a recyclate can or cannot be recycled—is a key to determining losses from the system. It is worth noting that this type of result cannot be predicted by MFA models (Graedel and Allenby 2003) as they are not detailed enough to predict the quality of recyclates.

First-principles recycling models can also be used to optimize the recycling system. Consider the results in Table 9.3, which shows that different recycling rates and energy recoveries are obtained depending on the optimization result. This is extremely useful when estimating the system's integrity, performance, and most importantly how it can be improved and managed.


It has long been a tenet of the sustainability of nonrenewable resources that recovery and recycling were central to minimizing the extraction of virgin materials. However, little attention was paid to the complexities of the separation process (e.g., Sekutowski 1994) until rather recently. We have shown herein that models of separation and subsequent processing can ameliorate this challenge and predict recovery and recycling rates as a function of time, as well as recyclate quality. In so doing, the models provide a first-principles framework for consistent and meaningful definition of data requirements and simulation so that OEMs, designers, legislators, consumers, metallurgists, etc. can (a) evaluate, (b) quantify the limits of, and (c) simulate recycling/recovery behavior of consumer products and materials. This fundamental basis is a necessity for monitoring and implementing progress in the use of nonrenewable materials by our society, and provides a much needed transparency of methodology and data to the product designer.

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