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Necessary but not sufficient: the role of energy efficiency in industrial sector low-carbon transformation

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Abstract

As the primary means for growth and development over the past two centuries, industry has played a central role in generating our current Anthropocene. The increasing impacts of climate change bring industry to the fore as the largest emitter of greenhouse gases and as a potential manufacturer of transformational technologies and infrastructure. While energy efficiency improvements are driving industrial sector emissions and cost reductions, additional switching away from fossil fuels and capture of carbon emissions is needed for climate stabilization.

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Notes

  1. Fischedick et al. (2014). The IPCC calculated the industrial share of total global emissions between 30 and 40% depending on sector definition and boundaries. Regardless of boundary assumptions, the IPCC consistently reported with high confidence that industry is the largest end-use sector source of GHGs (i.e., allocating electricity and heat production-related emissions to consuming sectors).

  2. Global cement production records commence in 1926; if the 1926 global rate of cement production (62 million tons per year) is extended prior to that year, then global cumulative production would be equal over the periods of 1869–1999 and 2000–2014. Source: Matos. 2015

  3. Real value added of industry was $20 trillion out of $73 trillion global GDP (constant 2010 dollars) in 2014, up from $14 trillion in 2000. World Bank, World Development Indicators, 2017.

  4. See BP (2017) for coal production data; although global coal production consistently declined from 2013 to 2016, global coal production in 2016 remained 58% higher than year 2000 levels

  5. UNEP 2013.

  6. Matos, 2015.

  7. World Bank, World Development Indicators 2017.

  8. Note that 2010 is the latest available year for global employment data; World Bank, World Development Indicators 2017.

  9. Global manufacturing value-added data are in chained 2010 dollar terms. Global industrial value-added data are not available. World Bank, World Development Indicators, 2017.

  10. The IPCC Fifth Assessment Report, Industry Chapter, details process emissions by source and gas; 2010 global cement process emissions from clinker calcination amounted to 1.4 billion tons CO2e (Fischedick et al. 2014).

  11. Additional information about GHG accounting is available in WBCSD (2013).

  12. Meanwhile, between 2000 and 2015 more than 30 countries have de-linked their GHG emissions and GDP. While GHG-GDP divergence is becoming increasingly prevalent, the larger challenge of decarbonizing industry still stands

  13. Nordhaus (1977) was the first published reference to the 2° goal, which has been repeatedly affirmed, most recently in ratification of the 2015 Paris Agreement. The 2° goal persists in spite of numerous critiques (e.g., Victor and Kennel 2014).

  14. The 2.7° estimate is from IEA (2016).

  15. Industrial sector value-added data are calculated as the sum of “Agriculture, forestry, fishing, and hunting,” “Mining,” “Construction,” and “Manufacturing” subsector data from the US Bureau of Economic Analysis. Chained 2009 data indicate that total industrial sector real value added reached its highest level in 2015. Real US industry and manufacturing value-added data from the World Bank exhibit similar trends with slightly different values.

  16. BEA (2006), supplemented by BLS (2016)

  17. Charles et al. (2016) have found that the secular decline of manufacturing employment after 2000 was initially masked by absorption of less educated workers by the construction sector, which made for a more debilitating collapse in 2007–2009.

  18. Note that 1997 industrial sector energy use was a subtle peak that only exceeded the previous 1979 high by 4%. Data from IEA (2016).

  19. The energy-related CO2 peak was more definitive than industrial energy use peaks. For example, the subsequent high point in 1997 was still 6% below the 1979 value. Data from IEA (2016).

  20. Total industrial greenhouse gas emissions more closely tracked industrial energy use over the 2000 to 2015 period, indicating that methane leakage related to natural gas production may have offset the carbon benefit of industrial switching from coal to natural gas. EPA (2017), IEA (2016), BEA (2017)

  21. Physical indicators are commonly used to assess activity in relatively homogenous subsectors. For paper and steel subsector examples, see Farla et al. (1997) and Worrell et al. (1997); for physical data incorporation into aggregate industry analysis, see Ang and Xu (2013).

