Heavy metals in agricultural soil receive much attention because they are easily absorbed by crop into the ecosystem. Managing the discharge of heavy metals from the source is an effective way to prevent and control heavy metals pollution. Grouped principal component analysis (GPCA) and Positive Matrix Factorization (PMF) receptor models were utilized in this study to conduct source apportionment, and the former was optimal because of the accuracy of predicting. Based on the source contribution by GPCA/APCS, heavy metals were evaluated by fuzzy synthetic evaluation model and health risk assessment model. The results of source apportionment showed that heavy metals in Zhangye agricultural soil were mainly affected by steel industry, traffic, agrochemicals, manures, mining activities, leather industry and metal processing industry source. Fuzzy synthetic evaluation showed that the pollution levels of Chromium (Cr) derived by leather industry and metal processing industry and Nickel (Ni) derived by steel industry and traffic source were higher. Health risk assessment revealed that the non-carcinogenic and carcinogenic risks of Cr derived by leather industry and metal processing industry and Lead (Pb) derived by steel industry and traffic source were higher.
Keywords: Agricultural soil heavy metals; Fuzzy synthetic evaluation; GPCA/APCS; Health risk assessment.
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