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北京冬季PM2.5中有机气溶胶的化学特征和来源解析
摘要点击 4117  全文点击 1124  投稿时间:2020-09-24  修订日期:2020-11-10
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中文关键词  大气细颗粒物  有机气溶胶  北京  冬季  来源解析
英文关键词  fine particulate matter  organic aerosols  Beijing  winter  source apportionment
作者单位E-mail
徐楠 北京大学环境科学与工程学院, 环境模拟与污染控制国家重点联合实验室, 教育部区域污染控制国际合作联合实验室, 北京 100871 nanxu@pku.edu.cn 
王甜甜 北京大学环境科学与工程学院, 环境模拟与污染控制国家重点联合实验室, 教育部区域污染控制国际合作联合实验室, 北京 100871  
李晓 北京大学环境科学与工程学院, 环境模拟与污染控制国家重点联合实验室, 教育部区域污染控制国际合作联合实验室, 北京 100871  
唐荣志 北京大学环境科学与工程学院, 环境模拟与污染控制国家重点联合实验室, 教育部区域污染控制国际合作联合实验室, 北京 100871  
郭松 北京大学环境科学与工程学院, 环境模拟与污染控制国家重点联合实验室, 教育部区域污染控制国际合作联合实验室, 北京 100871  
胡敏 北京大学环境科学与工程学院, 环境模拟与污染控制国家重点联合实验室, 教育部区域污染控制国际合作联合实验室, 北京 100871 minhu@pku.edu.cn 
中文摘要
      为探讨北京冬季大气细颗粒物(PM2.5)中有机气溶胶的浓度水平、分布特征和来源变化,对2016年11月10日~12月10日采集的北京大气PM2.5样品进行气相色谱-质谱测定,定量了129种颗粒有机物(POM),约占有机物总量的(9.3±1.2)%.其中含量最高的是糖类,仅左旋葡聚糖即可占到定量有机物的18%,其次是正构烷酸、正构烷烃、二元羧酸和多环芳烃.根据POM示踪物的变化特征,分析了供暖和生物质燃烧传输对北京冬季有机气溶胶的影响.相比于非供暖期间,供暖期间化石燃料示踪物藿烷的质量浓度及在有机物中的占比都明显升高,各组分间的分布也更加趋向于燃煤排放的特征.正构烷烃主峰碳数和奇偶分布的变化,反映了化石燃料贡献增强的影响.生物质燃烧示踪物左旋葡聚糖的浓度权重轨迹(CWT)模型结果表明,北京周围区域的秸秆燃烧污染会通过传输影响北京的有机气溶胶组成.利用分子示踪-化学质量平衡(MM-CMB)模型对2016年北京冬季有机碳(OC)进行了来源解析,并与2006年的结果进行比较,以定量10年间各污染来源贡献发生的变化.2016年与2006年相比,机动车对有机气溶胶贡献明显增加,燃煤和木材燃烧的贡献则大幅度降低,餐饮排放的贡献也不容忽视.因此,控制机动车和餐饮源的排放对改善北京冬季PM2.5污染问题至关重要.
英文摘要
      To explore the concentrations, characteristics, and sources of organic aerosols in winter in Beijing, atmospheric fine particulate matter (PM2.5) samples were collected from November 10, 2016 to December 10, 2016. One hundred and twenty-nine particulate organic matters (POM) were quantified by gas chromatography-mass spectrometry, accounting for approximately 9.3%±1.2% of the total concentration of organic matter. The most abundant class was sugar, among which levoglucosan alone accounted for 18% of the quantified organic matter mass. The next most abundant classes were alkanoic acids, normal alkanes, dicarboxylic acids, and polycyclic aromatic hydrocarbons. The influence of winter heating and biomass burning emissions on organic aerosols in winter in Beijing was analyzed by the characteristics of the molecular markers in the POM. Compared with those during the non-heating period, the concentrations and proportions of hopane species, which are tracers for fossil fuels, increased in the organic matters during the heating period. Moreover, the influence of coal burning emissions on the distribution of hopane species was enhanced. The species with the maximum concentration and carbon predominance index in n-alkanes also reflected the influence of enhanced fossil fuel emissions. The results of the concentration-weighted trajectory model for levoglucosan, a tracer for biomass combustion, suggested that straw burning pollution in the surrounding areas of Beijing would affect the composition of organic aerosols in Beijing via airmass transport. A molecular marker-based chemical mass balance model was used to apportion the sources of organic carbon in the winter of 2016 in Beijing, and the results were compared with those of research in 2006 to quantify the changes in the source contributions over 10 years. The contribution of motor vehicles increased significantly in 2016 compared with that in 2006, whereas the contribution of coal burning and wood burning decreased to a large extent. The contribution of cooking emissions could not be ignored. Therefore, the control of motor vehicle and cooking emissions is of great importance to reduce the problem of PM2.5 pollution in winter in Beijing.

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