Li Yueyan, Chang Miao, Ding Shanshan, Wang Shiwen, Ni Dun, Hu Hongtao
Division of Environmental Management & Policy, School of Environment, Tsinghua University, Beijing 100084, China; iSoftStone Information Technology (Group) Co., Ltd, Beijing 100193, China.
Division of Environmental Management & Policy, School of Environment, Tsinghua University, Beijing 100084, China.
J Environ Manage. 2017 Jul 1;196:16-25. doi: 10.1016/j.jenvman.2017.02.059. Epub 2017 Mar 8.
Fine particulate matter (PM) samples were collected simultaneously every hour in Beijing between April 2014 and April 2015 at five sites. Thirteen trace elements (TEs) in PM were analyzed by online X-ray fluorescence (XRF). The annual average PM concentrations ranged from 76.8 to 102.7 μg m. TEs accounted for 5.9%-8.7% of the total PM mass with Cl, S, K, and Si as the most dominant elements. Spearman correlation coefficients of PM or TE concentrations between the background site and other sites showed that PM and some element loadings were affected by regional and local sources, whereas Cr, Si, and Ni were attributed to substantial local emissions. Temporal variations of TEs in PM were significant and provided information on source profiles. The PM concentrations were highest in autumn and lowest in summer. Mn and Cr showed similar variation. Fe, Ca, Si, and Ti tended to show higher concentrations in spring, whereas concentrations of S peaked in summer. Concentrations of Cl, K, Pb, Zn, Cu, and Ni peaked in winter. PM and TE median concentrations were higher on Saturdays than on weekdays. The diurnal pattern of PM and TE median concentrations yielded similar bimodal patterns. Five dominant sources of PM mass were identified via positive matrix factorization (PMF). These sources included the regional and local secondary aerosols, traffic, coal burning, soil dust, and metal processing. Air quality management strategies, including regional environmental coordination and collaboration, reduction in secondary aerosol precursors, restrictive vehicle emission standards, promotion of public transport, and adoption of clean energy, should be strictly implemented. High time-resolution measurements of TEs provided detailed source profiles, which can greatly improve precision in interpreting source apportionment calculations; the PMF analysis of online XRF data is a powerful tool for local air quality management.
2014年4月至2015年4月期间，在北京的五个地点每小时同时采集细颗粒物（PM）样本。通过在线X射线荧光（XRF）分析PM中的13种微量元素（TEs）。PM的年平均浓度范围为76.8至102.7μg/m。TEs占PM总质量的5.9%-8.7%，其中Cl、S、K和Si是最主要的元素。背景站点与其他站点之间PM或TE浓度的Spearman相关系数表明，PM和一些元素负荷受区域和本地源的影响，而Cr、Si和Ni则主要归因于本地大量排放。PM中TEs的时间变化显著，并提供了源特征信息。PM浓度秋季最高，夏季最低。Mn和Cr表现出相似的变化。Fe、Ca、Si和Ti在春季往往浓度较高，而S的浓度在夏季达到峰值。Cl、K、Pb、Zn、Cu和Ni的浓度在冬季达到峰值。PM和TE的中位数浓度在周六高于工作日。PM和TE中位数浓度的日变化模式呈现出相似的双峰模式。通过正矩阵分解（PMF）确定了PM质量的五个主要来源。这些来源包括区域和本地二次气溶胶、交通、燃煤、土壤粉尘和金属加工。应严格实施空气质量管理策略，包括区域环境协调与合作、减少二次气溶胶前体、严格的车辆排放标准、推广公共交通以及采用清洁能源。TEs的高时间分辨率测量提供了详细的源特征，这可以大大提高解释源分配计算的精度；在线XRF数据的PMF分析是本地空气质量管理的有力工具。