  22. Apparent consumption of aluminum is defined as domestic primary metal production + recovery from old aluminum scrap + net imports; excludes imported scrap. Data from USGS (2016).

  23. Researchers in the field of industrial ecology have identified steel saturation effects via material flow analysis; see Cullen et al. (2012), Pauliuk et al. (2013), and Fishman et al. (2016).

  24. Net import reliance is calculated as \( \frac{\left(\mathrm{imports}-\mathrm{exports}-\mathrm{net}\ \mathrm{stock}\ \mathrm{change}\right)}{\left(\mathrm{apparent}\ \mathrm{consumption}\right)} \). Data source: USGS (2016).

  25. These data include emissions from fossil energy use and electricity consumption.

  26. The 16 manufacturing subsectors (in order of 2014 emissions): Refining, Bulk Chemicals, Iron and Steel, Food, Products, Paper Products, Aluminum, Transportation Equipment, Plastics, Fabricated Metal Products, Cement and Lime, Machinery, Computers and Electronics, Glass, Wood Products, Electrical Equipment (Balance of Manufacturing).

  27. This article uses the terms “divergence” and “de-linking” to describe reduction of GHG emissions with contemporaneous GDP growth instead of “decoupling” to avoid confusion with the regulatory term that describes disassociation of an electric utility’s profits from its sales of an energy commodity. The divergence described here is equivalent to “absolute decoupling” in its general use.

  28. For example, see OECD (2015) for discussion of impacts of overcapacity in global steel production.

  29. For additional information and analysis of the US pulp and paper sector, see Aden et al. 2013.

  30. Clarke et al. (2014). These numbers are based on scenarios with minimal overshoot (< 0.4 W/m2), i.e., less reliance on carbon removal technology deployment to achieve negative emissions in the second half of the century.

  31. Le Quéré et al. (2016) estimate 2014 total global emissions of 36 Gt CO2 and ~ 141 Gt CO2 cumulative emissions from 2011 to 2014.

  32. Rogelj et al. (2016) present a broad range of budgets based on varying assumptions.

  33. Geden (2016) argues that a net zero emissions target is more actionable than 2° budgets. However, some existing industrial companies and stakeholders find net zero targets to be unrealistic and detrimental to current efforts.

  34. In the 2° pathway, the industrial sector captures 24 billion tons carbon dioxide between 2015 and 2050.

  35. Krabbe et al. (2015) describe the assumptions used to translate emissions pathways into intensity targets for company reference.

  36. Fawcett et al. (2015) found that announced NDCs have a greater than 50% likelihood of 2° or 3° temperature rise this century and an 8% chance of limiting warming to less than 2°.

  37. McKinsey and Company (2009) quantified 2020 expected costs per sector and technology in their series of reports.

  38. Randers (2012) describes the assumptions, benefits, and shortcomings of the GEVA approach.

  39. Krabbe et al. (2015) describe the background, assumptions, and results of the SDA in detail.

  40. Material efficiency can in some cases be more profitable for a company than energy efficiency, as material costs often make up for much higher shares than energy cost. Industrial symbiosis can also be a very attractive alternative, where possible.

  41. IEA (2009).

  42. Allwood et al. (2010) present alternate CCS, recycling, demand reduction, and innovation scenarios that achieve more emissions mitigation. Sugiyama et al. (2014) also assess energy efficiency potentials for emissions mitigation

  43. Does not include separate energy-based targets.

  44. BSR, The B Team, CDP, Ceres, The Climate Group, The Prince of Wales’s Corporate Leaders Group, and WBCSD.

  45. We Mean Business. The Climate Has Changed, 2014 (p. 13).

  46. Doda et al. (2015).

  47. Borck and Coglianese (2009) develop a typology of voluntary environmental programs to assess the factors that lead to maximum effectiveness.

