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Article: Backward and forward multilevel indicators for identifying key sectors of China’s intersectoral CO 2 transfer network

TitleBackward and forward multilevel indicators for identifying key sectors of China’s intersectoral CO <inf>2</inf> transfer network
Authors
KeywordsCarbon emissions
Environmental input-output analysis
Key sectors
Network theory
Issue Date2019
Citation
Environmental Science and Pollution Research, 2019, v. 26, n. 10, p. 9661-9671 How to Cite?
AbstractMany countries face a dilemma of economic growth and carbon emission mitigation, which is highly associated with energy consumption. In order to initiate effective policies for controlling carbon emissions, it is important to identify the key sectors in the value chain, thus proposing corresponding measures. To date, however, energy and carbon emissions have been studied mainly from a production or consumption perspective, with important interactions between sectors being seldom considered. In response, a new CO 2 flow model is presented in which input-output analysis and network theory are combined with multilevel indicators to identify the key sectors affecting carbon emissions in terms of total, immediate, and mediative centrality effects. The model is demonstrated with an analysis of 2007 and 2012 China sectoral data, showing that Production & Supply of Electric Power, Steam and Hot Water (PESH), Nonmetal Mineral Products (NMMP), and Coal Mining & Dressing (CMDG) played key roles in China’s carbon transfer network; the roles of Electronic & Telecommunications Equipment (ETET), Instruments & Office Machinery (IOMY), and Electric Equipment & Machinery (EEMY) had the largest immediacy effect; and, acting as key transmission sectors, PESH, Smelting & Pressing of Metals (SPOM), and NMMP controlled a large share of CO 2 transfer. The measures used are closely related to, and provide new insights into, the traditional indicators of sector centrality. At the same time, the proposed multilevel indicators are supplements for techniques that aim to instruct sector-level carbon mitigation policies.
Persistent Identifierhttp://hdl.handle.net/10722/333362
ISSN
2022 Impact Factor: 5.8
2023 SCImago Journal Rankings: 1.006
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWei, Liyuan-
dc.contributor.authorWang, Zhen-
dc.contributor.authorZhang, Xiaoling-
dc.date.accessioned2023-10-06T05:18:46Z-
dc.date.available2023-10-06T05:18:46Z-
dc.date.issued2019-
dc.identifier.citationEnvironmental Science and Pollution Research, 2019, v. 26, n. 10, p. 9661-9671-
dc.identifier.issn0944-1344-
dc.identifier.urihttp://hdl.handle.net/10722/333362-
dc.description.abstractMany countries face a dilemma of economic growth and carbon emission mitigation, which is highly associated with energy consumption. In order to initiate effective policies for controlling carbon emissions, it is important to identify the key sectors in the value chain, thus proposing corresponding measures. To date, however, energy and carbon emissions have been studied mainly from a production or consumption perspective, with important interactions between sectors being seldom considered. In response, a new CO 2 flow model is presented in which input-output analysis and network theory are combined with multilevel indicators to identify the key sectors affecting carbon emissions in terms of total, immediate, and mediative centrality effects. The model is demonstrated with an analysis of 2007 and 2012 China sectoral data, showing that Production & Supply of Electric Power, Steam and Hot Water (PESH), Nonmetal Mineral Products (NMMP), and Coal Mining & Dressing (CMDG) played key roles in China’s carbon transfer network; the roles of Electronic & Telecommunications Equipment (ETET), Instruments & Office Machinery (IOMY), and Electric Equipment & Machinery (EEMY) had the largest immediacy effect; and, acting as key transmission sectors, PESH, Smelting & Pressing of Metals (SPOM), and NMMP controlled a large share of CO 2 transfer. The measures used are closely related to, and provide new insights into, the traditional indicators of sector centrality. At the same time, the proposed multilevel indicators are supplements for techniques that aim to instruct sector-level carbon mitigation policies.-
dc.languageeng-
dc.relation.ispartofEnvironmental Science and Pollution Research-
dc.subjectCarbon emissions-
dc.subjectEnvironmental input-output analysis-
dc.subjectKey sectors-
dc.subjectNetwork theory-
dc.titleBackward and forward multilevel indicators for identifying key sectors of China’s intersectoral CO <inf>2</inf> transfer network-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s11356-019-04350-8-
dc.identifier.pmid30729430-
dc.identifier.scopuseid_2-s2.0-85061289152-
dc.identifier.volume26-
dc.identifier.issue10-
dc.identifier.spage9661-
dc.identifier.epage9671-
dc.identifier.eissn1614-7499-
dc.identifier.isiWOS:000464852200022-

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