Trading pollutant discharge permits in rivers using fuzzy nonlinear cost functions

Transferable Discharge Permit (TDP) programs in water quality management produce environmental benefit, which closely achieves the same benefit through a command-and-control approach, with comparatively lower costs. Estimating abatement cost functions is one of the greatest challenges in these trading programs. According to the fact that water flows to the lowest level uni-directionally, the Trading Ratio System (TRS) is utilized for water quality management in river systems. TRS considers the river assimilative capacity and provides the optimum trading pattern. TRS has been designed for a single water quality variable and the existing uncertainties are not incorporated. In this study, an extended version of TRS is utilized which considers the uncertainties in treatment cost functions and can be used for BOD/DO management in rivers. Then, by combining the extended TRS and a fuzzy nonlinear regression, a novel model is proposed to configure a permit trading structure and provide decision maker with a wealth of cost-effective management strategies. The proposed model has been used for trading water pollutant discharge permits in the Zarjub river in northern part of Iran. The results show that trading discharge permit in this river system is a cost-effective strategy. It is also shown that the uncertainty in the wastewater treatment cost functions can be easily considered using the fuzzy set theory.