Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation

Shi, Jiacheng; Yang, Yu; Shen, Zhijie; Lin, Yuding; Mei, Nan; Luo, Chengzhong; Wang, Yongmin; Zhang, Cheng; Wang, Dingyong

doi:10.1016/j.jhazmat.2024.135481

Journal of Hazardous Materials

2024

DOI: 10.1016/j.jhazmat.2024.135481

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Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation

Jiacheng Shi,

Yu Yang,

Zhijie Shen

et al.

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Cited by 4 publications

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Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation

Cited by 4 publications

References 67 publications

Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence

Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence

Heavy metals release in lead-zinc tailings: Effects of weathering and acid rain

Identifying spatial drivers of soil heavy metal pollution risk integrating positive matrix factorization, machine learning, and multi-scale geographically weighted regression

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