MGDA-assisted plant washing agent for improving the removal of Cd and Cu from farmland soils
文献类型：期刊论文
| 作者 | Wang, Yi1,2; Tu, Chen2 ; Li, Yuan3; Yang, Shuai2; Liu, Ying2; Zhu, Xia2; Si, Shao-cheng3; Luo, Run-lai4; Pan, Xiang-liang1; Luo, Yong-ming2
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| 刊名 | ENVIRONMENTAL POLLUTION
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| 出版日期 | 2024-11-15 |
| 卷号 | 361页码:10 |
| 关键词 | Heavy metals Farmland soil Fructus mume residue Methylglycinediacetate acid Soil washing |
| ISSN号 | 0269-7491 |
| DOI | 10.1016/j.envpol.2024.124809 |
| 通讯作者 | Luo, Yong-ming(ymluo@issas.ac.cn) |
| 英文摘要 | Utilizing plant extracts for soil washing is a promising and cost-efficient strategy to permanently remove toxic metals from farmland soils. However, the efficiency of current plant extracts in heavy metals removal is constrained by the need of excessively high liquid-solid ratios (>10:1), which limits their practical application in the farmland soils. To address this challenge, we developed a novel binary washing agent consisting of Fructus mume residue extract (RPM) and methylglycinediacetate acid (MGDA). Through optimization experiments, we determined an optimal composition of 50 g L-1 RPM and 0.34 g L-1 MGDA (RPMG3), which exhibited a remarkable synergistic effect on the removal of Cd and Cu from two polluted farmland soils. Compared to the single use of RPM or MGDA, RPMG3 increased metal removal efficiency by 44.6%-303.8% in the alkaline dryland soil and 55.8%-141.9% in the slightly acidic paddy soil, at an optimum liquid-solid ratio of 2:1. The contents of soil Cd and Cu can be reduced to below the risk screening values via acid activation, metal ion exchange, and complexation of functional groups. Moreover, the potential ecological risks associated with Cd in the soils were significantly mitigated due to the decrease in exchangeable and reducible Cd fractions following RPMG3 washing. Additionally, RPM and RPMG3 washing led to enhancements in soil organic carbon and nutrient concentrations, as well as increased activities of soil enzymes including catalase, urease, and beta-glucosidase. Notably, RPMG3 washing exhibited the most pronounced promotion effect on wheat seed germination and growth. Taken together, the binary complex of RPMG3 demonstrates potential as an environmentally friendly green washing agent capable of in reducing heavy metals from farmland soil with great efficiency, even at low liquid-solid ratios. |
| WOS关键词 | HEAVY-METALS ; CHELATING-AGENTS ; WASTE ; ZN ; BIOAVAILABILITY ; FEASIBILITY ; BIOSORPTION ; MECHANISM ; SORPTION ; COPPER |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001313515200001 |
| 资助机构 | National Science Foundation of China ; National Key Research and Development Program of China ; CSCEC Eco-Environmental Engineering Research Center (Soil Remediation Technology and Equipment) ; China Construction Eighth Engineering Division Co., Ltd. |
| 源URL | [http://ir.yic.ac.cn/handle/133337/35638]  |
| 专题 | 烟台海岸带研究所_中科院海岸带环境过程与生态修复重点实验室 烟台海岸带研究所_近岸生态与环境实验室 |
| 通讯作者 | Luo, Yong-ming |
| 作者单位 | 1.Zhejiang Univ Technol, Coll Environm, Key Lab Microbial Technol Ind Pollut Control Zheji, Hangzhou 310014, Peoples R China 2.Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China 3.Chinese Acad Sci, Yantai Inst Coastal Zone Res YIC, CAS Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China 4.China Construct Eighth Engn Div Co Ltd, CSCEC Ecoenvironm Engn Res Ctr Soil Remediat Techn, Shanghai 200444, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Yi,Tu, Chen,Li, Yuan,et al. MGDA-assisted plant washing agent for improving the removal of Cd and Cu from farmland soils[J]. ENVIRONMENTAL POLLUTION,2024,361:10. |
| APA | Wang, Yi.,Tu, Chen.,Li, Yuan.,Yang, Shuai.,Liu, Ying.,...&Luo, Yong-ming.(2024).MGDA-assisted plant washing agent for improving the removal of Cd and Cu from farmland soils.ENVIRONMENTAL POLLUTION,361,10. |
| MLA | Wang, Yi,et al."MGDA-assisted plant washing agent for improving the removal of Cd and Cu from farmland soils".ENVIRONMENTAL POLLUTION 361(2024):10. |
入库方式： OAI收割
来源：烟台海岸带研究所
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