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Potentials of greenhouse gas emission reduction through energy efficiency improvement in Iran's petrochemical sector

Author

Listed:
  • Modirzadeh, Seyed Alireza
  • Khazaei, Ali
  • GhasemiKafrudi, Esmaeil
  • Sobhani, Zeynab
  • Kashefi, Kazem
  • Moradi, Muhammad Ali
  • Moradzadeh, Masoumeh

Abstract

Reducing energy consumption and increasing energy efficiency is a key strategy to mitigate greenhouse gases (GHGs) in the petrochemical sector, both because of the high share of energy-related emissions and because of the economic attractiveness in terms of return on investment. This paper aims to calculate the GHG mitigation potentials of the energy reduction projects in Iran's petrochemical sector. firstly, we estimated the trend of GHG emissions until 2035 using data collected from the petrochemical complexes in Iran. Then, by assessing the energy audits and other studies, we calculated the energy consumption reduction potentials as well as their costs and benefits for petrochemical complexes. Finally, we modelled the energy supply and demand of the petrochemical sector in LEAP software to evaluate the mitigation potentials of the energy reduction projects. The results show that a 6.7 % emission reduction in the existing petrochemical complexes can be achieved with a capital of about 160 million dollars. The net present value of the projects will be about 2 billion dollars, and the cost of carbon reduction will be −60.7 dollars per ton. The results of this research can be used for policymakers to plan the mitigation pathway of the sector since the revenues obtained from the energy conservation measures can be used to fund capital-intensive GHG mitigation projects.

Suggested Citation

  • Modirzadeh, Seyed Alireza & Khazaei, Ali & GhasemiKafrudi, Esmaeil & Sobhani, Zeynab & Kashefi, Kazem & Moradi, Muhammad Ali & Moradzadeh, Masoumeh, 2024. "Potentials of greenhouse gas emission reduction through energy efficiency improvement in Iran's petrochemical sector," Energy, Elsevier, vol. 311(C).
  • Handle: RePEc:eee:energy:v:311:y:2024:i:c:s0360544224030731
    DOI: 10.1016/j.energy.2024.133297
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    as
    1. Geng, Zhiqiang & Zeng, Rongfu & Han, Yongming & Zhong, Yanhua & Fu, Hua, 2019. "Energy efficiency evaluation and energy saving based on DEA integrated affinity propagation clustering: Case study of complex petrochemical industries," Energy, Elsevier, vol. 179(C), pages 863-875.
    2. Talaei, Alireza & Ahiduzzaman, Md. & Kumar, Amit, 2018. "Assessment of long-term energy efficiency improvement and greenhouse gas emissions mitigation potentials in the chemical sector," Energy, Elsevier, vol. 153(C), pages 231-247.
    3. Wang, Yao & Du, Jian & Wu, Jintao & He, Gaohong & Kuang, Guozhu & Fan, Xishan & Yao, Pingjing & Lu, Shenglin & Li, Peiyi & Tao, Jigang & Wan, Yong & Kuang, Zhengyang & Tian, Yong, 2003. "Application of total process energy-integration in retrofitting an ammonia plant," Applied Energy, Elsevier, vol. 76(4), pages 467-480, December.
    4. Han, Yongming & Cao, Lian & Guo, Qing & Geng, Zhiqiang & Yang, Weiyang & Fan, Jinzhen & Liu, Min, 2024. "Economy and carbon dioxide emissions effects of energy structures in China: Evidence based on a novel AHP-SBMDEA model," Energy, Elsevier, vol. 290(C).
    5. Neelis, Maarten & Patel, Martin & Blok, Kornelis & Haije, Wim & Bach, Pieter, 2007. "Approximation of theoretical energy-saving potentials for the petrochemical industry using energy balances for 68 key processes," Energy, Elsevier, vol. 32(7), pages 1104-1123.
    6. Lee, Cheng F. & Lin, Sue J. & Lewis, Charles & Chang, Yih F., 2007. "Effects of carbon taxes on different industries by fuzzy goal programming: A case study of the petrochemical-related industries, Taiwan," Energy Policy, Elsevier, vol. 35(8), pages 4051-4058, August.
    7. Saygin, D. & Patel, M.K. & Worrell, E. & Tam, C. & Gielen, D.J., 2011. "Potential of best practice technology to improve energy efficiency in the global chemical and petrochemical sector," Energy, Elsevier, vol. 36(9), pages 5779-5790.
    8. Li, Rongrong & Wang, Qiang & Li, Lejia & Hu, Sailan, 2023. "Do natural resource rent and corruption governance reshape the environmental Kuznets curve for ecological footprint? Evidence from 158 countries," Resources Policy, Elsevier, vol. 85(PB).
    9. Rafiqul, Islam & Weber, Christoph & Lehmann, Bianca & Voss, Alfred, 2005. "Energy efficiency improvements in ammonia production—perspectives and uncertainties," Energy, Elsevier, vol. 30(13), pages 2487-2504.
    10. Zhou, Wenji & Zhu, Bing & Li, Qiang & Ma, Tieju & Hu, Shanying & Griffy-Brown, Charla, 2010. "CO2 emissions and mitigation potential in China's ammonia industry," Energy Policy, Elsevier, vol. 38(7), pages 3701-3709, July.
    11. Han, Yongming & Wu, Hao & Geng, Zhiqiang & Zhu, Qunxiong & Gu, Xiangbai & Yu, Bin, 2020. "Review: Energy efficiency evaluation of complex petrochemical industries," Energy, Elsevier, vol. 203(C).
    12. Sardarmehni, Mojtaba & Tahouni, Nassim & Panjeshahi, M. Hassan, 2017. "Benchmarking of olefin plant cold-end for shaft work consumption, using process integration concepts," Energy, Elsevier, vol. 127(C), pages 623-633.
    13. Ren, Tao & Patel, Martin K. & Blok, Kornelis, 2008. "Steam cracking and methane to olefins: Energy use, CO2 emissions and production costs," Energy, Elsevier, vol. 33(5), pages 817-833.
    14. Geng, Zhiqiang & Zhang, Yanhui & Li, Chengfei & Han, Yongming & Cui, Yunfei & Yu, Bin, 2020. "Energy optimization and prediction modeling of petrochemical industries: An improved convolutional neural network based on cross-feature," Energy, Elsevier, vol. 194(C).
    15. Wang, Qiang & Hu, Sailan & Li, Rongrong, 2024. "Could information and communication technology (ICT) reduce carbon emissions? The role of trade openness and financial development," Telecommunications Policy, Elsevier, vol. 48(3).
    16. Freed, Randall & Mintz, Caren & Lanza, Robert & Hockstad, Leif, 2005. "Analytic framework for analyzing non-energy uses of fossil fuels as petrochemical feedstocks in the USA," Resources, Conservation & Recycling, Elsevier, vol. 45(3), pages 275-294.
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