Distribution characteristics and influencing factors of household consumption carbon emissions in China from a spatial perspective
Household consumption carbon emissions (HCCEs) have become the main growth point of China's carbon emissions in the future. It is important to investigate the factors affecting the demand-side carbon emissions in order to find the accurate entry point of emission reduction and achieve carbon pe...
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description | Household consumption carbon emissions (HCCEs) have become the main growth point of China's carbon emissions in the future. It is important to investigate the factors affecting the demand-side carbon emissions in order to find the accurate entry point of emission reduction and achieve carbon peaking and carbon neutrality goals. Different from previous studies, this study analyzed the spatial and temporal evolution characteristics of provincial HCCEs in China from a spatial perspective by using the Theil index and spatial auto-correlation and explored the key influencing factors and spatial spillover effects of HCCEs in different regions by using an econometric model. The results of the study showed that: (1) Per capita HCCEs increased by 11.90% annually, and the eastern region > northeastern region > western region > central region. (2) There were regional differences in per capita HCCEs, but the decrease was significant at 40.32%. (3) The spatial agglomeration effect of per capita HCCEs was significant, and the hot spots were mainly concentrated in the eastern coastal areas. (4) From the national level, every 1% increase in residents' consumption power would increase HCCEs by 2.489%. Which was the main factor for the growth of HCCEs, while the increase in fixed asset investment would restrain HCCEs. At the regional level, the change in population size significantly increased the HCCEs in the eastern and central regions. While for the western region, a 1% increase in population would reduce the HCCEs by 0.542%. For the eastern and central regions, the degree of aging and the consumption structure of residents could suppress regional HCCEs. However, the consumption structure of residents drove the growth of HCCEs in the western region. For the Northeast region, residents' consumption capacity and cooling degree days were the main factors for the growth of residents' consumption, while fixed asset investment could inhibit the growth of HCCEs.
•China's HCCEs showed a growing trend, with slow and fluctuating growth during 2006–2013 and rapid growth during 2014–2019.•The regional differences in China's HCCEs were mainly caused by regional differences, which showed a gradually decreasing trend.•The spatial agglomeration effect of China's HCCEs was obvious. The hot and cold spots of HCCEs showed dynamic changes within a certain range, gradually forming the “Bohai Rim” and “Yangtze River Delta” as the hot spot center.•The spatial econometric model was adopted to a |
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•China's HCCEs showed a growing trend, with slow and fluctuating growth during 2006–2013 and rapid growth during 2014–2019.•The regional differences in China's HCCEs were mainly caused by regional differences, which showed a gradually decreasing trend.•The spatial agglomeration effect of China's HCCEs was obvious. The hot and cold spots of HCCEs showed dynamic changes within a certain range, gradually forming the “Bohai Rim” and “Yangtze River Delta” as the hot spot center.•The spatial econometric model was adopted to analyze the influencing factors of China's HCCEs. It was found that the direct and indirect effects of influencing factors of HCCEs in eastern, central and western regions were different, and the spatial spillover effect was obvious. However, the northeast region was spatially independent.</description><identifier>ISSN: 0301-4797</identifier><identifier>EISSN: 1095-8630</identifier><identifier>DOI: 10.1016/j.jenvman.2023.119564</identifier><identifier>PMID: 38042085</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Carbon - analysis ; Carbon Dioxide - analysis ; China ; Economic Development ; Household consumption carbon emissions ; Investments ; Regional difference ; Spatial correlation ; Spatial econometric model ; STIRPAT model</subject><ispartof>Journal of environmental management, 2024-02, Vol.351, p.119564-119564, Article 119564</ispartof><rights>2023 Elsevier Ltd</rights><rights>Copyright © 2023 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c365t-30f2f8defd463f0abab0908436b8c71f79e4ba708d9617eba96ddd7a84a23f4f3</citedby><cites>FETCH-LOGICAL-c365t-30f2f8defd463f0abab0908436b8c71f79e4ba708d9617eba96ddd7a84a23f4f3</cites><orcidid>0000-0003-3280-3433 ; 