摘要
近年来我国城市地区灰霾污染频发,严重影响生态环境以及人体健康.了解PM2.5的化学组成、来源、大气传输过程和环境效应对灰霾污染有效控制对策的制定有重要意义,已成为国际大气环境领域的研究热点.本文通过总结国内外正定矩阵因子分析模型(positive matrix factorization,PMF)在PM2.5源解析方面的研究,阐释了PM2.5化学组成空间差异、待测化学组分选择、有机示踪物气固相分配、观测结果时间分辨率对PMF源解析结果的影响.评述结果表明,同一城市或地区基于不同采样点样品数据的源解析结果存在较大差异;对同组PM2.5样品,解析出的排放源类型和待观测化学组分的选择密切相关;因有机示踪物气固相分配作用的影响,低分子量有机物的源解析结果往往存在较大偏差;高时间分辨率观测可更好地反映不同示踪物间浓度的时间变化差异,有利于排放源的准确识别.
Chinese cities suffered from frequent haze pollution in recent years, and this brought a series of negative impacts on air quality and public health. In this case, studying the composition and sources of PM2.5 and its atmospheric processes and environmental effects are of great importance for drawing up effective regulatory strategies to reduce haze pollution, and become hotspots of the research on atmospheric environment. In this work, a number of studies on PM2.5 source apportionment using positive matrix factorization(PMF) were summarized, so as to elucidate the influence of spatial variability of PM2.5 composition, target components selection for analysis, gas/particle partitioning of organic tracers, and time resolution of speciation data on PMF results. The review showed that, even at the same city/area, PM2.5 source information retrieved from the compositional data at different sampling sites had substantial variance. For the same batch of aerosol samples, the output source types from PMF modeling were closely associated with the species selected for characterization. The source attribution of low molecular organic components was subject to large uncertainty due to the influences from gas/particle partitioning. High time-resolution measurements were more capable in capturing the difference in concentration time series between source tracers, improving the accuracy in source identification.
作者
缑亚峰
余欢
王成
谢鸣捷
GOU Yafeng;YU Huan;WANG Cheng;XIE Mingjie(School of Environmental Science and Engineering,Nanjing University of Information Science&Technology,Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control,Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing,210044,China;Department of Atmospheric Science,School of Environmental Studies,China University of Geosciences,Wuhan,430074,China)
出处
《环境化学》
CAS
CSCD
北大核心
2020年第7期1744-1753,共10页
Environmental Chemistry
基金
国家自然科学基金青年项目(41701551)资助
关键词
示踪物
空间差异
气固相分配
时间分辨率
正定矩阵因子分析
tracer
spatial variance
gas/particle partitioning
time resolution
positive matrix factorization
