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长三角城市低碳治理的灰色关联分析。

Grey Correlation Analysis of Low-Carbon Governance in Yangtze River Delta Cities.

机构信息

School of Marxism, Southeast University, Nanjing, 211189 Jiangsu, China.

出版信息

J Environ Public Health. 2022 Sep 12;2022:2029087. doi: 10.1155/2022/2029087. eCollection 2022.

DOI:10.1155/2022/2029087
PMID:36133167
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9484910/
Abstract

The excessive emission of carbon dioxide will bring unpredictable ecological crisis, so it is particularly urgent to study the related factors of carbon emissions. Based on the grey correlation model, 31 factors in 5 aspects are selected as the reference frame for low-carbon governance, and the grey correlation degree of urban carbon emissions is calculated by using the IPCC method to calculate the annual carbon emissions of 9 major cities in the Yangtze River Delta from 2010 to 2019. Through the calculation and analysis of panel data, the following conclusions are drawn: The allocation of urban environmental practitioners is an important factor in carbon governance, and the reasonable and scientific allocation of environmental practitioners can have a significant impact on low-carbon development; the relationship between the amount of industrial power consumption and carbon dioxide emissions is not significant. On the contrary, the power consumption of urban residents can well reflect the level of carbon emissions. High residential power consumption means that the living standard of the people in the region is high, and the corresponding resource and energy consumption is large, so the carbon emissions will increase; the size of population density is particularly important for carbon governance, which is more obvious in economically developed areas. Urban economic development will inevitably lead to the improvement of people's quality of life, a stronger demand for resources, and a significant increase in carbon emissions.

摘要

二氧化碳的过度排放将带来不可预测的生态危机,因此研究碳排放的相关因素尤为紧迫。基于灰色关联模型,选择 5 个方面的 31 个因素作为低碳治理的参考框架,利用 IPCC 方法计算了长三角 9 个主要城市 2010-2019 年的年度碳排放量。通过面板数据的计算分析,得出以下结论:城市环境从业者的配置是碳治理的重要因素,合理科学的环境从业者配置对低碳发展具有显著影响;工业电力消费总量与二氧化碳排放之间的关系不显著。相反,城镇居民的电力消耗可以很好地反映碳排放水平。高居民电力消耗意味着该地区人民的生活水平较高,相应的资源和能源消耗较大,因此碳排放会增加;人口密度的大小对碳治理特别重要,在经济发达地区更为明显。城市经济发展必然会导致人们生活质量的提高,对资源的需求增强,碳排放显著增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/50666ceb142e/JEPH2022-2029087.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/af95e29ada24/JEPH2022-2029087.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/ff94ca67321b/JEPH2022-2029087.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/8b5483e10875/JEPH2022-2029087.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/748602bc74fa/JEPH2022-2029087.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/50666ceb142e/JEPH2022-2029087.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/af95e29ada24/JEPH2022-2029087.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/ff94ca67321b/JEPH2022-2029087.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/8b5483e10875/JEPH2022-2029087.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/748602bc74fa/JEPH2022-2029087.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5c/9484910/50666ceb142e/JEPH2022-2029087.005.jpg

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引用本文的文献

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Retracted: Grey Correlation Analysis of Low-Carbon Governance in Yangtze River Delta Cities.撤稿:长江三角洲城市低碳治理的灰色关联分析
J Environ Public Health. 2023 Oct 18;2023:9791547. doi: 10.1155/2023/9791547. eCollection 2023.

本文引用的文献

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2
Global CO Emissions Level Off in 2019, with a Drop Predicted in 2020.2019年全球一氧化碳排放量趋于平稳,预计2020年将下降。
Engineering (Beijing). 2020 Sep;6(9):958-959. doi: 10.1016/j.eng.2020.07.005. Epub 2020 Jul 15.
3
Dataset normalization for low carbon cities in a multi-criteria evaluation model.
多标准评估模型中低碳城市的数据集归一化
Data Brief. 2018 Mar 31;18:1111-1116. doi: 10.1016/j.dib.2018.03.130. eCollection 2018 Jun.