Small-scale membrane-based arsenic removal for decentralized applications–Developing a conceptual approach for future utilization

Kurz, Edgardo E. Cañas; Hellriegel, Ulrich; Figoli, Alberto; Gabriele, Bartolo; Bundschuh, Jochen; Hoinkis, Jan

doi:10.1016/j.watres.2021.116978

Cited by 24 publications

(5 citation statements)

References 108 publications

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“…Recently, attempts have been made to integrate clean energy sources with RO to bring down the operational cost. 211 For example, RO-based As removal plants driven by solar energy have been newly constructed in some of the affected regions in India under pilot study to understand the feasibility of the process. 212 Such kind of integrated studies may help scale up the application of membrane processes for this purpose.…”

Section: Future Research Opportunitiesmentioning

confidence: 99%

A review of arsenic mitigation strategies in community water supplies with insights from South Asia: options, opportunities and constraints

Bhowmik

Sarkar

Bhattacharya

et al. 2022

Environ. Sci.: Water Res. Technol.

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Section: Future Research Opportunitiesmentioning

confidence: 99%

A review of arsenic mitigation strategies in community water supplies with insights from South Asia: options, opportunities and constraints

Bhowmik

Sarkar

Bhattacharya

et al. 2022

Environ. Sci.: Water Res. Technol.

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“…Various membrane technologies are used for arsenic remediation depending on the size of the membrane, such as ultra-filtration [31], nano-filtration [32], reverse osmosis [33], etc. The technologies are mostly used in small-scale water treatment units and exhibit wide applications in arsenic remediation [34].…”

Section: Membrane-based Technologiesmentioning

confidence: 99%

Neural Network and Random Forest-Based Analyses of the Performance of Community Drinking Water Arsenic Treatment Plants

Bhattacharya

Sahu

Telu

et al. 2021

Water

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A plethora of technologies has been developed over decades of extensive research on arsenic remediation, although the technical and financial perspective of arsenic removal plants in the field requires critical evaluation. In the present study, focusing on some of the pronounced arsenic-affected areas in West Bengal, India, we assessed the implementation and operation of different arsenic removal technologies using a dataset of 4000 spatio-temporal data collected from an in-depth field survey of 136 arsenic removal plants engaged in the public water supply. Our statistical analysis of this dataset indicates a 120% rise in the average cumulative capacity of the plants during 2014–2021. The majorities of the plants are based on the activated alumina with FeCl3 technology and serve about 49% of the population in the study area. The average cost of water production for the activated alumina with FeCl3 technology was found to be ₹ 7.56 /m3 (USD $1 ≈ INR ₹70), while the lowest was ₹ 0.39 /m3 for granular ferric hydroxide technology. A machine learning-based framework was employed to analyze the impact of water quality and treatment plant parameters on the removal efficiency, capital, and operational cost of the plants. The artificial neural network model exhibited adequate statistical significance, with a high F-value and R2 of 5830.94 and 0.72 for the capital cost model, 136954, and 0.98 for the operational cost model, respectively. The relative importance of the process variables was identified through random forest models. The models indicated that flow rate, media, and chemicals are the predominant costs, while contaminant loading in influent water and a coagulating agent was important for removal efficiency. The established framework may be instrumental as a decision-making tool for water providers to assess the expected performance and financial involvement for proposed or ongoing arsenic removal plants concerning various design and quality parameters.

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“…To maintain the WHO limits, new more effective elimination techniques should be applied, or existing ones should be modified and optimized accordingly. Numerous removal techniques [13] have been established for arsenic elimination from water, such as coagulation [14], adsorption [15], membranes [16,17], precipitation [18,19], ion exchange [20], etc. Comparing these methods, it appears that chemical precipitation and coagulation-flocculation are widely used due to their simplicity.…”

Section: Introductionmentioning

confidence: 99%

Magnesium/Silica/Lanthanum@Activated Carbon for the Remediation of As(III) from Water

Tolkou,

Kyzas

2023

Environments

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In this study, activated carbon was suitably modified with Mg/Si/La and its effectiveness in removing As(III) was investigated. The structure of Magnesium/Silica/Lanthamum@Activated Carbon (Mg-Si-La@AC) was fully characterized and several parameters, such the dosage, pH, contact time, and initial As(III) concentration, were studied. Thus, the BET surface area, total pore volume, and micropore volume of Mg-Si-La@AC were measured to be 271.46 m2/g, 0.006 cm3/g and 0.52 cm3/g, respectively. The results showed that the optimal condition for the reduction in As(III) from the initial concentration of 100 μg/L to below 10 μg/L was the addition of 1.5 g/L of adsorbent at pH 7.0. Furthermore, 4 h of contact time showed >90% removal. The Langmuir isotherm model was best fitted to the experimental results, exhibiting a maximum adsorption capacity of 322 μg/g, and the PSO kinetic model was found to be the most applicable according to kinetics. Consecutive regeneration studies were carried out and the results showed that the adsorbent was effectively used up to four cycles.

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Small-scale membrane-based arsenic removal for decentralized applications–Developing a conceptual approach for future utilization

Cited by 24 publications

References 108 publications

A review of arsenic mitigation strategies in community water supplies with insights from South Asia: options, opportunities and constraints

A review of arsenic mitigation strategies in community water supplies with insights from South Asia: options, opportunities and constraints

Neural Network and Random Forest-Based Analyses of the Performance of Community Drinking Water Arsenic Treatment Plants

Magnesium/Silica/Lanthanum@Activated Carbon for the Remediation of As(III) from Water

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