A multi-country meta-analysis on the role of behavioural change in reducing energy consumption and CO2 emissions in residential buildings

Abstract

Despite the importance of evaluating all mitigation options to inform policy decisions addressing climate change, a comprehensive analysis of household-scale interventions and their emissions reduction potential is missing. Here, we address this gap for interventions aimed at changing individual households’ use of existing equipment, such as monetary incentives or feedback. We have performed a machine learning-assisted systematic review and meta-analysis to comparatively assess the effectiveness of these interventions in reducing energy demand in residential buildings. We extracted 360 individual effect sizes from 122 studies representing trials in 25 countries. Our meta-regression confirms that both monetary and non-monetary interventions reduce the energy consumption of households, but monetary incentives, of the sizes reported in the literature, tend to show on average a more pronounced effect. Deploying the right combinations of interventions increases the overall effectiveness. We have estimated a global carbon emissions reduction potential of 0.35 GtCO2 yr−1, although deploying the most effective packages of interventions could result in greater reduction. While modest, this potential should be viewed in conjunction with the need for de-risking mitigation pathways with energy-demand reductions. Behavioural interventions can reduce energy consumption and hence carbon emissions among households. Khanna et al. compare the effectiveness of different types of monetary and non-monetary household interventions using a machine learning-assisted meta-analysis, and examine the situations where each is most useful.