Article(id=1314922140026101767, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314922077824578469, 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=1751904000000, receivedDateStr=2025-07-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791431468253, onlineDateStr=2026-10-08, pubDate=1771516800000, pubDateStr=2026-02-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791431468253, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791431468253, creator=13701087609, updateTime=1791431468253, updator=13701087609, issue=Issue{id=1314922077824578469, tenantId=1146029695717560320, journalId=1234093305789726721, year='2026', volume='46', issue='2', pageStart='593', pageEnd='1184', issueExtLink='null', onlineDate='null', pubDate='1771516800000', pubDateStr='2026-02-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791431453424, creator='13701087609', updateTime=1791431520751, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314922360277398376, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314922077824578469, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314922360277398377, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314922077824578469, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=666, endPage=675, ext={EN=ArticleExt(id=1314922140219039752, articleId=1314922140026101767, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Characterization and source apportionment of PM_2.5 along the Hubei stretch of the Yangtze River using ship-based mobile monitoring, columnId=1234106386020365051, journalTitle=China Environmental Science, columnName=Air Pollution Control, runingTitle=null, highlight=null, articleAbstract=

From August 28 to September 3, 2024, the concentrations of atmospheric pollutants and chemical compositions of PM_2.5 along the Hubei stretch of the Yangtze River were obtained using on aboard instruments. During the mobile survey, the average concentrations of CO, NO₂, O₃, and SO₂ were (0.75 ± 0.22) mg/m³, (19.87 ± 12.77) μg/m³, (74.23 ± 39.22) μg/m³, and (21.98 ± 8.81)μg/m³ respectively, all below China's Grade I Ambient Air Quality Standards. The mean PM_2.5 mass concentration was (35.84 ±12.08) μg/m³, with organic matters being the dominant component ((21.94 ± 7.36)%), followed by SO₄^2-((20.53 ± 10.31)%), NO₃^- ((19.88 ± 12.29)%), and ((12.80 ± 4.70)%). Using the receptor model, four PM_2.5 sources including secondary inorganic aerosols, ship emissions, biomass burning, and industrial emissions were apportioned with contributions of (47.86 ± 6.17)%, (26.61 ± 3.32)%, (18.29 ± 6.57)%, and (8.38 ± 4.68)%, respectively. Comparison between mobile ship-based observations and land-based stationary supersite observations revealed stronger secondary formation over the river surface. By coupling the FLEXPART backward simulation with the PM_2.5 emission inventory, the relative contribution of each grid point in the study area to the PM_2.5 concentration along the mobile monitoring route was calculated and the contribution rate along the Yangtze River was 76.90%, while other regions accounted for 23.10%. FLEXPART forward simulation indicated that the ship emissions exerting greater impacts on the riverine regions than other areas.

, authors=Huang ZHENG^{1, 2}, Nan CHEN^{3, 4}, Shu-rui ZHENG⁵, Ke XU^{3, 4}, Ming-ming ZHENG^{5, *}, authorsList=Huang ZHENG, Nan CHEN, Shu-rui ZHENG, Ke XU, Ming-ming ZHENG, authorCompany=null, correspAuthors=Ming-ming ZHENG, 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=1314922140638470155, articleId=1314922140026101767, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=基于船载走航的长江湖北段PM_2.5特征及来源, columnId=1234106388364981004, journalTitle=中国环境科学, columnName=大气污染与控制, runingTitle=null, highlight=null, articleAbstract=

2024年8月28日~9月3日，利用船载测量仪器对长江湖北段大气污染物浓度进行观测，获得了江面上大气污染浓度以及细颗粒物（PM_2.5）化学组分信息．结果表明，走航期间，长江湖北段上CO、NO₂、O₃和SO₂平均浓度分别为（0.75 ± 0.22）mg/m³、（19.87 ± 12.77）μg/m³、（74.23 ± 39.22）μg/m³和（21.98± 8.81）μg/m³，均未超过《环境空气质量标准》一级标准．走航期间PM_2.5质量浓度为（35.84 ± 12.08）μg/m³，其中有机物占比最高（（21.94 ± 7.36）%），其次为SO₄^2-（（20.53 ± 10.31）%）、NO₃^-（（19.88 ± 12.29）%）和NH₄⁺（（12.80 ± 4.70）%）．利用受体模型解析得到PM_2.5来源于二次无机气溶胶、船舶排放、生物质燃烧和工业排放，其贡献率分别为（47.86 ± 6.17）%、（26.61 ± 3.32）%、（18.29 ± 6.57）%和（8.38 ± 4.68）%．对比走航观测和陆地超站观测数据发现，江面上的二次生成作用更强．耦合FLEXPART后向模拟和PM_2.5排放清单，计算得到研究区域内各格点对走航路线上PM_2.5浓度的相对贡献，长江沿岸的贡献率为76.90%，其他区域的贡献为23.10%．FLEXPART前向模拟结果表明，船舶排放对长江沿线的影响高于其他地区．

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郑煌（1991-），男，湖北武汉人，副教授，博士，主要从区域大气污染研究．发表论文70余篇．zhengh@wust.edu.cn.

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郑煌（1991-），男，湖北武汉人，副教授，博士，主要从区域大气污染研究．发表论文70余篇．zhengh@wust.edu.cn.

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