| 北京城区PM2.5各组分污染特征及来源分析 |
| 摘要点击 4426 全文点击 1116 投稿时间：2021-09-15 修订日期：2021-10-16 |
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| 中文关键词 北京城区 PM2.5 水溶性离子 碳质组分 污染特征 来源分析 |
| 英文关键词 Beijing urban area PM2.5 water-soluble ions carbonaceous components pollution characteristics source analysis |
| 作者 | 单位 | E-mail | | 安欣欣 | 北京市生态环境监测中心, 大气颗粒物监测技术北京市重点实验室, 北京 100048 | anxinxin2002@163.com | | 曹阳 | 北京市生态环境监测中心, 大气颗粒物监测技术北京市重点实验室, 北京 100048 | | | 王琴 | 北京市生态环境监测中心, 大气颗粒物监测技术北京市重点实验室, 北京 100048 | | | 富佳明 | 北京市生态环境监测中心, 大气颗粒物监测技术北京市重点实验室, 北京 100048 | | | 王陈婧 | 北京市生态环境监测中心, 大气颗粒物监测技术北京市重点实验室, 北京 100048 | | | 景宽 | 北京市生态环境监测中心, 大气颗粒物监测技术北京市重点实验室, 北京 100048 | | | 刘保献 | 北京市生态环境监测中心, 大气颗粒物监测技术北京市重点实验室, 北京 100048
清华大学环境学院, 北京 100084 | liubaoxian28@163.com |
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| 中文摘要 |
| 为探索北京城区大气细颗粒物（PM2.5）及其各组分的浓度特征，于2019年全年在车公庄地区开展了PM2.5及水溶性离子、碳质组分及金属元素的连续在线监测.结果表明，2019年北京城区ρ（PM2.5）平均值为46.7μg ·m-3，化学组分中ρ[有机物（OM）]、ρ（NO3-）、ρ（SO42-）、ρ（NH4+）、ρ（EC）、ρ（Cl-）、ρ（微量元素）和ρ（地壳物质）分别为9.1、11.1、5.7、5.4、1.4、0.9、1.6和7.3μg ·m-3，SNA （SO42-、NO3-和NH4+）合计占到了PM2.5的47.4%，而碳质组分较以往研究质量分数偏低，体现出北京城区PM2.5具有较强的二次污染特征，其中NO3-/SO42-为1.96，与以往的研究结果相比放大明显.SNA在4个季节中均占有较高比例，其中NO3-为春、夏和秋季最主要组分，在PM2.5中质量分数为27.8%、23.2%和23.1%；受一次排放影响，冬季ρ[TCA （OM+EC）]和ρ（Cl-）较高，为14.2μg ·m-3和2.1μg ·m-3，分别是夏季的2倍和11倍.从季节日变化特征上看，各组分冬季日变化曲线均呈单峰分布特征，这与冬季燃烧源排放时间集中在夜间以及夜间边界层下降有关；其他三季OM日变化曲线特征较相似呈双峰型分布，NO3-在春夏季（06：00~09：00）浓度突出，SO42-、EC和Cl-日变化幅度较小.随着污染等级增加，SNA质量分数呈逐渐增加趋势，在五级重度污染时段，SO42-和Cl-质量分数升高，NO3-/SO42-下降，体现出区域污染影响.通过研究潜在源区发现，河北中南部地区为主要的潜在源区，相对贡献最大；其中冬季SO42-的高值区域主要集中在东部和东南部，分布范围更广且距离北京市较近.基于PMF的源解析结果表明，2019年北京城区PM2.5的来源依次为二次硝酸盐、二次硫酸盐+二次有机物、机动车源、扬尘源、工业源和燃煤+生物质源，贡献率分别为39%、24%、17%、7%、7%和5%；二次源是北京市的最主要来源，总贡献率达63%. |
| 英文摘要 |
| To explore the concentration characteristics of fine particulate matter (PM2.5) and its components in a Beijing urban area, PM2.5 and water-soluble ions, carbonaceous components, and metal elements were continuously measured online in the Chegongzhuang area throughout 2019. The results showed that the average ρ(PM2.5) in the Beijing urban area in 2019 was 46.7 μg·m-3, and the ρ[organic matter (OM)], ρ(NO3-), ρ(SO42-), ρ(NH4+), ρ(EC), ρ(Cl-), ρ(trace elements), and ρ(crustal matter) were 9.1, 11.1, 5.7, 5.4, 1.4, 0.9, 1.6, and 7.3 μg·m-3, respectively. The SNA including SO42-, NO3-, and NH4+ accounted for 47.4% of PM2.5, and the proportion of carbonaceous components was lower than that of the previous results, which showed significant secondary pollution characteristics of PM2.5 in Beijing. Additionally, the ratio of NO3-/SO42- was 1.96, which was obviously larger than that of the previous results. In terms of the characteristics of different seasons, SNA accounted for a large proportion in all seasons, and NO3- was the main component in spring, summer, and autumn, accounting for 27.8%, 23.2%, and 23.1% in PM2.5, whereas the concentrations of TCA(OM+EC) and Cl- in winter were 14.2 μg·m-3 and 2.1 μg·m-3, which were 2 and 11 times those in summer. The characteristics of seasonal diurnal variation indicated that all components showed a single-peak distribution of diurnal variation in winter, which was related to the emission of combustion sources and the decrease in the boundary layer at night. In the other three seasons, the diurnal variation in OM showed a double-peak distribution, and NO3- was higher from 06:00-09:00 in spring and summer, whereas there were no obvious variations in SO42-, EC, and Cl-. With the increase in pollution levels, SNA fractions gradually increased. During the heavy pollution, the proportion of SO42- and Cl- increased, whereas the ratio of NO3-/SO42- decreased, reflecting the influence of regional pollution. Potential source region analyses suggested that the air mass from the south-central area of Hebei province contributed most to the high PM2.5 concentrations in the urban area of Beijing. Furthermore, the high WPSCF value of SO42- in winter was mainly concentrated in the east and southeast, with a wider distribution and a closer distance to Beijing. The PMF model showed the sources of PM2.5 in Beijing in 2019 as:secondary nitrate, secondary sulfate+secondary organic matter, vehicle sources, dust sources, industrial sources, and coal combustion+biomass sources, with the contributions of 39%, 24%, 17%, 7%, 7%, and 5%, respectively. Secondary sources were the main source in Beijing, with a total contribution of 63%. |
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