Identifying marginal suppliers of construction materials: consistent modeling and sensitivity analysis on a Belgian case

  • Matthias Buyle
  • Massimo Pizzol
  • Amaryllis Audenaert
LCI METHODOLOGY AND DATABASES

Abstract

Purpose

The identification of marginal suppliers is a key element of consequential LCA. This study investigates how systematically the identification of marginal suppliers can be performed across different products, while maintaining consistent modeling choices. Some products relevant for the Belgian construction sector are taken as a case study.

Methods

To gain insight in the current practice of identifying marginal suppliers, 30 recent studies have been reviewed. Based on the findings of the review, a method was proposed to identify geographical market boundaries from trade data and sensitive suppliers from production data. Both retrospective and prospective approaches to anticipate the future effect of a change in demand were taken into account. The method was applied to compute both a retrospective and a prospective marginal supplier’s mix per product. Finally, the effect of the modeling choices on the size of geographical market boundaries and marginal mixes was estimated via regression analysis.

Results and discussion

The forecasts and marginal mixes obtained matched with those from the existing literature, although clear differences in results are observed between the retrospective and prospective approach. Deviations from default assumptions in LCA were observed as well, such as large regional geographical markets for cement and aggregates instead of local ones. The statistical sensitivity analysis showed that identifying geographical market boundaries has the largest effect on the final marginal mix and that these markets are relative stable over time.

Conclusions

The proposed method and corresponding sensitivity analysis is an attempt to gain insight into the effect of modeling choices in the context of the identification of marginal suppliers for consequential LCA. It can in principle be applied to any product for which trade and production data are available. The proposed method helps to identify marginal mixes on a consistent and transparent way, to improve the robustness of the results in future consequential LCAs.

Keywords

Consequential Construction sector Geographical market delimitation Life cycle assessment Marginal suppliers Sensitivity analysis 

Notes

Acknowledgements

Thanks to Erik Fransen for providing insightful and useful comments on the statistical analysis. We acknowledge three anonymous reviewers for the constructive suggestions and the stimulating discussion. This work was funded by the travel grant no V407616N of the Research Foundation - Flanders (FWO).

Supplementary material

11367_2017_1389_MOESM1_ESM.zip (61.4 mb)
ESM 1 (ZIP 61.4 MB)

