Abstract

Abstract There is a growing demand for sustainable products and systems. Sustainability encompasses environmental, social, and economic aspects, often referred to as the three pillars of sustainability. To make more sustainable design decisions, engineers need tools to predict the environmental, social, and economic impacts of products and characterize potential sustainability trade-offs. To predict the total impact of a product, the quantity of functional units of the product in society and impact of each product needs to be estimated. This article uses agent-based modeling (ABM), combined with tools such as life cycle assessment (LCA), to predict impacts across all three pillars of sustainability. Using the product impact results the multidimensional sustainability tradespace can be characterized. The approach described in this article is based on three main components for the predictive modeling of product impacts and the characterization of the sustainability trade space, i) ABM of product adoption, ii) the assessment of product impacts, and iii) an approach for the characterization of product sustainability trade-offs at the population level. The tradespace characterization uses a Pareto-based method presented visually to find the non-dominated solutions in the product impact space. To illustrate and describe how to use the method, a case study is presented that predicts the impact of residential solar panels in a region of the United States under various scenarios. The findings of the case study can help policy makers understand suitable implementation strategies for residential solar panels while considering the impact trade-offs involved.

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