Abstract
Urban agglomerations (UAs) are the largest carbon emitters; thus, the emissions must be controlled to achieve carbon peak and carbon neutrality. We use long time series land-use and energy consumption data to estimate the carbon emissions in UAs. The standard deviational ellipse (SDE) and spatial autocorrelation analysis are used to reveal the spatiotemporal evolution of carbon emissions, and the geodetector, geographically and temporally weighted regression (GTWR), and boosted regression trees (BRTs) are used to analyze the driving factors. The results show the following: (1) Construction land and forest land are the main carbon sources and sinks, accounting for 93% and 94% of the total carbon sources and sinks, respectively. (2) The total carbon emissions of different UAs differ substantially, showing a spatial pattern of high emissions in the east and north and low emissions in the west and south. The carbon emissions of all UAs increase over time, with faster growth in UAs with lower carbon emissions. (3) The center of gravity of carbon emissions shifts to the south (except for North China, where it shifts to the west), and carbon emissions in UAs show a positive spatial correlation, with a predominantly high-high and low-low spatial aggregation pattern. (4) Population, GDP, and the annual number of cabs are the main factors influencing carbon emissions in most UAs, whereas other factors show significant differences. Most exhibit an increasing trend over time in their impact on carbon emissions. In general, China still faces substantial challenges in achieving the dual carbon goal. The carbon control measures of different UAs should be targeted in terms of energy utilization, green and low-carbon production, and consumption modes to achieve the low-carbon and green development goals of the United Nations’ sustainable cities and beautiful China’s urban construction as soon as possible.
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Data availability
The land-use data are the 30-m resolution annual China Land Cover Dataset (CLCD) from 1990 to 2019 (http://irsip.Whu.edu.cn/resources/CLCD.php). The energy consumption data of raw coal, coke, gasoline, and natural gas are obtained from the China Energy Statistical Yearbook (1991–2020) and the China Urban Statistical Yearbook (1991–2020). Socioeconomic data, such as population, GDP, and urbanization rate, are obtained from the statistical yearbooks of the provinces and cities from 2001 to 2020. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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This study was supported by the supported by Yunnan Fundamental Research Projects (Grant Nos. 202301BD070001-093, 202301AT070227, 202201 AU70064) and Southwest Forestry University Campus level Launch Fund (01102/112105).
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Xuefu Pu: original draft, writing, methodology, software, formal analysis—original draft preparation. Qingping Cheng: conceptualization; methodology, validation, review and editing, supervision, visualization, project administration. Hongyue Chen: original draft, methodology, formal analysis—original draft preparation.
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Pu, X., Cheng, Q. & Chen, H. Spatial–temporal dynamics of land use carbon emissions and drivers in 20 urban agglomerations in China from 1990 to 2019. Environ Sci Pollut Res 30, 107854–107877 (2023). https://doi.org/10.1007/s11356-023-29477-7
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DOI: https://doi.org/10.1007/s11356-023-29477-7