Accuracy Verification of Satellite Products and Temporal and Spatial Distribution Analysis and Prediction of the CH4 Concentration in China
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Published:2023-05-29
Issue:11
Volume:15
Page:2813
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
Cai Kun12ORCID, Yang Xuan1, Li Shenshen3, Xiao Yizhuo1, Qiao Baojun1, Liu Yang12ORCID
Affiliation:
1. School of Computer and Information Engineering, Henan University, Kaifeng 475004, China 2. Henan Key Laboratory of Big Data Analysis and Processing, Kaifeng 475004, China 3. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Abstract
In this study, the spatiotemporal variations in CH4 concentrations in China from 2003 to 2021 are investigated, and their trends are forecasted over the next decade. Based on the seventh edition standard product retrieved by the atmospheric infrared detector (AIRS) at an altitude of 500 hPa, we verified monthly CH4 products using observational data provided by the World Data Center for Greenhouse Gases (WDCGG) from six ground stations in and around China. The correlation coefficients (R values) between the two data sets ranged from 0.68 to 0.92, signifying the ability of AIRS inversion data to represent temporal and spatial changes in surface CH4 concentrations. Additionally, China was classified into three regions (steps) based on terrain, and the changes in CH4 concentrations were assessed from three perspectives: spatial distribution, interannual variation, and seasonal variation. The results revealed that the CH4 concentration decreased with elevation along a topographic gradient, with high-value areas located in the first and second steps, corresponding to the eastern Qinghai–Tibet Plateau, northern Xinjiang Uygur Autonomous Region, and Inner Mongolia Autonomous Region. Over 19 years, the average increase in CH4 concentration has ranged from 65 to 175 ppb. In addition, the CH4 concentrations were higher during summer and autumn and lower during spring and winter. Finally, a SARIMA model was used to predict the near-surface CH4 concentration trend in China over the next ten years, which indicated a continued seasonal increase.
Funder
National Key R&D Program of China National Natural Science Foundation of China Key Research Projects of Henan Higher Education Institutions
Subject
General Earth and Planetary Sciences
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