Article(id=1314918662721598160, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918450573701162, 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=1747843200000, receivedDateStr=2025-05-22, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791430639199, onlineDateStr=2026-10-08, pubDate=1766160000000, pubDateStr=2025-12-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791430639199, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791430639199, creator=13701087609, updateTime=1791430639199, updator=13701087609, issue=Issue{id=1314918450573701162, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='12', pageStart='6513', pageEnd='7104', issueExtLink='null', onlineDate='null', pubDate='1766160000000', pubDateStr='2025-12-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791430588620, creator='13701087609', updateTime=1791431575400, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314922589479333965, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918450573701162, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314922589479333966, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918450573701162, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=6935, endPage=6942, ext={EN=ArticleExt(id=1314918663002616529, articleId=1314918662721598160, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Characteristics and scenario analysis of greenhouse gas emissions from motor vehicles in Henan Province, columnId=1234106390126588740, journalTitle=China Environmental Science, columnName=Carbon Emission Control, runingTitle=null, highlight=null, articleAbstract=

To evaluate the greenhouse gas (GHG) emissions and mitigation potential in the transportation sector of Henan Province, localized vehicle emission factors were calculated based on the COPERT model. A 3km × 3km gridded emission inventory was established using ArcGIS, and the spatiotemporal dynamics of vehicle-related GHG emissions were systematically analyzed. Vehicle ownership in Henan Province from 2025 to 2035 was forecast by combining the Gompertz function with the elasticity coefficient method, and emission trends under multiple policy scenarios were examined. The results showed that total vehicle GHG emissions increased from 140 million tonnes to 160 million tonnes during 2019 to 2023, with an average annual growth rate of 2.9%. Carbon dioxide (CO₂) accounted for more than 98% of total emissions, while light-duty passenger cars and heavy-duty trucks were identified as the primary contributors. Urban road traffic was responsible for 78.8% of total emissions, and high-emission areas were concentrated in core cities such as Zhengzhou and Luoyang, presenting a spatial pattern of central clustering and peripheral diffusion. Under the baseline scenario, total GHG emissions were projected to reach 170 million tonnes by 2035. In contrast, when new energy vehicle promotion, green commuting, and accelerated retirement of aging vehicles were jointly implemented, total emissions were reduced to 70 million tonnes, representing a 58.1% decrease compared with the baseline. These findings provided quantitative evidence to support carbon management and the optimization of mitigation pathways in the transportation sector of Henan Province.

, authors=Quan-kang HAN¹, Xue-xue JING¹, Ya-lun CHENG¹, Ling-ling WANG^{2, *}, Yu-zhe ZHANG³, Ren-cheng ZHU^{1, **}, Jing-nan HU³, authorsList=Quan-kang HAN, Xue-xue JING, Ya-lun CHENG, Ling-ling WANG, Yu-zhe ZHANG, Ren-cheng ZHU, Jing-nan HU, authorCompany=null, correspAuthors=Ling-ling WANG, Ren-cheng ZHU, 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=1314918663266857682, articleId=1314918662721598160, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=河南省机动车温室气体排放特征及情景分析, columnId=1234106391661704058, journalTitle=中国环境科学, columnName=碳排放控制, runingTitle=null, highlight=null, articleAbstract=

为评估河南省交通领域温室气体排放水平及减排潜力，基于COPERT模型计算本地化机动车排放因子，利用ArcGIS软件构建3km × 3km网格化排放清单，系统剖析全省机动车温室气体排放的时空演变特征，并结合Gompertz函数与弹性系数法预测2025~2035年河南省机动车保有量，探究不同控制情景下的排放变化趋势．结果表明：2019~2023年，河南省机动车温室气体排放总量从1.4亿t增至1.6亿t，年均增长率为2.9%；其中，CO₂占比超过98%，小型客车和重型货车是机动车碳排放的主要贡献者．城市道路系统排放占比达78.8%，排放高值区集中于郑州、洛阳等核心城市，呈现“中心集聚、外围扩散”的空间分布特征．基准情景下，2035年排放总量将升至1.7亿t；若协同推行新能源汽车推广、增加绿色通勤及老旧车辆淘汰三项措施，2035年排放量可降至0.7亿t，较基准情景下降58.1%．

, authors=韩全康¹, 景雪雪¹, 程亚伦¹, 王玲玲^{2, *}, 张宇哲³, 朱仁成^{1, **}, 胡京南³, authorsList=韩全康, 景雪雪, 程亚伦, 王玲玲, 张宇哲, 朱仁成, 胡京南, authorCompany=null, correspAuthors=王玲玲, 朱仁成, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=OCTTGC4SQj4FgmFtV6370A==, magXml=L52Qjnl5EonFGyXITfnNQA==, pdfUrl=null, pdf=dYSMQFeDL4AkoEbgy8PJ6A==, pdfFileSize=1969397, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=1owIDmsPBKUL+0hZhAsNNA==, mapNumber=null, fund=null)}, authors=[Author(id=1314918663757591261, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314918662721598160, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=hanqk@gs.zzu.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1314918663828894431, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314918662721598160, authorId=1314918663757591261, language=EN, stringName=Quan-kang HAN, firstName=Quan-kang, middleName=null, lastName=HAN, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=^1.School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1314918663912780512, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314918662721598160, authorId=1314918663757591261, language=CN, stringName=韩全康, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=^1.郑州大学生态与环境学院，河南 郑州 450001, bio={"content":"

韩全康（2000-），男，安徽亳州人，郑州大学在读硕士研究生，研究方向为大气环境污染与控制研究．hanqk@gs.zzu.edu.cn.

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韩全康（2000-），男，安徽亳州人，郑州大学在读硕士研究生，研究方向为大气环境污染与控制研究．hanqk@gs.zzu.edu.cn.

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