Sustainable Development Goals-Based Prospective Process Design Using Hybrid Modeling

Abstract

Replacing fossil technologies with renewable carbon-based technologies is of vital importance for the development of sustainable chemical processes in the future. However, impacts beyond climate change should be carefully evaluated to ensure that this transition to defossilized chemicals is truly sustainable. Here, we develop a framework for sustainable process design that explicitly accounts for the performance attained in the Sustainable Development Goals (SDGs), which is computed using standard life cycle assessment (LCA) metrics alongside the planetary boundaries (PBs) concept. We apply this approach to design a CO2 hydrogenation to methanol process, where economic and SDGs-based performance are the objectives optimized. We show that the environmentally optimal design reduces the impact on SDG 13 (climate action) substantially relative to the business-as-usual (BAU) fossil counterpart, yet this is done at the expense of worsening other categories. A prospective LCA reveals that such collateral damage will be drastically reduced in the future due to improvements in a range of economic sectors. Overall, this work highlights the need to embrace impacts beyond climate change in process design and the advantages of using hybrid surrogates to expedite the computation of Pareto designs.