Spatiotemporal heterogeneity, convergence and its impact factors: Perspective of carbon emission intensity and carbon emission per capita considering carbon sink effect
Clarifying the spatiotemporal heterogeneity, convergence and its impact factors of carbon emissions is not only beneficial to the formulation of differential carbon reduction policies, but also to achieve regional coordinated development. As the second largest source of carbon emissions, agricultura...
Gespeichert in:
| Veröffentlicht in: | Environmental impact assessment review 2022-01, Vol.92, p.106699, Article 106699 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | 106699 |
| container_title | Environmental impact assessment review |
| container_volume | 92 |
| creator | Cui, Yu Khan, Sufyan Ullah Deng, Yue Zhao, Minjuan |
| description | Clarifying the spatiotemporal heterogeneity, convergence and its impact factors of carbon emissions is not only beneficial to the formulation of differential carbon reduction policies, but also to achieve regional coordinated development. As the second largest source of carbon emissions, agricultural carbon emissions have attracted extensive attention practically and academically. The current study used the panel data of 31 provinces in China from 1997 to 2017, combining with the carbon emission accounting formula, Theil index method and convergence model, to analyze the spatiotemporal heterogeneity, convergence and its impact factors of carbon emission intensity (CEI) and carbon emission per capita (CEPC) of planting industry considering carbon sink effect. The results revealed that the total carbon emission shows a downward trend during the investigation, while evident differences exist in different regions and dimensions mainly caused by the inter-regional differences. The CEI Theil index demonstrated gradient decreasing pattern of “western (0.14) > central (0.09) > eastern (0.05) > northeast (0.03)” and the CEPC Theil index showed the distribution characteristics of “northeast (0.09) > central (0.08) > western (0.08) > eastern (0.05)”. Convergence existed in the whole country and in the four regions when taking CEI as the estimation index, while different divergence characteristics appeared (except central) when CEPC is applied. The impact effects of initial CEI/CEPC, rural GDP per capita, agricultural financial support level, agricultural mechanization degree, agricultural structure, rural population size and urbanization level have spatiotemporal heterogeneity.
[Display omitted]
•Agricultural carbon emission is assessed with consideration of carbon sink effect.•CEI Theil index is as western (0.14) > central (0.09) > eastern (0.05) > northeast (0.03).•CEPC Theil index is as northeast (0.09) > central (0.08) > western (0.08) > eastern (0.05).•The convergence features of CEI and CEPC varies under different dimensions.•The impact effects exist significant spatiotemporal heterogeneity. |
| doi_str_mv | 10.1016/j.eiar.2021.106699 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2619669852</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0195925521001499</els_id><sourcerecordid>2619669852</sourcerecordid><originalsourceid>FETCH-LOGICAL-c328t-847d01fb13a5c72296e430636ffed1c289d24903a4d803d7c0c1bb027c5d7e6f3</originalsourceid><addsrcrecordid>eNp9UctuFDEQtBBILIEf4GSJK7P4MeMZIy4o4iVFSqSEs-W1e0IvWXtoOyvlj_hMPCxcOHBxu9tV1e0uxl5KsZVCmjf7LaCnrRJKtoIx1j5iGzmNujO9Vo_ZRkg7dFYNw1P2rJS9aCRrpw37eb34irnCYcnk7_g3qED5FhJgfXjNQ05HoJYG4D5FjrVwPCw-VD63I1N5y6-AygKh4hF4nnnwtMuJwwFLwXbBVCGVpvZb4N_XBajVFqx-7VUwAmG6_QsrmL5zmOem_pw9mf1dgRd_4hn7-vHDzfnn7uLy05fz9xdd0Gqq3dSPUch5J7UfwqiUNdBrYbRpIlEGNdmoeiu07-MkdByDCHK3E2oMQxzBzPqMvTrpLpR_3EOpbp_vKbWWThlp22qnQTWUOqEC5VIIZrcQHjw9OCnc6ojbu9URtzriTo400rsTCdr8RwRyJeC62ojUfuhixv_RfwFaQZjs</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2619669852</pqid></control><display><type>article</type><title>Spatiotemporal heterogeneity, convergence and its impact factors: Perspective of carbon emission intensity and carbon emission per capita considering carbon sink effect</title><source>PAIS Index</source><source>Elsevier ScienceDirect Journals</source><creator>Cui, Yu ; Khan, Sufyan Ullah ; Deng, Yue ; Zhao, Minjuan</creator><creatorcontrib>Cui, Yu ; Khan, Sufyan Ullah ; Deng, Yue ; Zhao, Minjuan</creatorcontrib><description>Clarifying the spatiotemporal heterogeneity, convergence and its impact factors of carbon emissions is not only beneficial to the formulation of differential carbon reduction policies, but also to achieve regional coordinated development. As the second largest source of carbon emissions, agricultural carbon emissions have attracted extensive attention practically and academically. The current study used the panel data of 31 provinces in China from 1997 to 2017, combining with the carbon emission accounting formula, Theil index method and convergence model, to analyze the spatiotemporal heterogeneity, convergence and its impact factors of carbon emission intensity (CEI) and carbon emission per capita (CEPC) of planting industry considering carbon sink effect. The results revealed that the total carbon emission shows a downward trend during the investigation, while evident differences exist in different regions and dimensions mainly caused by the inter-regional differences. The CEI Theil index demonstrated gradient decreasing pattern of “western (0.14) > central (0.09) > eastern (0.05) > northeast (0.03)” and the CEPC Theil index showed the distribution characteristics of “northeast (0.09) > central (0.08) > western (0.08) > eastern (0.05)”. Convergence existed in the whole country and in the four regions when taking CEI as the estimation index, while different divergence characteristics appeared (except central) when CEPC is applied. The impact effects of initial CEI/CEPC, rural GDP per capita, agricultural financial support level, agricultural mechanization degree, agricultural structure, rural population size and urbanization level have spatiotemporal heterogeneity.
