Closing Data Gaps for LCA of Pharmaceutical Production: Estimating Energy Usage by Upscaling Laboratory Data.

Pharmaceutical production substantially contributes to global greenhouse gas emissions. The application of Life Cycle Assessment (LCA) to evaluate these impacts is hindered by the limited Life Cycle Inventory (LCI) data. Existing LCI estimation methods often exclude key operations such as waste treatment and tablet formulation, relying on broad assumptions that lead to incomplete assessments. To address these gaps, this study developed a method to estimate industrial energy usage by upscaling laboratory-scale data. This method includes Active Pharmaceutical Ingredient (API) synthesis, tablet formulation, and auxiliary operations. Process Design Calculations (PDCs) derived in our method improve the energy estimation for unit operations. The application of this method to six pharmaceuticals resulted in total energy estimates exceeding those of the existing methods by over 102% for Lidocaine, Diclofenac, Paracetamol, and Ibuprofen. Higher estimated energy usage led to a 3% to 49% increase in carbon footprint, primarily because operations previously left out contributed over 17% to the total carbon footprint. The new method's energy-based carbon footprint seems to align better with industrial reference data than other methods. We conclude that our method improves the estimation of industrial energy usage for pharmaceutical production and reduces the risk of impact underestimation. It enables LCA practitioners to conduct more reliable assessments, supporting sustainability decisions.