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农田土壤中复合污染物的空间相互作用及风险分区:来自中国赫章县重金属和多环芳烃的研究。

Spatial interaction and risk zoning of compound pollutants in farmland soils: Insights from heavy metals and polycyclic aromatic hydrocarbons in Hezhang County, China.

机构信息

College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.

College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Ecotoxicol Environ Saf. 2024 Oct 15;285:116965. doi: 10.1016/j.ecoenv.2024.116965. Epub 2024 Sep 30.

Abstract

The accurate identification and assessment of comprehensive risks associated with compound pollution in agricultural ecosystems remain significant challenges due to the complexity of pollution sources, soil heterogeneity, and spatial variability. In this study, bivariate local indicators of spatial association (LISA) were applied to analyze the spatial interaction between heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) in farmland soils in Hezhang County. The results revealed distinct clusters with elevated concentrations of both HMs and PAHs, predominantly in areas affected by long-standing lead-zinc mining and smelting activities. Positive matrix factorization (PMF) was utilized to identify mining and smelting activities, and associated coal consumption as common sources of both pollutants, contributing 53 % and 28 %, respectively. Ecological health risk assessment results indicated that the combined pollution in this area has led to particularly severe ecological and cancer risks, with the pollution coefficient (Pc) exceeding 3.0, and risk values for both adults and children surpassing the threshold of 10. Through the integration of advanced bivariate LISA mapping and thorough risk assessment, this study precisely delineated ecological risk zones (33.1 %) and more refined health risk zones (40.1 %) associated with combined pollution. The southwest of Hezhang was identified as a critical hotspot for combined pollution risks, primarily due to intensive mining and smelting activities in the region. Overall, this study underscores the utility of bivariate LISA as a robust approach for delineating spatial clustering patterns caused by combined pollutants. It provides crucial insights for identifying regions with heightened human health and ecological risks in rural settings.

摘要

由于污染源复杂、土壤异质性和空间变异性等原因,准确识别和评估农业生态系统中与复合污染相关的综合风险仍然是一个重大挑战。本研究应用双变量空间自相关局部指标(LISA)分析了赫章县农田土壤中重金属(HMs)和多环芳烃(PAHs)之间的空间相互作用。结果表明,存在高浓度 HMs 和 PAHs 的明显聚集区,主要分布在受长期铅锌矿开采和冶炼活动影响的地区。正矩阵因子分解(PMF)用于识别采矿和冶炼活动以及相关的煤炭消耗是两种污染物的共同来源,分别贡献了 53%和 28%。生态健康风险评估结果表明,该地区的综合污染导致了特别严重的生态和癌症风险,污染系数(Pc)超过 3.0,成人和儿童的风险值均超过 10 的阈值。通过先进的双变量 LISA 映射和彻底的风险评估相结合,本研究精确划定了与复合污染相关的生态风险区(33.1%)和更精细的健康风险区(40.1%)。赫章县西南部被确定为复合污染风险的关键热点地区,主要是由于该地区密集的采矿和冶炼活动。总的来说,本研究强调了双变量 LISA 作为一种强大方法来描绘由复合污染物引起的空间聚类模式的效用。它为识别农村地区人类健康和生态风险较高的地区提供了重要的见解。

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