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Estimating the impact of investing in a resource efficient, resilient global energy-intensive manufacturing industry

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  • Bassi, Andrea M.
  • Tan, Zhuohua
  • Mbi, Armstrong

Abstract

To examine the prospects of creating a resource efficient, low-carbon economy, this paper focuses on the impacts of investing in energy, water and waste. The broader industrial sector, as well as six energy-intensive manufacturing industries is studied. A system dynamics model is developed for each selected sub-sector, which is embedded in a broader integrated framework to fully appreciate the linkages within the industries and across the economy, environment and society. This study further simulates and analyzes the key factors affecting the economic performance and environmental impacts of these industries in a resource efficient scenario compared to a business-as-usual (BAU) case. Our analysis indicates that with no additional resource-efficiency and conservation actions taken, these industries – highly exposed to rising fuel prices under BAU – will suffer from declined profitability over time. Under the alternative scenario however, an incremental investment in efficiency will not only substantially curb energy demand and emissions, but will also effectively reduce energy expenditures in all analyzed industries yielding an overall positive return on investment after nine years. Though the extent of cost saving varies across the sub-sectors due to the variation in energy mix, they will all see considerable reduction in unit production costs and increase in operating margins and profits in the medium to longer term.

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  • Bassi, Andrea M. & Tan, Zhuohua & Mbi, Armstrong, 2012. "Estimating the impact of investing in a resource efficient, resilient global energy-intensive manufacturing industry," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 69-84.
  • Handle: RePEc:eee:tefoso:v:79:y:2012:i:1:p:69-84
    DOI: 10.1016/j.techfore.2011.05.011
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    References listed on IDEAS

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    1. Andrea Bassi & Joel Yudken, 2009. "Potential Challenges Faced by the U.S. Chemicals Industry under a Carbon Policy," Sustainability, MDPI, vol. 1(3), pages 1-20, September.
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    6. Hayashi, Daisuke & Krey, Matthias, 2007. "Assessment of clean development mechanism potential of large-scale energy efficiency measures in heavy industries," Energy, Elsevier, vol. 32(10), pages 1917-1931.
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    Cited by:

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    2. Sen, Parag & Roy, Mousumi & Pal, Parimal, 2016. "Application of ARIMA for forecasting energy consumption and GHG emission: A case study of an Indian pig iron manufacturing organization," Energy, Elsevier, vol. 116(P1), pages 1031-1038.
    3. Ricciardi, Francesca & De Bernardi, Paola & Cantino, Valter, 2020. "System dynamics modeling as a circular process: The smart commons approach to impact management," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    4. Sgouridis, Sgouris & Ali, Mohamed & Sleptchenko, Andrei & Bouabid, Ali & Ospina, Gustavo, 2021. "Aluminum smelters in the energy transition: Optimal configuration and operation for renewable energy integration in high insolation regions," Renewable Energy, Elsevier, vol. 180(C), pages 937-953.
    5. Florian Flachenecker & Jun Rentschler, 2019. "From barriers to opportunities: Enabling investments in resource efficiency for sustainable development," Public Sector Economics, Institute of Public Finance, vol. 43(4), pages 345-373.
    6. Abrahamsen, Eirik Bjorheim & Selvik, Jon Tømmerås & Milazzo, Maria Francesca & Langdalen, Henrik & Dahl, Roy Endre & Bansal, Surbhi & Abrahamsen, Håkon Bjorheim, 2021. "On the use of the ‘Return Of Safety Investments’ (ROSI) measure for decision-making in the chemical processing industry," Reliability Engineering and System Safety, Elsevier, vol. 210(C).

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