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Marginally Adjusted Average LCA - Bridging the Gulf Between Attributional and Consequential LCA

Received: 2 May 2021    Accepted: 17 May 2021    Published: 27 May 2021
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Abstract

Life Cycle Assessment (LCA) can often reveal unexpected or perverse outcomes from environmental initiatives. There are two main approaches to LCA: Attributional (ALCA) typically measures the impacts arising from producing a functional unit of product from average market suppliers and technologies. Consequential (CLCA) measures the marginal impacts to produce an additional functional unit of product, assuming that the resources consumed will come from new marginal supplies/technologies. As a result, ALCA and CLCA studies can give very different outcomes. The choice of method used for different LCA applications has divided practitioners and gives conflicting advice to decision-takers. The premise of this paper is that new production only causes marginal technologies to enter a market if the new producer specifically contracts the new marginal technology resources (e.g. Google sponsoring Solar Power for its operations). If the producer still purchases resources from average markets, then it is the aggregate demand in each market that motivates the entry of new marginal technologies and the effects of any addition should be shared with all co-consumers. The additional resources consumed are really the marginally adjusted average (MAA), not just the marginal. CLCA MAA results will usually closely resemble ALCA results, because entire markets are usually only perturbed to a small degree to meet new demand. In rare cases, where the existing market is substantially perturbed by an added demand, the CLCA results will differ significantly from the ALCA results. Many advantages are given for use of MAA to assess CLCA impacts, not least being to diminish the controversy between ALCA and CLCA outcomes.

Published in Engineering Science (Volume 6, Issue 2)
DOI 10.11648/j.es.20210602.11
Page(s) 17-26
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Consequential LCA, Attributional LCA, Marginal, Average, Marginally Adjusted Average, CLCA, ALCA, MAA