[Display omitted]
•Agricultural carbon emission is assessed with consideration of carbon sink effect.•CEI Theil index is as western (0.14) > central (0.09) > eastern (0.05) > northeast (0.03).•CEPC Theil index is as northeast (0.09) > central (0.08) > western (0.08) > eastern (0.05).•The convergence features of CEI and CEPC varies under different dimensions.•The impact effects exist significant spatiotemporal heterogeneity.</description><identifier>ISSN: 0195-9255</identifier><identifier>EISSN: 1873-6432</identifier><identifier>DOI: 10.1016/j.eiar.2021.106699</identifier><language>eng</language><publisher>Oxford: Elsevier Inc</publisher><subject>Accounting ; Agricultural mechanization ; Agriculture ; Automation ; Carbon ; Carbon emission ; Carbon sink ; Carbon sinks ; Convergence ; Emission analysis ; Emissions ; Financial support ; Heterogeneity ; Impact factors ; Indexes ; Mechanization ; Panel data ; Per capita ; Population number ; Provinces ; Regional development ; Regional differences ; Regional variations ; Rural population ; Rural populations ; Spatiotemporal heterogeneity ; Theil index ; Urbanization</subject><ispartof>Environmental impact assessment review, 2022-01, Vol.92, p.106699, Article 106699</ispartof><rights>2021 Elsevier Inc.</rights><rights>Copyright Elsevier BV Jan 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c328t-847d01fb13a5c72296e430636ffed1c289d24903a4d803d7c0c1bb027c5d7e6f3</citedby><cites>FETCH-LOGICAL-c328t-847d01fb13a5c72296e430636ffed1c289d24903a4d803d7c0c1bb027c5d7e6f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0195925521001499$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27843,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Cui, Yu</creatorcontrib><creatorcontrib>Khan, Sufyan Ullah</creatorcontrib><creatorcontrib>Deng, Yue</creatorcontrib><creatorcontrib>Zhao, Minjuan</creatorcontrib><title>Spatiotemporal heterogeneity, convergence and its impact factors: Perspective of carbon emission intensity and carbon emission per capita considering carbon sink effect</title><title>Environmental impact assessment review</title><description>Clarifying the spatiotemporal heterogeneity, convergence and its impact factors of carbon emissions is not only beneficial to the formulation of differential carbon reduction policies, but also to achieve regional coordinated development. As the second largest source of carbon emissions, agricultural carbon emissions have attracted extensive attention practically and academically. The current study used the panel data of 31 provinces in China from 1997 to 2017, combining with the carbon emission accounting formula, Theil index method and convergence model, to analyze the spatiotemporal heterogeneity, convergence and its impact factors of carbon emission intensity (CEI) and carbon emission per capita (CEPC) of planting industry considering carbon sink effect. The results revealed that the total carbon emission shows a downward trend during the investigation, while evident differences exist in different regions and dimensions mainly caused by the inter-regional differences. The CEI Theil index demonstrated gradient decreasing pattern of “western (0.14) > central (0.09) > eastern (0.05) > northeast (0.03)” and the CEPC Theil index showed the distribution characteristics of “northeast (0.09) > central (0.08) > western (0.08) > eastern (0.05)”. Convergence existed in the whole country and in the four regions when taking CEI as the estimation index, while different divergence characteristics appeared (except central) when CEPC is applied. The impact effects of initial CEI/CEPC, rural GDP per capita, agricultural financial support level, agricultural mechanization degree, agricultural structure, rural population size and urbanization level have spatiotemporal heterogeneity.
