Accurate spatial distribution of carbon dioxide (CO) emissions is essential information needed to peaking emissions and achieving carbon neutral in China. The aim of this study was to map CO emissions with high spatial resolution at provincial scale and then explore the scale effect on mapping results. As an example, the spatiotemporal pattern and factors influencing CO emissions were examined in Guizhou Province in Western China. With the proposed method, a reasonable spatial distribution of CO emissions with high spatial resolution was obtained, which had relatively accurate information on spatial details. The optimal resolution of CO emissions at the provincial scale under high spatial resolution was approximately 90 m and 1260 m. More detailed grid data can better reflect the spatial variability of CO emissions. Emissions of CO were spatially heterogeneous in Guizhou, with high emissions in centers of big cities that gradually spread and decreased from city centers. From 2009 to 2019, the spatial distribution of CO emissions developed from agglomeration to dispersion. Areas of high carbon emissions decreased, those of medium carbon emissions increased, and many areas changed from no emissions to carbon emissions. Industrial land had the highest emissions, followed by commercial and transportation lands. Over 10 years, changes occurred in the relation between interregional economic level of Guizhou and CO emissions, with the relation changing from linear into an inverted U-shaped relation. The effect of industrial structure on CO emissions decreased, and the linear increase between CO emissions and the urban scale became more evident. The results of this study will contribute to accurate monitoring and management of carbon emissions in Guizhou, as well as provide support to formulate policies related to controls on carbon emissions in different regions.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11381556 | PMC |
http://dx.doi.org/10.1038/s41598-024-71836-y | DOI Listing |
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