Article(id=1314918445792190689, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918356222829028, 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=1742400000000, receivedDateStr=2025-03-20, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791430587479, onlineDateStr=2026-10-08, pubDate=1763568000000, pubDateStr=2025-11-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791430587479, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791430587479, creator=13701087609, updateTime=1791430587479, updator=13701087609, issue=Issue{id=1314918356222829028, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='11', pageStart='5921', pageEnd='6512', issueExtLink='null', onlineDate='null', pubDate='1763568000000', pubDateStr='2025-11-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791430566125, creator='13701087609', updateTime=1791431596967, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314922679942078535, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918356222829028, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314922679942078536, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918356222829028, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=6398, endPage=6410, ext={EN=ArticleExt(id=1314918446161289442, articleId=1314918445792190689, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Source apportionment and uncertainty analysis of polycyclic aromatic hydrocarbon risks in Beijing's surface dust using coupled PMF-HHRA modeling, columnId=1234106388687934088, journalTitle=China Environmental Science, columnName=Environmental Toxicology and Environmental Health, runingTitle=null, highlight=null, articleAbstract=

In the present study, a comprehensive investigation of PAHs in surface dust from Beijing was conducted through the integration of the Positive Matrix Factorization (PMF) model, Health Risk Assessment (HHRA) model, Monte Carlo simulation, and bootstrap uncertainty analysis. This integrated approach enabled a systematic analysis of the occurrence characteristics, health risks, and primary risk sources of 16 priority PAHs, while simultaneously quantifying uncertainties inherent in both risk assessment and source apportionment processes. Results indicated that the total concentrations of PAHs in Beijing’s surface dust ranged from 2.33 to 19.22μg/g, with high-ring PAHs being the dominant component (mean concentration: 6.43μg/g). Specifically, traffic-dominated zones within core urban areas exhibited the highest PAH levels (13.39μg/g), whereas ecological zones displayed the lowest concentrations (5.24μg/g). Probabilistic analysis revealed that the probability of moderate carcinogenic risk associated with PAH exposure reached 90.02% for adults and 94.97% for children, respectively. Children were found to be more susceptible to PAH-related health risks via the hand-to-mouth ingestion pathway, whereas adults faced greater vulnerability through dermal contact. Key driving factors influencing PAH exposure risks included duration of exposure and skin contact area. Source apportionment results identified three primary contributors to PAHs in surface dust: vehicle exhaust emissions (37.4%), non-combustion vehicle-related emissions (26.6%), and biomass/coal combustion (33.8%). Notably, although biomass/coal combustion accounted for 33.84% of the total PAH concentrations, its contribution to associated health risks was only approximately 15%. This observation highlights a significant discrepancy between concentration-based and risk-based source apportionment outcomes. Collectively, these findings provide valuable scientific insights to support the development of targeted pollution control measures for PAHs in Beijing.

, authors=Yu MEN¹, Yi-di WANG^{1, *}, Yun-qi WANG¹, Long-long WANG², Bing GAO³, authorsList=Yu MEN, Yi-di WANG, Yun-qi WANG, Long-long WANG, Bing GAO, authorCompany=null, correspAuthors=Yi-di WANG, 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=1314918446425530595, articleId=1314918445792190689, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=基于PMF-HHRA模型耦合的北京市地表灰尘多环芳烃风险来源解析及不确定性分析, columnId=1234106394006311784, journalTitle=中国环境科学, columnName=环境毒理与健康, runingTitle=null, highlight=null, articleAbstract=

以北京市地表灰尘中的PAHs为研究对象,耦合正定矩阵因子分析模型（PMF）和健康风险评价模型（HHRA）,并结合Monte Carlo模拟和bootstrap不确定性分析方法,综合分析了地表灰尘中16种PAHs的赋存特征、健康风险及主要风险来源,并评估了风险评价及源解析结果的不确定性.结果表明:北京市地表灰尘中16种PAHs总含量为2.33~19.22μg/g,其中高环PAHs的总含量最高（平均值6.43μg/g）.北京市核心功能主导区域中交通主导区PAHs含量最高（13.39μg/g）,生态主导区PAHs含量最低（5.24μg/g）.地表灰尘PAHs对成人和儿童造成中等致癌风险的概率分别为90.02%和94.97%.儿童通过手-口直接摄入途径的风险较高,而成人通过皮肤接触摄入途径的风险较高.暴露持续时间和皮肤暴露面积是影响致癌风险的主要因素.PAHs的主要来源包括机动车尾气排放、机动车非燃烧类排放和生物质及煤炭燃烧. 基于PAHs含量得到的各来源占比与基于PAHs健康风险得到的各来源占比之间存在显著差异.生物质和煤炭燃烧对PAHs含量的贡献高达33.84%,但对PAHs健康风险的贡献仅为15%左右.研究结果可为北京市地表灰尘PAHs污染的有效管控提供重要理论支撑.

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门誉（2005-），女，吉林辽源人，北京林业大学本科生，主要从事污染物暴露途径及风险评价．menyumy@163.com.

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门誉（2005-），女，吉林辽源人，北京林业大学本科生，主要从事污染物暴露途径及风险评价．menyumy@163.com.

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