Fuzzy risk-based allocation of pollution load using extended trading-ratio system

Abstract

Abstract Today, one of the most important aspects of urban planning and management is the issue of environmental protection. It is necessary to consider the effects of urban development on the environment in urban planning to achieve sustainable economic and industrial development. In this paper, an optimal planning structure has been developed to reduce the pollution load of Khorramabad River, Lorestan Province, Iran. The developed fuzzy trading-ratio system was programmed based on risk-based fuzzy analysis for nine dischargers of biochemical oxygen demand (BOD5) as a water quality index and optimized using a genetic algorithm. The calibrated and verified model was utilized to simulate the BOD5 concentration at checkpoints of the river using four data sets of water quality collected from 2018 to 2021 in August (2018, 2019 and 2020 for calibration and 2021 for verification). The results showed that BOD5 exchange in the downstream stations is in critical condition. Optimization to reduce the cost of wastewater treatment showed that the proposed model could be economically improved by about 11%. The feasible domain of risk changes was assessed at three levels of 30, 60 and 90%, with the maximum value of the objective function calculated for the alcohol factory and the minimum value obtained for the flour factory.