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An Assessment of Anthropogenic CO_2 Emissions by Satellite-Based Observations in China

Yang, Shaoyuan and Lei, Liping and Zeng, Zhaocheng and He, Zhonghua and Zhong, Hui (2019) An Assessment of Anthropogenic CO_2 Emissions by Satellite-Based Observations in China. Sensors, 19 (5). Art. No. 1118. ISSN 1424-8220. PMCID PMC6427755. http://resolver.caltech.edu/CaltechAUTHORS:20190305-101624932

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Abstract

Carbon dioxide (CO_2) is the most important anthropogenic greenhouse gas and its concentration in atmosphere has been increasing rapidly due to the increase of anthropogenic CO_2 emissions. Quantifying anthropogenic CO_2 emissions is essential to evaluate the measures for mitigating climate change. Satellite-based measurements of greenhouse gases greatly advance the way of monitoring atmospheric CO2 concentration. In this study, we propose an approach for estimating anthropogenic CO_2 emissions by an artificial neural network using column-average dry air mole fraction of CO_2 (XCO_2) derived from observations of Greenhouse gases Observing SATellite (GOSAT) in China. First, we use annual XCO_2 anomalies (dXCO_2) derived from XCO_2 and anthropogenic emission data during 2010–2014 as the training dataset to build a General Regression Neural Network (GRNN) model. Second, applying the built model to annual dXCO_2 in 2015, we estimate the corresponding emission and verify them using ODIAC emission. As a results, the estimated emissions significantly demonstrate positive correlation with that of ODIAC CO_2 emissions especially in the areas with high anthropogenic CO_2 emissions. Our results indicate that XCO_2 data from satellite observations can be applied in estimating anthropogenic CO_2 emissions at regional scale by the machine learning. This developed method can estimate carbon emission inventory in a data-driven way. In particular, it is expected that the estimation accuracy can be further improved when combined with other data sources, related CO_2 uptake and emissions, from satellite observations.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3390/s19051118DOIArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427755PubMed CentralArticle
ORCID:
AuthorORCID
Zeng, Zhaocheng0000-0002-0008-6508
Alternate Title:An Assessment of Anthropogenic CO2 Emissions by Satellite-Based Observations in China
Additional Information:© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0). Received: 2 January 2019 / Revised: 13 February 2019 / Accepted: 28 February 2019 / Published: 5 March 2019. (This article belongs to the Section Remote Sensors). We acknowledge The ACOS-GOSAT v7.3 data were produced from the ACOS/OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the ACOS/OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center. We also acknowledge the Center for Global Environmental Research, National Institute for Environmental Studies for providing ODIAC2015a dataset at http://db.cger.nies.go.jp/dataset/ODIAC/. CARMA are provided by the Center for Global Development, Washington, DC. The dataset was available at http://carma.org/plant. Author Contributions: S.Y. and L.L. conceived and designed the experiments; S.Y. performed the experiments; S.Y. and L.L. analyzed the data; Z.Z., Z.H. and Z.H. contributed analysis tools; S.Y. and L.L. wrote the paper. All authors proofread the manuscript. This research were funded by Key Program of the Chinese Academy of Sciences (Grand No.ZDRW-ZS-2019-1) and CAS Earth Big Data Science Project: ”Global Medium and Low Resolution Time Series Spatial Information Products” (Grant No.XDA19080303). And the APC was funded by Key Program of the Chinese Academy of Sciences. The authors declare no conflict of interest.
Funders:
Funding AgencyGrant Number
Chinese Academy of SciencesZDRW-ZS-2019-1
Chinese Academy of SciencesXDA19080303
Subject Keywords:anthropogenic CO_2 emissions; GOSAT; atmospheric CO_2 concentration
PubMed Central ID:PMC6427755
Record Number:CaltechAUTHORS:20190305-101624932
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190305-101624932
Official Citation:Yang, S.; Lei, L.; Zeng, Z.; He, Z.; Zhong, H. An Assessment of Anthropogenic CO2 Emissions by Satellite-Based Observations in China. Sensors 2019, 19, 1118.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:93522
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:05 Mar 2019 18:36
Last Modified:18 Apr 2019 17:30

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