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Quantitative heterogeneous source apportionment of toxic metals through a hybrid method in spatial random fields

文献类型： 外文期刊

作者： Fei, Xufeng 1 ; Lou, Zhaohan 1 ; Sheng, Meiling 1 ; Lv, Xiaonan 1 ; Ren, Zhouqiao 1 ; Xiao, Rui 3 ;

作者机构： 1.Zhejiang Acad Agr Sci, Hangzhou, Peoples R China

2.Minist Agr & Rural Affairs, Key Lab Informat Traceabil Agr Prod, Beijing, Peoples R China

3.Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan, Peoples R China

关键词： Toxic metal; Source analysis; Bayesian maximum entropy; Positive matrix factorization; Integrative predictability criterion

期刊名称：JOURNAL OF HAZARDOUS MATERIALS （ 影响因子：13.6； 五年影响因子：12.7 ）

ISSN： 0304-3894

年卷期： 2024 年 465 卷

页码：

收录情况： SCI

摘要： Toxic metals in soils pose hazards to food security and human health. Accurate source apportionment provides foundation for pollution prevention. In this study, a novel hybrid method that combines positive matrix factorization, Bayesian maximum entropy and integrative predictability criterion is proposed to provide a new perspective for exploring the heterogeneity of pollution sources in spatial random fields. The results suggest that Cd, As and Cu are the predominant pollutants, with exceedance rates of 27%, 12% and 11%, respectively. The new method demonstrates superiority in predicting toxic metals when combined major and all sources as auxiliary information., with the improvements of 44% and 46%, respectively, Although the major sources identified with the hybrid method are the primary contributors to the accumulation of toxic metals (e.g. coal combustion for Hg, traffic emission for Pb and Zn, industrial activities for As, agricultural activities for Cd and Cu and natural sources for Cr and Ni), the impact of nonmajor sources on toxic metal sin specific regions should not be ignored (e.g. industrial activities on Ni, Pb and Zn in the north and natural sources on Cd, Cu, As, Pb and Zn in the south). For better pollution control, specific local sources should be considered.

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