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Forecasting global developments in the basic chemical industry for environmental policy analysis


  • Broeren, M.L.M.
  • Saygin, D.
  • Patel, M.K.


The chemical sector is the largest industrial energy user, but detailed analysis of its energy use developments lags behind other energy-intensive sectors. A cost-driven forecasting model for basic chemicals production is developed, accounting for regional production costs, demand growth and stock turnover. The model determines the global production capacity placement, implementation of energy-efficient Best Practice Technology (BPT) and global carbon dioxide (CO2) emissions for the period 2010–2030. Subsequently, the effects of energy and climate policies on these parameters are quantified. About 60% of new basic chemical production capacity is projected to be placed in non-OECD regions by 2030 due to low energy prices. While global production increases by 80% between 2010 and 2030, the OECD's production capacity share decreases from 40% to 20% and global emissions increase by 50%. Energy pricing and climate policies are found to reduce 2030 CO2 emissions by 5–15% relative to the baseline developments by increasing BPT implementation. Maximum BPT implementation results in a 25% reduction. Further emission reductions require measures beyond energy-efficient technologies. The model is useful to estimate general trends related to basic chemicals production, but improved data from the chemical sector is required to expand the analysis to additional technologies and chemicals.

Suggested Citation

  • Broeren, M.L.M. & Saygin, D. & Patel, M.K., 2014. "Forecasting global developments in the basic chemical industry for environmental policy analysis," Energy Policy, Elsevier, vol. 64(C), pages 273-287.
  • Handle: RePEc:eee:enepol:v:64:y:2014:i:c:p:273-287
    DOI: 10.1016/j.enpol.2013.09.025

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    References listed on IDEAS

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    2. Deger Saygin & Dolf Gielen, 2021. "Zero-Emission Pathway for the Global Chemical and Petrochemical Sector," Energies, MDPI, vol. 14(13), pages 1-28, June.
    3. Lucia Lavric & Nick Hanley, 2014. "The effects of energy costs on firm re-location decisions," Discussion Papers in Environment and Development Economics 2014-02, University of St. Andrews, School of Geography and Sustainable Development.
    4. Fais, Birgit & Sabio, Nagore & Strachan, Neil, 2016. "The critical role of the industrial sector in reaching long-term emission reduction, energy efficiency and renewable targets," Applied Energy, Elsevier, vol. 162(C), pages 699-712.
    5. Wang, Xiaonan & El-Farra, Nael H. & Palazoglu, Ahmet, 2017. "Optimal scheduling of demand responsive industrial production with hybrid renewable energy systems," Renewable Energy, Elsevier, vol. 100(C), pages 53-64.
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    7. Jing-Ming Chen & Biying Yu & Yi-Ming Wei, 2019. "CO2 emissions accounting for the chemical industry: an empirical analysis for China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(3), pages 1327-1343, December.
    8. Lawrence, Akvile & Karlsson, Magnus & Thollander, Patrik, 2018. "Effects of firm characteristics and energy management for improving energy efficiency in the pulp and paper industry," Energy, Elsevier, vol. 153(C), pages 825-835.
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    10. Makridou, Georgia & Andriosopoulos, Kostas & Doumpos, Michael & Zopounidis, Constantin, 2016. "Measuring the efficiency of energy-intensive industries across European countries," Energy Policy, Elsevier, vol. 88(C), pages 573-583.
    11. Gillian Foster, 2018. "Ethylene Supply in a Fluid Context: Implications of Shale Gas and Climate Change," Energies, MDPI, vol. 11(11), pages 1-17, November.
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    14. Chen, Jing-Ming & Yu, Biying & Wei, Yi-Ming, 2018. "Energy technology roadmap for ethylene industry in China," Applied Energy, Elsevier, vol. 224(C), pages 160-174.

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