  48. See, for example, Groenenberg et al. (2001).

  49. Akimoto et al. (2008) discuss the emissions unpredictability of sectoral intensity schemes.

  50. see Park (1992) for earlier example of industrial energy use decomposition analysis and Kopidou et al. (2016) for example of more recent emissions and employment industrial decomposition analysis)

  51. Rodrik (2016).

  52. Bossart (1)

  53. Akimoto et al. (2008), Boyd et al. (2011),Belzer (2014), Fugii and Managi (2015) Boyd et al. (2016).

References

  • Aden, N., Bradbury, J., & Tompkins, F. (2013). Energy efficiency in U.S. manufacturing: the case of Midwest pulp and paper mills. Washington, DC: World Resources Institute Report. http://pdf.wri.org/energy-efficiency-inus-manufacturing-midwest-pulp-and-paper.pdf http://pdf.wri.org/energy-efficiency-inus-manufacturing-midwest-pulp-and-paper.pdf.

  • Akimoto, K., Sano, F., Oda, J., Homma, T., Rout, U. K., & Tomoda, T. (2008). Global emission reductions through a sectoral intensity target scheme. Climate Policy, 8, S46–S59.

    Article  Google Scholar 

  • Allwood, J. M., Cullen, J. M., & Milford, R. L. (2010). Options for achieving a 50% cut in industrial carbon emissions by 2050. Environmental Science and Technology, 44(6), 1888–1894.

    Article  Google Scholar 

  • Ang, B. W., & Xu, X. Y. (2013). Tracking industrial energy efficiency trends using index decomposition analysis. Energy Economics, 40, 1014–1021.

    Article  Google Scholar 

  • Baldwin, R. (2013). Trade and industrialization after globalization’s second unbundling: how building and joining a supply chain are different and why it matters. In R. C. Feenstra & A. M. Taylor (Eds.), Globalization in an age of crisis: multilateral economic cooperation in the twenty-first century. Chicago: University of Chicago Press.

    Google Scholar 

  • Baldwin, R., & Lopez-Gonzalez, J. (2015). Supply-chain trade: a portrait of global patterns and several testable hypotheses. The World Economy, 38, 1682–1720. https://doi.org/10.1111/twec.12189.

    Article  Google Scholar 

  • Belzer, D. B. (2014). A comprehensive system of energy intensity indicators for the U.S.: methods, data, and key trends. PNNL-22267.

  • Borck, J. C., & Coglianese, C. (2009). Voluntary environmental programs: assessing their effectiveness. Annual Review of Environment and Resources, 34, 305–324.

    Article  Google Scholar 

  • Bossart, A. (2011). Better ROI and Lower Emissions– Smart Decisions Based on Energy Efficiency Facts Reduce the Emissions and Improve Your OPEX. Waste Management, 2, 285–301 ISBN: 978-3-935317-69-6. http://www.vivis.de/fachbuecher/english-books/156-waste-management-volume-2.

    Google Scholar 

  • Boyd, G., & Golden, J. S. (2016). Enhancing firm GHG reporting: using index numbers to report corporate level measures of sustainability. International Journal of Green Technology, 2, 29–37.

    Article  Google Scholar 

  • Boyd, G., Kuzmenko, T., Szemely, B., & Zhang, G. (2011). Preliminary analysis of the distribution of carbon and energy intensity for 27 energy intensive trade exposed industrial sectors. Duke Environmental Economics Working Paper EE 11–03. Durham: Duke University.

    Google Scholar 

  • BP (2017). Statistical Review of World Energy | Energy Economics | BP Global. Bp.com. Accessed 11 Aug 2017. https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html.

  • Charles, K. K., Hurst, E., & Notowidigdo, M. J. (2016). The masking of the decline in manufacturing employment by the housing bubble. Journal of Economic Perspectives, 30(2), 179–200.

