Remote sensing monitoring and spatiotemporal characteristics of CO2 and CH4 concentrations in coal-electricity production bases
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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 (XCO2) and CH4 (XCH4). A source inventory method 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 showed an overall upward trend 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) The analytical results of the spatiotemporal distribution characteristics of the XCH4 concentration in various zones of Huainan City based on data from the high-resolution Tropospheric Monitoring Instrument (TROPOMI) equipped in the Sentinel-5P satellite revealed that, 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 source inventory method 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 predominantly 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 in the context of reaching the goals of peak carbon dioxide emissions and carbon neutrality.
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