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贵州省二氧化碳排放的高分辨率映射及其尺度效应。

High-resolution mapping of carbon dioxide emissions in Guizhou Province and its scale effects.

作者信息

Zeng Canying, Wu Shaohua, Cheng Min, Zhou Hua, Li Fanglin

机构信息

School of Public Administration, Zhejiang University of Finance and Economics, Hangzhou, 310018, China.

Institute of Land and Resources Survey and Planning of Guizhou Province, Guiyang, 550004, Guizhou, China.

出版信息

Sci Rep. 2024 Sep 9;14(1):20916. doi: 10.1038/s41598-024-71836-y.

Abstract

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.

摘要

准确的二氧化碳(CO)排放空间分布是中国实现碳排放达峰和碳中和所需的关键信息。本研究旨在绘制省级尺度高空间分辨率的CO排放图,并探讨尺度效应如何影响制图结果。以中国西部的贵州省为例,研究了CO排放的时空格局及其影响因素。利用所提出的方法,获得了具有高空间分辨率的合理CO排放空间分布,其在空间细节方面具有相对准确的信息。高空间分辨率下省级尺度CO排放的最佳分辨率约为90米和1260米。更详细的网格数据能更好地反映CO排放的空间变异性。贵州省CO排放在空间上具有异质性,大城市中心排放量高,且从市中心向外逐渐扩散并减少。2009年至2019年,CO排放的空间分布从集聚型向分散型发展。高碳排放区域减少,中等碳排放区域增加,许多区域从无排放变为有排放。工业用地排放最高,其次是商业和交通用地。10多年来,贵州省区域间经济水平与CO排放的关系发生了变化,从线性关系转变为倒U形关系。产业结构对CO排放的影响减弱,CO排放与城市规模之间的线性增长关系更加明显。本研究结果将有助于贵州省碳排放的精准监测与管理,为不同地区制定碳排放控制相关政策提供支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d432/11381556/7c3613098b61/41598_2024_71836_Fig1_HTML.jpg

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