Fuzzy Wastewater Quality Index Determination for Environmental Quality Assessment under Uncertain and Vagueness Conditions

Abstract

Utilization of water in different parts of industrial life cycles brings a huge concern on environmental water and wastewater pollutions. In this research, environmental quality assessment of wastewater is studied using fuzzy logic. Fuzzy appliance is due to existance of statistical considerations (including standard deviations), various uncertainties, non-linearity and complexity of functions. A Mamdani fuzzy inference system (FIS) is developed for prediction of a fuzzy wastewater quality index (FWWQI) where four variables of Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and pH are considered. To assess the performance of the proposed index under actual conditions, water quality data of refineries at South Pars Special Economic and Energy Zone, Iran, are employed in the time interval from 2011 to 2014. Findings of this research indicated that only BOD and COD were the dominant pollutants for about 66% and 34% of analyzed time, respectively, which exceeds the standards. Moreover, the time pattern for the output indices represents that FWWQI varied from "Moderate" in 2011 to "Good" in 2014. In addition, comparison of the FWWQI results with two conventional classic methodologies indicated that the proposed fuzzy method well covers the two classic methodologies. Finally, it is noticed that all three proposed WQIs exhibit correspondingly "Good" level in the year 2014. Thus, the time pattern for the parameters and indices express continual improvement as outcome of ISO 14001 and HSE-MS.