The EU Carbon-CAP project assembled a comprehensive portfolio of consumer initiatives in order to assess the potential total impact of consumer options on national carbon footprints. Existing evaluations of behavioural change have focused primarily on direct energy reductions, typically in households and buildings. However, changes in consumer demand have deeper impacts via their upstream supply chains. The consumer behaviour options considered in the portfolio focus on green household initiatives. Combining existing micro-level studies with a multiregional input-output economic model, we estimated the potential efficacy and uptake of each behaviour across the European Union (EU). The results suggest that adopting these consumer options could reduce carbon footprints by approximately 25%. While 75% of this is delivered as reductions in emissions within Europe, one-quarter of the effect is delivered as a reduced imported carbon footprint, due to changes in the composition of imports. Key policy insights

Consumption-based carbon accounts (CBCAs) track how final demand in a region causes carbon emissions elsewhere due to supply chains in the global economic network, taking into account international trade. Despite the importance of CBCAs as an approach for understanding and quantifying responsibilities in climate mitigation efforts, very little is known of their uncertainties. Here we use five global multiregional input-output (MRIO) databases to empirically calibrate a stochastic multivariate model of the global economy and its GHG emissions in order to identify the main drivers of uncertainty in global CBCAs. We find that the uncertainty of country CBCAs varies between 2 and 16% and that the uncertainty of emissions does not decrease significantly with their size. We find that the bias of ignoring correlations in the data (that is, independent sampling) is significant, with uncertainties being systematically underestimated. We find that both CBCAs and source MRIO tables exhibit strong correlations between the sector-level data of different countries. Finally, we find that the largest contributors to global CBCA uncertainty are the electricity sector data globally and Chinese national data in particular. We anticipate that this work will provide practitioners an approach to understand CBCA uncertainties and researchers compiling MRIOs a guide to prioritize uncertainty reduction efforts.