Multiple parameter comprehensive index by fuzzy logic is an innovative approach toward environmental indexing. An attempt was carried out to express strength of municipal wastewater and sludge considering their potential for biogasification in terms of wastewater comprehensive index (WWCI) and sludge comprehensive index (SCI), respectively. Both these indices were calculated using fuzzy multiple criteria decisions making (FMCDM). Further biogas was predicted using these WWCI and SCI by multiple linear regression. A significant relation was found in suspended solids concentration of influent wastewater and digester feedstock with WWCI and SCI, respectively. Considering this linear relation, an empirical equation was developed consisting WWCI and SCI giving biogas, which was found a user friendly and precise over established biogas prediction models. As both of these indices will be obtained simply by measuring suspended solids concentration by digital inline meter at wastewater treatment plant there will be no any need to practice laborious sampling, characterization, and calculations.

Deciding which are the best performing wastewater treatment plants can be complicated, as their operations comprise different parameters which are either dependent or non-dependent on each other, and are important when deciding the type of treatment. The relative importance of these parameters in terms of weight indicates the priority assigned by decision-makers to the criteria when ranking the alternatives. These weights are calculated by statistical relativity and Saaty's nine point scale. The sensitivity of both of these approaches is analyzed. The performance of six municipal wastewater treatment plants is evaluated using the Multi-criteria Decision Making (MCDM) Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Efficiency is monitored on the basis of nine wastewater characteristics and compared with the limits established by the Central Pollution Control Board of India. The analysis uses both qualitative and quantitative approaches, which result in differential rankings; accordingly, plants with maximum organic loading removal efficiency were found to be most efficient when weights were applied as per Saaty's scale. The study proposes a field base approach with regard to the suitability of the weight allocation method for respective utilization of the fuzzy approach in environmental monitoring systems.

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Due to fluctuations in organic and hydraulic loading in a wastewater treatment plant, the application of fuzzy logic, using linguistic variables gave a better description of performance parameters. The study describes the strength of wastewater in terms of effluent wastewater index (EWWI). The EWWI was has been developed with fuzzy composite programming (FCP). Further dissolved oxygen (DO) of effluent wastewater is correlated with EWWI to predict different parameters such as, BOD, COD, SS, and TDS. Data for eight indicators (temperature, pH, SS, TDS, BOD 5 , COD, oil and grease, and chlorides), were collected. Weights were assigned on expert's perception. The index is equal to 0 if none of the eight pollutants are present in the effluent and to 1 when all eight parameters have corresponding value equal to, limits for discharge into surface water bodies defined by Gujarat pollution control board (GPCB). EWWI for irrigation and fishery was developed which is 0.5134 and 0.3205, respectively. The index is a good tool for rapidly predicting the different parameters of effluent wastewater and monitoring the feasibility of wastewater in terms of its reuse. The proposed index could be of great help for managers and decision makers when monitoring the effluent samples and planning for reuse.