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探究中国京津冀地区土地利用相关碳排放的时空变化及影响因素。

Investigating spatio-temporal variations and contributing factors of land use-related carbon emissions in the Beijing-Tianjin-Hebei Region, China.

作者信息

Yuan Debao, Zhang Liuya, Fan Yuqing, Yang Renxu

机构信息

College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, 100083, China.

出版信息

Sci Rep. 2024 Aug 16;14(1):18976. doi: 10.1038/s41598-024-69573-3.

DOI:10.1038/s41598-024-69573-3
PMID:39152183
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11329513/
Abstract

The land use change is the primary factor in influencing the regional carbon emissions. Studying the effects of land use change on carbon emissions can provide supports for the development policies of carbon emission. Using land use and energy consumption data, this study measures carbon emissions from land use dynamics in the Beijing-Tianjin-Hebei region from 2000 to 2020. The standard deviation ellipse model is employed to investigate the distribution characteristics of the spatial patterns of carbon emissions, while the Geographically and Temporally Weighted Regression (GTWR) model is used to examine the contributing factors of carbon emissions and their spatial and temporal heterogeneity. Results indicate a consistently increasing trend in carbon emissions from land use in the Beijing-Tianjin-Hebei region from 2000 to 2020. Construction land is characterized with both the primary source and an increasing intensity of carbon emissions. Besides, the spatial distribution of carbon emissions from land use in the Beijing-Tianjin-Hebei region demonstrates an aggregation pattern from in the northeast-southwest direction towards the center, with a greater aggregation trend in the east-west direction compared to that in the south-north direction. During the study period, a positive correlation was documented between carbon emissions and factors including total population, economic development level, land use degree, and landscape patterns. This correlation showed a decreasing trend and reached a stable level at the end of the study period. Moreover, the analysis showed a negative correlation between industrial structure and carbon emissions, which showed an increasing trend and reached a relatively high level at the end of the study period.

摘要

土地利用变化是影响区域碳排放的主要因素。研究土地利用变化对碳排放的影响可为碳排放发展政策提供支持。本研究利用土地利用和能源消耗数据,测算2000年至2020年京津冀地区土地利用动态变化产生的碳排放。采用标准差椭圆模型研究碳排放空间格局的分布特征,同时运用地理加权回归(GTWR)模型考察碳排放的影响因素及其时空异质性。结果表明,2000年至2020年京津冀地区土地利用碳排放呈持续增加趋势。建设用地既是碳排放的主要来源,其碳排放强度也在增加。此外,京津冀地区土地利用碳排放的空间分布呈现出由东北-西南方向向中心聚集的格局,东西方向的聚集趋势大于南北方向。研究期间,碳排放与总人口、经济发展水平、土地利用程度和景观格局等因素呈正相关。这种相关性呈下降趋势,并在研究期末达到稳定水平。此外,分析表明产业结构与碳排放呈负相关,且呈上升趋势,在研究期末达到较高水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/9caa3da2cb41/41598_2024_69573_Fig11_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/b64e9716977e/41598_2024_69573_Fig7_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/4d2fc825cf56/41598_2024_69573_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/9caa3da2cb41/41598_2024_69573_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/98ff5fb3bdad/41598_2024_69573_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/7d393cb1eb44/41598_2024_69573_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/0e8a9dc6f01f/41598_2024_69573_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/d23c913c05b6/41598_2024_69573_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/a7a2851ba666/41598_2024_69573_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/d437f19cbd92/41598_2024_69573_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/b64e9716977e/41598_2024_69573_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/ea604bf6ffa7/41598_2024_69573_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/a3f6b5b058ad/41598_2024_69573_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/4d2fc825cf56/41598_2024_69573_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/745d/11329513/9caa3da2cb41/41598_2024_69573_Fig11_HTML.jpg

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