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新乡市大气PM2.5载带金属元素季节分布、来源特征与健康风险

本站小编 Free考研考试/2021-12-31

中文关键词PM2.5金属元素季节变化分源类健康风险工业城市 英文关键词PM2.5metal elementsseasonal variationssource-specific health risktypical industrial city
作者单位E-mail
刘桓嘉河南师范大学环境学院, 黄淮水环境污染与防治教育部重点实验室, 河南省环境污染控制重点实验室, 新乡 453007liuhuanjia@htu.edu.cn
贾梦珂河南师范大学环境学院, 黄淮水环境污染与防治教育部重点实验室, 河南省环境污染控制重点实验室, 新乡 453007
刘永丽河南师范大学环境学院, 黄淮水环境污染与防治教育部重点实验室, 河南省环境污染控制重点实验室, 新乡 453007
赵艺洁河南师范大学环境学院, 黄淮水环境污染与防治教育部重点实验室, 河南省环境污染控制重点实验室, 新乡 453007
郑爱华北京师范大学分析测试中心, 北京 100875
刘恒志河南师范大学环境学院, 黄淮水环境污染与防治教育部重点实验室, 河南省环境污染控制重点实验室, 新乡 453007
徐肃阳河南师范大学环境学院, 黄淮水环境污染与防治教育部重点实验室, 河南省环境污染控制重点实验室, 新乡 453007
肖晴晴河南师范大学环境学院, 黄淮水环境污染与防治教育部重点实验室, 河南省环境污染控制重点实验室, 新乡 453007
苏晓燕河南师范大学环境学院, 黄淮水环境污染与防治教育部重点实验室, 河南省环境污染控制重点实验室, 新乡 453007
任言河南师范大学环境学院, 黄淮水环境污染与防治教育部重点实验室, 河南省环境污染控制重点实验室, 新乡 453007
中文摘要 为探究典型工业城市大气PM2.5载带重金属的季节分布、来源及健康风险,于2019~2020年分季节采集PM2.5有效样品112个,利用电感耦合等离子体发射光谱法(ICP-AES)测定了19种元素含量.结果表明,PM2.5及其载带重金属元素的年均浓度分别为(66.25±35.73)μg·m-3和(1.32±0.84)μg·m-3.PM2.5及其元素组分夏季浓度最低,Al、Ca、Fe、Mg和Ti等元素春季浓度最高,其它元素则是冬季浓度最高.利用PMF-PSCF模型共解析出5类排放源,分别为Ni和Co相关排放源(5.8%)、机动车源(13.7%)、Cd相关排放源(5.1%)、燃烧源(18.2%)和扬尘源(57.3%).风险评价结果表明,每一类排放源的危害指数(HI)值均小于1,不存在明显的非致癌风险;致癌风险均处于10-6~10-4范围内,具有一定的致癌风险.与其它排放源相比,燃烧源的致癌风险(8.74×10-6,36.9%)和非致癌风险(0.60,25.6%)最大,建议优先对燃烧源进行治理以降低区域人群暴露风险. 英文摘要 This study analyzed the seasonal variation, sources, and source-specific health risks of PM2.5-bound metals in Xinxiang city, Henan province. A total of 112 daily PM2.5 samples were collected over four consecutive seasons during 2019-2020. In total, 19 elements were identified using inductively coupled plasma atomic emission spectroscopy (ICP-AES). The annual concentrations of PM2.5 and 11 heavy metals were calculated to be (66.25±35.73) μg·m-3 and (1.32±0.84) μg·m-3, respectively. Strong seasonal variations were observed in PM2.5 concentrations and the concentrations of associated metal elements, with the lowest concentrations all occurring in summer. The highest concentrations of dust-related elements (e.g., Al, Ca, Fe, Mg,and Ti) were recorded in spring, differing significantly from other elements, which all exhibited the highest mass concentrations in winter. The results apportioned from positive matrix factorization (PMF) and potential source contribution function (PSCF) models showed that the major sources of PM2.5-bound elements were Ni-and Co-related emissions (5.8%), motor vehicles (13.7%), Cd-related emissions(5.1%), combustion emissions (18.2%), and dust (57.3%). Health risk models showed that there were no obvious non-carcinogenic risks associated with these metals, because their hazard quotient (HQ) values were all below 1. Lifetime carcinogenic risks of the five apportioned sources were all higher than the acceptable level (1×10-6). Of these five sources, combustion emissions were the largest contributors to cancer risk (8.74×10-6, 36.9%) and non-cancer risk (0.60, 25.6%). This study suggests that control strategies to mitigate exposure risk in Xinxiang should emphasize reducing the sources of combustion emissions.

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