    Article  Google Scholar 

  • Clarke, L., Jiang, K., Akimoto, K., Babiker, M., Blanford, G., Fisher-Vanden, K., Hourcade, J.-C., Krey, V., Kriegler, E., Löschel, A., McCollum, D., Paltsev, S., Rose, S., Shukla, P. R., Tavoni, M., van der Zwaan, B. C. C., & van Vuuren, D. P. (2014). Assessing transformation pathways. In O. Edenhofer, R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel, & J. C. Minx (Eds.), Climate change 2014: mitigation of climate change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.

    Google Scholar 

  • Cullen, J. M., Allwood, J. M., & Bamback, M. D. (2012). Mapping the global flow of steel: from steelmaking to end-use goods. Environmental Science & Technology, 46, 13048–13055.

    Article  Google Scholar 

  • Doda, B., Gennaioli, C., Gouldson, A., Grover, D., & Sullivan, R. (2015). Are corporate carbon management practices reducing corporate carbon emissions? Corporate Social Responsibility and Environmental Management. https://doi.org/10.1002/csr.1369

  • Farla, J., Blok, K., & Schipper, L. (1997). Energy efficiency developments in the pulp and paper industry: a cross-country comparison using physical production data. Energy Policy, 25, 745–758.

    Article  Google Scholar 

  • Food and Agriculture Organization of the United Nations (FAO) (2016). FAOSTAT. http://www.fao.org/faostat/en/#data/QC.

  • Fawcett, A. A., Iyer, G. C., Clarke, L. E., Edmonds, J. A., Hultman, N. E., McJeon, H. C., Rogelj, J., Schuler, R., Alsalam, J., Asrar, G. R., Creason, J., Jeong, M., McFarland, J., Mundra, A., & Shi, W. J. (2015). Can Paris pledges avert severe climate change? Science, 350(6265), 1168–1169.

    Article  Google Scholar 

  • Fischedick, M., Roy, J., Abdel-Aziz, A., Acquaye, A., Allwood, J. M., Ceron, J.-P., Geng, Y., Kheshgi, H., Lanza, A., Perczyk, D., Price, L., Santalla, E., Sheinbaum, C., & Tanaka, K. (2014). Industry. In O. Edenhofer, R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel, & J. C. Minx (Eds.), Climate change 2014: mitigation of climate change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.

    Google Scholar 

  • Fishman, T., Schandl, H., & Tanikawa, H. (2016). Stochastic analysis and forecasts of the patterns of speed, acceleration, and levels of material stock accumulation in society. Environmental Science & Technology, 50, 3729–3737. https://doi.org/10.1021/acs.est.5b05790.

    Article  Google Scholar 

  • Fugii, H., & Managi, S. (2015). Optimal production resource allocation for CO2 emissions reduction in manufacturing sectors. Global Environmental Change, 35, 505–513.

    Article  Google Scholar 

  • Geden, O. (2016). An actionable climate target. Nature Geoscience. https://doi.org/10.1038/ngeo2699.

  • Groenenberg, H., Phylipsen, D., & Blok, K. (2001). Differentiating commitments world wide: global differentiation of GHG emissions reductions based on the Triptych approach—a preliminary assessment. Energy Policy, 29(12), 1007–1030. https://doi.org/10.1016/S0301-4215(01)00027-1.

    Article  Google Scholar 

  • IEA. (2009). Energy technology transitions for industry. Strategies for the next industrial revolution. Paris: International Energy Agency.

    Google Scholar 

  • IEA (2012). CO2 emissions from fuel combustion. Beyond 2020 Online Database. 2012 edition. Paris: International Energy Agency.

  • IEA. (2016). Energy, climate change and environment: 2016 insights. Paris: International Energy Agency.

    Book  Google Scholar 

  • IEA. (2017). Energy technology perspectives 2017. Paris: International Energy Agency.

    Google Scholar 

  • JRC/PBL (2013). Emission Database for Global Atmospheric Research (EDGAR), Release Version 4.2 FT2010. European Commission, Joint Research Centre (JRC) / PBL Netherlands Environmental Assessment Agency.

