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Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East

Improved observational understanding of urban CO(2) emissions, a large and dynamic global source of fossil CO(2), can provide essential insights for both carbon cycle science and mitigation decision making. Here we compare three distinct global CO(2) emissions inventory representations of urban CO(2...

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Autores principales: Yang, Emily G., Kort, Eric A., Wu, Dien, Lin, John C., Oda, Tomohiro, Ye, Xinxin, Lauvaux, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7380315/
https://www.ncbi.nlm.nih.gov/pubmed/32728501
http://dx.doi.org/10.1029/2019JD031922
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author Yang, Emily G.
Kort, Eric A.
Wu, Dien
Lin, John C.
Oda, Tomohiro
Ye, Xinxin
Lauvaux, Thomas
author_facet Yang, Emily G.
Kort, Eric A.
Wu, Dien
Lin, John C.
Oda, Tomohiro
Ye, Xinxin
Lauvaux, Thomas
author_sort Yang, Emily G.
collection PubMed
description Improved observational understanding of urban CO(2) emissions, a large and dynamic global source of fossil CO(2), can provide essential insights for both carbon cycle science and mitigation decision making. Here we compare three distinct global CO(2) emissions inventory representations of urban CO(2) emissions for five Middle Eastern cities (Riyadh, Mecca, Tabuk, Jeddah, and Baghdad) and use independent satellite observations from the Orbiting Carbon Observatory‐2 (OCO‐2) satellite to evaluate the inventory representations of afternoon emissions. We use the column version of the Stochastic Time‐Inverted Lagrangian Transport (X‐STILT) model to account for atmospheric transport and link emissions to observations. We compare XCO(2) simulations with observations to determine optimum inventory scaling factors. Applying these factors, we find that the average summed emissions for all five cities are 100 MtC year(−1) (50–151, 90% CI), which is 2.0 (1.0, 3.0) times the average prior inventory magnitudes. The total adjustment of the emissions of these cities comes out to ~7% (0%, 14%) of total Middle Eastern emissions (~700 MtC year(−1)). We find our results to be insensitive to the prior spatial distributions in inventories of the cities' emissions, facilitating robust quantitative assessments of urban emission magnitudes without accurate high‐resolution gridded inventories.
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spelling pubmed-73803152020-07-27 Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East Yang, Emily G. Kort, Eric A. Wu, Dien Lin, John C. Oda, Tomohiro Ye, Xinxin Lauvaux, Thomas J Geophys Res Atmos Research Articles Improved observational understanding of urban CO(2) emissions, a large and dynamic global source of fossil CO(2), can provide essential insights for both carbon cycle science and mitigation decision making. Here we compare three distinct global CO(2) emissions inventory representations of urban CO(2) emissions for five Middle Eastern cities (Riyadh, Mecca, Tabuk, Jeddah, and Baghdad) and use independent satellite observations from the Orbiting Carbon Observatory‐2 (OCO‐2) satellite to evaluate the inventory representations of afternoon emissions. We use the column version of the Stochastic Time‐Inverted Lagrangian Transport (X‐STILT) model to account for atmospheric transport and link emissions to observations. We compare XCO(2) simulations with observations to determine optimum inventory scaling factors. Applying these factors, we find that the average summed emissions for all five cities are 100 MtC year(−1) (50–151, 90% CI), which is 2.0 (1.0, 3.0) times the average prior inventory magnitudes. The total adjustment of the emissions of these cities comes out to ~7% (0%, 14%) of total Middle Eastern emissions (~700 MtC year(−1)). We find our results to be insensitive to the prior spatial distributions in inventories of the cities' emissions, facilitating robust quantitative assessments of urban emission magnitudes without accurate high‐resolution gridded inventories. John Wiley and Sons Inc. 2020-04-04 2020-04-16 /pmc/articles/PMC7380315/ /pubmed/32728501 http://dx.doi.org/10.1029/2019JD031922 Text en ©2020. The Authors. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Articles
Yang, Emily G.
Kort, Eric A.
Wu, Dien
Lin, John C.
Oda, Tomohiro
Ye, Xinxin
Lauvaux, Thomas
Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East
title Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East
title_full Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East
title_fullStr Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East
title_full_unstemmed Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East
title_short Using Space‐Based Observations and Lagrangian Modeling to Evaluate Urban Carbon Dioxide Emissions in the Middle East
title_sort using space‐based observations and lagrangian modeling to evaluate urban carbon dioxide emissions in the middle east
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7380315/
https://www.ncbi.nlm.nih.gov/pubmed/32728501
http://dx.doi.org/10.1029/2019JD031922
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