Soil Heavy Metals for Sustainable Risk Management: A Systematic Review and a Context-Aware Method Selection Framework
文献类型：期刊论文
| 作者 | Yang, Leqi1,2,3; Yue, Tianxiang2; Ma, Maohua1,3 |
| 刊名 | SUSTAINABILITY
 |
| 出版日期 | 2026-02-12 |
| 卷号 | 18期号:4页码:1893 |
| 关键词 | soil heavy metals spatial interpolation sustainable land management precision environmental monitoring method selection context diagnosis decision support tool uncertainty geostatistics machine learning |
| DOI | 10.3390/su18041893 |
| 产权排序 | 3 |
| 文献子类 | Review |
| 英文摘要 | Sustainable land use requires precise monitoring of soil pollution, yet accurately predicting the spatial distribution of heavy metals often relies on post hoc accuracy comparisons with limited a priori diagnosis. To address the challenge of cost effective environmental monitoring, we conducted a PRISMA guided systematic review (2000-2024) and synthesized 135 studies to develop a mechanism-informed, context aware method selection framework. Evidence revealed three regularities: (i) element-driver coupling is structured (Pb/Cd/Zn predominantly anthropogenic; Cr/Ni geogenic; As/Hg mixed), with dominant influence scales from local to regional; (ii) model performance hinges on alignment between algorithmic assumptions, and context hybrid machine learning models integrating multi-source covariates tend to excel under strong, non-stationary anthropogenic heterogeneity, whereas kriging variants are more robust when geogenic continuity holds; and (iii) applicability is jointly constrained by environmental context, data foundations, and management objectives. Building on these insights, we propose a three-step decision workflow-goal definition, contextual diagnosis, and method matching. This framework serves as a decision support tool that shifts selection from trial and error to a priori alignment, optimizing resource allocation and enhancing the reliability of pollution assessments for sustainable soil remediation and policymaking. |
| URL标识 | 查看原文 |
| WOS关键词 | SPATIAL-DISTRIBUTION ; SURFACE SOIL ; URBAN ; INTERPOLATION ; POLLUTION ; GIS ; IDENTIFICATION ; GEOSTATISTICS ; CONTAMINATION ; IMPROVEMENT |
| WOS研究方向 | Science & Technology - Other Topics ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001701285500001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/221344]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Yue, Tianxiang |
| 作者单位 | 1.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China; 2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Chongqing Sch, Chongqing 400714, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Yang, Leqi,Yue, Tianxiang,Ma, Maohua. Soil Heavy Metals for Sustainable Risk Management: A Systematic Review and a Context-Aware Method Selection Framework[J]. SUSTAINABILITY,2026,18(4):1893. |
| APA | Yang, Leqi,Yue, Tianxiang,&Ma, Maohua.(2026).Soil Heavy Metals for Sustainable Risk Management: A Systematic Review and a Context-Aware Method Selection Framework.SUSTAINABILITY,18(4),1893. |
| MLA | Yang, Leqi,et al."Soil Heavy Metals for Sustainable Risk Management: A Systematic Review and a Context-Aware Method Selection Framework".SUSTAINABILITY 18.4(2026):1893. |
入库方式： OAI收割
来源：地理科学与资源研究所
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