Identification of key sectors and key provinces at the view of CO2 reduction and economic growth in China: Linkage analyses based on the MRIO model
Identification of key sectors and key provinces at the view of CO2 reduction and economic growth in China: Linkage analyses based on the MRIO model
复制标题
从CO2减排与经济增长的角度识别中国重点行业和重点省份：基于MRIO模型的关联分析
DOI：
10.1016/j.ecolind.2018.08.036
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发表时间：
2019-01
影响因子：
6.9
通讯作者：
Qi Wang
中科院分区：
文献类型：
--
作者：
Wen Wen;Qi Wang
中国是世界上最大的二氧化碳排放国，如何在保持经济增长的同时减少全国二氧化碳排放量已成为一个重要课题。可应用产业联系分析来确定需要为此目的制定政策的关键部门和省份。为了确定这些省份的具体关键部门，我们设计了一种基于部门间联系分析的方法，并采用多区域投入产出模型，以30个省份的27个行业为研究对象。我们分析了后向和前向联系，结合部门间生产和CO2排放的联系，并使用边际和绝对措施。在后向联系中，重点减排部门包括山西和内蒙古的电力和热力的生产和供应，以及辽宁等省的运输和储存。在前向联动中，重点减排行业包括河北的非金属矿产业、内蒙古等省份的黑色金属冶炼及压制业。从需求和供应双方来看，重点省份是河北、山西、内蒙古和山东。从需求侧和供应侧的角度得出了对决策者的政策含义，分别指导行业级和省级二氧化碳减排策略。
In China, the largest carbon dioxide (CO2) emitter in the world, reducing national CO2emissions while maintaining economic growth has become an important issue. Industrial linkage analyses can be applied to identify key sectors and provinces where policies need to be developed for this purpose. To identify the specific key sectors in these provinces, we designed a method based on inter-sector linkage analyses with a multi-regional input–output model, using 27 industries in 30 provinces as research objects. We analyzed backward and forward linkages, combined inter-sector production and CO2emissions linkages, and used both marginal and absolute measures. In the backward linkages, the key emissions reduction sectors included production and supply of electricity and heat in Shanxi and Inner Mongolia, and transportation and storage in Liaoning and other provinces. In the forward linkages, the key emissions reduction sectors included nonmetal mineral products in Hebei, and the smelting and pressing of ferrous metals in Inner Mongolia and other provinces. The key provinces from both the demand and supply sides were Hebei, Shanxi, Inner Mongolia, and Shandong. Policy implications for decision makers were derived from the demand and supply side perspectives, to guide sector-level and province-level CO2emissions mitigation strategies, respectively.
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影响因子：
4
作者：
Isara Muangthai;Sue J. Lin;C. Lewis
通讯作者：
Isara Muangthai;Sue J. Lin;C. Lewis
影响因子：
7
作者：
Alexandra Marques;João F. D. Rodrigues;M. Lenzen;T. Domingos
通讯作者：
Alexandra Marques;João F. D. Rodrigues;M. Lenzen;T. Domingos
中国经济部门大气污染物排放：联动分析
影响因子：
6.9
作者：
Wang Yuan;Lai Nan;Mao Guozhu;Zuo Jian;John Crittenden;Jin Yi;Juan Moreno-Cruz
通讯作者：
Juan Moreno-Cruz
DOI：
--
发表时间：
2013
期刊：
China Population, Resources and Environment
影响因子：
--
作者：
Xiping Liu
通讯作者：
Xiping Liu
影响因子：
2.5
作者：
S. Shishido;Makoto Nobukuni;Kazumi Kawamura;Takahiro Akita;Shun’ichi Furukawa
通讯作者：
S. Shishido;Makoto Nobukuni;Kazumi Kawamura;Takahiro Akita;Shun’ichi Furukawa