دورية أكاديمية

An Uncertainty Assessment of Human Health Risk for Toxic Trace Elements Using a Sequential Indicator Simulation in Farmland Soils

التفاصيل البيبلوغرافية
العنوان: An Uncertainty Assessment of Human Health Risk for Toxic Trace Elements Using a Sequential Indicator Simulation in Farmland Soils
المؤلفون: Hao Yang, Yingqiang Song, A-Xing Zhu, Yueming Hu, Bo Li
المصدر: MDPI, Sustainability. 12(9):1-17
سنة النشر: 2020
الوصف: Toxic trace elements in farmland soils are potential threats to human health. In this study, we collected soil samples from the farmlands of southern Guangzhou. We used a sequential indicator simulation (SIS) to deal with the problem of skewed distribution in the sample data. We assessed the human health risks, as well as the uncertainties, of five toxic trace elements: arsenic (As), cadmium (Cd), chromium (Cr), lead (Pb), and mercury (Hg). The results were as follows: (1) The risk indices of two trace elements (Cd and Hg) were less than the standard threshold, which means that there was no human health risk due to Cd and Hg in the study area. However, the maximum risk indices of As, Cr, and Pb exceeded the standard threshold. In particular, the maximum risk index of Pb was twice the standard threshold; (2) The risk probabilities of As and Cr were less than 25% in most areas, and only a few parcels of farmland have a 100% risk probability. The risk map of Pb was used to identify contiguous areas of high-risk probability (i.e., 75%–100%) in the center of the study area. (3) E-type estimation by the SIS method overestimates the risk when the number of samples with concentrations above the threshold have a large proportion of total samples. Our conclusions are as follows: (1) The simulation results show that areas with high-risk indices were concentrated in the Panyu District, which is close to the Pearl River and the core urban area of Guangzhou; (2) Except for Pb, these trace elements are not likely to pose health risks in southern Guangzhou; (3) This study considers the risk probability found with the SIS method to be more reliable for visualizing regional risk.
نوع الوثيقة: redif-article
اللغة: English
الإتاحة: https://ideas.repec.org/a/gam/jsusta/v12y2020i9p3852-d355553.html
رقم الأكسشن: edsrep.a.gam.jsusta.v12y2020i9p3852.d355553
قاعدة البيانات: RePEc