One of the most important drawbacks of life cycle assessment (LCA)-related analysis is the generation of reliable data. In the proposed methodology, this drawback is addressed using data from process simulations, based on first-principles models in the LCA calculations. Furthermore, uncertainty that arises from industrial data and a simulation hypothesis are explicitly incorporated, using Monte Carlo sampling, which allows statistical information to be translated into a set of representative scenarios for which the LCA calculations are performed. The combined use of LCA, process simulation, and sampling techniques results in a powerful environmentally conscious quantitative tool whose objective is to guide decision-makers toward the adoption of more-sustainable process alternatives. The main objective of the methodology is to show the main differences between production options. This novel methodology is applied to the specific case of phosphoric acid (PA) production

Peer Reviewed