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利用天基观测和拉格朗日模型评估中东地区城市二氧化碳排放量

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

作者信息

Yang Emily G, Kort Eric A, Wu Dien, Lin John C, Oda Tomohiro, Ye Xinxin, Lauvaux Thomas

机构信息

Department of Climate and Space Sciences and Engineering University of Michigan Ann Arbor MI USA.

Department of Atmospheric Sciences University of Utah Salt Lake City UT USA.

出版信息

J Geophys Res Atmos. 2020 Apr 16;125(7):e2019JD031922. doi: 10.1029/2019JD031922. Epub 2020 Apr 4.

DOI:10.1029/2019JD031922
PMID:32728501
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7380315/
Abstract

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

摘要

对城市一氧化碳排放(化石一氧化碳的一个庞大且动态的全球来源)有更深入的观测理解,可为碳循环科学和减排决策提供重要见解。在此,我们比较了中东五个城市(利雅得、麦加、塔布克、吉达和巴格达)三种不同的全球一氧化碳排放清单中城市一氧化碳排放的呈现情况,并利用轨道碳观测站 -2(OCO -2)卫星的独立卫星观测数据来评估下午排放的清单呈现情况。我们使用随机时间反演拉格朗日传输(X - STILT)模型的柱浓度版本来考虑大气传输,并将排放与观测联系起来。我们将XCO模拟结果与观测数据进行比较,以确定最佳的清单缩放因子。应用这些因子后,我们发现所有五个城市的平均总排放量为每年100百万吨碳(50 - 151,90%置信区间),这是先前平均清单排放量的2.0(1.0,3.0)倍。这些城市排放的总调整量约占中东总排放量(约每年700百万吨碳)的7%(0%,14%)。我们发现我们的结果对城市排放清单中先前的空间分布不敏感这有助于在没有精确高分辨率网格化清单的情况下,对城市排放规模进行稳健的定量评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/ed178b73edb0/JGRD-125-e2019JD031922-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/8bbeeb062e19/JGRD-125-e2019JD031922-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/49cbbafeb24e/JGRD-125-e2019JD031922-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/38f5a1e9c14c/JGRD-125-e2019JD031922-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/4576dc29aa7f/JGRD-125-e2019JD031922-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/05a6843026dc/JGRD-125-e2019JD031922-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/ed178b73edb0/JGRD-125-e2019JD031922-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/8bbeeb062e19/JGRD-125-e2019JD031922-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/49cbbafeb24e/JGRD-125-e2019JD031922-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/38f5a1e9c14c/JGRD-125-e2019JD031922-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/4576dc29aa7f/JGRD-125-e2019JD031922-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/05a6843026dc/JGRD-125-e2019JD031922-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0f5/7380315/ed178b73edb0/JGRD-125-e2019JD031922-g006.jpg

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