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...
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| Published in | Journal of cleaner production Vol. 86; pp. 67 - 77 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.01.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0959-6526 1879-1786 |
| DOI | 10.1016/j.jclepro.2014.08.062 |
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| 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 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%. |
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| AbstractList | 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%. 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 sub(2.5) eq ha super(-1), 9485.5 kg CO sub(2) eq ha super(-1) and 186,432 MJ primary energy ha super(-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%. 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%. |
| Author | Bolandnazar, Elham Shamshirband, Shahaboddin Mat Kiah, Miss Laiha Khoshnevisan, Benyamin Anuar, Nor Badrul Shariati, Hanifreza Motamed |
| Author_xml | – sequence: 1 givenname: Benyamin surname: Khoshnevisan fullname: Khoshnevisan, Benyamin email: b_khoshnevisan@alumni.ut.ac.ir organization: Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran – sequence: 2 givenname: Elham surname: Bolandnazar fullname: Bolandnazar, Elham email: e_bolandnazar@ut.ac.ir organization: Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran – sequence: 3 givenname: Shahaboddin orcidid: 0000-0002-6605-498X surname: Shamshirband fullname: Shamshirband, Shahaboddin email: shamshirband@um.edu.my organization: Department of Computer Science, Chalous Branch, Islamic Azad University (IAU), 46615-397 Chalous, Iran – sequence: 4 givenname: Hanifreza Motamed surname: Shariati fullname: Shariati, Hanifreza Motamed email: hr_motamed@ut.ac.ir organization: Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran – sequence: 5 givenname: Nor Badrul surname: Anuar fullname: Anuar, Nor Badrul organization: Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia – sequence: 6 givenname: Miss Laiha surname: Mat Kiah fullname: Mat Kiah, Miss Laiha organization: Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia |
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| Title | Decreasing environmental impacts of cropping systems using life cycle assessment (LCA) and multi-objective genetic algorithm |
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