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城市空间结构要素对发展中特大城市碳排放效率的影响:以成都为例。

Impact of urban spatial structure elements on carbon emissions efficiency in growing megacities: the case of Chengdu.

机构信息

College of Architecture and Environment, Sichuan University, Chengdu, 610065, China.

出版信息

Sci Rep. 2023 Jun 19;13(1):9939. doi: 10.1038/s41598-023-36575-6.

DOI:10.1038/s41598-023-36575-6
PMID:37336925
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10279684/
Abstract

Quantitative research on the impact weight and impact of regional heterogeneity of urban spatial structure elements on carbon emissions efficiency can provide a scientific basis and practical guidance for low-carbon and sustainable urban development. This study uses the megacity of Chengdu as an example to measure and analyze the spatial carbon emission efficiency and multidimensional spatial structure elements by building a high-resolution grid and identifying the main spatial structure elements that affect urban carbon emissions and their impact weights via the Ordinary Least Squares regression (OLS) and Geographically Weighted Regression (GWR). The spatial heterogeneity of the impact of each element is also explored. The results show that the overall carbon emission efficiency of Chengdu is high in the center and low on the sides, which is related to urban density, functional mix, land use, and traffic structure. However, the influence of each spatial structure element is different in the developed central areas, developing areas of the plain, mountainous developing areas, underdeveloped areas of the plain, and mountainous underdeveloped areas. Thus, it is appropriate to form differentiated urban planning strategies based on the characteristics of the development of each zone. The findings provide inspiration and a scientific basis for formulating policies and practice to the future low-carbon development of Chengdu, while provide a reference for other growing megacities.

摘要

对城市空间结构要素的区域异质性权重和影响进行碳排放量效率的定量研究,可以为低碳和可持续城市发展提供科学依据和实践指导。本研究以成都市为例,通过构建高分辨率网格,采用普通最小二乘法(OLS)和地理加权回归(GWR)识别影响城市碳排放的主要空间结构要素及其影响权重,对空间碳排放量效率和多维空间结构要素进行了测量和分析。还探讨了每个要素影响的空间异质性。结果表明,成都市的整体碳排放量效率中心高、两侧低,这与城市密度、功能混合、土地利用和交通结构有关。然而,每个空间结构要素在发达的中心区域、平原发展区域、山区发展区域、平原欠发达区域和山区欠发达区域的影响是不同的。因此,根据每个区域的发展特点,制定差异化的城市规划策略是合适的。该研究结果为成都市未来的低碳发展提供了政策制定和实践的启示和科学依据,同时也为其他快速发展的特大城市提供了参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/3a94c251495d/41598_2023_36575_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/1f682a98fd01/41598_2023_36575_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/cafcb08bfa3b/41598_2023_36575_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/79307c95e6ec/41598_2023_36575_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/abc9ce63592d/41598_2023_36575_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/8aaec50e62c3/41598_2023_36575_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/82574e0a4077/41598_2023_36575_Fig6a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/ce085d6d32da/41598_2023_36575_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/897cdc951a74/41598_2023_36575_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/3a94c251495d/41598_2023_36575_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/1f682a98fd01/41598_2023_36575_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/cafcb08bfa3b/41598_2023_36575_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/79307c95e6ec/41598_2023_36575_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/abc9ce63592d/41598_2023_36575_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/8aaec50e62c3/41598_2023_36575_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/82574e0a4077/41598_2023_36575_Fig6a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/ce085d6d32da/41598_2023_36575_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/897cdc951a74/41598_2023_36575_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa24/10279684/3a94c251495d/41598_2023_36575_Fig9_HTML.jpg

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Coupling coordination degree and driving factors of new-type urbanization and low-carbon development in the Yangtze River Delta: based on nighttime light data.
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