Stojić A, Stojić S Stanišić, Reljin I, Čabarkapa M, Šoštarić A, Perišić M, Mijić Z
Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080, Belgrade, Serbia.
Faculty of Physical Chemistry, University of Belgrade, Studentski Trg 12-16, 11000, Belgrade, Serbia.
Environ Sci Pollut Res Int. 2016 Jun;23(11):10722-10732. doi: 10.1007/s11356-016-6266-4. Epub 2016 Feb 18.
In this study, we investigated the impact of potential emission sources and transport pathways on annual and seasonal PM10 loadings in an urban area of Belgrade (Serbia). The analyzed dataset comprised PM10 mass concentrations for the period 2003-2015, as well as their chemical composition (organic/elemental carbon, benzo[a]pyrene, As, Cd, Cr, Mn, Ni, Pb, Cl(-), Na(+), Mg(2+), Ca(2+), K(+), NO3 (-), SO4 (2-), and NH4 (+)), meteorological parameters, and concentrations of inorganic gaseous pollutants and soot for the period 2011-2015. The combination of different methods, such as source apportionment (Unmix), ensemble learning method (random forest), and multifractal and inverse multifractal analysis, was utilized in order to obtain a detailed description of the PM10 origin and spatio-temporal distribution and to determine their relationship with other pollutants and meteorological parameters. The contribution of long-range and regional transport was estimated by means of trajectory sector analysis, whereas the hybrid receptor models were applied to identify potential areas of concern.
在本研究中,我们调查了潜在排放源和传输路径对塞尔维亚贝尔格莱德市区年度和季节性PM10负荷的影响。分析数据集包括2003 - 2015年期间的PM10质量浓度及其化学成分(有机/元素碳、苯并[a]芘、砷、镉、铬、锰、镍、铅、氯离子、钠离子、镁离子、钙离子、钾离子、硝酸根离子、硫酸根离子和铵根离子)、气象参数,以及2011 - 2015年期间无机气态污染物和烟尘的浓度。为了详细描述PM10的来源和时空分布,并确定它们与其他污染物和气象参数之间的关系,我们采用了不同方法的组合,如源解析(Unmix)、集成学习方法(随机森林)以及多重分形和反多重分形分析。通过轨迹扇区分析估计了长距离和区域传输的贡献,而应用混合受体模型来识别潜在的关注区域。