Remote sensing monitoring and spatiotemporal characteristics of CO₂ and CH₄ concentrations in coal-electricity production bases

Authors

XU Yanfei, State Key Laboratory for Safe Mining of Deep Coal Resources and Environment Protection, Huainan 232001, China; School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China; Anhui Province Engineering Research Center of Coal Mining Green Low-Carbon Development, Huainan 232001, ChinaFollow
CHEN Yongchun, State Key Laboratory for Safe Mining of Deep Coal Resources and Environment Protection, Huainan 232001, China; Anhui Province Engineering Research Center of Coal Mining Green Low-Carbon Development, Huainan 232001, ChinaFollow
LI Jing, Huainan Academy of Atmospheric Sciences, Huainan 232001, China
LIU Xiaozhou, Huainan Academy of Atmospheric Sciences, Huainan 232001, China
MIAO Wei, State Key Laboratory for Safe Mining of Deep Coal Resources and Environment Protection, Huainan 232001, China; Anhui Province Engineering Research Center of Coal Mining Green Low-Carbon Development, Huainan 232001, China
ZHAO Derong, State Key Laboratory for Safe Mining of Deep Coal Resources and Environment Protection, Huainan 232001, China; Anhui Province Engineering Research Center of Coal Mining Green Low-Carbon Development, Huainan 232001, China
RUI Chengqi, State Key Laboratory for Safe Mining of Deep Coal Resources and Environment Protection, Huainan 232001, China; Anhui Province Engineering Research Center of Coal Mining Green Low-Carbon Development, Huainan 232001, China

Abstract

[Objective] CO₂ and CH₄ are identified as the primary greenhouse gases emitted from energy production in coal-electricity production bases. Mointoring these emissions and analyzing their spatiotemporal distribution are essential components of building a carbon monitoring system in the study area. [Methods] This study investigated Huainan City, Anhui Province as an example to explore the spatiotemporal characteristics of CO₂ and CH₄ in coal-electricity production bases. Specifically, this study examined the CO₂ and CH₄ concentrations in the study area based on data from the GOSAT，OCO-2, and Sentinel-5P satellites，determining the column concentration changes and distribution of CO₂ and CH₄, which are XCO₂ and XCH₄. A sourcing method of inventory was employed to analyze the industrial and regional CO₂ emission characteristics, and Pearson's correlation coefficient and multivariate regression were used to analyze the dominant factors affecting the XCO₂ and XCH₄ concentrations in the study area. [Results and Conclusions] Key findings are as follows: (1) The analysis of fusion data from the GOSAT and OCO-2 satellites indicate that the XCO₂ and XCH₄ concentrations in Huainan generally trended upward from 2016 to 2020, with the XCO₂ and XCH₄ concentrations increasing by 12×10⁻⁶ and 23×10⁻⁹, respectively. The Pearson's correlation coefficient between the XCO₂ concentration and cumulative power generation was 0.98, and that between the XCH₄ concentration and cumulative coal production was 0.99, both indicating extremely strong correlations. (2) As revealed by the analytical results of the spatiotemporal distribution characteristics of the XCH₄ concentration in various zones of Huainan City derived based on data from the high-resolution Tropospheric Monitoring Instrument (TROPOMI) equipped in the Sentinel-5P satellite, the XCH₄ concentration in the city is affected by both energy and agricultural production, being higher in autumn than in summer. (3) The results obtained using the sourcing method of inventory indicate that the maximum CO₂ emissions of the primary sources originated from the stationary combustion sources of fossil fuels, accounting for 89.59% of the total CO₂ emissions across the city. Furthermore, over 99% of the stationary combustion sources of fossil fuels were used for electric heating. The primary CO₂ emissions sources include the coal-fired power plants in Panji District and Fengtai County of Huainan City. Source identification results indicate that the fossil-fired power plants concentrated in the northern Huainan proved to be predominant sources of CO₂ emissions in the study area. (4) The dominant factors affecting the XCO₂ concentration in the study area include regional GDP, cumulative power generation, and the output of the secondary industries, while those influencing the XCH₄ concentration encompass cumulative coal production, the output of the primary industries, and the sown area. The results of this study provide a valuable reference for the construction and improvement of carbon monitoring systems for coal-electricity production bases under the context of reaching the goals of peak carbon dioxide emissions and carbon neutrality.

Keywords

carbon emission, remote sensing monitoring, XCO2, XCH4, dominant controlling factor, multivariate regression analysis, coal-electricity production base, Huainan City, Anhui Province

DOI

10.12363/issn.1001-1986.23.09.0537

Recommended Citation

XU Yanfei, CHEN Yongchun, LI Jing, et al. (2024) "Remote sensing monitoring and spatiotemporal characteristics of CO₂ and CH₄ concentrations in coal-electricity production bases," Coal Geology & Exploration: Vol. 52: Iss. 6, Article 9.
DOI: 10.12363/issn.1001-1986.23.09.0537
Available at: https://cge.researchcommons.org/journal/vol52/iss6/9

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