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黄河流域碳排放的时空变化及其驱动因素。

Spatiotemporal Variations of Carbon Emissions and Their Driving Factors in the Yellow River Basin.

机构信息

School of Geography and Tourism, Qufu Normal University, Rizhao 276826, China.

College of Land Science and Technology, China Agriculture University, Beijing 100193, China.

出版信息

Int J Environ Res Public Health. 2022 Oct 8;19(19):12884. doi: 10.3390/ijerph191912884.

DOI:10.3390/ijerph191912884
PMID:36232186
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9566256/
Abstract

The Yellow River Basin (YRB) is a significant area of economic development and ecological protection in China. Scientifically clarifying the spatiotemporal patterns of carbon emissions and their driving factors is of great significance. Using the methods of spatial autocorrelation analysis, hot-spot analysis, and a geodetector, the analysis framework of spatiotemporal differentiation and the driving factors of carbon emissions in the YRB was constructed in this paper from three aspects: natural environment, social economy, and regional policy. Three main results were found: (1) The carbon emissions in the YRB increased gradually from 2000 to 2020, and the growth rates of carbon emissions in the different river reaches were upper reaches > middle reaches > lower reaches. (2) Carbon emissions have an obvious spatial clustering character from 2000-2020, when hot spots were concentrated in the transition area from the Inner Mongolia Plateau to the Loess Plateau. The cold spots of carbon emissions tended to be concentrated in the junction area of Qinghai, Gansu, and Shaanxi. (3) From 2000 to 2020, the driving factors of spatial differentiation of carbon emissions in the YRB and its different reaches tended to be diversified, so the impacts of socioeconomic factors increased, while the impacts of natural environmental factors decreased. The influence of the interactions of each driving factor showed double factor enhancement and nonlinear enhancement. This study will provide a scientific reference for green and low-carbon development, emphasizing the need to pay more attention to environmental protection, develop the green economy vigorously, and promote the economic cycle, so as to achieve green development and reduce carbon emissions.

摘要

黄河流域是中国经济发展和生态保护的重要区域。科学厘清碳排放的时空格局及其驱动因素具有重要意义。本文运用空间自相关分析、热点分析和地理探测器等方法,从自然环境、社会经济和区域政策三个方面构建了黄河流域碳排放的时空分异及其驱动因素分析框架。主要得出以下三个结论:(1)黄河流域碳排放呈逐渐上升趋势,且不同河段的碳排放增长率为上游>中游>下游。(2)2000-2020 年黄河流域碳排放具有明显的空间集聚特征,热点主要集中在内蒙古高原向黄土高原过渡区,碳排放冷点则集中在青、甘、陕三省交界处。(3)2000-2020 年黄河流域及其不同河段碳排放的空间分异驱动因素趋于多元化,社会经济因素的影响增大,自然环境因素的影响减小。各驱动因素交互作用的影响呈现出双重因子增强和非线性增强。本研究将为绿色低碳发展提供科学参考,强调需要更加注重环境保护,大力发展绿色经济,促进经济循环,实现绿色发展,减少碳排放。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/feacae1ea1fa/ijerph-19-12884-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/d206f8a255c7/ijerph-19-12884-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/2c2b51c3b78b/ijerph-19-12884-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/43ac59368a46/ijerph-19-12884-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/292957bb6d63/ijerph-19-12884-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/3cae5919ce65/ijerph-19-12884-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/feacae1ea1fa/ijerph-19-12884-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/d206f8a255c7/ijerph-19-12884-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/2c2b51c3b78b/ijerph-19-12884-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/43ac59368a46/ijerph-19-12884-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/292957bb6d63/ijerph-19-12884-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/3cae5919ce65/ijerph-19-12884-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0f/9566256/feacae1ea1fa/ijerph-19-12884-g006.jpg

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本文引用的文献

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[Governance mechanisms of industrial carbon emissions in heavy industrial zones under environmental justice based on evolutionary game perspective].基于演化博弈视角的环境正义下重工业区工业碳排放治理机制
Ying Yong Sheng Tai Xue Bao. 2022 Dec;33(12):3195-3204. doi: 10.13287/j.1001-9332.202212.020.
2
The nonlinearity and nonlinear convergence of CO emissions: Evidence from top 20 highest emitting countries.CO 排放的非线性和非线性收敛:来自前 20 大排放国的证据。
Environ Sci Pollut Res Int. 2022 Aug;29(39):59466-59482. doi: 10.1007/s11356-022-19470-x. Epub 2022 Apr 6.
3
New land-use-change emissions indicate a declining CO airborne fraction.
新的土地利用变化排放表明大气中二氧化碳的占比在下降。
Nature. 2022 Mar;603(7901):450-454. doi: 10.1038/s41586-021-04376-4. Epub 2022 Mar 16.
4
Asymmetric effects of premature deagriculturalization on economic growth and CO emissions: fresh evidence from Pakistan.过早去农业化对经济增长和二氧化碳排放的非对称影响:来自巴基斯坦的新证据。
Environ Sci Pollut Res Int. 2021 Dec;28(47):66772-66786. doi: 10.1007/s11356-021-15077-w. Epub 2021 Jul 8.
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Structural decomposition analysis of global carbon emissions: The contributions of domestic and international input changes.全球碳排放的结构分解分析:国内和国际投入变化的贡献。
J Environ Manage. 2021 Sep 15;294:112942. doi: 10.1016/j.jenvman.2021.112942. Epub 2021 Jun 7.
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County-level CO emissions and sequestration in China during 1997-2017.1997-2017 年中国县级 CO 排放与封存。
Sci Data. 2020 Nov 12;7(1):391. doi: 10.1038/s41597-020-00736-3.