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从复杂代谢网络的角度分析和识别中国空气污染物排放的关键部门的特征。

Characteristics Analysis and Identification of Key Sectors of Air Pollutant Emissions in China from the Perspective of Complex Metabolic Network.

机构信息

School of Economics and Management, China University of Petroleum, Qingdao 266580, China.

出版信息

Int J Environ Res Public Health. 2022 Jul 31;19(15):9396. doi: 10.3390/ijerph19159396.

DOI:10.3390/ijerph19159396
PMID:35954753
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9368571/
Abstract

Presently, China is in a critical period of economic transformation and upgrading. At the same time, it is also facing the pressure of serious atmospheric environmental pollution, which seriously threatens human health and hinders the sustainable economic development. Air pollutants are closely related to economic sectors, which together constitute a complex network. Air pollutants form an input-output ecological metabolic relationship among different sectors. Therefore, from the perspective of complex metabolic network, this study first constructs an environmental input-output model and then comprehensively uses the relevant methods of ecological network analysis and complex network analysis to analyze the characteristics of China's air pollutant emission system. Secondly, the key joint sectors of NO and PM emissions are determined from the supply side and the demand side, respectively. Finally, the corresponding emission reduction measures are proposed for the identified key sectors.

摘要

目前，中国正处于经济转型和升级的关键时期。同时，中国也面临着严重的大气环境污染压力，这严重威胁着人类健康，阻碍了经济的可持续发展。空气污染物与经济部门密切相关，它们共同构成了一个复杂的网络。空气污染物在不同部门之间形成了输入-输出生态代谢关系。因此，从复杂代谢网络的角度出发，本研究首先构建了一个环境投入产出模型，然后综合运用生态网络分析和复杂网络分析的相关方法，分析了中国大气污染物排放系统的特征。其次，从供应侧和需求侧两个方面确定了 NO 和 PM 排放的关键联合部门。最后，针对所识别的关键部门提出了相应的减排措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/a3ef6fa7e3c7/ijerph-19-09396-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/dd2f0ffaede6/ijerph-19-09396-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/e5bfc6de2c27/ijerph-19-09396-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/31680fd0ee98/ijerph-19-09396-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/ad4dad31d806/ijerph-19-09396-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/d206e6a86620/ijerph-19-09396-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/5c5f9c33a11e/ijerph-19-09396-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/824276b36907/ijerph-19-09396-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/a8fc9535d64f/ijerph-19-09396-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/7803a350adc0/ijerph-19-09396-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/a3ef6fa7e3c7/ijerph-19-09396-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/dd2f0ffaede6/ijerph-19-09396-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/e5bfc6de2c27/ijerph-19-09396-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/31680fd0ee98/ijerph-19-09396-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/ad4dad31d806/ijerph-19-09396-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/d206e6a86620/ijerph-19-09396-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/5c5f9c33a11e/ijerph-19-09396-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/824276b36907/ijerph-19-09396-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/a8fc9535d64f/ijerph-19-09396-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/7803a350adc0/ijerph-19-09396-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/9368571/a3ef6fa7e3c7/ijerph-19-09396-g010.jpg

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