Abstract
Agricultural systems, as results of food security and production growth, are nowadays significant energy consumers. Owing to various reasons, energy consumption in these systems, especially those in developing countries, are often inefficient. As such, there are three objectives in this study. The first objective is the assessment of energy flow, cumulative exergy demand and life cycle of paddy fields. The second goal is the optimization of energy consumption by employing Data Envelopment Analysis (DEA) and Multi-Objective Genetic Algorithm (MOGA) for enhancement of energy efficiency (reduction in energy consumption and increase performance in paddy production) and reduction of adverse environmental effects in paddy production. The third objective is the provision of the optimum pattern of energy consumption in paddy production in Guilan Province of Iran. Optimization results indicate that energy savings by employing DEA and MOGA are 21.15% and 71.63%, respectively. They indicate that the enhancement of the efficiency of paddy production is mainly in terms of toxins and chemical fertilizers. Besides, all adverse environmental impacts by MOGA are significantly less than from its counterparts by DEA and present farms. The most significant difference between MOGA and DEA is associated to ozone layer depletion. As a result, MOGA can be introduced as an adequate optimization method to determine the best mix of paddy production inputs, minimizing adverse environmental impact and maximizing performances of farms and energy efficiency simultaneously. This study highlights the utilization and the performance of MOGA in paddy production systems to determine the optimized composition for mixing energy, yield and environmental impacts. The implementation of the recommended consumption patterns will be able to attain sustainable development in paddy production in Guilan province of Iran, owing to the protection of non-renewable resources, the reduction of adverse environmental effects and the improvement of economic conditions for rice farmers.
Original language | English |
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Pages (from-to) | 571-586 |
Number of pages | 16 |
Journal | Journal of Cleaner Production |
Volume | 162 |
DOIs | |
Publication status | Published - 20 Sept 2017 |
Keywords
- Energy
- Environmental impact
- Genetic algorithm
- Optimization
- Paddy
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- General Environmental Science
- Strategy and Management
- Industrial and Manufacturing Engineering