Using wastewater treatment performance, biomass and physiological plant characteristics for selection of a floating macrophyte for phytoremediation of swine wastewater through the integrative Entropy-Fuzzy AHP-TOPSIS method

Abstract

Phytoremediation success depends on the selection of suitable plant species. To this end, the multiple-attribute decision-making process (MADM) is a useful tool for selecting plants to remediate wastewater. Here, macrophytes were used to treat synthetic swine wastewater (SSW) and the best plant alternative for phytoremediation of SSW was chosen based on the hybrid Entropy-Fuzzy AHP TOPSIS MADM method. The attributes used to feed the MADM method were treatment performance, physiological endpoint changes and biomass by-products. Macrophyte-treated wastewater achieved higher pollutants removal than controls. Lemna, Landoltia, Salvinia, Azolla and Control units had removals of 81 %, 79 %, 68 %, 81 %, 25 % for tCOD; 66 %, 71 %, 65 %, 68 %, 8 % for P-PO43−; 51 %, 63 %, 40 %, 66 %, 14 % for N-NO3−; 36 %, 36 %; 26 %; 42 %; 7 % for N-NH4+; 51 %, 40 %, 52 %, 63 %, 3 % for Cu; and 25 %, 18 %, 26 %, 42 %, 14 % for Zn, respectively. Furthermore, Azolla and Lemna removed more SSW toxicity and presented the lowest phyto-stress index (0.09) and highest lipids production (14 % dw) during treatment. Azolla proved to be the best option for phytoremediation of swine wastewater, since it had the highest rank as determined by the proposed method. Acute toxic units of the treated effluent (0.38) and phyto-stress index (0.49) had the greatest weight in choosing the best plant while the production of biomass volatile solids and removals of P-PO43− and tCOD were the least influential. This study provided a reliable approach to select the best plant from available macrophytes capable of improving physicochemical and ecotoxicological quality of wastewater and offer value-added plant biomass products.