Streamlined column-based disaggregation method for carbon footprint quantification for multi-regional input–output (MRIO) models

Abstract Multi-regional input–output (MRIO) models are a valuable source of data for environmental assessments. They encompass all products in an economy and capture the full inter-relationships of global supply chains. This provides a comprehensive set of environmental coefficients (e.g., kgCO 2 e) that are complete and free from truncation. However, the environmental coefficients in these models are highly aggregated, meaning all products within a sector share the same coefficient value. This can mis-represent the true environmental impacts of individual products. To rectify this, disaggregation methods may be employed to break down both the rows and columns in MRIO tables to obtain a more precise representation of products. However, the conventional disaggregation method is data-intensive, time-consuming, technically demanding, and requires complex reconciliation, which undermines efficiency and broader practical use. This study addresses this limitation and introduces a streamlined and data-efficient disaggregation method to derive sector-specific impact factors (multipliers). The method simplifies the disaggregation process by focusing solely on the columns. This results in a partial matrix augmentation (rectangular matrix) that yields refined subsector multipliers without requiring the full reconstruction of the MRIO system. Therefore, it requires less data than the typical disaggregation method, reduces technical burden, and eliminates the need for complex reconciliation techniques. The method was applied to the EXIOBASE database v3.9.5 2022 $$(\text{P}\times \text{P})$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>(</mml:mo> <mml:mtext>P</mml:mtext> <mml:mo>×</mml:mo> <mml:mtext>P</mml:mtext> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> for Great Britain (GB). With minimal data, the cement, lime, and plaster sector, as well as the aluminium and aluminium products sector, were disaggregated into subsectors. The results reveal variations ranging from − 50% to + 220% in total embodied carbon intensities. The method shows promise in streamlining disaggregation, enabling sustainability practitioners, corporations and policymakers to obtain more precise environmental coefficients for informed decision-making and guiding sustainability efforts.