Machine learning-supported determination for site-specific natural background values of soil heavy metals.

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Tác giả: Chengmin Huang, Jian Wu

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: Netherlands : Journal of hazardous materials , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 701046

Heavy metal natural background values play a crucial role in distinguishing anthropogenic sources from natural sources to assess human impacts in polluted areas, thereby accurately formulating environmental policies. However, due to limitations imposed by human activities, research methods, and regional constraints, the determination of heavy metal background values, particularly on site or profile scale, is often challenging, highlighting the urgent need for new methodologies. To establish a comprehensive dataset containing heavy metal concentrations and soil properties, the study systematically collected and screened 82 soil profiles from areas minimally affected by human activities, resulting in a total of 2185 data sets. Using soil depth, pH, organic matter, weathering indices (SAF, BA), Fe
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