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Dynamic global warming impact assessment integrating temporal variables: Application to a residential building in China
Institution:1. Roskilde University, Department of Environmental, Social and Spatial Change, Roskilde, Denmark;2. Quantitative Sustainability Assessment Division, Department of Management Engineering, Technical University of Denmark (DTU), Produktionstorvet 424, DK-2800 Kgs. Lyngby, Denmark;1. Université de Toulouse, INSA, UPS, INP, LISBP, 135 Avenue de Rangueil, F-31077 Toulouse, France;2. INRA, UMR792, Laboratoire d’Ingénierie des Systèmes Biologiques et des Procédés, F-31400 Toulouse, France;3. CNRS, UMR5504, F-31400 Toulouse, France;4. LITIS, Normandy University, 25 rue Philippe Lebon CS 80540, 76058 Le Havre Cedex, France;5. Luxembourg Institute of Science and Technology (LIST), 5, avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg;1. Technical University of Denmark, Department of Civil Engineering, Lyngby, Denmark;2. Technical University of Denmark, Department of Management Engineering, Lyngby, Denmark;3. SDU Life Cycle Engineering, Department of Chemical Engineering, Biotechnology and Environmental Technology, University of Southern Denmark, Odense, Denmark;1. Department of Civil and Environmental Engineering, Northeastern University, 400 Snell Engineering Center, 360 Huntington Ave., Boston, MA 02115, United States;2. School of Architecture Northeastern University, 151 Ryder Hall, 360 Huntington Ave., Boston, MA 02115, United States
Abstract:Climate warming is a global concern, and buildings have been recognized as a major contributor because the carbon emissions during their entire life cycles constitute a large share of the total value (almost 40% globally). Many life cycle assessments of buildings have been conducted to quantify the associated global warming impacts. However, few studies have considered the potential temporal variation over the long lifetimes of buildings. In this study, various temporal variables were combined to evaluate the dynamic life cycle global warming impact of a residential building in China. First, annual material and energy consumption data throughout the entire life cycle were acquired from questionnaire survey, statistical reports and literatures. Five dynamic variables (household size, usage behavior, replacement and improvement of components, waste treatment, and energy mix) and their effects on consumption levels were considered. Second, a dynamic inventory analysis tool (DyPLCA) was used to transform the temporal consumption data into dynamic greenhouse gas quantities. The global warming effects of these emissions were quantified using a dynamic characterization tool (DynCO2). Finally, emission reduction targets for future decades were used to weight the severities of the impacts at different times. The dynamic instantaneous and cumulative global warming impacts of the building were calculated. Dynamic and static assessment results were compared. We also analyzed the contribution of each dynamic variable to the final results and found that the dynamic variables had very different effects (ranging from ?42.00% to 45.34%). This study provided an operable dynamic assessment model and available dynamic data for the global warming impact assessment of buildings in China.
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