References

  1. Alvarez-Gaitan JP, Short MD, Peters GM et al (2014) Consequential cradle-to-gate carbon footprint of water treatment chemicals using simple and complex marginal technologies for electricity supply. Int J Life Cycle Assess 19:1974–1984CrossRefGoogle Scholar
  2. Baeza R, Martelli M, Rilo R (2013) The cement sector: a strategic contributor to Europe’s future. The Boston Consulting Group, New York, p 51. https://cembureau.eu/media/1505/strategiccontributoreurope_bcg_2013-03-06.pdf. Accessed 21 Aug 2017
  3. Baeza R, Marten I, Rilo R, Yanez M, and Wittum L (2008) Assessment of the impact of the 2013–2020 ETS proposal on the European cement industry. Final project report. Boston Consulting Group, New York, p 53Google Scholar
  4. Bolscher H, Graichen V, Hay G, Healy S, Lenstra J, Meindert L, Regeczi D, von Schickfus M-T, Schumacher K, Timmons-Smakman F (2013) Carbon leakage evidence project. Factsheets for selected sectors. Rotterdam, Ecorys; European Commission, DG Climate Action, p 192. https://ec.europa.eu/clima/sites/clima/files/ets/allowances/leakage/docs/cl_evidence_factsheets_en.pdf. Accessed 21 Aug 2017
  5. Boyer M, Ponssard J (2013) Economic analysis of the European cement industry. Montréal, CanadaGoogle Scholar
  6. Brown TJ, Idoine NE, Bide T et al (2010) European mineral statistics 2004–2008. British Geological Survey, NottinghamGoogle Scholar
  7. Brown TJ, Hobbs SF, Mills AJ et al (2015) European mineral statistics 2009–2013. British Geological Survey, NottinghamGoogle Scholar
  8. Buongiorno J, Zhu S, Raunikar R, Prestemon J (2012) Outlook to 2060 for world forests and forest industries: a technical document supporting the Forest Service 2010 RPA assessment. Asheville, U.S. Department of Agriculture Forest Service, Southern Research Station, p 132. https://permanent.access.gpo.gov/gpo30965/gtr_srs151.pdf. Accessed 21 Aug 2017
  9. Buyle M, Braet J, Audenaert A, Debacker W (2016) Strategies for optimizing the environmental profile of dwellings in a Belgian context: a consequential versus an attributional approach. J Clean Prod.  https://doi.org/10.1016/j.jclepro.2016.08.114
  10. Capros P, De Vita A, Tasios N, Papadopoulos D, Siskos P, Apostolakmi E, Zampara M, Paroussos L, Fragiadakis K, Kouvaritakis N, Hoglund-Isaksson L, Winiwarter W, Purohit P, Bottcher H, Frank S, Havlik P, Gusti M, Witzke HP (2013) EU Energy, transport and GHG emissions: Trends to 2050, reference scenario 2013. European Commission, Luxembourg, p 176.  https://doi.org/10.2833/17897. https://ec.europa.eu/energy/sites/ener/files/documents/trends_to_2050_update_2013.pdf
  11. Cembureau (2012) Cements for a low-carbon Europe. Brussels, The European Cement Association, p 28. https://cembureau.eu/media/1501/cembureau_cementslowcarboneurope.pdf. Accessed 21 Aug 2017
  12. CEPII (2016) BACI World trade database http://www.cepii.fr/cepii/en/bdd_modele/presentation.asp?id=1. Accessed 23 Dec 2016
  13. Chalmers NG, Brander M, Revoredo-Giha C (2015) The implications of empirical and 1:1 substitution ratios for consequential LCA: using a 1% tax on whole milk as an illustrative example. Int J Life Cycle Assess 20:1268–1276CrossRefGoogle Scholar
  14. Cook G (2011) Investment, carbon pricing and leakage - a cement sector perspective. UK, CambridgeGoogle Scholar
  15. Crossin E (2015) The greenhouse gas implications of using ground granulated blast furnace slag as a cement substitute. J Clean Prod 95:101–108CrossRefGoogle Scholar
  16. Curran M, Mann M, Norris G (2005) The international workshop on electricity data for life cycle inventories. J Clean Prod 13:853–862CrossRefGoogle Scholar
  17. Dalgaard R, Schmidt J, Flysjo A (2014) Generic model for calculating carbon footprint of milk using four different life cycle assessment modelling approaches. J Clean Prod 73:146–153CrossRefGoogle Scholar
  18. De Smet L, Bogaert S, Vandenbroucke D, Van Hyfte, A, De Coster K (2009) Onderzoek duurzame bevoorrading: gebruik lokale oppervlaktedelfstoffen of import van minerale grondstoffen [research sustainable supply: use of local surface minerals or import of mineral raw materials]. Brussels, Departement Leefmilieu Natuur en Energie - afdeling Land en Bodembescherming Ondergrond Natuurlijke Rijkdommen. p 190. http://www.ebl.vlaanderen.be/publications/documents/64687. Accessed 21 Aug 2017
