Habeebullah Turki M, Munir Said, Zeb Jahan, Morsy Essam A
Department of Environmental and Health Research, The Custodian of the Holy Two Mosques Institute for Hajj and Umrah Research, Umm Al Qura University, Makkah 24382, Saudi Arabia.
Faculty of Environment, Institute for Transport Studies, University of Leeds, Leeds LS2 9JT, UK.
Toxics. 2022 Mar 2;10(3):119. doi: 10.3390/toxics10030119.
In this paper, the emission sources of PM10 are characterised by analysing its trace elements (TE) and ions contents. PM10 samples were collected for a year (2019−2020) at five sites and analysed. PM10 speciated data were analysed using graphical visualization, correlation analysis, generalised additive model (GAM), and positive matrix factorization (PMF). Annual average PM10 concentrations (µg/m3) were 304.68 ± 155.56 at Aziziyah, 219.59 ± 87.29 at Misfalah, 173.90 ± 103.08 at Abdeyah, 168.81 ± 82.50 at Askan, and 157.60 ± 80.10 at Sanaiyah in Makkah, which exceeded WHO (15 µg/m3), USEPA (50 µg/m3), and the Saudi Arabia national (80 µg/m3) annual air quality standards. A GAM model was developed using PM10 as a response and ions and TEs as predictors. Among the predictors Mg, Ca, Cr, Al, and Pb were highly significant (p < 0.01), Se, Cl, and NO2 were significant (p < 0.05), and PO4 and SO4 were significant (p < 0.1). The model showed R-squared (adj) 0.85 and deviance explained 88.1%. PMF identified four main emission sources of PM10 in Makkah: (1) Road traffic emissions (explained 51% variance); (2) Industrial emissions and mineral dust (explained 27.5% variance); (3) Restaurant and dwelling emissions (explained 13.6% variance); and (4) Fossil fuel combustion (explained 7.9% variance).
在本文中，通过分析PM10的微量元素（TE）和离子含量来表征其排放源。在五个地点采集了一年（2019 - 2020年）的PM10样本并进行分析。使用图形可视化、相关性分析、广义相加模型（GAM）和正定矩阵因子分解（PMF）对PM10的物种数据进行分析。麦加的阿齐济耶、米斯法拉、阿卜德耶、阿斯坎和萨纳伊亚的PM10年平均浓度（μg/m³）分别为304.68±155.56、219.59±87.29、173.90±103.08、168.81±82.50和157.60±80.10，超过了世界卫生组织（15μg/m³）、美国环境保护局（50μg/m³）和沙特阿拉伯国家（80μg/m³）的年度空气质量标准。以PM10作为响应变量，离子和TE作为预测变量建立了GAM模型。在预测变量中，Mg、Ca、Cr、Al和Pb具有高度显著性（p < 0.01），Se、Cl和NO₂具有显著性（p < 0.05），PO₄和SO₄具有显著性（p < 0.1）。该模型的调整后决定系数（R-squared）为0.85，偏差解释率为88.1%。PMF确定了麦加PM10的四个主要排放源：（1）道路交通排放（解释了51%的方差）；（2）工业排放和矿物粉尘（解释了27.5%的方差）；（3）餐厅和住宅排放（解释了13.6%的方差）；（4）化石燃料燃烧（解释了7.9%的方差）。
