A BIM–LCA Approach for the Whole Design Process of Green Buildings in the Chinese Context

The integrated description of the building geometry and the element attributes of the building information model (BIM) can reduce the effort needed to acquire data for life cycle assessment (LCA) and life cycle costing (LCC) at each design stage while supporting their potential for analyzing life cycle performances and feeding back to the design process. To support this, several methods and tools have been proposed that aim to obtain the life cycle performances of buildings following the level of model fidelity with the life cycle inventory (LCI) database at different scales. However, inconsistencies in decision-making caused by regional differences in LCA/LCC data sources, benchmarks, and building standards cannot be ignored. In this study, a scalable LCA/LCC method integrated with the BIM platform is proposed for the whole green building design process in the Chinese context, and it is implemented with a developed tool based on Revit. A national-/regional-specified database of building elements and materials is established. Referring to China’s carbon-neutral target and relevant standards for green buildings, the baseline values are deduced, and a reference building is defined accordingly to facilitate the evaluation and improvement of the design scheme. According to the Assessment Standard for Green Building (GB50378-2019) and the survey of architectural design practices in China, the key parameters at different design stages are defined. The method and tool are demonstrated using the case study of a school building, analyzing its life cycle carbon emissions and life cycle costs throughout the design process. The results show that the proposed method can facilitate the improvement of the scheme at different design stages and that it can cope with different data accuracies and different LODs in the building information model in the Chinese green building design process. Lastly, the uncertainties raised by the data quality and time-associated factors are discussed.