Abstract
The identification of best practice technologies to remediate arsenic-enriched drinking water involves the resolution of several technical, environmental, economic, and social factors. Multi-criteria analysis (MCA) provides a procedure to sort through diverse influencing factors as a means of facilitating the stakeholder decision-making process. The primary key MCA criteria used to define arsenic treatment options are expressed as source-exposure vector, health risk, cost, social acceptance, and technical competency. MCA not only can handle a complex mix of quantitative and qualitative information but also fosters means to resolve conflicting stakeholder opinion (or strategies). The MCA procedure involves construction of a performance matrix from utility scores for each key performance indicator (KPIs) that may influence outcomes. Data in the performance matrix are converted into numerical values through application of a specific utility scale scoring and weighting technique for each criterion. Inspection of the performance matrix scores facilitates decision making because they summarize arsenic treatment options numerically for all important criteria and KPIs. The weighting procedure enables stakeholder preferences (or strategies) to be incorporated into the selection process. Given the "fuzzy logic" nature of the KPI information, uncertainty may influence data outcome; this can be addressed by using an outranking procedure such as ELECTRE III or a simpler "swing" pairwise preference method. Sensitivity analysis can also be performed by reiterating the analysis using different utility scores and/or weights to assess influence on performance matrix outcomes. This approach enables the MCA methodology to be used as a negotiating tool in the decision-making process and allows areas of stakeholder agreement and disagreement to be highlighted.
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