[Display omitted]
•Agricultural carbon emission is assessed with consideration of carbon sink effect.•CEI Theil index is as western (0.14) > central (0.09) > eastern (0.05) > northeast (0.03).•CEPC Theil index is as northeast (0.09) > central (0.08) > western (0.08) > eastern (0.05).•The convergence features of CEI and CEPC varies under different dimensions.•The impact effects exist significant spatiotemporal heterogeneity.</description><subject>Accounting</subject><subject>Agricultural mechanization</subject><subject>Agriculture</subject><subject>Automation</subject><subject>Carbon</subject><subject>Carbon emission</subject><subject>Carbon sink</subject><subject>Carbon sinks</subject><subject>Convergence</subject><subject>Emission analysis</subject><subject>Emissions</subject><subject>Financial support</subject><subject>Heterogeneity</subject><subject>Impact factors</subject><subject>Indexes</subject><subject>Mechanization</subject><subject>Panel data</subject><subject>Per capita</subject><subject>Population number</subject><subject>Provinces</subject><subject>Regional development</subject><subject>Regional differences</subject><subject>Regional variations</subject><subject>Rural population</subject><subject>Rural populations</subject><subject>Spatiotemporal heterogeneity</subject><subject>Theil index</subject><subject>Urbanization</subject><issn>0195-9255</issn><issn>1873-6432</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><recordid>eNp9UctuFDEQtBBILIEf4GSJK7P4MeMZIy4o4iVFSqSEs-W1e0IvWXtoOyvlj_hMPCxcOHBxu9tV1e0uxl5KsZVCmjf7LaCnrRJKtoIx1j5iGzmNujO9Vo_ZRkg7dFYNw1P2rJS9aCRrpw37eb34irnCYcnk7_g3qED5FhJgfXjNQ05HoJYG4D5FjrVwPCw-VD63I1N5y6-AygKh4hF4nnnwtMuJwwFLwXbBVCGVpvZb4N_XBajVFqx-7VUwAmG6_QsrmL5zmOem_pw9mf1dgRd_4hn7-vHDzfnn7uLy05fz9xdd0Gqq3dSPUch5J7UfwqiUNdBrYbRpIlEGNdmoeiu07-MkdByDCHK3E2oMQxzBzPqMvTrpLpR_3EOpbp_vKbWWThlp22qnQTWUOqEC5VIIZrcQHjw9OCnc6ojbu9URtzriTo400rsTCdr8RwRyJeC62ojUfuhixv_RfwFaQZjs</recordid><startdate>202201</startdate><enddate>202201</enddate><creator>Cui, Yu</creator><creator>Khan, Sufyan Ullah</creator><creator>Deng, Yue</creator><creator>Zhao, Minjuan</creator><general>Elsevier Inc</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TQ</scope><scope>8BJ</scope><scope>8FD</scope><scope>C1K</scope><scope>DHY</scope><scope>DON</scope><scope>FQK</scope><scope>FR3</scope><scope>JBE</scope><scope>KR7</scope><scope>SOI</scope></search><sort><creationdate>202201</creationdate><title>Spatiotemporal heterogeneity, convergence and its impact factors: Perspective of carbon emission intensity and carbon emission per capita considering carbon sink effect</title><author>Cui, Yu ; Khan, Sufyan Ullah ; Deng, Yue ; Zhao, Minjuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c328t-847d01fb13a5c72296e430636ffed1c289d24903a4d803d7c0c1bb027c5d7e6f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Accounting</topic><topic>Agricultural mechanization</topic><topic>Agriculture</topic><topic>Automation</topic><topic>Carbon</topic><topic>Carbon emission</topic><topic>Carbon sink</topic><topic>Carbon sinks</topic><topic>Convergence</topic><topic>Emission analysis</topic><topic>Emissions</topic><topic>Financial support</topic><topic>Heterogeneity</topic><topic>Impact factors</topic><topic>Indexes</topic><topic>Mechanization</topic><topic>Panel data</topic><topic>Per capita</topic><topic>Population number</topic><topic>Provinces</topic><topic>Regional development</topic><topic>Regional differences</topic><topic>Regional variations</topic><topic>Rural population</topic><topic>Rural populations</topic><topic>Spatiotemporal heterogeneity</topic><topic>Theil index</topic><topic>Urbanization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cui, Yu</creatorcontrib><creatorcontrib>Khan, Sufyan Ullah</creatorcontrib><creatorcontrib>Deng, Yue</creatorcontrib><creatorcontrib>Zhao, Minjuan</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>PAIS Index</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>International Bibliography of the Social Sciences</collection><collection>Engineering Research Database</collection><collection>International Bibliography of the Social Sciences</collection><collection>Civil Engineering Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Environmental impact assessment review</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cui, Yu</au><au>Khan, Sufyan