A binary linear programming approach for LCA system boundary identification

Abstract

One of the very first steps in conducting life cycle assessment (LCA) is system boundaries identification. A binary linear programming (LP) model is proposed to identify boundary between significant and insignificant processes in a LCA study. The proposed model is designed based on Relative Mass-Energy-Economic (RMEE) methodology. There are two types of objective function that can be solved by the proposed model, (1) to minimize number of processes considered in LCA or (2) to maximize cut-off criteria values. A numerical example and sensitivity analysis are provided to verify the applicability of the proposed model.