Article(id=1314923051993625268, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314922986466009203, 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=1752595200000, receivedDateStr=2025-07-16, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791431685683, onlineDateStr=2026-10-08, pubDate=1773936000000, pubDateStr=2026-03-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791431685683, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791431685683, creator=13701087609, updateTime=1791431685683, updator=13701087609, issue=Issue{id=1314922986466009203, tenantId=1146029695717560320, journalId=1234093305789726721, year='2026', volume='46', issue='3', pageStart='1185', pageEnd='1776', issueExtLink='null', onlineDate='null', pubDate='1773936000000', pubDateStr='2026-03-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1791431670061, creator='13701087609', updateTime=1791431955369, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314924183251935526, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314922986466009203, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314924183251935527, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314922986466009203, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1694, endPage=1709, ext={EN=ArticleExt(id=1314923052194951861, articleId=1314923051993625268, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Spatio-temporal patterns and evolutionary characteristics of provincial carbon lock-in in China, columnId=1234106390126588740, journalTitle=China Environmental Science, columnName=Carbon Emission Control, runingTitle=null, highlight=null, articleAbstract=

The carbon lock-in effect represents a systematic challenge to achieve the goal of carbon peaking and carbon neutrality. Identifying its spatio-temporal evolution patterns and regional transmission mechanisms is of great significance for facilitating China's low-carbon transformation. Based on an improved evaluation system, the study measured the carbon lock-in levels of 30 provinces in China from 2002 to 2022. Spatio-temporal analysis method was employed to depict their spatial patterns and evolutionary laws, and further explore their spatial association mechanisms and evolutionary trends. The results show that: The national carbon lock-in level exhibits a three-stage trend overall: a slow decline, accelerated unlocking, and gentle fluctuation. It also demonstrates an evolutionary characteristic of "eastern regions taking the lead in unlocking, central regions undergoing rapid transformation, and western regions following suit continuously" in spatial patterns. Moreover, a comprehensive spatio-temporal analysis indicates that the degree of national carbon lock-in discretization has increased, regional disparities have expanded, and a multi-polarization tendency is evident. Carbon lock-in demonstrates a significant positive spatial spillover effect. The growth rate of fixed asset investment has a positive influence on carbon lock-in in adjacent areas, while the urbanization rate and the proportion of labor compensation have substantial negative impacts. The inter-provincial carbon lock-in network interaction shows a three-stage evolutionary trend bounded by the Hu Huanyong Line and transmission characteristics of "continuous deepening of inter-provincial connections, significant polarization of hub nodes, and explicit regional transmission paths". The differentiated evolution of functional interactions between northern and southern blocks bounded by the Qinling-Huaihe Line is obvious. The prediction results indicate that the carbon lock-in level is under pressure from diminishing marginal returns and faces risks of local rebound. The key to breaking the carbon lock-in network lies in the provinces with high betweenness centrality.

, authors=Xi-wu HU^{1, 2}, Zhong-hao LI¹, Qian ZHANG^{3, *}, authorsList=Xi-wu HU, Zhong-hao LI, Qian ZHANG, authorCompany=null, correspAuthors=Qian 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=1314923053939782326, articleId=1314923051993625268, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=我国省域碳锁定时空格局及演进特征, columnId=1234106391661704058, journalTitle=中国环境科学, columnName=碳排放控制, runingTitle=null, highlight=null, articleAbstract=

本文在以改进的碳锁定评价指标体系对2002~2022年我国省域碳锁定水平进行测度的基础上，以时空分析方法刻画了其时空格局及演进规律，并探讨其空间关联机制和演进趋势．结果显示：全国碳锁定水平在时间上呈现缓慢下降、加速解锁和平缓波动三阶段变动趋势，在空间格局上呈现“东部率先解锁、中部快速转型、西部持续跟进”分布演化特征，且离散化程度加深、区域差异扩大且多极化趋势明显；碳锁定具有显著正向空间溢出效应，固定资产投资增长率、城镇化率、劳动者报酬比重对周边地区碳锁定影响显著，前者影响为正，后二者影响为负；省际碳锁定网络互动关系呈现以胡焕庸线为界的三阶段演化趋势和“省际关联持续深化、枢纽节点极化显著、区域传导路径显化”的传导特点，以秦岭淮河线为界的南北板块功能互动演进分异特征明显；预测结果显示，碳锁定水平面临边际效益递减压力，存在局部反弹风险，破解碳锁定网络的关键点在于高中介中心度省份．

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^2.天津大学-青海民族大学双碳研究院，青海 西宁 810007, bio={"content":"

胡西武（1973-），男，湖北荆州人，教授，博士，主要研究方向为生态经济学与气候变化经济学等．发表论文100余篇．2827617701@qq.com.

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胡西武（1973-），男，湖北荆州人，教授，博士，主要研究方向为生态经济学与气候变化经济学等．发表论文100余篇．2827617701@qq.com.

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