Despite its relevance for global mitigation, quantifying scope-3 emissions at the city level remains challenging. This study presents a consumption-based carbon footprint of Madrid over 2010-2023, integrating municipal data, regional supply and use tables, the FIGARO multiregional input-output database, and the first air emissions account for the city. The household CF fell from 31,135 ktCO2e in 2010 to 21,308 ktCO2e in 2023, with per capita emissions at 6113 kgCO2e and over 55% of emissions coming from international supply chains. Distributional analysis reveals pronounced carbon inequality: high-expenditure households emitted 5.2 times more than the lowest-expenditure quintile. Simulations suggest that reshaping expenditure patterns among top-spending households and fostering limited carbon-neutral transport adoption could jointly reduce the household CF by 29.6%. These findings underscore the need for consumption-focused mitigation strategies to complement Madrid's Roadmap toward Climate Neutrality.
This paper presents a matrix balancing technique based on Generalized Cross-Entropy (GCE) that can be suitable for matrices containing both positive and negative entries. One comparative advantage of the technique presented here is that it allows for the incorporation of inference into the estimates. An additional advantage is that this technique makes possible sign flips in the cells of the initial and the estimated matrices, which can be something desirable in situations where assuming sign-preservation for all the entries of the matrix could be too restrictive. A simple illustrative example shows how GCE works when adjusting a matrix characterized by having positive and negative entries within a Supply and Use Tables (SUT) framework, producing comparatively better indicators of error than other adjusting techniques.
