A model for streamlining and automating path exchange hybrid life cycle assessment

  • André Stephan
  • Robert H. CrawfordEmail author
  • Paul-Antoine Bontinck



Life cycle assessment (LCA) is inherently complex and time consuming. The compilation of life cycle inventories (LCI) using a traditional process analysis typically involves the collection of data for dozens to hundreds of individual processes. More comprehensive LCI methods, such as input-output analysis and hybrid analysis can include data for billions of individual transactions or transactions/processes, respectively. While these two methods are known to provide a much more comprehensive overview of a product’s supply chain and related environmental flows, they further compound the complex and time-consuming nature of an LCA. This has limited the uptake of more comprehensive LCI methods, potentially leading to ill-informed environmental decision-making. A more accessible approach for compiling a hybrid LCI is needed to facilitate its wider use.


This study develops a model for streamlining a hybrid LCI by automating various components of the approach. The model is based on the path exchange hybrid analysis method and includes a series of inter-related modules developed using object-oriented programming in Python. Individual modules have been developed for each task involved in compiling a hybrid LCI, including data processing, structural path analysis and path exchange or hybridisation.

Results and discussion

The production of plasterboard is used as a case study to demonstrate the application of the automated hybrid model. Australian process and input-output data are used to determine a hybrid embodied greenhouse gas emissions value. Full automation of the node correspondence process, where nodes relating to identical processes across process and input-output data are identified, remains a challenge. This is due to varied dataset coverage, different levels of disaggregation between data sources and lack of detail of activities and coverage for specific processes. However, by automating other aspects of the compilation of a hybrid LCI, the comprehensive supply chain coverage afforded by hybrid analysis is able to be made more accessible to the broader LCA community.


This study shows that it is possible to automate various aspects of a hybrid LCI in order to address traditional barriers to its uptake. The object-oriented approach used enables the data or other aspects of the model to be easily updated to contextualise an analysis in order to calculate hybrid values for any environmental flow for any variety of products in any region of the world. This will improve environmental decision-making, critical for addressing the pressing global environmental issues of our time.


Automation Life cycle assessment Life cycle inventory Path exchange hybrid 


Authors’ contributions

RC and AS conceived the research and secured funding; RC, AS and PAB defined the model’s functionalities; AS and PAB designed, developed, programmed and tested the model; PAB conducted the case study analysis; and AS, RC and PAB wrote the paper.

Funding information

This research was supported by the Australian Research Council’s Discovery Projects funding scheme (project number DP150100962) and the Australian Research Council’s Linkage Infrastructure, Equipment and Facilities funding scheme (project number LE160100066).

Supplementary material

11367_2018_1521_MOESM1_ESM.docx (32 kb)
ESM 1 (DOCX 32 kb)


