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Multi-objective optimization of energy use and environmental emissions for walnut production using imperialist competitive algorithm

Author

Listed:
  • Khanali, Majid
  • Akram, Asadollah
  • Behzadi, Javad
  • Mostashari-Rad, Fatemeh
  • Saber, Zahra
  • Chau, Kwok-wing
  • Nabavi-Pelesaraei, Ashkan

Abstract

Although the agricultural sector is an important source of bioenergy production, this production can be considered sustainable when energy consumed and environmental emissions are optimal. As such, the assessment of energy flow, environmental emissions of walnut orchards in Alborz province of Iran and their simultaneous optimization by multi-objective imperialist competitive algorithm are the main goals of this investigation. Input-output energy analysis, IMPACT 2002+ method of life cycle assessment, and multi-objective imperialist competitive algorithm are used in the energy-environmental evaluation for optimization in this study. Results ascertain that energy uses of the entire output and input are computed to be 31,015 and 27200 MJ ha−1, respectively and that gasoline with 40% is the dominated consumer of energy. Moreover, energy use efficiency is 0.88, which indicates energy inefficiency in walnut production. Environmental results shows that On-Orchard emissions with a share more than 50% in ecosystem quality, human health, and climate changes and gasoline in resources category are the main hotspots. Multi-objective optimization illustrates that the reduction in total energy is 19316 MJ ha−1 (about 62%) and gasoline with 58% is the most energy saving input among all. On the other hand, the total weighted emission decreases by about 1.47Pt (about 40%). Generally, results reveal that timely maintenance can help orchardist attain close to optimal condition. Furthermore, the application of imperialist competitive algorithm not only can offer optimum pattern of walnut production, but also be extended to the world for different crops.

Suggested Citation

  • Khanali, Majid & Akram, Asadollah & Behzadi, Javad & Mostashari-Rad, Fatemeh & Saber, Zahra & Chau, Kwok-wing & Nabavi-Pelesaraei, Ashkan, 2021. "Multi-objective optimization of energy use and environmental emissions for walnut production using imperialist competitive algorithm," Applied Energy, Elsevier, vol. 284(C).
  • Handle: RePEc:eee:appene:v:284:y:2021:i:c:s0306261920317244
    DOI: 10.1016/j.apenergy.2020.116342
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    1. Kaab, Ali & Sharifi, Mohammad & Mobli, Hossein & Nabavi-Pelesaraei, Ashkan & Chau, Kwok-wing, 2019. "Use of optimization techniques for energy use efficiency and environmental life cycle assessment modification in sugarcane production," Energy, Elsevier, vol. 181(C), pages 1298-1320.
    2. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach," Energy, Elsevier, vol. 36(5), pages 2765-2772.
    3. Alissa Kendall & Elias Marvinney & Sonja Brodt & Weiyuan Zhu, 2015. "Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production, Part I: Analytical Framework and Baseline Results," Journal of Industrial Ecology, Yale University, vol. 19(6), pages 1008-1018, December.
    4. Fan, Xing & Zhang, Wen & Chen, Weiwei & Chen, Bin, 2020. "Land–water–energy nexus in agricultural management for greenhouse gas mitigation," Applied Energy, Elsevier, vol. 265(C).
    5. Breen, M. & Murphy, M.D. & Upton, J., 2019. "Development of a dairy multi-objective optimization (DAIRYMOO) method for economic and environmental optimization of dairy farms," Applied Energy, Elsevier, vol. 242(C), pages 1697-1711.
    6. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach," Applied Energy, Elsevier, vol. 88(11), pages 3765-3772.
    7. Ghasemi-Mobtaker, Hassan & Mostashari-Rad, Fatemeh & Saber, Zahra & Chau, Kwok-wing & Nabavi-Pelesaraei, Ashkan, 2020. "Application of photovoltaic system to modify energy use, environmental damages and cumulative exergy demand of two irrigation systems-A case study: Barley production of Iran," Renewable Energy, Elsevier, vol. 160(C), pages 1316-1334.
    8. Rafiee, Shahin & Mousavi Avval, Seyed Hashem & Mohammadi, Ali, 2010. "Modeling and sensitivity analysis of energy inputs for apple production in Iran," Energy, Elsevier, vol. 35(8), pages 3301-3306.
    9. Tabatabaie, Seyed Mohammad Hossein & Rafiee, Shahin & Keyhani, Alireza & Heidari, Mohammad Davoud, 2013. "Energy use pattern and sensitivity analysis of energy inputs and input costs for pear production in Iran," Renewable Energy, Elsevier, vol. 51(C), pages 7-12.
    10. Mostashari-Rad, Fatemeh & Nabavi-Pelesaraei, Ashkan & Soheilifard, Farshad & Hosseini-Fashami, Fatemeh & Chau, Kwok-wing, 2019. "Energy optimization and greenhouse gas emissions mitigation for agricultural and horticultural systems in Northern Iran," Energy, Elsevier, vol. 186(C).
    11. Boehmel, Constanze & Lewandowski, Iris & Claupein, Wilhelm, 2008. "Comparing annual and perennial energy cropping systems with different management intensities," Agricultural Systems, Elsevier, vol. 96(1-3), pages 224-236, March.
    12. Nabavi-Pelesaraei, Ashkan & Rafiee, Shahin & Mohtasebi, Seyed Saeid & Hosseinzadeh-Bandbafha, Homa & Chau, Kwok-wing, 2019. "Assessment of optimized pattern in milling factories of rice production based on energy, environmental and economic objectives," Energy, Elsevier, vol. 169(C), pages 1259-1273.
    13. Ghorbani, Reza & Mondani, Farzad & Amirmoradi, Shahram & Feizi, Hassan & Khorramdel, Surror & Teimouri, Mozhgan & Sanjani, Sara & Anvarkhah, Sepideh & Aghel, Hassan, 2011. "A case study of energy use and economical analysis of irrigated and dryland wheat production systems," Applied Energy, Elsevier, vol. 88(1), pages 283-288, January.
    14. Bacenetti, Jacopo & Sala, Cesare & Fusi, Alessandra & Fiala, Marco, 2016. "Agricultural anaerobic digestion plants: What LCA studies pointed out and what can be done to make them more environmentally sustainable," Applied Energy, Elsevier, vol. 179(C), pages 669-686.
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