Decreasing environmental impacts of cropping systems using life cycle assessment (LCA) and multi-objective genetic algorithm

Abstract The environmental awareness of people has increased in recent decades, and the demand for environmentally friendly products has caused agro-scientists to give more attention to cleaner production. Life cycle assessment (LCA) has been identified as a suitable tool for assessing environmental impacts associated with a product over its life cycle. The implementation of LCA with other management tools can help LCA practitioners to evaluate agri-food systems from different viewpoints. In this study, LCA, multi-objective genetic algorithm (MOGA), and data envelopment analysis (DEA) were combined, and the pros and cons of their application were investigated. Three impact categories – global warming (GW), respiratory inorganics (RI) and non-renewable energy use (NRE) – were selected to be evaluated. The results revealed mean RI, GW and NRE in a case study of watermelon production of 10.3 kg PM 2.5 eq ha −1 , 9485.5 kg CO 2 eq ha −1 and 186,432 MJ primary energy ha −1 respectively. The results of LCA + MOGA showed that a reduction of 27% in RI and 35% in GW and NRE can occur if an appropriate combination of resources is used in watermelon production. The use of LCA + DEA revealed that if all farmers operate on the efficient frontier (suggested values) impacts in all three categories can be reduced by 8%.