College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China.
College of Geography and Environment, Shandong Normal University, Jinan 250358, PR China.
Sci Total Environ. 2023 Jun 20;878:163211. doi: 10.1016/j.scitotenv.2023.163211. Epub 2023 Mar 31.
Contamination and source identifications of metals in urban road dust are critical for remediation and health protection. Receptor models are commonly used for metal source identification, whereas the results are usually subjective and not verified by other indicators. Here we present and discuss a comprehensive approach to study metal contamination and sources in urban road dust (Jinan) in spring and winter by integrating the enrichment factor (EF), receptor models (positive matrix factorization (PMF) and factor analysis with nonnegative constraints (FA-NNC)), local Moran's index, traffic factors and Pb isotopes. Cadmium, Cr, Cu, Pb, Sb, Sn and Zn were the main contaminants, with mean EFs of 2.0-7.1. The EFs were 1.0-1.6 times higher in winter than in spring but exhibited similar spatial trends. Chromium contamination hotspots occurred in the northern area, with other metal contamination hotspots in the central, southeastern and eastern areas. The FA-NNC results indicated Cr contamination primarily resulting from industrial sources and other metal contamination primarily originating from traffic emissions during the two seasons. Coal burning emissions also contributed to Cd, Pb and Zn contamination in winter. FA-NNC model-identified metal sources were verified via traffic factors, atmospheric monitoring and Pb isotopes. The PMF model failed to differentiate Cr contamination from other detrital metals and the above anthropogenic sources, largely due to the model grouping metals by emphasizing hotspots. Considering the FA-NNC results, industrial and traffic sources accounted for 28.5 % (23.3 %) and 44.7 % (28.4 %), respectively, of the metal concentrations in spring (winter), and coal burning emissions contributed 34.3 % in winter. Industrial emissions primarily contributed to the health risks of metals due to the high Cr loading factor, but traffic emissions dominated metal contamination. Through Monte Carlo simulations, Cr had 4.8 % and 0.4 % possibilities posing noncarcinogenic and 18.8 % and 8.2 % possibilities posing carcinogenic risks for children in spring and winter, respectively.
城市道路灰尘中金属的污染和来源识别对于修复和保护健康至关重要。受体模型通常用于金属源识别，但其结果通常是主观的，并且没有其他指标验证。在这里，我们提出并讨论了一种综合方法，通过整合富集因子（EF）、受体模型（正矩阵因子化（PMF）和非负约束因子分析（FA-NNC））、局部 Moran 指数、交通因素和 Pb 同位素，研究城市道路灰尘（济南）在春季和冬季的金属污染和来源。镉、铬、铜、铅、锑、锡和锌是主要污染物，平均 EF 为 2.0-7.1。冬季的 EF 比春季高 1.0-1.6 倍，但表现出相似的空间趋势。铬污染热点出现在北部地区，其他金属污染热点出现在中部、东南部和东部地区。FA-NNC 结果表明，两个季节铬污染主要来自工业源，其他金属污染主要来自交通排放。燃煤排放也导致冬季镉、铅和锌的污染。FA-NNC 模型识别的金属源通过交通因素、大气监测和 Pb 同位素得到验证。PMF 模型未能区分铬污染与其他碎屑金属和上述人为源，主要是因为该模型通过强调热点来分组金属。考虑到 FA-NNC 的结果，工业和交通源分别占春季（冬季）金属浓度的 28.5%（28.4%）和 44.7%（44.7%），冬季燃煤排放贡献 34.3%。由于高 Cr 负载因子，工业排放主要导致金属的健康风险，但交通排放主导了金属污染。通过蒙特卡罗模拟，铬在春季和冬季分别有 4.8%和 0.4%的可能性对儿童产生非致癌风险，有 18.8%和 8.2%的可能性对儿童产生致癌风险。
