We address the multicriterion optimization of utility plants with economic and environmental concerns. Rather than optimizing a single environmental metric, which was the traditional approach followed in the past, we focus on optimizing these systems considering simultaneously several environmental indicators based on life cycle assessment (LCA) principles. We combine a multiobjective optimization model with an MILP-based dimensionality reduction method that allows identifying key environmental metrics that exhibit the property that their optimization will very likely improve the system simultaneously in all of the remaining damage categories. This analysis reduces the complexity of the underlying multiobjective optimization problem from the viewpoints of generation and interpretation of the solutions. The capabilities of the proposed method are illustrated through a case study based on a real industrial scenario, in which we show that a small number of environmental indicators suffice to optimize the environmental performance of the plant.