  19. Deng Y, Tian Y (2015) Assessing the environmental impact of flax fibre reinforced polymer composite from a consequential life cycle assessment perspective. Sustainability 7:11462–11483CrossRefGoogle Scholar
  20. Devogelaer D, and Gusbin D (2014) Het Belgische energiesysteem in 2050: Waar naartoe? - Beschrijving van een Referentiescenario voor België [The Belgian energy system in 2050: where to go?- Description of a reference scenario for Belgium]. Brussels, Federal Planning Bureau, p 125. http://www.plan.be/publications/publication-1388-nlhet+belgische+energiesysteem+in+2050+waar+naartoe+beschrijving+van+een+referentiescenario+voor+belgie. Accessed 21 Aug 2017
  21. Devogelaer D, and Gusbin D (2015) 2030 climate and energy framework for Belgium: impact assessment of a selection of policy scenarios up to 2050. Brussels, Federal Planning Bureau, p 89. http://www.plan.be/admin/uploaded/201504270958240.WP_1503_10941.pdf. Accessed 21 Aug 2017
  22. Earles JM, Halog A (2011) Consequential life cycle assessment: a review. Int J Life Cycle Assess 16:445–453CrossRefGoogle Scholar
  23. Ekvall T, Weidema BPB (2004) System boundaries and input data in consequential life cycle inventory analysis. Int J Life Cycle Assess 9:161–171CrossRefGoogle Scholar
  24. ENTSO-E (2016) Statistical database https://www.entsoe.eu/data/data-portal/Pages/default.aspx. Accessed 23 Dec 2016
  25. Eriksson LO, Gustavsson L, Hänninen R et al (2012) Climate change mitigation through increased wood use in the European construction sector-towards an integrated modelling framework. Eur J For Res 131:131–144CrossRefGoogle Scholar
  26. Escobar N, Ribal J, Clemente G, Sanjuán N (2014) Consequential LCA of two alternative systems for biodiesel consumption in Spain, considering uncertainty. J Clean Prod 79:61–73CrossRefGoogle Scholar
  27. FAO (2012) The Russian Federation Forest Sector: Outlook Study to 2030. Food and Agriculture Organization of the United Nations, p 93. http://www.fao.org/docrep/016/i3020e/i3020e00.pdf. Accessed 21 Aug 2017
  28. FAO (2016) FAOSTAT database. In: Database. http://www.fao.org/faostat/en/#home. Accessed 22 Dec 2016
  29. FIM Services Limited (2015) Global Timber Outlook. May 2015. Burford, United KingdomGoogle Scholar
  30. Firoz AS (2014) Long term perspectives for Indian steel industry. New Delhi, Government of India Ministry of Steel, p 100. https://mme.iitm.ac.in/shukla/LongTermPerspectives(3).pdf. Accessed 21 Aug 2017
  31. FOA (2009) State of the World’s forests 2009. Rome, Food and Agriculture Organization, p 168. http://www.fao.org/3/a-i0350e.pdf. Accessed 21 Aug 2017
  32. Global Cement (2015) Turkey’s cement industry: Onwards and upwards http://www.globalcement.com/magazine/articles/929-turkeys-cement-industry-onwards-and-upwards. Accessed 26 Jan 2016
  33. Hänninen R, Hetemäki L, Hurmekoski E Mutanen A, Nayha A, Forsstrom J, Viitanen J, Koljonen T (2014) European Forest industry and Forest bioenergy outlook up to 2050: a synthesis. Helsinki, Finland, leen/Fibic Research Report no D 1.1.1. http://jukuri.luke.fi/handle/10024/504484. Accessed 21 Aug 2017
  34. HeidelbergCement (2016) HeidelbergCement 2015 Trading Statement https://www.heidelbergcement.com/en/system/files_force/assets/document/7a/c0/fy_2015_results.pdf?download=1. Accessed 15 Mar 2017
  35. Hetemäki L (2014) Future of the European Forest-based sector: structural changes Towords bioeconomy. Joensuu, European Forest Institute, p 110. http://www.efi.int/files/attachments/publications/efi_wsctu_6_2014.pdf
  36. Hurmekoski E (2016) Long-term outlook for wood construction in Europe. Dissertationes Forestales 211. University of Eastern Finland, p 57.  http://dx.doi.org/10.14214/df.211. http://www.dissertationesforestales.fi/pdf/article1994.pdf
  37. IEA (2015a) Energy statistics of non-OECD countries. 2015 Edition. Paris, International Energy Agency.  https://doi.org/10.1787/energy_stats_oecd-2015-en
  38. IEA (2015b) World energy outlook 2015. Paris, International Energy Agency, p 726. http://www.worldenergyoutlook.org/weo2015/
  39. IHS Economics (2013) Global construction outlook: executive outlook. Lexington, IHS Economics, p 30Google Scholar
