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.