Comparative study of chemical characterization and source apportionment of PM2.5 in South China by filter-based and single particle analysis
Comparative study of chemical characterization and source apportionment of PM2.5 in South China by filter-based and single particle analysis
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基于过滤和单颗粒分析的华南 PM2.5 化学特征和来源解析的比较研究
DOI：
10.1525/elementa.2021.00046
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发表时间：
2021-04
影响因子：
3.9
通讯作者：
Xuemei Wang
中科院分区：
文献类型：
--
作者：
Jingying Mao;Liming Yang;Zhaoyu Mo;Zongkai Jiang;Padmaja Krishnan;Sayantan Sarkar;Qi Zhang;Weihua Chen;Buqing Zhong;Yuan Yang;Shiguo Jia;Xuemei Wang
单粒子气溶胶质谱仪（SPAMS）由于能够提供关于气溶胶化学成分的实时尺寸分辨信息，引起了大气科学家的极大兴趣。本研究的目的是评估新开发的单粒子分析技术的化学表征和源解析环境气溶胶通过比较它与传统的过滤器为基础的方法。在这项研究中，空气质量监测活动进行了为期25天，在玉林市，中国南部的城市地区，通过采用SPAMS和传统的过滤器为基础的测量，以建立SPAMS的性能。据观察，基于SPAMS的颗粒的化学表征与基于过滤器的分析不一致。基于过滤器分析，硫酸盐是PM2.5中最丰富的组分（23.5%），其次是OC（18.1%），而对于单颗粒物分析（数量浓度），含EC颗粒物对PM2.5的贡献最大（>40%），其次是OC（15.7%）。在通过正矩阵分解的源解析方面，两种方法分别确定了六个源。这两种方法都显示出相对较好的协议，为次要物种，交通和灰尘来源，但是，差异注意到工业，化石燃料和生物质燃烧源。最后，调查的昼夜配置文件和两个特定的排放事件监测在中国新年和交通活动证明了单粒子分析的相对优势，过滤器为基础的方法。总体而言，单颗粒物分析可以提供高时间分辨率的源解析，这有助于政策制定者在空气污染事件中分析和实施应急控制策略。然而，SPAMS执行数量浓度而不是质量浓度的定量，并且仅限于大于200 nm的颗粒，这导致两种方法之间的差异。因此，SPAMS测量不能简单地取代传统的基于过滤器的分析，这需要在选择监控实施时仔细考虑。
Single particle aerosol mass spectrometers (SPAMS) have created significant interest among atmospheric scientists by virtue of their ability to provide real-time size-resolved information on the chemical composition of aerosols. The objective of this study is to evaluate the newly developed single particle analysis technique in terms of chemical characterization and source apportionment of ambient aerosols by comparing it with traditional filter-based methods. In this study, an air quality monitoring campaign was conducted over a period of 25 days at an urban area in Yulin city, southern China, by employing both SPAMS and traditional filter-based measurements to establish the performance of SPAMS. It was observed that the chemical characterization of particles based on SPAMS did not agree well with the filter-based analysis. Based on the filter analysis, sulfate was the most abundant component in PM2.5 (23.5%), followed by OC (18.1%), while for single particle analysis (number concentration), EC-containing particles showed the largest contribution to PM2.5 (>40%), followed by OC (15.7%). In terms of source apportionment via positive matrix factorization, six sources were identified by each of the two approaches. Both the approaches showed relatively good agreements for secondary species, traffic, and dust sources; however, discrepancies were noted for industry, fossil fuel, and biomass burning sources. Finally, investigation of diurnal profiles and two specific emission episodes monitored during the Chinese New Year and traffic activities demonstrated the relative advantage of single particle analysis over filter-based methods. Overall, single particle analysis can provide source apportionment with a high time resolution, which is helpful for policy makers to analyze and implement emergency control strategies during air pollution episodes. However, SPAMS performs quantification of number concentration rather than mass concentration and is limited to particles larger than 200 nm, which leads to discrepancies between the two methods. SPAMS measurements can therefore not simply replace traditional filter-based analyses, which needs to be carefully considered in the selection of the monitoring implementation.
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影响因子：
3
作者：
Wendl MC
通讯作者：
Wendl MC
描述重庆（中国）夏季城市颗粒物的组成和演变
影响因子：
5.5
作者：
Chen Yang;Yang Fumo;Mi Tian;Cao Junji;Shi Guangming;Huang Rujin;Wang Huanbo;Chen Jun;Lou Shengrong;Wang Qiyuan
通讯作者：
Wang Qiyuan
影响因子：
5
作者：
Al-Momani, IF
通讯作者：
Al-Momani, IF
影响因子：
13.6
作者：
Jiun-Homg, Tsai;Kuo-Hsiung, Lin;Hung-Lung, Chiang
通讯作者：
Hung-Lung, Chiang
中国西南部四川盆地特大城市的单颗粒特征、混合状态和演化
影响因子：
5.5
作者：
Zhang Junke;Huang Xiaojuan;Wang Yuesi;Luo Bin;Zhang Jianqiang;Song Hongyi;Zhang Wei;Liu Peichuan;Schafer Klaus;Wang Shigong;Luo Jinqi;Wu Pan
通讯作者：
Wu Pan