Distribution patterns and characterization of outdoor fine and coarse particles

Developmental Biology

Na Lv⁴  Wan-li Ma³  Wei-wei Song³  Li-yan Liu³  Mohammed A.E.M. Ibrahim¹  Mei-yun Qi⁴  Mohammed O.A. Mohammed²  Feng-yan Wang⁴  Yi-Fan Li³  Ahmed A. Elzaki¹ 

[1] Faculty of Public and Environmental Health, University of Khartoum, Khartoum 205, Sudan$$;International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), State Key Laboratory of Urban Water Resource and Environment, School of Municipal and Environmental Engineering, Harbin Institute of Technology, Harbin 150090, China$$Faculty of Public and Environmental Health, University of Khartoum, Khartoum 205, Sudan$$;International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), State Key Laboratory of Urban Water Resource and Environment, School of Municipal and Environmental Engineering, Harbin Institute of Technology, Harbin 150090, China$$;Harbin Scientific Research Institute of Environmental Protection, Harbin 150076, China$$

关键词: Discriminant analysis;    Positive matrix factorization;    Hierarchical clustering;    Severe cold;    PM2.5;    PM10;   

DOI  :  10.1016/j.apr.2016.05.001

学科分类：农业科学（综合）

来源: Dokuz Eylul Universitesi * Department of Environmental Engineering

【 摘 要 】

Simultaneous measurements of fine (PM_2.5) and coarse (PM₁₀) particles have been performed during three sampling period: summertime, early winter before the heating period, and during the winter heating. The sampling was done at an urban site, Harbin City, China, to apportion pollution sources and to investigate the impacts of weather parameters and emission sources on distribution patterns of PM_2.5 and PM₁₀ and their chemical compositions. Two chemometric techniques, hierarchical clustering analysis (HCA) and discriminant analysis (DA), and a receptor model (PMF5) were applied. The average mass concentrations of fine and coarse particles during the whole study period (i.e. annual averages), were 82.4 μg/m³ and 120.1 μg/m³, with relative humidity and wind speed being the main factors influencing distribution patterns of PM_2.5 and PM_10, while sum of major ions (NO₃⁻${{\text{NO}}_3}^{-}$, NH₄⁺${{\text{NH}}_4}^{+}$, SO₄²⁻${{\text{SO}}_4}^{2-}$), and organic carbon (OC) were the greater contributor to total mass concentrations. According to DA, the distribution patterns of PM_2.5 and PM₁₀ during the winter heating period were distinct but overlapping in summer and early winter before heating, implying that, PM_2.5 and PM₁₀ were originated from different sources during the winter heating period but from similar sources during the other two sampling periods. This claim was further supported by PMF results. Canonical discriminant function coefficients of DA have shown species such as OC, EC, SO₄²⁻${{\text{SO}}_4}^{2-}$, NO₃⁻${{\text{NO}}_3}^{-}$, Cl⁻, Ti, Sr, Ca²⁺, Ni, and Ba to be good predictors/discriminants responsible for the differences between the three sampling periods. HCA visualized the interrelations among the source markers, while the PMF5 modeling confirmed HCA findings.

【 授权许可】

Unknown   

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