A new method for spatial three-dimensional prediction of soil heavy metals contamination
文献类型：期刊论文
| 作者 | Shen, Fengbei1,4; Xu, Chengdong1,4; Wang, Jinfeng1,4; Hu, Maogui4; Guo, Guanlin3; Fang, Tingting3; Zhu, Xingbao3; Cao, Hongying2; Tao, Huan2; Hou, Yixuan2 |
| 刊名 | CATENA
 |
| 出版日期 | 2024-02-01 |
| 卷号 | 235页码:12 |
| ISSN号 | 0341-8162 |
| 关键词 | Spatial pattern Spatial stratified heterogeneity Geodetector Statistical model Estimation uncertainty |
| DOI | 10.1016/j.catena.2023.107658 |
| 通讯作者 | Xu, Chengdong(xucd@lreis.ac.cn) ; Guo, Guanlin(guogl@craes.org.cn) |
| 英文摘要 | Soil heavy metals contamination are highly correlated to human health. It is crucial to employ three-dimensional heavy metals modeling and mapping for site assessment and remediation. However, current methods are limited due to the poor consideration of both spatial auto-correlation and stratified heterogeneity concurrently. The present study established a novel methodology 3D-MSN to model soil metals, encompassing autocorrelation and heterogeneity. In addition to considering in-strata correlation and between-strata heterogeneity like traditional methods, 3D-MSN accounted for the between-strata correlation to enhance the accuracy of prediction. A former agrochemical plant was used as a case to validate the superiority of the 3D-MSN method over traditional approaches. The accuracy of different methods was evaluated using mean absolute error (MAE) and root-mean-square error (RMSE), through leave-one-out cross-validation. Results demonstrated significant spatial autocorrelation and stratified heterogeneity for the presence of As and Cu in soil. 3D-MSN exhibited the lowest MAEs (2.424 mg/kg for As, 4.863 mg/kg for Cu) and RMSEs (3.439 mg/kg, 7.279 mg/kg) compared to 3D-ordinary kriging (MAEs (2.949 mg/kg, 6.482 mg/kg) and RMSEs (3.890 mg/kg, 8.364 mg/kg)) and 3D-stratified kriging (MAEs (2.571 mg/kg,5.184 mg/kg) and RMSEs (3.570 mg/kg, 7.412 mg/kg)). 3D-MSN also accounted for estimation uncertainties. Considering autocorrelation and stratified heterogeneity, 3D-MSN presented superior performance. This research contributes to advancing the field of three-dimensional heavy metal modeling and provides valuable insights for site assessment and remediation efforts. |
| WOS关键词 | SIZE FRACTIONS ; VARIABILITY ; CADMIUM ; RISK ; REMEDIATION ; POLLUTION ; PATTERN ; SITE |
| 资助项目 | National Key R&D Program of China[2020YFC1807404] ; National Natural Science Foundation of China[41971357] ; National Natural Science Foundation of China[41930651] ; National Natural Science Foundation of China[42071375] ; National Natural Science Foundation of China[42130713] ; National Natural Science Foundation of China[42225707] ; Innovation Project of LREIS[O88RA205YA] |
| WOS研究方向 | Geology ; Agriculture ; Water Resources |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:001112285500001 |
| 资助机构 | National Key R&D Program of China ; National Natural Science Foundation of China ; Innovation Project of LREIS |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200492]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Xu, Chengdong; Guo, Guanlin |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing Key Lab Environm Damage Assessment & Remed, Beijing 100101, Peoples R China 3.Minist Ecol & Environm, Tech Ctr Soil Agr & Rural Ecol & Environm, Beijing 100012, Peoples R China 4.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shen, Fengbei,Xu, Chengdong,Wang, Jinfeng,et al. A new method for spatial three-dimensional prediction of soil heavy metals contamination[J]. CATENA,2024,235:12. |
| APA | Shen, Fengbei.,Xu, Chengdong.,Wang, Jinfeng.,Hu, Maogui.,Guo, Guanlin.,...&Hou, Yixuan.(2024).A new method for spatial three-dimensional prediction of soil heavy metals contamination.CATENA,235,12. |
| MLA | Shen, Fengbei,et al."A new method for spatial three-dimensional prediction of soil heavy metals contamination".CATENA 235(2024):12. |
入库方式： OAI收割
来源：地理科学与资源研究所
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