Pollution trading as a mathematical game

Abstract

A game theory approach is used to study a market-based pollution trading strategy among different point sources. Point sources discharge effluents to the same watershed and participate as rational entities with particular objectives, interacting with each other in a hierarchical organization. Each point source must implement technologies to sell credits to other sources or buy credits to compensate for non-compliance with environmental regulations. The objective function of the formulations proposed considers the minimization of total annual costs for each point source. The participants in the pollutant credit trading are related in a Nash Game by a mixed complementarity problem (MCP) and in a Stackelberg Game by a bilevel optimization problem (BLP). Both systems are solved using the disjunctive constraint method. Different scenarios of interaction among the participants are proposed in order to observe the behavior of each decision strategy. These models should generate more reliable results with respect to non-competitive approaches as the interaction of the participants is considered.