Developing an approach for the sustainability assessment of groundwater remediation technologies based on multi criteria decision making

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Abstract

Groundwater is regarded as an important supply of drinking water, as well as for agricultural and industrial purposes. Groundwater pollution worsens as a result of several contaminants such as industrial, urban, and agricultural activities, and the difficulty is to select appropriate groundwater remediation methods. This research develops a technique for assessing the sustainability of groundwater remediation methods by integrating the Multi-Criteria Decision Making (MCDM) method with a Fuzzy Inference Engine. A standard approach for assessing the sustainability of groundwater remediation systems has been developed, consisting of four major criteria: economic, technical, environmental, and social. Following the calculations and determining the priority of all the criteria and techniques based on the weights, the results show the sequence of technologies in which Pump and Treat is the best with 7.83, followed by air stripping with 7.04, and monitored natural attenuation and permeable reactive barrier were the last with 3.70 and 3.19, respectively. The criteria that give P&T the most weight is both the technical and social criterion, with a weight of 8.18, while the criterion with the lowest weight was the economic criterion, with a weight of 4.22. The technical, environmental, and social aspects of P&T were all high, making it the optimum technology where the decision-maker or stakeholder can deal with the decline in the economic component, which is also proof of P&T's preferability and the most sustainable one, and It was also feasible to examine all options to determine which factors are reducing their sustainability and which should be addressed in order to enhance sustainability.

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APA

Idris, S. S., & Topuz, E. (2021). Developing an approach for the sustainability assessment of groundwater remediation technologies based on multi criteria decision making. Environmental Research and Technology, 4(4), 293–307. https://doi.org/10.35208/ert.903897

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