作者: Yoann Pigné , Tomás Navarrete Gutiérrez , Thomas Gibon , Thomas Schaubroeck , Emil Popovici
DOI: 10.1007/S11367-019-01696-6
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摘要: The objective is to demonstrate an operational tool for dynamic LCA, based on the model by Tiruta-Barna et al. (J Clean Prod 116:198-206, 2016). main innovation lies in combination of full temporalization background inventory and a graph search algorithm leading LCI, further coupled LCIA. following objectives were addressed: (1) development database with temporal parameters all processes ecoinvent 3.2, (2) implementation integrated software, (3) demonstration case study comparing conventional internal combustion engine car electric one. Calculation LCA (including foreground system) implies (i) LCI model, (ii) including characterization (iii) algorithm, (iv) LCIA models, this specific climate change. relies supply chain modeling perspective, instead accounting Unit are operations showing functioning over time. Mass energy exchanges depend models. Production described functions. implements using database, derive life cycle environmental interventions scaled functional unit distributed combined models obtain temporally differentiated results. A web-based calculations (DyPLCA) implementing was developed. available testing (http://dyplca.univ-lehavre.fr/). showed that can change significantly It fair say offers little interest activities high downstream emissions. provide insightful results when applied systems where significant occur upstream. Those concern, example, renewable electricity generation, which most emissions embodied infrastructure also observed higher degree contribution leads spreading impacts Finally, potential impact time window choice discounting study, comparison decision-making. Time differentiation as whole may thus influence conclusions study. feasibility system, demonstrated through database. considering across complete cycle, especially This particularly relevant product material long periods upstream unit. number inherent limitations discussed shall be considered opportunities research. requires collegial effort, involving industrial experts from different sectors.