Article(id=1314918376850420054, 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=1741708800000, receivedDateStr=2025-03-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791430571043, onlineDateStr=2026-10-08, pubDate=1763568000000, pubDateStr=2025-11-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791430571043, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791430571043, creator=13701087609, updateTime=1791430571043, 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=5950, endPage=5958, ext={EN=ArticleExt(id=1314918377043358039, articleId=1314918376850420054, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Characteristics and source analysis of atmospheric volatile organic compounds pollution in Wuhan urban area based on photochemical loss, columnId=1234106386020365051, journalTitle=China Environmental Science, columnName=Air Pollution Control, runingTitle=null, highlight=null, articleAbstract=

Assessment of photochemical losses is essential for characterizing VOC pollution and apportioning its sources. Continuous online monitoring of VOCs was conducted in urban Wuhan from September 8 to 18, 2021, capturing two ozone pollution episodes with active photochemical reactions. The parameterized method based on photochemical age was employed to correct observed VOC concentrations (Ob) for photochemical losses, deriving initial concentrations (In) for pollution characterization. Source apportionment was performed using the Positive Matrix Factorization (PMF) model. Results indicate that alkenes exhibited the highest photochemical loss concentrations and ozone formation potential (OFP) among VOC categories, identifying them as key species governing ozone pollution. PMF analysis based on initial and observed values identified six major emission sources with concentration contributions (initial, observed) as follows: vehicle emissions (16.5%, 17.7%), industrial chemical emissions (14.7%, 13.7%), biogenic sources (4.6%, 4.0%), combustion sources (20.2%, 33.1%), LPG/NG usage (21.1%, 18.9%), and solvent use (22.9%, 12.6%). The PMF results were significantly influenced by photochemical reactions, underscoring the necessity of employing initial VOC concentrations in source apportionment to avoid underestimating contributions from solvent use, LPG/NG sources, biogenic emissions, and industrial chemical sources.

, authors=Han YUE1, Ke HU2, An-xiong CHEN2, Hai-qun GONG2, Hai-rong CHENG1, *, authorsList=Han YUE, Ke HU, An-xiong CHEN, Hai-qun GONG, Hai-rong CHENG, authorCompany=null, correspAuthors=Hai-rong CHENG, 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=1314918377324376408, articleId=1314918376850420054, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=基于光化学损失的武汉城区大气挥发性有机物污染特征和来源解析, columnId=1234106388364981004, journalTitle=中国环境科学, columnName=大气污染与控制, runingTitle=null, highlight=null, articleAbstract=

对VOCs的污染特征和来源解析需要对VOCs的光化学损失进行评估.选取2021年9月8~18日在武汉城区开展VOCs连续在线监测,期间发生两次臭氧高污染过程,光化学反应较为活跃.利用光化学年龄的参数化方法对VOCs观测浓度(Ob)进行光化学损失矫正获取VOCs初始浓度(In),并分析VOCs的污染特征,使用正交矩阵因子模型(PMF)进行来源解析.研究结果表明,各类VOCs中光化学损失浓度和臭氧生成潜势(OFP)最高的均为烯烃,烯烃是控制臭氧污染的关键组分.基于初始值和测量值进行PMF源解析得到的6个主要排放源浓度贡献(初始值,观测值)为:机动车排放源(16.5%,17.7%)、化工排放源(14.7%,13.7%)、植物源(4.6%,4.0%)、燃烧源(20.2%,33.1%)、LPG/NG使用源(21.1%,18.9%)和溶剂使用源(22.9%,12.6%).PMF源解析结果受光化学反应影响显著,因此进行源解析时应考虑VOCs初始值,避免低估溶剂使用源,LPG/NG源,植物源,化工排放源等的贡献.

, authors=乐翰1, 胡柯2, 陈安雄2, 龚海群2, 成海容1, *, authorsList=乐翰, 胡柯, 陈安雄, 龚海群, 成海容, authorCompany=null, correspAuthors=成海容, authorNote=

乐翰(1998-),男,湖北咸宁人,武汉大学硕士研究生,主要从事大气挥发性有机物来源解析研究..

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* 责任作者,教授,
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乐翰(1998-),男,湖北咸宁人,武汉大学硕士研究生,主要从事大气挥发性有机物来源解析研究..

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乐翰(1998-),男,湖北咸宁人,武汉大学硕士研究生,主要从事大气挥发性有机物来源解析研究..

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基于光化学损失的武汉城区大气挥发性有机物污染特征和来源解析
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乐翰 1 , 胡柯 2 , 陈安雄 2 , 龚海群 2 , 成海容 1, *
中国环境科学 | 大气污染与控制 2025,45(11): 5950-5958
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中国环境科学 |大气污染与控制 2025 , 45 (11) : 5950 -5958
基于光化学损失的武汉城区大气挥发性有机物污染特征和来源解析
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乐翰(1998-),男,湖北咸宁人,武汉大学硕士研究生,主要从事大气挥发性有机物来源解析研究..

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乐翰(1998-),男,湖北咸宁人,武汉大学硕士研究生,主要从事大气挥发性有机物来源解析研究..

