Institute of Food Science and Technology, Chinese Academy of Agriculture Sciences/ Key Laboratory of Agro-products Quality and Safety Control in Storage and Transport Process, Ministry of Agriculture, Beijing 100193, PR China.
Institute of Food Science and Technology, Chinese Academy of Agriculture Sciences/ Key Laboratory of Agro-products Quality and Safety Control in Storage and Transport Process, Ministry of Agriculture, Beijing 100193, PR China.
Ecotoxicol Environ Saf. 2018 Sep 15;159:354-362. doi: 10.1016/j.ecoenv.2018.04.072. Epub 2018 May 21.
Characterizing the distribution and defining potential sources of arsenic and heavy metals are the basic preconditions for reducing the contamination of heavy metals and metalloids. 71 topsoil samples and 61 subsoil samples were collected by grid method to measure the concentration of cadmium (Cd), arsenic (As), lead (Pb), copper (Cu), zinc (Zn), nickel (Ni) and chromium (Cr). Principle components analysis (PCA), GIS-based geo-statistical methods and Positive Matrix Factorization (PMF) were applied. The results showed that the mean concentrations were 9.59 mg kg, 51.28 mg kg, 202.07 mg kg, 81.32 mg kg and 771.22 mg kg for Cd, As, Pb, Cu and Zn, respectively, higher than the guideline values of Chinese Environmental Quality Standard for Soils; while the concentrations of Ni and Cr were very close to recommended value (50 mg kg, 200 mg kg), and some site were higher than guideline values. The soil was polluted by As and heavy metals in different degree, which had harmful impact on human health. The results from principle components analysis methods extracted three components, namely industrial sources (Cd, Zn and Pb), agricultural sources (As and Cu) and nature sources (Cr and Ni). GIS-based geo-statistical combined with local conditions further apportioned the sources of these trace elements. To better identify pollution sources of As and heavy metals in soil, the PMF was applied. The results of PMF demonstrated that the enrichment of Zn, Cd and Pb were attributed to industrial activities and their contribution was 24.9%; As was closely related to agricultural activities and its contribution was 19.1%; Cr, a part of Cu and Ni were related to subsoil and their contribution was 30.1%; Cu and Pb came from industry and traffic emission and their contribution was 25.9%.
表征砷和重金属的分布并确定其潜在来源是减少重金属和类金属污染的基本前提。采用网格法采集了 71 个表层土样和 61 个底土样，以测定镉（Cd）、砷（As）、铅（Pb）、铜（Cu）、锌（Zn）、镍（Ni）和铬（Cr）的浓度。应用主成分分析（PCA）、基于 GIS 的地统计方法和正矩阵因子分解（PMF）。结果表明，Cd、As、Pb、Cu 和 Zn 的平均浓度分别为 9.59mg/kg、51.28mg/kg、202.07mg/kg、81.32mg/kg和 771.22mg/kg，高于中国土壤环境质量标准的指导值；而 Ni 和 Cr 的浓度非常接近推荐值（50mg/kg、200mg/kg），部分地点高于指导值。土壤受到不同程度的 As 和重金属污染，对人体健康有危害。主成分分析方法的结果提取了三个成分，即工业源（Cd、Zn 和 Pb）、农业源（As 和 Cu）和自然源（Cr 和 Ni）。基于 GIS 的地统计与当地条件相结合，进一步分配了这些微量元素的来源。为了更好地识别土壤中 As 和重金属的污染源，应用了 PMF。PMF 的结果表明，Zn、Cd 和 Pb 的富集归因于工业活动，其贡献率为 24.9%；As 与农业活动密切相关，其贡献率为 19.1%；Cr、部分 Cu 和 Ni 与底土有关，其贡献率为 30.1%；Cu 和 Pb 来自工业和交通排放，其贡献率为 25.9%。