  40. Ito K, Morita Y, Yanagisawa A, Suehiro S, Komiyama R, Shen Z (2006) Japan long-term energy outlook a projection up to 2030 under environmental constraints and changing energy markets. Tokyo, The Institute of Energy Economics, Japan, p 70. http://eneken.ieej.or.jp/data/en/data/pdf/342.pdf
  41. Kamp B, Vanthournout E, Couderé K, Gregoor C (2006) Analyse van vraag naar oppervlaktedelfstoffen in Vlaanderen [Analysis of demand for surface minerals in Flanders]. Brussels, ANRE / ALBON, p 72. http://www.ebl.vlaanderen.be/publications/documents/61729
  42. LNA-ALBON (2014) 2de Algemeen Oppervlaktedelfstoffenplan [2nd General plan for surface materials]. Brussels, Departement Leefmilieu Natuur en Energie - afdeling Land en Bodembescherming Ondergrond Natuurlijke Rijkdommen, p 248Google Scholar
  43. Lund H, Mathiesen BV, Christensen P, Schmidt JH (2010) Energy system analysis of marginal electricity supply in consequential LCA. Int J Life Cycle Assess 15:260–271CrossRefGoogle Scholar
  44. Manninen H (2014) Long-term outlook for engineered wood products in Europe Technical Report 91. Joensuu, European Forest Institute, p 46. http://www.efi.int/files/attachments/publications/efi_tr_91_2014_manninen.pdf. Accessed 21 Aug 2017]
  45. Mazerolle M (2006) Improving data analysis in herpetology: using Akaike’s Information Criterion (AIC) to assess the strength of biological hypotheses. Amphibia-Reptilia 27:169–180CrossRefGoogle Scholar
  46. Menten F, Tchung-Ming S, Lorne D, Bouvart F (2015) Lessons from the use of a long-term energy model for consequential life cycle assessment: the BTL case. Renew Sust Energ Rev 43:942–960CrossRefGoogle Scholar
  47. OECD (2015) Future investment projects in the global steel industry and implications for the balance of steelmaking processes. OECD Sci Technol Ind Policy Pap 18:38. doi: 10.1787/5js65x46nxhj-en. http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=DSTI/SU/SC(2014)16/FINAL&docLanguage=En. Accessed 21 Aug 2017
  48. Pizzol M, Scotti M (2017) Identifying marginal suppliers of wood products via trade network analysis. Int J Life Cycle Assess 22:1146–1158CrossRefGoogle Scholar
  49. Prateep Na Talang R, Pizzol M, Sirivithayapakorn S (2016) Comparative life cycle assessment of fired brick production in Thailand. Int J Life Cycle Assess.  https://doi.org/10.1007/s11367-016-1197-3
  50. Rajagopal D (2017) A step towards a general framework for consequential life cycle assessment. J Ind Ecol 21(2):261–271CrossRefGoogle Scholar
  51. Rodríguez G (2007) Lecture notes on generalized linear models. http://data.princeton.edu/wws509/notes/. Accessed 20 Jan 2017
  52. Sandin G, Peters GM, Svanström M (2013) Moving down the cause-effect chain of water and land use impacts: an LCA case study of textile fibres. Resour Conserv Recycl 73:104–113CrossRefGoogle Scholar
  53. Schmidt JH (2015) Life cycle assessment of five vegetable oils. J Clean Prod 87:130–138CrossRefGoogle Scholar
  54. Schmidt JH, Thrane M (2009) Life cycle assessment of aluminium production in new Alcoa smelter in Greenland. Aalborg, 2.-0 LCA consultants; Aalborg University, p 202. http://lca-net.com/publications/show/life-cycle-assessment-aluminium-production-new-alcoa-smelter-greenland/
  55. Sevigné-Itoiz E, Gasol CM, Rieradevall J, Gabarrell X (2015) Contribution of plastic waste recovery to greenhouse gas (GHG) savings in Spain. Waste Manag 46:557–567CrossRefGoogle Scholar
  56. Styles D, Gibbons J, Williams AP et al (2015) Consequential life cycle assessment of biogas, biofuel and biomass energy options within an arable crop rotation. GCB Bioenergy 7:1305–1320CrossRefGoogle Scholar
  57. Supekar SD, Skerlos SJ (2014) Market-driven emissions from recovery of carbon dioxide gas. Environ Sci Technol 48:14615–14623CrossRefGoogle Scholar
  58. Taylor LE, Brown TJ, Lusty PAJ et al (2006) European mineral statistics 2000–2004. Keyworth, NottinghamGoogle Scholar
  59. Tonini D, Hamelin L, Alvarado-Morales M, Astrup TF (2016) GHG emission factors for bioelectricity, biomethane, and bioethanol quantified for 24 biomass substrates with consequential life-cycle assessment. Bioresour Technol 208:123–133CrossRefGoogle Scholar
  60. Turk J, Cotič Z, Mladenovič A, Šajna A (2015) Environmental evaluation of green concretes versus conventional concrete by means of LCA. Waste Manag 45:194–205CrossRefGoogle Scholar
