Monitoring and source apportionment of trace elements in PM2.5: Implications for local air quality management

Yueyan Li; Miao Chang; Shanshan Ding; Shiwen Wang; Dun Ni; Hongtao Hu

doi:10.1016/j.jenvman.2017.02.059

Monitoring and source apportionment of trace elements in PM_2.5: Implications for local air quality management

J Environ Manage. 2017 Jul 1:196:16-25. doi: 10.1016/j.jenvman.2017.02.059. Epub 2017 Mar 8.

Authors

Yueyan Li¹, Miao Chang², Shanshan Ding³, Shiwen Wang⁴, Dun Ni⁵, Hongtao Hu⁵

Affiliations

¹ Division of Environmental Management & Policy, School of Environment, Tsinghua University, Beijing 100084, China; iSoftStone Information Technology (Group) Co., Ltd, Beijing 100193, China.
² Division of Environmental Management & Policy, School of Environment, Tsinghua University, Beijing 100084, China. Electronic address: changmiao@tsinghua.edu.cn.
³ Division of Environmental Management & Policy, School of Environment, Tsinghua University, Beijing 100084, China.
⁴ Institute of Quantitative & Technical Economics, Chinese Academy of Social Sciences, Beijing 100732, China.
⁵ iSoftStone Information Technology (Group) Co., Ltd, Beijing 100193, China.

PMID: 28284133
DOI: 10.1016/j.jenvman.2017.02.059

Abstract

Fine particulate matter (PM_2.5) samples were collected simultaneously every hour in Beijing between April 2014 and April 2015 at five sites. Thirteen trace elements (TEs) in PM_2.5 were analyzed by online X-ray fluorescence (XRF). The annual average PM_2.5 concentrations ranged from 76.8 to 102.7 μg m^-3. TEs accounted for 5.9%-8.7% of the total PM_2.5 mass with Cl, S, K, and Si as the most dominant elements. Spearman correlation coefficients of PM_2.5 or TE concentrations between the background site and other sites showed that PM_2.5 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_2.5 were significant and provided information on source profiles. The PM_2.5 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_2.5 and TE median concentrations were higher on Saturdays than on weekdays. The diurnal pattern of PM_2.5 and TE median concentrations yielded similar bimodal patterns. Five dominant sources of PM_2.5 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.

Keywords: Air quality management; PMF; Source apportionment; Trace element; XRF.

MeSH terms

Air Pollutants*
Beijing
Environmental Monitoring
Particulate Matter
Trace Elements*

Substances

Air Pollutants
Particulate Matter
Trace Elements