Evaluating the influence of functional unit on life cycle assessment (LCA) reliability of concrete

Abstract

The linear lifecycle of concrete, from production through usage to disposal, highlights its status as one of the most carbon-, energy-, and resource-intensive processes in the industry. The development of life cycle assessment (LCA) models to quantify concrete’s embodied and buildings’ operational emissions is strongly influenced by the selection of the functional unit (FU) since it dictates the magnitude and significance of the environmental burdens from concrete and buildings' life span. The chosen FU should comprehensively capture the concrete's functionalities and construction parameters. Nonetheless, establishing a FU that encompasses spatial, temporal, and intensity aspects of cement/concrete and its applications remains a significant limitation in the practice of current LCA models. This study analyzed the FU influence on the environmental footprint of concrete samples with specific compressive strengths (material level) via LCA. The LCA was conducted in OneClick LCA using the environmental product declaration (EPD) provided by the software for each ready-mix concrete sample. From the LCA results, the C 30/37 concrete mix (lowest compressive strength) exhibited the lowest carbon footprint for all the environmental indicators when a volume-based FU was considered. In contrast, the results were more favorable for the C 65/70 concrete specimen when the compressive strength (28 curing days) was chosen because less cement is needed to achieve one MPa of strength. This behavior was also observed in the modeling of a column in a building, where the mixture with the highest compressive strength (C 65/70) showed the lowest environmental impact for all the indicators. However, this assessment does not represent the actual building system's footprint. Thus, regionally specific functional units need to be established, considering not just concrete functionalities but also national regulations, stakeholder needs, and local resource availability.