Article(id=1314918328376849327, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918247384834796, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1741536000000, receivedDateStr=2025-03-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791430559486, onlineDateStr=2026-10-08, pubDate=1760889600000, pubDateStr=2025-10-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791430559486, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791430559486, creator=13701087609, updateTime=1791430559486, updator=13701087609, issue=Issue{id=1314918247384834796, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='10', pageStart='5329', pageEnd='5920', issueExtLink='null', onlineDate='null', pubDate='1760889600000', pubDateStr='2025-10-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791430540175, creator='13701087609', updateTime=1791431660009, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314922944367784036, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918247384834796, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314922944367784037, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918247384834796, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=5907, endPage=5920, ext={EN=ArticleExt(id=1314918328620118960, articleId=1314918328376849327, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Spatio-temporal changes and influence factors of energy-related carbon emissions at county-level in Northeast China, columnId=1234106390126588740, journalTitle=China Environmental Science, columnName=Carbon Emission Control, runingTitle=null, highlight=null, articleAbstract=

The per capita carbon emissions(PCCE) of energy consumption in 182 county-level districts in Northeast China were measured in this paper. The spatio-temporal change of the PCCE from 2000 to 2020 were analyzed by using kernel density estimation, spatial autocorrelation analysis and Theil index and its influencing factors were discussed by panel data model, which provides a basis for determining carbon emission reduction targets and refining policy design. The results were as follows: The in county-level districts has shown a sustained growth trend since 2000. The growth rate in the first 10 years was faster than that in the second 10 years. Agricultural counties experienced faster growth than forestry counties, whereas urban core districts experienced the slowest growth. A significant spatial positive correlation was observed among county-level districts, exhibiting an overall south-north gradient with higher values in the southern regions and lower values in the northern areas. The relative difference of PCCE among county-level districts gradually decreased, and the differences among prefecture-level districts constituted the main factors behind the reduction in total differences, whereas total differences were mainly manifested as the differences among counties. Economic growth and population quality had significant effects on all types of counties, with economic growth being the primary promoting factor to PCCE. Improving population quality had contributed to PCCE reductions, except in forestry counties. Consumption and population size also had important effects on the regional overall, urban core, and agricultural counties, with consumption contributing to carbon emissions, population shrinkage in the regional overall and in agricultural counties, and population growth in urban core districts suppressing carbon emissions. Urbanization promoted regional carbon emissions overall, but it suppressed emissions in forest counties. Higher technological development and population aging contributed to carbon emissions, albeit to a lesser extent. Environmental regulation had no effect on all county-level districts. To realize carbon emission reduction, it is necessary to strengthen the development of low-carbon industries, enhance the effectiveness of scientific and technological personnel, promote the management of population shrinkage and aging, advocate a low-carbon life and take a county-specific and multi-pronged approach.

, authors=Shou-zhong ZHANG^{1, 2, *}, Xiang-li WU², Yi-lin ZHANG², authorsList=Shou-zhong ZHANG, Xiang-li WU, Yi-lin ZHANG, authorCompany=null, correspAuthors=Shou-zhong ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314918328926303153, articleId=1314918328376849327, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=东北三省县区能源消费碳排放时空变化与影响因素研究, columnId=1234106391661704058, journalTitle=中国环境科学, columnName=碳排放控制, runingTitle=null, highlight=null, articleAbstract=

测度了东北三省182个县区能源消费引致的人均碳排放量，采用核密度估计、空间自相关分析、Theil指数、面板数据模型分析了2000年以来人均碳排放量的时空变化并剖析了影响因素的干扰作用，可为确定碳减排目标和细化政策设计提供依据．结果表明：期间县区人均碳排放量均呈持续增长态势，前10a增速快于后10a，农业县的增长快于林业县，城市中心区最慢．县区人均碳排放存在空间正相关关系，总体上呈现为南高北低格局；从发展趋势看县区间的总差异逐渐缩小，城市间差异是引致总差异减小的主要因子，但总差异主要表现为城市内部各县区间的差异；经济增长和人口素质对所有类型县区均有显著影响，其中经济增长是促进碳排放的首要因素，除林业县外提高人口素质均有助于碳减排；居民消费和人口规模对区域总体、城市中心区以及农业县也有重要影响，其中居民消费表现为促进碳排放，区域总体与农业县的人口收缩和城市中心区的人口增长均会抑制碳排放；城镇化促进了区域总体的碳排放，但会抑制林业县的碳排放；技术水平和老龄化的提高均会促进碳排放，但作用较弱；环境规制对所有类型县区均无影响．实现碳减排，需加强低碳产业发展、提升科技人员效能、推进人口收缩与老龄化治理、倡导低碳生活，走因县制宜多策并举的道路．

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张守忠（1977-），男，山东莒南人，副教授，博士，研究方向为区域与城市发展．发表论文30余篇．13674633817@163.com.

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张守忠（1977-），男，山东莒南人，副教授，博士，研究方向为区域与城市发展．发表论文30余篇．13674633817@163.com.

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