0000-0002-7091-1809</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jenvman.2023.119564$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38042085$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lian, Yinghuan</creatorcontrib><creatorcontrib>Lin, Xiangyi</creatorcontrib><creatorcontrib>Luo, Hongyun</creatorcontrib><creatorcontrib>Zhang, Jianhua</creatorcontrib><creatorcontrib>Sun, Xiaochun</creatorcontrib><title>Distribution characteristics and influencing factors of household consumption carbon emissions in China from a spatial perspective</title><title>Journal of environmental management</title><addtitle>J Environ Manage</addtitle><description>Household consumption carbon emissions (HCCEs) have become the main growth point of China's carbon emissions in the future. It is important to investigate the factors affecting the demand-side carbon emissions in order to find the accurate entry point of emission reduction and achieve carbon peaking and carbon neutrality goals. Different from previous studies, this study analyzed the spatial and temporal evolution characteristics of provincial HCCEs in China from a spatial perspective by using the Theil index and spatial auto-correlation and explored the key influencing factors and spatial spillover effects of HCCEs in different regions by using an econometric model. The results of the study showed that: (1) Per capita HCCEs increased by 11.90% annually, and the eastern region > northeastern region > western region > central region. (2) There were regional differences in per capita HCCEs, but the decrease was significant at 40.32%. (3) The spatial agglomeration effect of per capita HCCEs was significant, and the hot spots were mainly concentrated in the eastern coastal areas. (4) From the national level, every 1% increase in residents' consumption power would increase HCCEs by 2.489%. Which was the main factor for the growth of HCCEs, while the increase in fixed asset investment would restrain HCCEs. At the regional level, the change in population size significantly increased the HCCEs in the eastern and central regions. While for the western region, a 1% increase in population would reduce the HCCEs by 0.542%. For the eastern and central regions, the degree of aging and the consumption structure of residents could suppress regional HCCEs. However, the consumption structure of residents drove the growth of HCCEs in the western region. For the Northeast region, residents' consumption capacity and cooling degree days were the main factors for the growth of residents' consumption, while fixed asset investment could inhibit the growth of HCCEs.
•China's HCCEs showed a growing trend, with slow and fluctuating growth during 2006–2013 and rapid growth during 2014–2019.•The regional differences in China's HCCEs were mainly caused by regional differences, which showed a gradually decreasing trend.•The spatial agglomeration effect of China's HCCEs was obvious. The hot and cold spots of HCCEs showed dynamic changes within a certain range, gradually forming the “Bohai Rim” and “Yangtze River Delta” as the hot spot center.•The spatial econometric model was adopted to analyze the influencing factors of China's HCCEs. It was found that the direct and indirect effects of influencing factors of HCCEs in eastern, central and western regions were different, and the spatial spillover effect was obvious. However, the northeast region was spatially independent.</description><subject>Carbon - analysis</subject><subject>Carbon Dioxide - analysis</subject><subject>China</subject><subject>Economic Development</subject><subject>Household consumption carbon emissions</subject><subject>Investments</subject><subject>Regional difference</subject><subject>Spatial correlation</subject><subject>Spatial econometric model</subject><subject>STIRPAT model</subject><issn>0301-4797</issn><issn>1095-8630</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE1v1DAQhi0EotvCTwD5yCWLHSeOc0JoaSlSpV7gbE3sMetVYgc7WalXfjmusnDlNJqZ952Ph5B3nO054_LjaX_CcJ4g7GtWiz3nfSubF2THWd9WSgr2kuyYYLxqur67Itc5nxhjoubda3IlFGtqptod-f3F5yX5YV18DNQcIYFZMJWiN5lCsNQHN64YjA8_qSvNmDKNjh7jmvEYR0tNDHmd5m0ApKEEnHzOJc_FTQ9HH4C6FCcKNM-weBjpjCnPaBZ_xjfklYMx49tLvCE_7m6_H-6rh8ev3w6fHyojZLtUgrnaKYvONlI4BgMMrGeqEXJQpuOu67EZoGPK9pJ3OEAvrbUdqAZq4RonbsiHbe6c4q8V86LLlQbHEQKWZ3Steqk474Qs0naTmhRzTuj0nPwE6Ulzpp_x65O-4NfP-PWGv_jeX1asw4T2n-sv7yL4tAmwPHr2mHQ2vsBF61OhoW30_1nxB_vknTs</recordid><startdate>202402</startdate><enddate>202402</enddate><creator>Lian, Yinghuan</creator><creator>Lin, Xiangyi</creator><creator>Luo, Hongyun</creator><creator>Zhang, Jianhua</creator><creator>Sun, Xiaochun</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-3280-3433</orcidid><orcidid>https://orcid.org/0000-0002-7091-1809</orcidid></search><sort><creationdate>202402</creationdate><title>Distribution characteristics and influencing factors of household consumption carbon emissions in China from a spatial perspective</title><author>Lian, Yinghuan ; Lin, Xiangyi ; Luo, Hongyun ; Zhang, Jianhua ; Sun, Xiaochun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c365t-30f2f8defd463f0abab0908436b8c71f79e4ba708d9617eba96ddd7a84a23f4f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Carbon - analysis</topic><topic>Carbon Dioxide - analysis</topic><topic>China</topic><topic>Economic Development</topic><topic>Household consumption carbon emissions</topic><topic>Investments</topic><topic>Regional difference</topic><topic>Spatial correlation</topic><topic>Spatial econometric model</topic><topic>STIRPAT model</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lian, Yinghuan</creatorcontrib><creatorcontrib>Lin, Xiangyi</creatorcontrib><creatorcontrib>Luo, Hongyun</creatorcontrib><creatorcontrib>Zhang, Jianhua</creatorcontrib><creatorcontrib>Sun, Xiaochun</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of environmental management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lian, Yinghuan</au><au>Lin, Xiangyi</au><au>Luo, Hongyun</au><au>Zhang, Jianhua</au><au>Sun, Xiaochun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distribution characteristics and influencing factors of household consumption carbon emissions in China from a spatial perspective</atitle><jtitle>Journal of environmental management</jtitle><addtitle>J Environ Manage</addtitle><date>2024-02</date><risdate>2024</risdate><volume>351</volume><spage>119564</spage><epage>119564</epage><pages>119564-119564</pages><artnum>119564</artnum><issn>0301-4797</issn><eissn>1095-8630</eissn><abstract>Household consumption carbon emissions (HCCEs) have become the main growth point of China's carbon emissions in the future. It is important to investigate the factors affecting the demand-side carbon emissions in order to find the accurate entry point of emission reduction and achieve carbon peaking and carbon neutrality goals. Different from previous studies, this study analyzed the spatial and temporal evolution characteristics of provincial HCCEs in China from a spatial perspective by using the Theil index and spatial auto-correlation and explored the key influencing factors and spatial spillover effects of HCCEs in different regions by using an econometric model. The results of the study showed that: (1) Per capita HCCEs increased by 11.90% annually, and the eastern region > northeastern region > western region > central region. (2) There were regional differences in per capita HCCEs, but the decrease was significant at 40.32%. (3) The spatial agglomeration effect of per capita HCCEs was significant, and the hot spots were mainly concentrated in the eastern coastal areas. (4) From the national level, every 1% increase in residents' consumption power would increase HCCEs by 2.489%. Which was the main factor for the growth of HCCEs, while the increase in fixed asset investment would restrain HCCEs. At the regional level, the change in population size significantly increased the HCCEs in the eastern and central regions. While for the western region, a 1% increase in population would reduce the HCCEs by 0.542%. For the eastern and central regions, the degree of aging and the consumption structure of residents could suppress regional HCCEs. However, the consumption structure of residents drove the growth of HCCEs in the western region. For the Northeast region, residents' consumption capacity and cooling degree days were the main factors for the growth of residents' consumption, while fixed asset investment could inhibit the growth of HCCEs.
•China's HCCEs showed a growing trend, with slow and fluctuating growth during 2006–2013 and rapid growth during 2014–2019.•The regional differences in China's HCCEs were mainly caused by regional differences, which showed a gradually decreasing trend.•The spatial agglomeration effect of China's HCCEs was obvious. The hot and cold spots of HCCEs showed dynamic changes within a certain range, gradually forming the “Bohai Rim” and “Yangtze River Delta” as the hot spot center.•The spatial econometric model was adopted to analyze the influencing factors of China's HCCEs. It was found that the direct and indirect effects of influencing factors of HCCEs in eastern, central and western regions were different, and the spatial spillover effect was obvious. However, the northeast region was spatially independent.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>38042085</pmid><doi>10.1016/j.jenvman.2023.119564</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-3280-3433</orcidid><orcidid>https://orcid.org/0000-0002-7091-1809</orcidid></addata></record> |
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subjects | Carbon - analysis Carbon Dioxide - analysis China Economic Development Household consumption carbon emissions Investments Regional difference Spatial correlation Spatial econometric model STIRPAT model |
title | Distribution characteristics and influencing factors of household consumption carbon emissions in China from a spatial perspective |
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