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

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 PM2.5 eq ha(-1), 9485.5 kg CO2 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%. (C) 2014 Elsevier Ltd. All rights reserved.