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Article Dans Une Revue Journal of Cleaner Production Année : 2016

Framework and computational tool for the consideration of time dependency in Life Cycle Inventory: proof of concept

Résumé

Conventional Life Cycle Inventories (LCIs) are static models of product systems without time dependent functioning of plants and time lags between supply and demand of products. The aggregation of environmental interventions without consideration of the time dimension represents an acknowledged limitation of the Life Cycle Assessment (LCA) method. In this paper we present a novel conceptual and computational framework for the consideration of time dependency in LCIs. Process modeling is used to describe the production flows and environmental interventions of each unit process and supply modeling is used to include time lags on the raw materials exchanged by unit processes of the product system. The combination of production and supply models in life cycle networks, based on a set of specific temporal parameters (representative functioning period, production time, supply delay, supply frequency), allows the characterization of time dependency in each node. For the computation of time dependent LCI, i.e. of the time resolved environmental interventions, graph search algorithm is proposed and implemented in a prototype Web application. In terms of results, the new approach provides time dependent LCI expressed as: i) time as a function of individual emission (or resource consumption) for individual processes, ii) aggregated time as a function of a given environmental intervention. A test bed case illustrating the effectiveness of the conceptual and computational approaches (proof of concept) is presented and successfully solved both analytically and numerically.
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Dates et versions

hal-01886373 , version 1 (02-10-2018)

Identifiants

Citer

Ligia Tiruta-Barna, Yoann Pigne, Tomas Navarrete Gutierrez, Enrico Benetto. Framework and computational tool for the consideration of time dependency in Life Cycle Inventory: proof of concept. Journal of Cleaner Production, 2016, 116, pp.198-206. ⟨10.1016/j.jclepro.2015.12.049⟩. ⟨hal-01886373⟩
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