Ullah</au><au>Deng, Yue</au><au>Zhao, Minjuan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatiotemporal heterogeneity, convergence and its impact factors: Perspective of carbon emission intensity and carbon emission per capita considering carbon sink effect</atitle><jtitle>Environmental impact assessment review</jtitle><date>2022-01</date><risdate>2022</risdate><volume>92</volume><spage>106699</spage><pages>106699-</pages><artnum>106699</artnum><issn>0195-9255</issn><eissn>1873-6432</eissn><abstract>Clarifying the spatiotemporal heterogeneity, convergence and its impact factors of carbon emissions is not only beneficial to the formulation of differential carbon reduction policies, but also to achieve regional coordinated development. As the second largest source of carbon emissions, agricultural carbon emissions have attracted extensive attention practically and academically. The current study used the panel data of 31 provinces in China from 1997 to 2017, combining with the carbon emission accounting formula, Theil index method and convergence model, to analyze the spatiotemporal heterogeneity, convergence and its impact factors of carbon emission intensity (CEI) and carbon emission per capita (CEPC) of planting industry considering carbon sink effect. The results revealed that the total carbon emission shows a downward trend during the investigation, while evident differences exist in different regions and dimensions mainly caused by the inter-regional differences. The CEI Theil index demonstrated gradient decreasing pattern of “western (0.14) > central (0.09) > eastern (0.05) > northeast (0.03)” and the CEPC Theil index showed the distribution characteristics of “northeast (0.09) > central (0.08) > western (0.08) > eastern (0.05)”. Convergence existed in the whole country and in the four regions when taking CEI as the estimation index, while different divergence characteristics appeared (except central) when CEPC is applied. The impact effects of initial CEI/CEPC, rural GDP per capita, agricultural financial support level, agricultural mechanization degree, agricultural structure, rural population size and urbanization level have spatiotemporal heterogeneity.
[Display omitted]
•Agricultural carbon emission is assessed with consideration of carbon sink effect.•CEI Theil index is as western (0.14) > central (0.09) > eastern (0.05) > northeast (0.03).•CEPC Theil index is as northeast (0.09) > central (0.08) > western (0.08) > eastern (0.05).•The convergence features of CEI and CEPC varies under different dimensions.•The impact effects exist significant spatiotemporal heterogeneity.</abstract><cop>Oxford</cop><pub>Elsevier Inc</pub><doi>10.1016/j.eiar.2021.106699</doi></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0195-9255 |
| ispartof | Environmental impact assessment review, 2022-01, Vol.92, p.106699, Article 106699 |
| issn | 0195-9255 1873-6432 |
| language | eng |
| recordid | cdi_proquest_journals_2619669852 |
| source | PAIS Index; Elsevier ScienceDirect Journals |
| subjects | Accounting Agricultural mechanization Agriculture Automation Carbon Carbon emission Carbon sink Carbon sinks Convergence Emission analysis Emissions Financial support Heterogeneity Impact factors Indexes Mechanization Panel data Per capita Population number Provinces Regional development Regional differences Regional variations Rural population Rural populations Spatiotemporal heterogeneity Theil index Urbanization |
| title | Spatiotemporal heterogeneity, convergence and its impact factors: Perspective of carbon emission intensity and carbon emission per capita considering carbon sink effect |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T19%3A43%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Spatiotemporal%20heterogeneity,%20convergence%20and%20its%20impact%20factors:%20Perspective%20of%20carbon%20emission%20intensity%20and%20carbon%20emission%20per%20capita%20considering%20carbon%20sink%20effect&rft.jtitle=Environmental%20impact%20assessment%20review&rft.au=Cui,%20Yu&rft.date=2022-01&rft.volume=92&rft.spage=106699&rft.pages=106699-&rft.artnum=106699&rft.issn=0195-9255&rft.eissn=1873-6432&rft_id=info:doi/10.1016/j.eiar.2021.106699&rft_dat=%3Cproquest_cross%3E2619669852%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2619669852&rft_id=info:pmid/&rft_els_id=S0195925521001499&rfr_iscdi=true |