than the oil and gas emissions, in contrast to the EDGAR v4.2 and EPA inventories where these two sources are of comparable magnitude. ©2014. The Authors. This is an open ... Article in Journal/Newspaper Hudson Bay Caltech Authors (California Institute of Technology) Hudson Hudson Bay Journal of Geophysical Research: Atmospheres 119 12 7741 7756 |
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Caltech Authors (California Institute of Technology) |
op_collection_id |
ftcaltechauth |
language |
unknown |
topic |
methane inversion emissions satellite |
spellingShingle |
methane inversion emissions satellite Wecht, Kevin J. Jacob, Daniel J. Frankenberg, Christian Jiang, Zhe Blake, Donald R. Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data |
topic_facet |
methane inversion emissions satellite |
description |
We estimate methane emissions from North America with high spatial resolution by inversion of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite observations using the Goddard Earth Observing System Chemistry (GEOSâ€Chem) chemical transport model and its adjoint. The inversion focuses on summer 2004 when data from the Intercontinental Chemical Transport Experimentâ€North America (INTEXâ€A) aircraft campaign over the eastern U.S. are available to validate the SCIAMACHY retrievals and evaluate the inversion. From the INTEXâ€A data we identify and correct a water vaporâ€dependent bias in the SCIAMACHY data. We conduct an initial inversion of emissions on the horizontal grid of GEOSâ€Chem (1/2° × 2/3°) to identify correction tendencies relative to the Emission Database for Global Atmospheric Research (EDGAR) v4.2 emission inventory used as a priori. We then cluster these grid cells with a hierarchical algorithm to extract the maximum information from the SCIAMACHY observations. A 1000 cluster ensemble can be adequately constrained, providing ~100 km resolution across North America. Analysis of results indicates that the Hudson Bay Lowland wetlands source is 2.1 Tg a^(−1), lower than the a priori but consistent with other recent estimates. Anthropogenic U.S. emissions are 30.1 ± 1.3 Tg a^(−1), compared to 25.8 Tg a^(−1) and 28.3 Tg a^(−1) in the EDGAR v4.2 and Environmental Protection Agency (EPA) inventories, respectively. We find that U.S. livestock emissions are 40% greater than in these two inventories. No such discrepancy is apparent for overall U.S. oil and gas emissions, although this may reflect some compensation between overestimate of emissions from storage/distribution and underestimate from production. We find that U.S. livestock emissions are 70% greater than the oil and gas emissions, in contrast to the EDGAR v4.2 and EPA inventories where these two sources are of comparable magnitude. ©2014. The Authors. This is an open ... |
format |
Article in Journal/Newspaper |
author |
Wecht, Kevin J. Jacob, Daniel J. Frankenberg, Christian Jiang, Zhe Blake, Donald R. |
author_facet |
Wecht, Kevin J. Jacob, Daniel J. Frankenberg, Christian Jiang, Zhe Blake, Donald R. |
author_sort |
Wecht, Kevin J. |
title |
Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data |
title_short |
Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data |
title_full |
Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data |
title_fullStr |
Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data |
title_full_unstemmed |
Mapping of North American methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data |
title_sort |
mapping of north american methane emissions with high spatial resolution by inversion of sciamachy satellite data |
publisher |
American Geophysical Union |
publishDate |
2014 |
url |
https://doi.org/10.1002/2014jd021551 |
geographic |
Hudson Hudson Bay |
geographic_facet |
Hudson Hudson Bay |
genre |
Hudson Bay |
genre_facet |
Hudson Bay |
op_source |
Journal of Geophysical Research. Atmospheres, 119(12), 7741-7756, (2014-06-27) |
op_relation |
https://doi.org/10.1002/2014jd021551 oai:authors.library.caltech.edu:57kha-ag836 eprintid:91253 resolverid:CaltechAUTHORS:20181127-155643512 |
op_rights |
info:eu-repo/semantics/openAccess Other |
op_doi |
https://doi.org/10.1002/2014jd021551 |
container_title |
Journal of Geophysical Research: Atmospheres |
container_volume |
119 |
container_issue |
12 |
container_start_page |
7741 |
op_container_end_page |
7756 |
_version_ |
1802645298251563008 |