Influencing factors and prediction of arsenic concentration in Pteris vittata: A combination of geodetector and empirical models
文献类型：期刊论文
| 作者 | Zeng, Weibin1,2; Wan, Xiaoming1,2; Lei, Mei1,2; Gu, Gaoquan1,2; Chen, Tongbin1,2 |
| 刊名 | ENVIRONMENTAL POLLUTION
 |
| 出版日期 | 2022 |
| 卷号 | 292页码:10 |
| ISSN号 | 0269-7491 |
| 关键词 | Field trials Heavy metal Multivariate linear stepwise regression Phytoextraction Hyperaccumulator |
| DOI | 10.1016/j.envpol.2021.118240 |
| 通讯作者 | Wan, Xiaoming(wanxm.06s@igsnrr.ac.cn) |
| 英文摘要 | Phytoextraction using hyperaccumulator, Pteris vittata, to extract arsenic (As) from soil has been applied to large areas to achieve an As removal rate of 18% per year. However, remarkable difference among different studies and field practices has led to difficulties in the standardization of phytoextraction technology. In this study, data on As concentration in P. vittata and related environmental conditions were collected through literature search. A conceptual framework was proposed to guide the improvement of phytoextraction efficiency in the field. The following influencing factors of As concentration in this hyperaccumulator were identified: total As concentration in soil, soil available As, organic matter in soil, total potassium (K) concentration in soil, and annual rainfall. The geodetection results show that the main factors that affect As concentration in P. vittata include soil organic matter (q = 0.75), soil available As (q = 0.67), total K (q = 0.54), and rainfall (q = 0.42). The predictive models of As concentration in P. vittata were established separately for greenhouse and field conditions through multivariate linear stepwise regression method. Under greenhouse condition, soil available As was the most important influencing factor and could explain 41.4% of As concentration in P. vittata. Two dominant factors were detected in the field: soil available As concentration and average annual rainfall. The combination of these two factors gave better prediction results with R-2 = 0.762. The establishment of the model might help predict phytoextraction efficiency and contribute to technological standardization. The strategies that were used to promote As removal from soil by P. vittata were summarized and analyzed. Intercropping with suitable plants or a combination of different measures (e.g., phosphate fertilizer and water retention) was recommended in practice to increase As concentration in P. vittata. |
| WOS关键词 | MAJOR CONTROLLING FACTORS ; SOIL ; PHYTOREMEDIATION ; HYPERACCUMULATOR ; FERN ; ACCUMULATION ; MECHANISMS ; IMPACT ; RICE ; L. |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| 出版者 | ELSEVIER SCI LTD |
| WOS记录号 | WOS:000711688300002 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/167469]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wan, Xiaoming |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100089, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zeng, Weibin,Wan, Xiaoming,Lei, Mei,et al. Influencing factors and prediction of arsenic concentration in Pteris vittata: A combination of geodetector and empirical models[J]. ENVIRONMENTAL POLLUTION,2022,292:10. |
| APA | Zeng, Weibin,Wan, Xiaoming,Lei, Mei,Gu, Gaoquan,&Chen, Tongbin.(2022).Influencing factors and prediction of arsenic concentration in Pteris vittata: A combination of geodetector and empirical models.ENVIRONMENTAL POLLUTION,292,10. |
| MLA | Zeng, Weibin,et al."Influencing factors and prediction of arsenic concentration in Pteris vittata: A combination of geodetector and empirical models".ENVIRONMENTAL POLLUTION 292(2022):10. |
入库方式： OAI收割
来源：地理科学与资源研究所
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