Skip Navigation Links
Journal of Environmental Accounting and Management
António Mendes Lopes (editor), Jiazhong Zhang(editor)
António Mendes Lopes (editor)

University of Porto, Portugal

Email: aml@fe.up.pt

Jiazhong Zhang (editor)

School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China

Fax: +86 29 82668723 Email: jzzhang@mail.xjtu.edu.cn


Topological Network Theory and Its Application to LCA and IOA and Related Industrial Ecology Tools: Principles and Promise

Journal of Environmental Accounting and Management 3(2) (2015) 151--167 | DOI:10.5890/JEAM.2015.06.005

Reinout Heijungs

Department of Econometrics and Operations Research, VU University Amsterdam, Amsterdam, The Netherlands

Institute of Environmental Sciences, Leiden University, Leiden, The Netherlands

Download Full Text PDF

 

Abstract

One way to study complex systems is by methods from topological network theory, that concentrate on the topological structure of the system in terms of vertices (nodes) and edges that connect pairs of vertices. The last two decades, topological network theory has seen a wide range of applications. In this paper, we explore its potential for two of the model systems that are central to industrial ecology (IE): life cycle assessment (LCA) and input-output analysis (IOA), with the aim of finding out whether this theory offers insights that are useful to IE. We describe the principles of topological network theory, as well as the possible rules for translating LCA and IOA systems into a formal network. We apply this theory to two cases, the ecoinvent LCA database, and the monetary IOtable for the European Union in 2007. Our conclusions are mixed. It is not entirely clear what the resulting network indicators imply for a specific LCA case or IOA case. Although the results obtained are perfectly explainable and thus do make sense, they appear to be very sensitive to arbitrary choices, such as the level of aggregation. Moreover, it appears to be difficult to include the environmental aspect in the network analysis, so that we end up with analyzing an industrial network rather than industrial-ecological network.

