Sustainability Metrics, Assessment and Performance Prediction by Computation

Papers are desired in two main areas: first, the development of new frameworks and approaches (including life cycle assessment) for quantitatively comparing process alternatives, particularly those that have the potential for widespread application to different industries, and second, in developing computational methods for generating data needed in assessment frameworks. Examples of interest could include the use of process-based modeling to examine environmental trade-offs like the optimum amount of pollution reduction for the greatest economic and environmental benefit, or trade-offs between energy/material usage during the use phase of a process compared to those of post-use disposal. Computational methods of interest include the use of quantum chemistry/molecular modeling approaches for predicting environmental impacts like global warming potentials, ozone depletion potentials, eco-toxicity, environmental transport and fate, energetic performance, etc. Also, rigorous development and testing of emerging quantitative structure activity relationships (QSARs) for prediction of toxicity, phase partitioning behavior, and other physical phenomena related to environmental transport and fate are of interest.