References
[1] ISO 2006a. ISO 14040 International Standard. In: Environmental Management – Life Cycle Assessment – Principles and Framework. International Organisation for Standardization, Geneva, Switzerland.
[2] ISO. 2006b. ISO 14044 International Standard. In: Environmental Management – Life Cycle Assessment – Requirements and Guidelines. International Organisation for Standardisation, Geneva, Switzerland.
[3] Curran M A, Mann M, Norris G. 2005. The international workshop on electricity data for life cycle inventories. J. Cleaner Prod. 13 (8), 853–862
[4] UNEP. 2011. www.unep.org/pdf/Global-Guidance-Principles-for-LCA.pdf.
[5] Finnveden G, Hauschild M, Ekvall T, Guinée J, Heijungs R, Hellweg S, Koehler A, Pennington D, Suh S. 2009. Recent developments in Life Cycle Assessment. Journal of environmental management 91 1-21101016/jjenvman2009618.
[6] Consoli F, Allen D, Boustead I, Fava J, Franklin W, Jensen A A, de Oude N, Parrish R, Perriman R, Postlethwaite D, Quay B, Sie´guin J, Vigon B (Eds.). 1993. Guidelines for Life Cycle Assessment. A Code of Practice. SETAC Press, Pensacola, FL.
[7] Guine´e J B, Gorre´e M, Heijungs R, Huppes G, Kleijn R, de Koning A, van Oers L, Wegener Sleeswijk A, Suh S, Udo de Haes H A, de Bruijn J A, van Duin R, Huijbregts M A J. 2002. Handbook on Life Cycle Assessment: Operational Guide to the ISO Standards. Series: Eco-efficiency in Industry and Science. Kluwer Academic Publishers, Dordrecht.
[8] Lundie S, Ciroth A, Huppes G. 2007. Inventory methods in LCA: towards consistency and improvement – Final Report. UNEP-SETAC Life Cycle Initiative.
[9] Weidema B P. 2003. Market Information in Life Cycle Assessment. In: Environmental Project No. 863. Danish Environmental Protection Agency, Copenhagen.
[10] Ekvall T, Tillman A M, Molander S. 2005. Normative ethics and methodology for life cycle assessment. J. Cleaner Prod 13 (13–14), 1225–1234.
[11] Sande´n B and Karlstro¨m M. 2007. Positive and negative feedback in consequential life-cycle assessment. J. Clean. Prod. 15, 1469–1481.
[12] Tillman A M. 2000. Significance of decision-making for LCA methodology. Environ. Impact Assess. Rev. 20, 113–123.
[13] Ekvall T and Weidema B. 2004. System boundaries and input data in consequential life cycle inventory analysis. Int J Life Cycle Assess 9 (3): 161–171.
[14] Weidema B P, Frees N, Nielsen A M. 1999. Marginal production technologies for life cycle inventories. Int. J. Life Cycle Assess. 4, 448–456.
[15] Eriksson O, Finnveden G, Ekvall T, Bjo¨ rklund A. 2007. Life Cycle Assessment of fuels for district heating: a comparison of waste incineration, biomass- and natural gas combustion. Energy Policy 35, 1346–1362.
[16] Ekvall T. 2000. A market-based approach to allocation at open-loop recycling. Resour. Conserv. Recycling 29 (1–2), 93–111.
[17] Ekvall T and Andrae A. 2006. Attributional and consequential environmental assessment of the shift to lead-free solders. Int. J. LCA 11 (5), 344–353.
[18] Lesage P, Ekvall T, Deschenes L, Samson R. 2007a. Environmental assessment of brownfield rehabilitation using two different life cycle inventory models: Part I: Methodological approach. Int. J. Life Cycle Assess 12, 391–398.
[19] Lesage P, Ekvall T, Deschenes L, Samson R. 2007b. Environmental assessment of brownfield rehabilitation using two different life cycle inventory models: Part 2: Case study. Int. J. Life Cycle Assess. 12, 497–513.
[20] Kløverpris J, Wenzel H, Nielsen P H. 2008. Life cycle inventory modelling of land use induced by crop consumption. Part 1: Conceptual analysis and methodological proposal. Int. J. LCA 13, 13–21.
[21] Ibenholt K. 2002. Materials flow analysis and economic modelling. In: Ayres, R. U., Ayres, L. W. (Eds.), Handbook of Industrial Ecology. Edward Elgar, Cheltenham, pp. 177–184.
[22] Thiesen J, Christensen T S, Kristensen T G, Andersen R D, Brunoe B, Gregersen T K, Thrane M, Weidema B P. 2008. Rebound effects of price differences. Int. J. LCA 13, 104–114.
[23] Spielmann M, de Haan P, Scholz R W. 2008. Environmental rebound effects of high-speed transport technologies: a case study of climate change rebound effects of a future underground maglev train system. J. Cleaner Prod. 16, 1388– 1398.
[24] Weidema B P, Wesnæs M, Hermansen J, Kristensen T, Halberg N, Eder P, Delgado L. 2008. Environmental improvement potentials of meat and dairy products. Institute for Prospective Technological Studies, Sevilla.
[25] Claeson U. 2000. Analyzing Technological Change Using Experience Curves – A Study of the Combined Cycle Gas Turbine Technology. LicEng thesis, Chalmers University of Technology, Gothenburg, Sweden.
[26] Ekvall T, Mattsson N, Mu¨nter M. 2006. Consequential modelling of Vistar combustion: a feasibility study. In: Abstracts – 16th Annual Meeting of SETAC – Europe, The Hague, The Netherlands, May 2006, p. 281.
[27] Mattsson N. 1997. Internalizing Technological Development in Energy Systems Models. LicEng thesis, Chalmers University of Technology, Gothenburg, Sweden
[28] Stewart M and Weidema B. 2005. A consistent framework for assessing the impacts from resource use. Int. J. LCA 10, 240–247.
[29] Steen B. 1999. A Systematic Approach to Environmental Priority Strategies in Product Development (EPS). Version 2000 – General System Characteristics/ Models and Data of the Default Method. CPM Report 1999 and CPM Report 1999, Chalmers University of Technology, Gothenburg, Sweden, p. 4 and 5.
[30] Goedkoop M and Spriensma R. 2000. The Eco-indicator 99 – A Damage-oriented Method for Life Cycle Impact Assessment. Methodology Report, second ed., 17- 4-2000. Pre´ Consultants, B. V. Amersfoort, The Netherlands.
[31] Rebitzer G, Ekvall T, Frischknecht R, Hunkeler D, Norris G, Rydberg T, Schmidt W P, Suh S, Weidema B P, Pennington D W. 2004. Life cycle assessment – Part 1: Framework, goal & scope definition, inventory analysis, and applications. Environ. Int. 30, 701–720.
[32] Mattsson N, Unger T, Ekvall T. 2003. Effects of perturbations in a dynamic system – the case of nordic power production. In: Unger, T. (Ed.), Common Energy and Climate Strategies for the Nordic Countries – A Model Analysis. PhD thesis, Chalmers University of Technology, Go¨teborg, Sweden.
[33] Yang Y. 2017a. Personal Communiction.
[34] Yang Y. 2017b. Does hybrid LCA with a complete system boundary yield adequate results for product promotion? Int J Life Cycle Assess 22 (3): 456–406.
[35] Weidema B P and Schmidt J H. 2010. Avoiding Allocation in Life Cycle Assessment Revisited. Journal of Industrial Ecology, 14: 192–195. doi: 10.1111/j.1530-9290.2010.00236.x.
[36] Consequential-LCA (2015). Marginal Suppliers. Last updated: 2015-06-18 https://consequential-lca.org/clca/marginal-suppliers/.
[37] Weidema. 2017. Personal communications.
[38] EN 15804: 2012. 2012 Sustainability of construction works – Environmental product declaration – Core rules for the product category of construction products.
[39] Google. 2017. https://environment.google/projects/announcement-100/.
[40] Zamagni A, Guinée J, Heijungs R, Masoni P, Raggi A. 2012. Lights and shadows in consequential LCA Int J Life Cycle Assess 17 (3): 904–918.
Cite This Article
  • APA Style

