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  • Title: EDTA-enhanced phytoremediation of heavy metals from sludge soil by Italian ryegrass (Lolium perenne L.).
    Author: Li FL, Qiu Y, Xu X, Yang F, Wang Z, Feng J, Wang J.
    Journal: Ecotoxicol Environ Saf; 2020 Mar 15; 191():110185. PubMed ID: 31986455.
    Abstract:
    Landscaping of sludge is a kind of recycling disposal, but the potential heavy metal risks limit its application. In this paper, the sludge soil was remediated by ryegrass, and the effect of ethylene diamine tetraacetic acid (EDTA) was studied through pot experiments. Italian ryegrass was planted in the sludge soil treated with six gradients concentrations of 0, 1, 2, 3, 4, 5 mmol kg-1 of EDTA, and the planting conditions were kept the same. After 45 days of planting, compared with the control group (without EDTA treated), the application of 1-5 mmol kg-1 EDTA decreased ryegrass biomass by 2-43%, reduced soil pH value by 0.21-0.34 unit, and reduced 4.1-9.7% capacity of exchange cation, but increased 1.4-8.6% soil organic matter. After growing ryegrass, the contents of heavy metals decreased by 10% for Cu, 15% for Zn, 6% for Ni, 14% for Cd and 44% for Pb; and after spraying EDTA decreased again by 33% for Cu, 31% for Zn, 56% for Ni, 24% for Cd, and 68% for Pb. In ryegrass, the uptake heavy metals were enhanced, and bio-concentration factor of Cu, Zn, Ni, Cd, and Pb of EDTA treated groups were 1.9, 1.6, 4.1, 2.7, and 4.8 times of the control group, respectively. However, EDTA only significantly increased transfer factor values of Cu and Zn, and made bio-extraction factor value of Cu greater than 1. The remediation factor values were used to comprehensive assess accumulation capacity of heavy metals by ryegrass under EDTA treating, and they ordered in Zn > Cu > Ni > Cd > Pb, and the best dose was 2 mmol kg-1 EDTA. Prediction models for bio-concentration factor were established by using stepwise multiple linear regression, explaining 94.9-99.3% of the corresponding elements with soil organic matter, EDTA dosage, and/or pH value (p < 0.005). This paper provided effective heavy metals remediation data for municipal sludge landscape and the prediction models.
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