A data quality matrix for carbon footprint of buildings

a framework for identifying and communication uncertainty sources

Abstract

This research aims to evaluate data quality in the calculation of building carbon footprint through the following objectives: (1) to identify and present the main variables involved in the data collection and use process in building carbon footprint studies; (2) propose a “Data Quality Matrix for Carbon Footprint of Buildings” (DQM-CF), and (3) use different specifications of structural concrete masonry walls in Brazil as a case study. A systematic literature review (SLR) was conducted to identify uncertainty sources reported in carbon footprint and Life Cycle Assessment (LCA) studies. The identified variables were then organized and synthesized into the DQM-CF framework, which was subsequently applied to different wall configurations to evaluate the influence of modelling assumptions and material specifications on carbon footprint results. The calculated carbon footprints ranged from 17.89 to 74.31 kg CO₂/m². The DQM-CF provides a structured framework for identifying, classifying, and communicating uncertainty sources in building carbon footprint assessments. This study contributes to advancing the discussion on decarbonization within the construction sector and highlights the importance and influence of data selection on accurate modeling and informed decision-making.