Rapid estimation of carbon footprints in agrochemical development: correlation of process mass intensity with CO2 emissions
Year: 2024
Type: article
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: = 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.
Source: Pest Management Science
DOI: 10.1002/ps.8511
Authors: John Rohanna, Audra Tenzeldam, Robin Jenkins, Yuan Li, Abe Schuitman
Institution: Corteva (United States)
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4404045508