Article(id=1314917582973534705, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314917567911788907, 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=1740412800000, receivedDateStr=2025-02-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791430381767, onlineDateStr=2026-10-08, pubDate=1758297600000, pubDateStr=2025-09-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791430381767, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791430381767, creator=13701087609, updateTime=1791430381767, updator=13701087609, issue=Issue{id=1314917567911788907, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='9', pageStart='4737', pageEnd='5328', issueExtLink='null', onlineDate='null', pubDate='1758297600000', pubDateStr='2025-09-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791430378177, creator='13701087609', updateTime=1791431890195, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314923910001418489, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314917567911788907, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314923910001418490, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314917567911788907, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4786, endPage=4795, ext={EN=ArticleExt(id=1314917584768696818, articleId=1314917582973534705, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Localized fine-tuned emission reduction plan and effect evaluation based on ozone source apportionment, columnId=1241049967662518582, journalTitle=China Environmental Science, columnName=Ozone Pollution Control, runingTitle=null, highlight=null, articleAbstract=

Taking a region in the Hangzhou Bay area of China as an example, this study refined the local anthropogenic emission inventory and incorporated it into the regional air quality model WRF-CMAQ. The source contributions to ozone pollution during a typical month were quantitatively analyzed using the Integrated Source Apportionment Method (ISAM) and the Integrated Reaction Rate (IRR) method within CMAQ. The results showed that ozone pollution in this area was mainly attributed to contributions from outside the region, accounting for 73.3%, while local contributions accounted for 26.7%. However, on pollution days, the local contribution was found to increase to 35.6%. Furthermore, the contributions of different local emission sectors were analyzed, and industrial and transportation emissions were identified as the major anthropogenic sources of local ozone formation, contributing 38.3% and 35.4%, respectively. Based on the source apportionment results and considering the region's actual control policies and reduction potential, a refined emission reduction strategy was designed for 40subcategories of anthropogenic sources. This strategy was implemented as an emission control scenario in the CMAQ model to assess its effectiveness. The results indicated that the refined reduction plan significantly reduced locally formed ozone on pollution days, with a maximum reduction of up to 26.44μg/m³ and an average reduction of 3.5μg/m³, representing 7.1% of the locally produced ozone concentration during the pollution period.

, authors=Xin-yu XI^{1, 2}, Yi-fei XU³, Wen-jing DENG², Yu-xuan HUANG², Ao SHEN², Yi-ming LIU², Xiao LU², Qi FAN², Ze-jian LIN¹, Qing LU^{1, *}, authorsList=Xin-yu XI, Yi-fei XU, Wen-jing DENG, Yu-xuan HUANG, Ao SHEN, Yi-ming LIU, Xiao LU, Qi FAN, Ze-jian LIN, Qing LU, authorCompany=null, correspAuthors=Qing LU, 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=1314917585234264563, articleId=1314917582973534705, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=基于臭氧来源解析的局地精细化减排方案及效果评估, columnId=1241049969449292093, journalTitle=中国环境科学, columnName=臭氧污染与控制, runingTitle=null, highlight=null, articleAbstract=

本研究以我国杭州湾某地区为例，对该地区人为源排放清单进行精细化处理并作为本地源更新至区域空气质量数值模型WRF-CMAQ中，同时采用CMAQ的源解析ISAM方法以及综合反应速率IRR方法定量计算分析了该地区典型月份臭氧污染的来源贡献．结果显示：该地区的臭氧污染主要来自区域外贡献，占比高达73.3%，本地贡献占比为 26.7%，但在污染日本地贡献会上升至 35.6%．进一步对该地区不同行业的贡献占比进行解析，其中工业类排放源与交通类排放源分别占比38.3%和35.4%，是本地人为源排放生成臭氧的主要来源．基于臭氧来源解析结果，结合该地区的实际减排政策及减排潜力，对40个小类人为排放源进行精细化减排方案设计，并作为减排情景输入CMAQ模型中进行减排效果评估，结果显示：精细化减排方案对于该地区臭氧污染日中化学生成的臭氧具有较显著的削减效果，最大减少量可达 26.44μg/m³，平均减少量为 3.5μg/m³，平均减少浓度占该时段本地化学生成臭氧浓度的7.1%．

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席欣煜（1999-），男，甘肃兰州人，中山大学硕士研究生，主要从事大气环境数值模拟研究．发表论文1篇．xixy3@mail2.sysu.edu.cn.

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席欣煜（1999-），男，甘肃兰州人，中山大学硕士研究生，主要从事大气环境数值模拟研究．发表论文1篇．xixy3@mail2.sysu.edu.cn.

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