Data mining for evaluating the rebounds-associated emissions due to energy-related consumer behavioural shifts in Switzerland

Abstract

Energy-related household consumption lead to a substantial share of the total household GHG emissions (direct and indirect). The policies or technologies, which try to mitigate these emissions often end up 'rebounding' i.e. the savings of energy (bills) caused by these measures, induce further expenses in other (e.g. travel) or same (e.g. electricity) categories, leading to (partial) offsetting of the emissions saving. This research introduces application of a data-driven bottom up method to evaluate these rebound emissions based on the household consumption (expenses) and properties. Two scenarios of energy-savings measures are evaluated here: (1) switching to energy-efficient devices, and (2) switching to renewable energy. The results are discussed for households with varying income, region of residence and household size. The results show that higher income and bigger households have higher total rebounds for both scenarios, while Zurich has lowest compared to all other Swiss regions.