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Constraining Anthropogenic Emission Sources from Tropomi: A Case Study in Northern China

Zong, Haotian and Zeng, Zhao-Cheng and Liu, Xinhuiyu (2019) Constraining Anthropogenic Emission Sources from Tropomi: A Case Study in Northern China. In: 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE , Piscataway, NJ, pp. 7676-7679. ISBN 978-1-5386-9154-0.

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This study aims to investigate whether the high spatial resolution atmospheric CO and NO₂ column mixing ratios (xCO and xNO₂, respectively) retrieved from Tropospheric Monitoring Instrument (TROPOMI) can be used to constrain the temporal and spatial fluctuation of anthropogenic emission of CO and NO₂. Using a simple statistical method on the spatial distributions of xCO and xNO₂ observations in northern China from July to December in 2018, we can locate most of the large anthropogenic emission sources, indicating that satellite observations with high spatial resolution have high sensitivity on pollution emitters. At large scale, we found a high correlation between bottom-up emission inventory from MEIC (Multi-resolution Emission Inventory for China) and TROPOMI observations (with correlation coefficient of 0.64 for CO). At small scale, satellite observations can effectively capture the seasonal change of emissions which may be missed by inventories. These results provide a preliminary conclusion for the feasibility of constraining anthropogenic emissions using high-resolution satellite observations.

Item Type:Book Section
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Zeng, Zhao-Cheng0000-0002-0008-6508
Additional Information:© 2019 IEEE. We would like to acknowledge the following datasets available for our study: TROPOMI xCO and xNO₂ data are available from the Sentinel-5P Pre-Operations Data Hub for TROPOMI at; MEIC data are available at
Subject Keywords:Anthropogenic emissions, source detection, TROPOMI, China
Record Number:CaltechAUTHORS:20191121-135205153
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Official Citation:H. Zong, Z. Zeng and X. Liu, "Constraining Anthropogenic Emission Sources from Tropomi: A Case Study in Northern China," IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 7676-7679. doi: 10.1109/IGARSS.2019.8899006
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:99994
Deposited By: Tony Diaz
Deposited On:21 Nov 2019 22:01
Last Modified:16 Nov 2021 17:50

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