  1. Alic D, Omanovic S, Giedrimas V (2016) Comparative analysis of functional and object-oriented programming. Paper presented at the 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, Croatia, May 30th - June 3rdGoogle Scholar
  2. Atlassian (2017) SourceTreeGoogle Scholar
  3. Augspurger T et al (2017) Python Data Analysis Library vol 0.20.2Google Scholar
  4. Baboulet O (2009) Path exchange method for hybrid life-cycle assessment Norwegian University of Science and TechnologyGoogle Scholar
  5. Blengini GA, Di Carlo T (2010) The changing role of life cycle phases, subsystems and materials in the LCA of low energy buildings. Energ Buildings 42:869–880CrossRefGoogle Scholar
  6. Bontinck P-A (2018) Summary of path exchange hybrid life cycle greenhouse gas emissions inventory for Plasterboard in Australia. Figshare. Accessed 23 Feb 2018
  7. Bontinck P-A, Crawford RH, Stephan A (2017) Improving the uptake of hybrid life cycle assessment in the construction industry. Procedia Engineering 196:822–829CrossRefGoogle Scholar
  8. Crama Y, Defourny J, Gazon J (1984) Structural decompostion of multipliers in input-output or social accounting matrix analysis. Econ Appl 37:215–222Google Scholar
  9. Crawford RH (2008) Validation of a hybrid life cycle inventory analysis method. J Environ Manag 88:496–506CrossRefGoogle Scholar
  10. Crawford RH (2011) Life cycle assessment in the built environment. Spon Press, LondonCrossRefGoogle Scholar
  11. Crawford RH, Bartak EL, Stephan A, Jensen CA (2016) Evaluating the life cycle energy benefits of energy efficiency regulations for buildings. Renew Sust Energ Rev 63:435–451CrossRefGoogle Scholar
  12. Crawford RH, Bontinck P-A, Stephan A, Wiedmann T (2017) Towards an automated approach for compiling hybrid life cycle inventories. Procedia Engineering 180:157–166CrossRefGoogle Scholar
  13. Crawford RH, Bontinck P-A, Stephan A, Wiedmann T, Yu M (2018a) Hybrid life cycle inventory methods—a review. J Clean Prod 172:1273–1288CrossRefGoogle Scholar
  14. Crawford RH, Stephan A, Bontinck P-A (2018b) Improving the life cycle environmental performance of Australian construction projects. Accessed 11 May 2018
  15. Defourny J, Thorbecke E (1984) Structural path analysis and multiplier decomposition within a social accounting matrix framework. Econ J 94:111–136CrossRefGoogle Scholar
  16. Dixit MK (2017) Life cycle embodied energy analysis of residential buildings: a review of literature to investigate embodied energy parameters. Renew Sust Energ Rev 79:390–413CrossRefGoogle Scholar
  17. Dubois PF (2005) Maintaining correctness in scientific programs. Comput Sci Eng 7:80–85CrossRefGoogle Scholar
  18. Eurostat (2008) Eurostat manual of supply, use and input-output tables. Office for Official Publications of the European Communities, LuxembourgGoogle Scholar
  19. Gibon T, Schaubroeck T (2017) Lifting the fog on characteristics and limitations of hybrid LCA—a reply to “Does hybrid LCA with a complete system boundary yield adequate results for product promotion?” by Yi Yang. Int J Life Cycle Assess 22(3):456–406. Int J Life Cycle Assess 22:1005–1008CrossRefGoogle Scholar
  20. Grant T (2016) AusLCI database manual, vol 1.26, 1.26 ed. Australian Life Cycle Assessment Society (ALCAS)Google Scholar
  21. Hammond G, Jones C (2008) Inventory of carbon & energy: ICE. Sustainable Energy Research Team, Department of Mechanical Engineering, University of Bath, BathGoogle Scholar
  22. Junnila S (2004) The environmental impact of an office building throughout its life cycle. PhD thesis, Helsinki University of Technology Construction Economics and ManagementGoogle Scholar
  23. Lenzen M (2000) Errors in conventional and input-output-based life-cycle inventories. J Ind Ecol 4:127–148CrossRefGoogle Scholar
  24. Lenzen M, Crawford RH (2009) The path exchange method for hybrid LCA. Environ Sci Technol 43:8251–8256CrossRefGoogle Scholar
  25. Lenzen M, Geschke A, Wiedmann T, Lane J, Anderson N, Baynes T, Boland J, Daniels P, Dey C, Fry J, Hadjikakou M, Kenway S, Malik A, Moran D, Murray J, Nettleton S, Poruschi L, Reynolds C, Rowley H, Ugon J, Webb D, West J (2014) Compiling and using input–output frameworks through collaborative virtual laboratories. Sci Total Environ 485-486:241–251CrossRefGoogle Scholar
  26. Leontief W (1970) Environmental repercussions and the economic structure: an input-output approach. Rev Econ Stat 52:262–271CrossRefGoogle Scholar
  27. Lutz M (2013) Learning Python, 5th edn. O'Reilly Media, SebastopolGoogle Scholar
  28. Majeau-Bettez G (2014) ecospold2matrix: a Python class for recasting Ecospold2 LCA datasets into Leontief matrix representations or supply and use tables. GitHubGoogle Scholar
