Applying analytical decision methods for determination of the best treatment alternative to remove emerging micropollutants from drinking water and wastewater: triclosan example

Abstract

Increasing human activities have not only substantially altered the natural material cycle but also created new synthetic chemicals flows. Some of these chemicals, which are described as micropollutants (MPs), may result in adverse effects on human health, aquatic organisms, and ecosystems. MPs can be transported to the environment and water resources in a variety ways including domestic and industrial wastewater. Unfortunately, most MPs are only partially removed in existing conventional treatment plants. Therefore, conventional treatment plants should be modernized by advanced treatment technologies to protect the environment and human health. However, there are various mysteries about best treatment techniques, evaluation criteria, and decision-making methods. In this study, it was aimed to determine the best treatment alternatives for triclosan (TCS) which is one of the priority MPs. A total of 18 evaluation criteria were identified and prioritized by employing analytical hierarchy process (AHP) and entropy methods. Treatment alternatives were identified and their performance was assessed through a comprehensive literature investigation. In decision-making processes of determining these alternatives, “technique for order preference by similarity to ideal solution (TOPSIS),” “preference ranking organization method for enrichment evaluation (PROMETHEE),” and “Višekriterijumsko kompromisno rangiranje (VIKOR)” analytical decision-making methods were employed, and priority rankings were determined according to each decision method. The final priority ranking was found as adsorption > membrane filtration > hybrid processes > advanced oxidation processes > constructed wetlands > conventional treatment processes > biological treatment > other treatment processes. Although the obtained results are specific to TCS, the employed analytical decision methods can be also used to decide the best treatment alternatives for other MPs.

Appendix

Appendix 1. Used questionnaire list for collecting expert opinions

Table 9 Weighting of evaluation criteria according to priorities

Table 10 Weighting of treatment alternatives according to evaluation criteria

Appendix 2

Table 11 Beginning decision matrix of the TOPSIS method

Appendix 3

Table 12 Standard (normalized) decision matrix of the TOPSIS method

Appendix 4

Table 13 Weighted standard decision matrix according to the TOPSIS method

Appendix 5

Table 14 Positive and negative ideal solutions set according to the TOPSIS method

Appendix 6

Table 15 Positive ideal solutions according to the TOPSIS method

Appendix 7

Table 16 Negative ideal solutions according to the TOPSIS method

Appendix 8

Table 17 The relative closeness to the ideal solution according to the TOPSIS method

Appendix 9

Table 18 Beginning decision matrix of PROMETHEE

Appendix 10

Table 19 Criteria, preference functions, and direction according to the PROMETHEE method

Appendix 11

Table 20 Preference flows according to the PROMETHEE method

Appendix 12

Table 21 Partial ranking values according to the PROMETHEE method

Appendix 13

Table 22 Ranking score and ranking according to the PROMETHEE method

Appendix 14

Table 23 Beginning decision matrix of the VIKOR method: calculation of best f_j⁺ and worst f_j⁻ values

Appendix 15

Table 24 Normalized decision matrix of the VIKOR method

Appendix 16

Table 25 Weighted standard decision matrix of the VIKOR method

Appendix 17

Table 26 Calculated E, F, and P values according to the VIKOR method

Appendix 18

Table 27 Ranking of alternatives according to the VIKOR method