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PublicationLCA of buildings in Germany: Proposal for a future benchmark based on existing databases( 2019)
;Schlegl, Friederike ;Gantner, Johannes ;Traunspurger, RenéThe evaluation of environmental aspects in the early planning phase of buildings can support the reduction of the resource use and environmental impacts associated with the building sector over the whole building life-cycle. The integration of life cycle assessment (LCA) benchmarks in the planning phase is one potential measure. To derive these benchmarks a large database of existing building assessment is essential. Potential data input is available from the German Sustainable Building Council (DGNB), as it certifies more than 200 buildings annually and the certification includes a mandatory LCA. In this study, the current submission files and database of the DGNB are assessed and critically reviewed with regard to their usability for automated LCA benchmarks. First, a harmonized database is created from the large number of assessed buildings. Second, the data is examined for its suitability for benchmarking with regard to data format, structure and level of detail. The data that were declared fit for purpose were used to create an exemplary, harmonized data set with 22 office buildings. The evaluation of these data for various environmental indicators of the individual life-cycle phases shows their respective relevance and can thus serve as a benchmark. Another focus is to encourage improvement of the additional documentation like the energy source required for better benchmarking, interpretation of results and auditing of the LCA rules for building certification. The results of this study highlight the opportunities and challenges in the development of a database for benchmarking. Before long-term LCA benchmarks can be developed and deployed, a standardized and uniform submission format of results, that is indifferent regarding the used LCA software, needs to be developed. In the future the submission process should be extended by an automated quality assurance to prevent restraints from low data quality and data gaps that otherwise have to be detected manually.