  29. Majeau-Bettez G, Strømman AH, Hertwich EG (2011) Evaluation of process- and input-output-based life cycle inventory data with regard to truncation and aggregation issues. Environ Sci Technol 45:10170–10177CrossRefGoogle Scholar
  30. Miotto R, Wang F, Wang S, Jiang X, Dudley JT (2017) Deep learning for healthcare: review, opportunities and challenges. Brief Bioinform.
  31. Oregi X, Hernandez P, Gazulla C, Isasa M (2015) Integrating simplified and full life cycle approaches in decision making for building energy refurbishment: benefits and barriers. Buildings 5:354–380CrossRefGoogle Scholar
  32. Pauliuk S, Majeau-Bettez G, Mutel CL, Steubing B, Stadler K (2015) Lifting industrial ecology modeling to a new level of quality and transparency: a call for more transparent publications and a collaborative open source software framework. J Ind Ecol 19:937–949CrossRefGoogle Scholar
  33. Pomponi F, Lenzen M (2018) Hybrid life cycle assessment (LCA) will likely yield more accurate results than process-based LCA. J Clean Prod 176:210–215CrossRefGoogle Scholar
  34. PRé Sustainability (2018) Simapro, 8.4 ednGoogle Scholar
  35. Python Software Foundation (2017) Python programming language - official website, 3.4 ednGoogle Scholar
  36. Rauf A, Crawford RH (2015) Building service life and its effect on the life cycle embodied energy of buildings. Energy 79:140–148CrossRefGoogle Scholar
  37. Säynäjoki A, Heinonen J, Junnila S, Horvath A (2017) Can life-cycle assessment produce reliable policy guidelines in the building sector? Environ Res Lett 12:013001. CrossRefGoogle Scholar
  38. Schaubroeck T, Gibon T (2017) Outlining reasons to apply hybrid LCA—a reply to “Rethinking system boundary in LCA” by Yi Yang (2017). Int J Life Cycle Assess 22:1012–1013CrossRefGoogle Scholar
  39. Stephan A (2018) Walkthrough the path exchange hybrid analysis graphical user interface. Figshare. Accessed 23 Feb 2018
  40. Stephan A, Stephan L (2014) Reducing the total life cycle energy demand of recent residential buildings in Lebanon. Energy 74:618–637CrossRefGoogle Scholar
  41. Suh S, Huppes G (2000) Gearing input-output model to LCA, part I: general framework for hybrid approach. CML, Leiden University, LeidenGoogle Scholar
  42. Suh S, Huppes G (2005) Methods for life cycle inventory of a product. J Clean Prod 13:687–697CrossRefGoogle Scholar
  43. Suh S, Lenzen M, Treloar GJ, Hondo H, Horvath A, Huppes G, Jolliet O, Klann U, Krewitt W, Moriguchi Y, Munksgaard J, Norris G (2004) System boundary selection in life-cycle inventories using hybrid approaches. Environ Sci Technol 38:657–664CrossRefGoogle Scholar
  44. Suh S, Weidema B, Schmidt JH, Heijungs R (2010) Generalized make and use framework for allocation in life cycle assessment. J Ind Ecol 14:335–353CrossRefGoogle Scholar
  45. Tettey UYA, Dodoo A, Gustavsson L (2014) Effects of different insulation materials on primary energy and CO2 emission of a multi-storey residential building. Energ Building 82:369–377CrossRefGoogle Scholar
  46. Treloar GJ (1997) Extracting embodied energy paths from input-output tables: towards an input-output-based hybrid energy analysis method. Econ Syst Res 9:375–391CrossRefGoogle Scholar
  47. Treloar GJ (1998) A comprehensive embodied energy analysis framework. Ph.D. Thesis, Deakin UniversityGoogle Scholar
  48. van Rossum G, Warsaw B, Coghlan N (2018) PEP 8—style guide for Python code. Accessed 11 May 2018
  49. Wernet G, Bauer C, Steubing B, Reinhard J, Moreno-Ruiz E, Weidema B (2016) The ecoinvent database version 3 (part I): overview and methodology. Int J Life Cycle Assess 21:1218–1230CrossRefGoogle Scholar
  50. Wilson G et al (2014) Best practices for scientific computing. PLoS Biol 12:1–7CrossRefGoogle Scholar
  51. World Bank Group (2017) Population, totalGoogle Scholar
  52. WU Global Material Flows Database (2017) Vienna University of Economics and Business.
  53. wxPython (2018) Welcome to wxPython. Accessed 21 Feb 2018
  54. Yang Y (2017a) Does hybrid LCA with a complete system boundary yield adequate results for product promotion? Int J Life Cycle Assess 22:456–460CrossRefGoogle Scholar
  55. Yang Y (2017b) Rethinking system boundary in LCA—reply to “Lifting the fog on the characteristics and limitations of hybrid LCA” by Thomas Gibon and Thomas Schaubroeck (2017). Int J Life Cycle Assess 22:1009–1011CrossRefGoogle Scholar
  56. Yang Y, Heijungs R, Brandão M (2017) Hybrid life cycle assessment (LCA) does not necessarily yield more accurate results than process-based LCA. J Clean Prod 150:237–242CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Architecture, Building and PlanningThe University of MelbourneMelbourneAustralia

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