  • Kopidou, D., Tsakanikas, A., & Diakoulaki, D. (2016). Common trends and drivers of CO2 emissions and employment: a decomposition analysis in the industrial sector of selected European Union countries. Journal of Cleaner Production, 112, 4159–4172.

    Article  Google Scholar 

  • Krabbe, O., Linthorst, G., Blok, K., Crijns-Graus, W., van Vuuren, D. P., Hohne, N., Faria, P., Aden, N., & Pineda, A. C. (2015). Aligning corporate greenhouse-gas emissions targets with climate goals. Nature Climate Change, 5, 1057–1060. https://doi.org/10.1038/nclimate2770.

    Article  Google Scholar 

  • Le Quéré, C., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Peters, G. P., Manning, A. C., Boden, T. A., Tans, P. P., Houghton, R. A., Keeling, R. F., Alin, S., Andrews, O. D., Anthoni, P., Barbero, L., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Currie, K., Delire, C., Doney, S. C., Friedlingstein, P., Gkritzalis, T., Harris, I., Hauck, J., Haverd, V., Hoppema, M., Klein Goldewijk, K., Jain, A. K., Kato, E., Körtzinger, A., Landschützer, P., Lefèvre, N., Lenton, A., Lienert, S., Lombardozzi, D., Melton, J. R., Metzl, N., Millero, F., Monteiro, P. M. S., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S., O’Brien, K., Olsen, A., Omar, A. M., Ono, T., Pierrot, D., Poulter, B., Rödenbeck, C., Salisbury, J., Schuster, U., Schwinger, J., Séférian, R., Skjelvan, I., Stocker, B. D., Sutton, A. J., Takahashi, T., Tian, H., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., & Zaehle, S. (2016). Global carbon budget 2016. Earth System Science Data, 8, 605–649. https://doi.org/10.5194/essd-8-605-2016 http://www.earth-syst-sci-data.net/8/605/2016/essd-8-605-2016.pdf.

    Article  Google Scholar 

  • Matos, G. R., (2015). Historical global statistics for mineral and material commodities (2015 version): U.S. Geological Survey Data Series 896, at https://doi.org/10.3133/ds896.

  • McKinsey and Company (2009). Pathways to a low-carbon economy: version 2 of the global greenhouse gas abatement cost curve. McKinsey Report.

  • Nordhaus, WD. (1977). Economic growth and climate: the carbon dioxide problem. The American Economic Review, 67(1):341–346. Papers and Proceedings of the Eighty-ninth Annual Meeting of the American Economic Association.

  • OECD (2015). Excess capacity in the global steel industry and the implications of new investment projects. OECD Science, Technology and Industry Policy Papers, No. 18, OECD Publishing.

  • Park, S. H. (1992). Decomposition of industrial energy consumption: an alternative method. Energy Economics, 14, 265–270.

    Article  Google Scholar 

  • Pauliuk, S., Milford, R. L., Muller, D. B., & Allwood, J. M. (2013). The Steel Scrap Age. Environmental Science and Technology, 2013(47), 3448–3454. https://doi.org/10.1021/es303149z.

    Article  Google Scholar 

  • Randers, J. (2012). Greenhouse gas emissions per unit of value added (GEVA)—a corporate guide to voluntary climate action. Energy Policy, 48, 46–55.

    Article  Google Scholar 

  • Rockström, J., Steffen, W., Noone, K., Persson, Å., Chapin, F. S., Lambin, E. F., Lenton, T. M., Scheffer, M., Folke, C., Schellnhuber, H., Nykvist, B., De Wit, C. A., Hughes, T., van der Leeuw, S., Rodhe, H., Sorlin, S., Snyder, P. K., Costanza, R., Svedin, U., Falkenmark, M., Karlberg, L., Corell, R. W., Fabry, V. J., Hansen, J., Walker, B., Liverman, D., Richardson, K., Crutzen, P., & Foley, J. (2009). Planetary boundaries: exploring the safe operating space for humanity. Ecology and Society, 14(2), 32 http://www.ecologyandsociety.org/vol14/iss2/art32/.

