| 重庆典型城区PM2.5生物标志物组分特征及源指示 |
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| 引用本文： | 冯婷,王锋文,卢培利,刘莉.重庆典型城区PM2.5生物标志物组分特征及源指示[J].中国环境科学,2021,41(12):5578-5590. |
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| 作者姓名： | 冯婷 王锋文 卢培利 刘莉 |
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| 作者单位： | 1. 重庆大学, 煤矿灾害动力学与控制国家重点实验室, 重庆 400044;2. 重庆大学环境科学系, 重庆 400044;3. 城市大气环境综合观测与污染防控重庆市重点实验室, 重庆 401147 |
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| 基金项目： | 国家自然科学基金资助项目（42077319）；国家重点研发计划（2018YFC0214000）；重庆市重点实验室开放课题（CQKLAE202104）；重庆市技术创新与应用示范专项重点示范项目（cstc2019jscx-gksb0241）；重庆市研究生科研创新项目（CYS20035） |
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| 摘 要： | 于2015年10月~2016年8月在重庆大学A区采集秋冬春夏4个季节PM2.5样品（n=77），分析生物标志物（n-alkanes、UCM、藿烷和甾烷）组分特征，探讨季节变化和对来源的指示.结果表明，重庆沙坪坝区PM2.5中Σn-alkanes （C11~C38）和UCM年均浓度分别为328.69ng/m3和2.52μg/m3，均为冬季最高，夏季最低.28n-alkanes PMF源解析识别出4个因子：化石燃料燃烧（23.45%）、化石燃料残留（29.1%）、生物质燃烧（21.35%）和高等植物蜡排放（26.1%）.UCM与可分离烷烃组分比例（U：R）为1.29~3.33.夏季U：R最低，可能是受温度和光照的驱使，微生物和植物的生命活动旺盛所致.藿烷Ts/Tm、C30αβ/C31αβ（22R）和C31αβ（22S）/（22S+22R）的年均值分别为1.15，5.26和0.59，指示以机动车尾气排放为主的高成熟度石油烃输入.甾烷C29αββ/（ααα+αββ）和C29ααα（20S）/（20S+20R）的年均值分别为0.40和0.53，主要指示高成熟度化石燃料残余物输入.PSCF分析表明，Σn-alkanes的潜在源区主要集中在四川东南部和重庆西部及其相接壤附近区域，UCM的潜在源区主要分布在四川东南部.
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| 关 键 词： | 重庆 PM2.5 生物标志物 正定矩阵因子分析 潜在源贡献函数 |
| 收稿时间： | 2021-04-30 |
Composition characteristics and source implications of biomarkers in PM2.5 at a typical urban area of Chongqing |
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| FENG Ting,WANG Feng-wen,LU Pei-li,LIU Li.Composition characteristics and source implications of biomarkers in PM2.5 at a typical urban area of Chongqing[J].China Environmental Science,2021,41(12):5578-5590. |
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| Authors: | FENG Ting WANG Feng-wen LU Pei-li LIU Li |
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| Institution: | 1. State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China;2. Department of Environmental Science, Chongqing University, Chongqing 400044, China;3. Key Laboratory for Urban Atmospheric Environment Integrated Observation & Pollution Prevention and Control of Chongqing, Chongqing 401147, China |
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| Abstract: | Seventy-seven PM2.5 samples covering four seasons from October 2015 to August 2016 were collected at an urban site of Chongqing University Campus A. These samples were analyzed for biomarkers including n-alkanes, UCM, hopanes and steranes to reveal the composition characteristics, seasonal variation and assess their source implications. The results showed that the annual average concentrations of Σn-alkanes (C11~C38) and UCM were 328.69ng/m3 and 2.52 μg/m3, respectively. Both of them are the highest in winter, lowest in summer. The PMF analysis of 28n-alkanes identified 4source categories, including fossil fuel combustion (23.45%), fossil fuel residue (29.1%), biomass burning (21.35%) and plants wax emission (26.1%). The ratio of UCM to alkanes (U: R) ranged from 1.29 to 3.33. Possibly owning to the high temperature and intense light, the activities of microorganisms and plants were vigorous and resulted in the lowest U: R value in summer. The annual average of Ts/Tm, C30αβ/C31αβ(22R) and C31αβ(22S)/(22S+22R) for hopanes were 1.15, 5.26 and 0.59, respectively, indicating sources from high-maturity petroleum hydrocarbons, such as the exhaustion from motor vehicles. The annual average of C29αββ/(ααα+αββ) and C29ααα(20S)/(20S+20R) for steranes were 0.40 and 0.53, respectively, indicating sources from fossil fuel residues with high thermal maturity. PSCF analysis showed that the potential source areas of Σn-alkanes were mainly in southeastern Sichuan, western Chongqing and their adjacent areas; while the potential source areas of UCM were mainly in southeastern Sichuan. |
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| Keywords: | Chongqing PM2 5 biomarkers positive matrix factorization potential source contribution function |
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