Abstract

Abstract: Pollution is one of the most important challenging political and social issues of our day. Reducing or eliminating pollution and solid waste is a critical issue. Hence the current awareness about the environment encourages citizens, governments, and corporations to take drastic measures to minimize their environmental footprints. Industrial Symbiosis (IS) network is a subfield of Industrial Ecology which tries to develop exchanges between firms in order to reduce waste and material use. The goal is to encourage trading relationships between firms (networks) to avoid waste disposal to the environment. Ideally, these exchanges can also reduce or eliminate the use of new materials and reduce energy use. In our research, we use agent-based simulation to analyze how these networks function and what motivates firms to engage in industrial symbiosis (IS) networks. Active exchanges between firms are referred to as network synergy. We also evaluate the specific environmental benefits of these IS exchanges. We use these results to determine how existing IS networks can be improved and how new IS networks can be developed. Using a sensitivity analysis, we evaluate the impact of parameters changes to the level of material exchanges and environmental impacts in the IS network. In addition to parameters commonly modeled for IS exchanges such as the distance between firms, participation in IS information sessions, the similarity of waste streams, and landfill cost, we modeled the level of trust in the network and the impact of taxation for landfill use or avoidance. Significantly, our results indicate that increasing trust within the network has a significant effect on increasing synergy in the network. We tested our idea by using a large dataset from the National Industrial Symbiosis Program (NISP) network. NISP was a facilitated industrial symbiosis program in the UK from 2003 to 2012. We base our results on five geographic regions of the NISP network.