Rapid estimation of carbon footprints in agrochemical development: correlation of process mass intensity with CO2 emissions.

Abstract

Background: The agricultural sector faces a challenge in balancing increasing food demand while minimizing environmental impacts. Crop protection products are crucial for achieving high crop yields and ensuring food security. However, life cycle assessment (LCA), the standard framework for evaluating environmental impact, is time-consuming and costly, especially during early product development. To address this, a novel tool correlating process mass intensity (PMI) with greenhouse gas (GHG) emissions has been developed as a streamlined alternative.

Results: A strong linear correlation (R² = 0.95) was identified between PMI and product GHG emissions, enabling rapid carbon footprint estimation using simplified PMI data. The model was validated using 13 small molecule active ingredients (AIs), showing a mean absolute error (MAE) of 55 g CO₂/kg AI and a root mean square error (RMSE) of 64 kg CO₂/kg AI. Residual analysis demonstrated random distribution, suggesting reliable predictions.

Conclusion: The PMI-based tool provides rapid, accurate estimates of product carbon footprint (PCF), supporting early-stage decision-making in research and development for agrochemical processes. Its simplicity makes it applicable across various chemical sectors and valuable for sustainability efforts. © 2024 Society of Chemical Industry.