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Evaluation of Modeling Approaches to Determine End‐of‐Life Flows Associated with Buildings: A Viennese Case Study on Wood and Contaminants

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  • Nađa Džubur
  • David Laner

Abstract

Dynamic material flow analysis enables the forecasting of secondary raw material potential for waste volumes in future periods, by assessing past, present, and future stocks and flows of materials in the anthroposphere. Analyses of waste streams of buildings stocks are uncertain with respect to data and model structure. Wood construction in Viennese buildings serve as a case study to compare different modeling approaches for determining end‐of‐life (EoL) wood and corresponding contaminant flows (lead, chlorine, and polycyclic aromatic hydrocarbons). A delayed input and a leaching stock modeling approach are used to determine wood stocks and flows from 1950 until 2100. Cross‐checking with independent estimates and sensitivity analyses are used to evaluate the results’ plausibility. In the situation of the given data in the present case study, the delay approach is a better choice for historical observations of EoL wood and for analyses at a substance level. It has some major drawbacks for future predictions at the goods level, though, as the durability of a large number of historical buildings with considerably higher wood content is not reflected in the model. The wood content parameter differs strongly for the building periods and has therefore the highest influence on the results. Based on this knowledge, general recommendations can be derived for analyses on waste flows of buildings at a goods and substance level.

Suggested Citation

  • Nađa Džubur & David Laner, 2018. "Evaluation of Modeling Approaches to Determine End‐of‐Life Flows Associated with Buildings: A Viennese Case Study on Wood and Contaminants," Journal of Industrial Ecology, Yale University, vol. 22(5), pages 1156-1169, October.
    • Handle: RePEc:bla:inecol:v:22:y:2018:i:5:p:1156-1169
    DOI: 10.1111/jiec.12654
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    References listed on IDEAS

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    2. Fritz Kleemann & Jakob Lederer & Helmut Rechberger & Johann Fellner, 2017. "GIS-based Analysis of Vienna's Material Stock in Buildings," Journal of Industrial Ecology, Yale University, vol. 21(2), pages 368-380, April.
    3. David Laner & Helmut Rechberger & Thomas Astrup, 2015. "Applying Fuzzy and Probabilistic Uncertainty Concepts to the Material Flow Analysis of Palladium in Austria," Journal of Industrial Ecology, Yale University, vol. 19(6), pages 1055-1069, December.
    4. Hiroki Tanikawa & Tomer Fishman & Keijiro Okuoka & Kenji Sugimoto, 2015. "The Weight of Society Over Time and Space: A Comprehensive Account of the Construction Material Stock of Japan, 1945–2010," Journal of Industrial Ecology, Yale University, vol. 19(5), pages 778-791, October.
    5. Plischke, Elmar, 2010. "An effective algorithm for computing global sensitivity indices (EASI)," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 354-360.
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    1. Fernando Aguilar Lopez & Romain G. Billy & Daniel B. Müller, 2022. "A product–component framework for modeling stock dynamics and its application for electric vehicles and lithium‐ion batteries," Journal of Industrial Ecology, Yale University, vol. 26(5), pages 1605-1615, October.

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