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Screening the Capacity of 34 Wetland Plant Species to Remove Heavy Metals from Water.

ABSTRACT: Floating treatment wetlands (FTWs), consisting of vegetated rafts, may reduce heavy metal levels in polluted water, but the choice of plant species for efficient metal removal needs to be further investigated. We screened the capacity of 34 wetland plant species to remove metals dissolved in water to identify suitable species for FTWs. The plants were grown hydroponically for 5 days in a solution containing 1.2 µg Cd L-1, 68.5 µg Cu L-1, 78.4 µg Pb L-1, and 559 µg Zn L-1. Results show large variation in metal removal rate and capacity between the investigated species. The species with highest removal capacity could remove up to 52-94% of the metals already after 0.5 h of exposure and up to 98-100% of the metals after 5 days of exposure. Plant size contributed more to high removal capacity than did removal per unit of fine roots. Carex pseudocyperus and C. riparia were the most efficient and versatile species. The findings of this study should be considered as a starting point for further investigation of plant selection for improved water purification by FTWs.

SUBMITTER: Schuck M

PROVIDER: S-EPMC7369712 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Screening the Capacity of 34 Wetland Plant Species to Remove Heavy Metals from Water.

Schück Maria M Greger Maria M

International journal of environmental research and public health 20200627 13

Floating treatment wetlands (FTWs), consisting of vegetated rafts, may reduce heavy metal levels in polluted water, but the choice of plant species for efficient metal removal needs to be further investigated. We screened the capacity of 34 wetland plant species to remove metals dissolved in water to identify suitable species for FTWs. The plants were grown hydroponically for 5 days in a solution containing 1.2 µg Cd L-1, 68.5 µg Cu L-1, 78.4 µg Pb L-1, and 559 µ ...[more]

PMID: 32605055

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Project description:To enhance the adsorption capacity of biochar (BC), herein a novel multifunction modified biochar (SDMBC) was prepared by directly crosslinking of the nanomicelle of sodium dodecyl sulfate/sapindus-saponin (SDS/SAP) composite system onto the BC through a simple, environmental friendly approach. Result showed that the adsorption performance of SDMBC has been greatly improved, compared with BC or using alone SDS and SAP, adsorption ability increased by 48.83%, 29.50%, 36.44%, respectively, the best modified effect was appeared when the concentration of SAP to SDS was 0.8 and 0.8 CMC. SDMBC exhibited high adsorption abilities of 130.23, 108.43, 277.09 125.27, 112.78 mg/g for heavy metal ions lead Pb(II), Cadmium Cd(II) and organic pollutants with different chemical properties bisphenol A(BPA), Methylene blue (MB), P-nitrophenol (PNP), respectively, higher than most previously reported adsorbents, importantly, SDMBC can still efficient removal capabilities even in the binary competition. Subsequently, the SDMBC and BC was characterized by Fourier Transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), Zeta potential (Zeta), it found SDMBC has a more layered structure, richer functional groups and more amorphous structure compared with BC, which are closely related with improving its adsorption capacity. The adsorption behavior of SDMBC for MB show that process was found to be spontaneous, propitious, endothermic, the adsorption isotherms fitted Freundlich models well, pseudo-second-order best describes kinetics adsorption, suggesting that the process is multi-layer chemical adsorption. The little affected by ionic strength and coexisting substances, could remained removal rate over a wide pH range, SDMBC still keep high removal rates even after 5 reuses. Based on FT-IR analysis, plausible adsorption mechanism proposed, including hydrogen bond, electrostatic attraction and π-π bonding. Cost analysis manifests that the SDMBC are high efficiency and cheap eco-adsorbents compared with commercial activated carbon, and the SDMBC dosage required for the removal of 99% of a fixed amount of MB in different volumes of effluent was predicted. Seven machine learning (ML) models were used to predict the MB (60 mg/L) adsorption of the SDMBC, using Shapley Additive Explanations (SHAP) for model interpretation. Finding Extreme Gradient Boosting (XGBoost) exhibited best performance, the order of feature importance as time> Ratio> pH> concentration> temperature. Thus, SDMBC as a new cheap and eco-adsorbents, can be used to effectively remove various types of pollutants, has a great application potential in sewage treatment, while the accurate ML prediction model presented a valuable advice for designing efficient adsorbents and optimization operating conditions in the future.

Dataset Information

Screening the Capacity of 34 Wetland Plant Species to Remove Heavy Metals from Water.

Publications

Screening the Capacity of 34 Wetland Plant Species to Remove Heavy Metals from Water.

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