Dynamic assessment elements and their prospective solutions in dynamic life cycle assessment of buildings

Abstract

Life cycle assessment (LCA) is a mature and widely used tool for quantifying environmental performance in the building sector. Temporal variations in building characteristics over their long life cycles significantly influence LCA results. Therefore, in recent years, dynamic LCA (DLCA) has become an emerging research field. However, DLCA research is still in its infancy, as demonstrated by the lack of systematic analysis regarding the dynamic aspects that should be considered. By examining the data transformation pathway in accordance with the standard LCA framework, this study formalizes four identified dynamic assessment elements (DAEs), namely dynamic consumption, dynamic basic inventory datasets, dynamic characterization factors, and dynamic weighting factors. A DLCA framework for buildings is proposed to enable the incorporation of DAEs into the static LCA framework. Furthermore, to better support the DLCA applications, viable prospective solutions and the availability of related data regarding the four DAEs are discussed. A case study shows that the assessment results are sensitive to the DAEs at varying degrees, and the DLCA model potentially offers a more realistic evaluation result. This study is expected to serve as a reference and provide guidelines for developing further in-depth DLCA models and methods that consider complex temporal variations.