    Article  Google Scholar 

  • Rodrik, D. (2016). Premature deindustrialization. Journal of Economic Growth, 21, 1–33. https://doi.org/10.1007/s10887-015-9122-3.

    Article  Google Scholar 

  • Rogelj, J., Schaeffer, M., Friedlingstein, P., Gillett, N. P., van Vuuren, D. P., Riahi, K., Allen, M., & Knutti, R. (2016). Differences between carbon budget estimates unravelled. Nature Climate Change, 6, 245–252.

    Article  Google Scholar 

  • Sugiyama, M., Akashi, O., Wada, K., Kanudia, A., Li, J., & Weyant, J. (2014). Energy efficiency potentials for global climate change mitigation. Climatic Change, 123, 397–411. https://doi.org/10.1007/s10584-013-0874-5.

    Article  Google Scholar 

  • United Nations Environment Programme (UNEP) (2013). Global chemicals outlook—towards sound management of chemicals. ISBN: 978-92-807-3320-4. http://www.unep.org/chemicalsandwaste/sites/unep.org.chemicalsandwaste/files/publications/GCO_web.pdf

  • United States Bureau of Labor, Bureau of Labor Statistics (BLS) (2016). Occupational Employment Statistics. https://www.bls.gov/oes/.

  • United States Department of Energy, Energy Information Administration (EIA) (2017a). Monthly Energy Review (MER). https://www.eia.gov/totalenergy/data/monthly/.

  • United States Department of Energy, Energy Information Administration (EIA) (2017b). Annual Energy Outlook (AEO). https://www.eia.gov/outlooks/aeo/.

  • United States Department of Commerce, Bureau of Economic Analysis (BEA) (2006). Employment Estimates for 1948-1997 Based on the North American Industry Classification System. “GDPbyInd_VA_NAICS_47to97R.xls” via http://www.bea.gov/industry/NAICSemployment_datarelease.htm.

  • United States Department of Commerce, Bureau of Economic Analysis (BEA) (2017). Gross-Domestic-Product-(GDP)-by-Industry Data. https://www.bea.gov/industry/gdpbyind_data.htm.

  • United States Geological Survey (USGS) (2016). Minerals Yearbook 2016. https://minerals.usgs.gov/minerals/pubs/myb.html.

  • United States Environmental Protection Agency (EPA) (2017). Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2015. https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks-1990-2015.

  • Victor, D. G., & Kennel, C. F. (2014). Climate policy: ditch the 2 °C warming goal. Nature, 514, 30–31. https://doi.org/10.1038/514030a.

    Article  Google Scholar 

  • World Bank (2017). World Development Indicators. http://databank.worldbank.org/data/reports.aspx?source=worlddevelopment-indicators.

  • World Business Council for Sustainable Development (WBCSD) and World Resources Institute (WRI) (2013). A Corporate Accounting and Reporting Standard, Revised Edition. https://www.ghgprotocol.org/standards/corporate-standard.

  • World Steel Association (WSA) (2016). Steel Statistical Yearbook 2016. https://www.worldsteel.org/steel-bytopic/statistics/steel-statistical-yearbook-.html.

  • Worrell, E., Price, L., Martin, N., Farla, J., & Schaeffer, R. (1997). Energy Intensity in the Iron and Steel Industry: A Comparison of Physical and Economic Indicators. Energy Policy, Cross-country comparisons of indicators of energy use, energy efficiency and CO2 emissions. 25(7), 727–44. https://doi.org/10.1016/S0301-4215(97)00064-5.

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Aden, N. Necessary but not sufficient: the role of energy efficiency in industrial sector low-carbon transformation. Energy Efficiency 11, 1083–1101 (2018). https://doi.org/10.1007/s12053-017-9570-z

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