This chapter has presented a conceptual framework for a process analysis approach to industrial ecology. Current process simulation technology based on mass and energy balance principles can provide a unified framework for this approach. The capabilities of existing process simulation tools and their deficiencies in performing this task have been elucidated. A multi-objective optimization framework provides a mechanism to include the multiple, often conflicting, goals associated with industrial ecology. However, to address the issues of accuracy and relative weights assigned to these goals one must wrestle with the problem of uncertainty - in this case addressing how to value different environmental impacts, some of which are well characterized and some highly speculative. Uncertainty analysis coupled with the multi-objective framework can be truly beneficial in this context. This framework can also provide a basis for dealing with the problem of dispersed and scarce data, given that there is little or no commercial experience with industrial symbiosis, or with applying industrial ecology at larger scales, in practice. While the case study of benzene production illustrates the usefulness of the process analysis approach to industrial ecology using multi-objective optimization under uncertainty, we expect that applications at higher levels of economic aggregation, at the plant, community, national and even global level, will one day provide comparable insights into broader strategies for improving economic and environmental sustainability.

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