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articleId=1314918376850420054, companyId=1314918377601200476, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.武汉市生态环境监控中心,湖北 武汉 430022)])]), Author(id=1314918378721079668, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314918376850420054, orderNo=4, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=chenghr@whu.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=1, authorType=1, ext={EN=AuthorExt(id=1314918378800771446, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314918376850420054, authorId=1314918378721079668, language=EN, stringName=Hai-rong CHENG, firstName=Hai-rong, middleName=null, lastName=CHENG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, *, address=1.School of Resource and Environment Science, Wuhan 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乐翰1 , 胡柯2, 陈安雄2, 龚海群2, 成海容1, *
作者信息
  • 1.武汉大学资源与环境科学学院,湖北 武汉 430072
  • 2.武汉市生态环境监控中心,湖北 武汉 430022
通讯作者:
* 责任作者,教授,
作者简介:

乐翰(1998-),男,湖北咸宁人,武汉大学硕士研究生,主要从事大气挥发性有机物来源解析研究..

Characteristics and source analysis of atmospheric volatile organic compounds pollution in Wuhan urban area based on photochemical loss
Han YUE1 , Ke HU2, An-xiong CHEN2, Hai-qun GONG2, Hai-rong CHENG1, *
Affiliations
  • 1.School of Resource and Environment Science, Wuhan University, Wuhan 430072, China
  • 2.Wuhan Environment Monitoring Center, Wuhan 430022, China
出版时间: 2025-11-20
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对VOCs的污染特征和来源解析需要对VOCs的光化学损失进行评估.选取2021年9月8~18日在武汉城区开展VOCs连续在线监测,期间发生两次臭氧高污染过程,光化学反应较为活跃.利用光化学年龄的参数化方法对VOCs观测浓度(Ob)进行光化学损失矫正获取VOCs初始浓度(In),并分析VOCs的污染特征,使用正交矩阵因子模型(PMF)进行来源解析.研究结果表明,各类VOCs中光化学损失浓度和臭氧生成潜势(OFP)最高的均为烯烃,烯烃是控制臭氧污染的关键组分.基于初始值和测量值进行PMF源解析得到的6个主要排放源浓度贡献(初始值,观测值)为:机动车排放源(16.5%,17.7%)、化工排放源(14.7%,13.7%)、植物源(4.6%,4.0%)、燃烧源(20.2%,33.1%)、LPG/NG使用源(21.1%,18.9%)和溶剂使用源(22.9%,12.6%).PMF源解析结果受光化学反应影响显著,因此进行源解析时应考虑VOCs初始值,避免低估溶剂使用源,LPG/NG源,植物源,化工排放源等的贡献.

挥发性有机物(VOCs)  /  光化学损失  /  正交矩阵因子分析(PMF)  /  臭氧生成潜势(OFP)

Assessment of photochemical losses is essential for characterizing VOC pollution and apportioning its sources. Continuous online monitoring of VOCs was conducted in urban Wuhan from September 8 to 18, 2021, capturing two ozone pollution episodes with active photochemical reactions. The parameterized method based on photochemical age was employed to correct observed VOC concentrations (Ob) for photochemical losses, deriving initial concentrations (In) for pollution characterization. Source apportionment was performed using the Positive Matrix Factorization (PMF) model. Results indicate that alkenes exhibited the highest photochemical loss concentrations and ozone formation potential (OFP) among VOC categories, identifying them as key species governing ozone pollution. PMF analysis based on initial and observed values identified six major emission sources with concentration contributions (initial, observed) as follows: vehicle emissions (16.5%, 17.7%), industrial chemical emissions (14.7%, 13.7%), biogenic sources (4.6%, 4.0%), combustion sources (20.2%, 33.1%), LPG/NG usage (21.1%, 18.9%), and solvent use (22.9%, 12.6%). The PMF results were significantly influenced by photochemical reactions, underscoring the necessity of employing initial VOC concentrations in source apportionment to avoid underestimating contributions from solvent use, LPG/NG sources, biogenic emissions, and industrial chemical sources.

volatile organic compounds  /  photochemical loss  /  positive matrix factorization  /  ozone formation potential
乐翰, 胡柯, 陈安雄, 龚海群, 成海容. 基于光化学损失的武汉城区大气挥发性有机物污染特征和来源解析. 中国环境科学, 2025 , 45 (11) : 5950 -5958 .
Han YUE, Ke HU, An-xiong CHEN, Hai-qun GONG, Hai-rong CHENG. Characteristics and source analysis of atmospheric volatile organic compounds pollution in Wuhan urban area based on photochemical loss[J]. China Environmental Science, 2025 , 45 (11) : 5950 -5958 .
  • 国家自然科学基金资助项目(42277093)
  • 湖北省杰出青年项目(2023AFA057)
  • 校基本科研业务费专项资金(2042024kf0013)
  • 湖北省联合基金项目(2024AFD204)
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  • 接收时间:2025-03-12
  • 首发时间:2026-10-08
  • 出版时间:2025-11-20
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  • 收稿日期:2025-03-12
基金
国家自然科学基金资助项目(42277093)
湖北省杰出青年项目(2023AFA057)
校基本科研业务费专项资金(2042024kf0013)
湖北省联合基金项目(2024AFD204)
作者信息
    1.武汉大学资源与环境科学学院,湖北 武汉 430072
    2.武汉市生态环境监控中心,湖北 武汉 430022

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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