    Nigel Howard. (2021). Marginally Adjusted Average LCA - Bridging the Gulf Between Attributional and Consequential LCA. Engineering Science, 6(2), 17-26. https://doi.org/10.11648/j.es.20210602.11

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    ACS Style

    Nigel Howard. Marginally Adjusted Average LCA - Bridging the Gulf Between Attributional and Consequential LCA. Eng. Sci. 2021, 6(2), 17-26. doi: 10.11648/j.es.20210602.11

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    AMA Style

    Nigel Howard. Marginally Adjusted Average LCA - Bridging the Gulf Between Attributional and Consequential LCA. Eng Sci. 2021;6(2):17-26. doi: 10.11648/j.es.20210602.11

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  • @article{10.11648/j.es.20210602.11,
      author = {Nigel Howard},
      title = {Marginally Adjusted Average LCA - Bridging the Gulf Between Attributional and Consequential LCA},
      journal = {Engineering Science},
      volume = {6},
      number = {2},
      pages = {17-26},
      doi = {10.11648/j.es.20210602.11},
      url = {https://doi.org/10.11648/j.es.20210602.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.es.20210602.11},
      abstract = {Life Cycle Assessment (LCA) can often reveal unexpected or perverse outcomes from environmental initiatives. There are two main approaches to LCA: Attributional (ALCA) typically measures the impacts arising from producing a functional unit of product from average market suppliers and technologies. Consequential (CLCA) measures the marginal impacts to produce an additional functional unit of product, assuming that the resources consumed will come from new marginal supplies/technologies. As a result, ALCA and CLCA studies can give very different outcomes. The choice of method used for different LCA applications has divided practitioners and gives conflicting advice to decision-takers. The premise of this paper is that new production only causes marginal technologies to enter a market if the new producer specifically contracts the new marginal technology resources (e.g. Google sponsoring Solar Power for its operations). If the producer still purchases resources from average markets, then it is the aggregate demand in each market that motivates the entry of new marginal technologies and the effects of any addition should be shared with all co-consumers. The additional resources consumed are really the marginally adjusted average (MAA), not just the marginal. CLCA MAA results will usually closely resemble ALCA results, because entire markets are usually only perturbed to a small degree to meet new demand. In rare cases, where the existing market is substantially perturbed by an added demand, the CLCA results will differ significantly from the ALCA results. Many advantages are given for use of MAA to assess CLCA impacts, not least being to diminish the controversy between ALCA and CLCA outcomes.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Marginally Adjusted Average LCA - Bridging the Gulf Between Attributional and Consequential LCA
    AU  - Nigel Howard
    Y1  - 2021/05/27
    PY  - 2021
    N1  - https://doi.org/10.11648/j.es.20210602.11
    DO  - 10.11648/j.es.20210602.11
    T2  - Engineering Science
    JF  - Engineering Science
    JO  - Engineering Science
    SP  - 17
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    PB  - Science Publishing Group
    SN  - 2578-9279
    UR  - https://doi.org/10.11648/j.es.20210602.11
    AB  - Life Cycle Assessment (LCA) can often reveal unexpected or perverse outcomes from environmental initiatives. There are two main approaches to LCA: Attributional (ALCA) typically measures the impacts arising from producing a functional unit of product from average market suppliers and technologies. Consequential (CLCA) measures the marginal impacts to produce an additional functional unit of product, assuming that the resources consumed will come from new marginal supplies/technologies. As a result, ALCA and CLCA studies can give very different outcomes. The choice of method used for different LCA applications has divided practitioners and gives conflicting advice to decision-takers. The premise of this paper is that new production only causes marginal technologies to enter a market if the new producer specifically contracts the new marginal technology resources (e.g. Google sponsoring Solar Power for its operations). If the producer still purchases resources from average markets, then it is the aggregate demand in each market that motivates the entry of new marginal technologies and the effects of any addition should be shared with all co-consumers. The additional resources consumed are really the marginally adjusted average (MAA), not just the marginal. CLCA MAA results will usually closely resemble ALCA results, because entire markets are usually only perturbed to a small degree to meet new demand. In rare cases, where the existing market is substantially perturbed by an added demand, the CLCA results will differ significantly from the ALCA results. Many advantages are given for use of MAA to assess CLCA impacts, not least being to diminish the controversy between ALCA and CLCA outcomes.
    VL  - 6
    IS  - 2
    ER  - 

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  • Clarity Environment Consultancy, Beacon Hill, New South Wales, Australia

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