Abstract
When evaluated at the scale of individual processes, next-generation technologies may be more energy and emissions intensive than current technology. However, many advanced technologies have the potential to reduce material and energy consumption in upstream or downstream processing stages. In order to fully understand the benefits and consequences of technology deployment, next-generation technologies should be evaluated in context, as part of a supply chain. This work presents the Materials Flow through Industry (MFI) supply chain modeling tool. The MFI tool is a cradle-to-gate linear network model of the US industrial sector that can model a wide range of manufacturing scenarios, including changes in production technology and increases in industrial energy efficiency. The MFI tool was developed to perform supply chain scale analyses in order to quantify the impacts and benefits of next-generation technologies and materials at that scale. For the analysis presented in this paper, the MFI tool is utilized to explore a case study comparing three lightweight vehicle supply chains to the supply chain of a conventional, standard weight vehicle. Several of the lightweight vehicle supply chains are evaluated under manufacturing scenarios that include next-generation production technologies and next-generation materials. Results indicate that producing lightweight vehicles is more energy and emission intensive than producing the non-lightweight vehicle, but the fuel saved during vehicle use offsets this increase. In this case study, greater reductions in supply chain energy and emissions were achieved through the application of the next-generation technologies than from application of energy efficiency increases.
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Notes
Information on accessing the MFI tool is given in Supplementary Information.
References
Argonne National Laboratory (2015) The Greenhouse gases, regulated emissions, and energy use in transportation fuel-cycle model. https://greet.es.anl.gov/
Das S (2012) Achieving carbon neutrality in the global aluminum industry. JOM 64(2):285–290
Das S (2013) Life cycle assessment of carbon fiber-reinforced polymer composites. Int J Life Cycle Assess 16(3):268–282
Das S, Graziano D, Upadhyayula VKK, Masanet E, Riddle M, Cresko J (2016) Vehicle lightweighting energy use impacts in U.S. light-duty vehicle fleet. J Sustain Mater 8:5–13
Eggleston HS, Buendia L, Miwa K, Ngara T, Tanabe K (2006) Guidelines for national greenhouse gas inventories. IPCC National Greenhouse Gas Inventories Programme, Hayama
Frischknecht R, Jungbluth N, Althaus H-J, Doka G, Dones R, Heck T, Hellweg S, Hischier R, Nemecek T, Rebitzer G, Spielmann M (2005) The ecoinvent database: overview and methodological framework. Int J Life Cycle Assess 10:3–9
Green Design Institute (2008) Economic input–output life cycle assessment (EIO-LCA), US 2002 Industry Benchmark model. Carnegie Mellon University. www.eiolca.net
Guinée JB, De Haes HAU, Huppes G (1993) Quantitative life cycle assessment of products 1: goal definition and inventory. J Clean Prod 1(1):3–13
Gutowski TG, Sahni S, Allwood JM, Ashby MF, Worrell E (2013) The energy required to produce materials: constraints on energy-intensity improvements, parameters of demand. Philos Trans R Soc A 371(1986):20120003
Hanes RJ, Das S, Carpenter A (2016) Reducing supply chain energy use in next-generation vehicle lightweighting. Presented at LCA XVI, Charleston, SC, September 2016. http://www.nrel.gov/docs/fy16osti/67172.pdf
ICF International (2012) Internal report. Note: Reference available from authors on request
IHS Chemicals (2014) Process Economics Program Yearbook
Leontief W (1970) Environmental repercussions and the economic structure: an input-output approach. Rev Econ Stat 52(3):262–271
Masanet E, Kramer KJ, Homan G, Brown R, Worrell E (2009a) Assessment of supply chain energy efficiency potentials: A US case study. In: IEEE international symposium on sustainable systems and technology, vol 2009, pp 1–6
Masanet E, Kramer KJ, Homan G, Brown R, Worrell E (2009b) Assessment of household carbon footprint reduction potentials. Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US). No. LBNL-2291E
Miller S, Keoleian G (2015) Framework for analyzing transformative technologies in life cycle assessment. Environ Sci Technol 49(5):3067–3075
Modaresi R, Pauliuk S, Løvik AN, Müller DB (2014) Global carbon benefits of material substitution in passenger cars until 2050 and the impact on the steel and aluminum industries. Environ Sci Technol 48(18):10776–10784
National Renewable Energy Laboratory (2016) U.S. Life Cycle Inventory Database. https://uslci.lcacommons.gov/uslci/search
Park C-K, Kan C-D, Hollowell W, Hill SI (2012) Investigation of opportunities for lightweight vehicles using advanced plastics and composites (Report No. DOT HS 811 692). National Highway Traffic Safety Administration, Washington
U.S. Department of Energy (2016) Carbon fiber reinforced polymer bandwidth study (DRAFT). http://energy.gov/eere/amo/energy-analysis-sector#5
Wender BA, Foley RW, Hottle TA, Sadowski J, Prado-Lopez V, Eisenberg DA, Laurin L, Seager TP (2014) Anticipatory life-cycle assessment for responsible research and innovation. J. Responsible Innov 1(2):200–207
Acknowledgements
Funding provided by the U.S. Department of Energy, Advanced Manufacturing Office. The current work is in support of the Advanced Manufacturing Office’s objective of identifying and analyzing opportunities to reduce the energy and carbon intensities of the US industrial sector. In this work, we focus on two such opportunities: next-generation materials and production technologies that offer reductions in life cycle energy use and emissions, and improvements in the energy efficiency of existing industrial processes.
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Hanes, R.J., Carpenter, A. Evaluating opportunities to improve material and energy impacts in commodity supply chains. Environ Syst Decis 37, 6–12 (2017). https://doi.org/10.1007/s10669-016-9622-5
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DOI: https://doi.org/10.1007/s10669-016-9622-5