References

  1. [1]  Abarca-Arenas, L.G. and Ulanowicz, R.E. (2002), The effects of taxonomic aggregation on network analysis, Ecological Modelling 149(3): 285-296.
  2. [2]  Albert, R., Jeong, H. and Barabási, A.L. (2000), Error and attack tolerance of complex networks, Nature 406(6794): 378-382.
  3. [3]  Allesina, A. and Ulanowicz, R.B. (2004), Cycling in ecological networks: Finn’s index revisited, Computational Biology and Chemistry 28(3): 227-233.
  4. [4]  Andrews, D. and DeVault, D. (2009), Green niche market development: A model with heterogeneous agents, Journal of Industrial Ecology 13(2): 228-246.
  5. [5]  Baird, D., Fath, B.D., Ulanowicz, R.E., Asmus, H. and Asmus, R. (2009), On the consequences of aggregation and balancing of networks on system properties derived from ecological network analysis, Ecological Modelling 220(23): 3465-3471.
  6. [6]  Barabási, A.L. and Albert, R. (1999), Emergence of scaling in random networks, Science 286(5439): 509-512.
  7. [7]  Cassettia, M. (1995), A New Method for the Identification of Patterns in Input–Output Matrices, Economic Systems Research 7: 363- 382.
  8. [8]  CMLCA. Academic software for LCA, IOA, EIOA, and more. http://www.cmlca.eu/.
  9. [9]  Dietzenbacher, E. (1990), Seton's Eigenprices: Further Evidence, Economic Systems Research 2: 103-124.
  10. [10]  Ecoivent. http://www.ecoinvent.ch/.
  11. [11]  EUROSTAT. http://epp.eurostat.ec.europa.eu/portal/page/portal/esa95_supply_use_input_tables/introduction.
  12. [12]  Eurostat. (2008), Eurostat manual of supply-use and input-output tables. European Commission.
  13. [13]  Fiksel, J. and Bakshi, B. (2010), Industrial Ecology Network Optimization with Life Cycle Metrics. Proc. of IEEE International Symposium on Sustainable Systems & Technology, Washington.
  14. [14]  Finn, J.T. (1976), Measures of ecosystem structure and function derived from analysis of flows, Journal of Theoretical Biology 56(2): 363-380.
  15. [15]  Fröhling, M., Schwaderer, F., Bartusch, H. and Schultmann, F. (2013), A material flow-based approach to enhance resource efficiency in production and recycling networks, Journal of Industrial Ecology 17(1): 5-19.
  16. [16]  Heijungs, R. and Suh, S. (2002), The computational structure of life cycle assessment. Kluwer Academic Publishers (ISBN 1-4020- 0672-1), Dordrecht, xii+241 pp.
  17. [17]  Heijungs, R. (2012). Spatial differentiation, GIS-based regionalization, hyperregionalization, and the boundaries of LCA. p. 167-175. In: G. Ioppolo (Ed.). Environment and Energy. FrancoAngeli (ISBN 9788856849271), 219 pp.
  18. [18]  Kempener, R., Beck, J. and Petrie, J. (2009), Design and analysis of bioenergy networks. A Complex Adaptive Systems Approach, Journal of Industrial Ecology 13(2): 284-305.
  19. [19]  Kharrazi, A., Rovenskaya, E., Fath, B.D., Yarime, M. and Kraines, S. (2013), Quantifying the sustainability of economic resource networks: An ecological information-based perspective, Ecological Economics 90: 177-186.
  20. [20]  Wood, R. and Lenzen, M. (2009), Aggregate measures of complex economic structure and evolution. A review and case study, Journal of Industrial Ecology 13: 264-283.
  21. [21]  Marvuglia, A., Benetto, E., Rios, G. and Rugani, B. (2013a), SCALE: Software for Calculating Emergy based on life cycle inventories, Ecological Modelling 248: 80-91.
  22. [22]  Marvuglia, A., Rugani, B., Rios, G., Pigne, Y., Benetto, E. and Tiruta-Barna, L. (2013b), Using graph search algorithms for a rigorous application of emergy algebra rules, Revue de Métallurgie-Cahiers D Informations Techniques 110(1): 87-94.
  23. [23]  May, R.M., Levin, S.A. and Sugihara, G. (2008), Complex systems: Ecology for bankers, Nature 451: 893-895.
  24. [24]  McNerney, J., Fath, B.D., and Silverberg, G. (2013), Network structure of inter-industry flows, Physica A 392: 6427-6441.
  25. [25]  Merciai, S. and Heijungs, R. (2014), Balance issues in monetary input-output tables, Ecological Economics 102: 69-74.
  26. [26]  Milgram, S. (1967), The small world problem, Psychology Today 1: 61-67.
  27. [27]  Miller, R.E. and Blair, P.D. (2009), Input-output analysis. Foundation and Extensions. Cambridge University Press, Cambridge.
  28. [28]  Mitchell, M. (2006), Complex systems: Network thinking, Artificial Intelligence 170: 1194-1212.
  29. [29]  Newman, M.E.J. (2010), Networks. An Introduction. Oxford University Press, Oxford.
  30. [30]  Raa, T. ten. (1995), Linear analysis of competitive economics. Harvester Wheatsheaf, New York.
  31. [31]  Schaubroek, T., Staelens, J., Verheyen, K., Muys, B. and Dewulf, J. (2012), Improved ecological network analysis for sustainability assessment; a case study on a forest ecosystem, Ecological Modelling 247: 144-156.
  32. [32]  Solow, R.M. (1964), Capital, labor, and income in manufacturing. In: National Bureau of Economic Research, The behavior of income shares: selected theoretical and empirical Issues. NBER.
  33. [33]  Suh, S. (2005), Theory of materials and energy flow analysis in ecology and economics, Ecological Modelling 189: 251-269.
  34. [34]  Tesfatsion, L. (2002), Agent-Based Computational Economics: Growing Economies From the Bottom Up. Artificial Life 8, 55-82.
  35. [35]  The Erdös Number Project. http://www.oakland.edu/enp/.
  36. [36]  Ulanowicz, R.E. (2004), Quantitative methods for ecological network analysis, Computational Biology and Chemistry 28(5): 321-339.
  37. [37]  yEd Graph Editor. http://www.yworks.com/en/products_yed_about.html.
  38. [38]  Zorach, A.C. and Ulanowicz, R.E. (2003), Quantifying the complexity of flow networks: how many roles are there? Complexity 8(3): 68-76.