Abstract
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, 136,954, 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.
Highlights
It has been observed that the removal of arsenic is comparatively easier in an iron-arsenic water system with good reactivity under natural conditions and corresponding treatment methods are attributed to low costs and low energy requirements [23]
A study performed by Kurz et al, in 2020, discussed subsurface arsenic removal (SAR) from groundwater in Mekong Delta, Vietnam, based on the principles of adsorption and the co-precipitation of arsenic with iron-(hydr)oxides or hydrous ferric oxide (HFO) and found arsenic concentration reduction to be below 10 μg/L from an average initial concentration of 81 ± 8 μg/L
The study area has been selected as 27 blocks of four districts (Nadia, Maldah, Murshidabad, and North 24 Parganas) in West Bengal (Figure 1a), where a pronounced arsenic prevalence is reported, and piped water supplies from groundwater sources are necessarily associated with arsenic iron removal plants (AIRPs) comprising various technologies
Summary
Extensive researches on arsenic decontamination conducted globally are implemented in the field. Several insitu technologies for arsenic removal comprise permeable reactive barriers (PRB), subsurface arsenic removal (SAR), natural attenuation, arsenic immobilization by sorption, bioremediation techniques, and electrokinetics, which are limited due to a lack of long-term experience of these techniques [11]. It has been observed that the removal of arsenic is comparatively easier in an iron-arsenic water system with good reactivity under natural conditions and corresponding treatment methods are attributed to low costs and low energy requirements [23]. The implementation of some of these promising technologies in field-scale plants around the globe is highlighted to compare the arsenic management in the study area
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