  61. U.S. Geological Survey (2016) Minerals Yearbook-Cement https://minerals.usgs.gov/minerals/pubs/commodity/cement/index.html#myb. Accessed 23 Dec 2016
  62. UNECE/FAO (2011) The European forest sector outlook study II -2010-2030. Geneva, United Nations Economic Commission for Europe/ Food and Agriculture Organization of the United Nations, p 111. https://www.unece.org/fileadmin/DAM/timber/publications/sp-28.pdf. Accessed 21 Aug 2017
  63. UNECE/FAO (2012) The North American Forest Sector Outlook Study. 2006-2030. Geneva, United Nations Economic Commission for Europe/ Food and Agriculture Organization of the United Nations, p 68Google Scholar
  64. UNECE/FAO (2014) Competitiveness of the European forest sector - a contribution to EFSOS II. Geneva timber and forest discussion paper 62. Geneva, SwitserlandGoogle Scholar
  65. United Nations (2016) UN Comtrade Database http://comtrade.un.org/. Accessed 17 Mar 2016
  66. USGS (2014) Mineral commodity summaries. Cement, U.S. Geological Survey. http://minerals.usgs.gov/minerals/pubs/commodity/cement/
  67. Van Ruijven BJ, Van Vuuren DP, Boskaljon W et al (2016) Long-term model-based projections of energy use and CO2 emissions from the global steel and cement industries. Resour Conserv Recycl 112:15–36CrossRefGoogle Scholar
  68. Vieira PS, Horvath A (2008) Assessing the end-of-life impacts of buildings. Environ Sci Technol 42:4663–4669CrossRefGoogle Scholar
  69. Weidema BP (2003) Environmental Project No. 863. Market information in life cycle assessment. Copenhagen, Danish Environmental Protection Agency, p 147. http://www2.mst.dk/Udgiv/publications/2003/87-7972-991-6/pdf/87-7972-992-4.pdf. Accessed 21 Aug 2017
  70. Weidema BP (2004) Geographical, technological and temporal delimitation in LCA. UMIP 2003 method. Environmental News No. 74 2004. Kopenhagen, The Danish Environmental Protection Agency, p 69. http://www2.mst.dk/Udgiv/Publications/2004/87-7614-305-8/pdf/87-7614-306-6.PDF. Accessed 21 Aug 2017
  71. Weidema BP, Frees N, Nielsen A-M (1999) Marginal production technologies for life cycle inventories. Int J Life Cycle Assess 4:48–56CrossRefGoogle Scholar
  72. Weidema BP, Ekvall T, Heijungs R (2009) Guidelines for application of deepened and broadened LCA. Deliverable D18 of work package 5 of the CALCAS project. Rome, ENEA, The Italian National Agency on new Technologies, Energy and the Environment. http://www.leidenuniv.nl/cml/ssp/publications/calcas_report_d18.pdf. Accessed 21 Aug 2017
  73. Weidema BP, Bauer C, Hischier R et al (2013) Overview and methodology. Data quality guideline for the ecoinvent database version 3. St. Gallen, SwitserlandGoogle Scholar
  74. World Steel Association (2006) Steel statistical yearbook 2006. Brussels, BelgiumGoogle Scholar
  75. World Steel Association (2015a) Global steel market outlook OECD steel committee meeting. OECD Steel Committee Meeting Paris, 11 - 12 May 2015. Paris, World Steel Association, p 18Google Scholar
  76. World Steel Association (2015b) Steel statistical yearbook 2015. Brussels, World Steel Association, p 121. https://www.worldsteel.org/en/dam/jcr:3e501c1b-6bf1-4b31-8503-a2e52431e0bf/Steel+Statistical+Yearbook+2015+r3.pdf. Accessed 21 Aug 2017
  77. Zamagni A, Guinée J, Heijungs R et al (2012) Lights and shadows in consequential LCA. Int J Life Cycle Assess 17:904–918CrossRefGoogle Scholar
  78. Zink T, Maker F, Geyer R et al (2014) Comparative life cycle assessment of smartphone reuse: repurposing vs. refurbishment. Int J Life Cycle Assess 19:1099–1109CrossRefGoogle Scholar
  79. Zweig M, Agrawal A, Stall B, Bremer C, Mangers P, Beifus A, and Chauhan M (2016) Globalize or customize: finding the right balance. Global steel 2015–2016. London, Ernst & Young Global Limited, p 32. http://www.ey.com/Publication/vwLUAssets/EY-global-steel-2015-2016/$FILE/EY-global-steel-2015-2016.pdf. Accessed 21 Aug 2017

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© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Energy and Materials in Infrastructure and Buildings (EMIB), Applied EngineeringUniversity of AntwerpAntwerpBelgium
  2. 2.Department of PlanningAalborg UniversityAalborgDenmark
  3. 3.Department Engineering Management, Applied EconomicsUniversity of AntwerpAntwerpBelgium

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