Greenhouse gas (GHG) emission inventories form the basis of evidence-based climate change planning across the local, regional, national, and international levels. In this letter, we present a consumption-based GHG accounting approach for estimating the carbon footprint (CF) comprising direct and indirect emissions of households in Switzerland for 2008, 2011, and 2014 and examine the impact of urbanity and socioeconomic variables on these estimates. The CF model used herein couples regionalized household budget surveys (HBS) with environmentally-extended input-output analysis (EEIOA). We provide greater insight into the obscure process of combining bottom-up consumption data (i.e., HBS) and top-down input-output tables (IOT) in a CF model. The findings show that urban households tend to have lower direct emissions than rural households whereas indirect emissions are higher. Therefore, the nature of both direct and indirect emissions should be considered when evaluating the role of urbanization, as each has a different focus. Overall, our results indicate that income is the most important driver of household total cf Some local features specific to Switzerland have also been found to be important in shaping the relationship between the household CF and its drivers. We argue that household composition should be the focal point for future study of CF mitigation in Switzerland, and that policies should prioritise measures that target consumer behaviour and lifestyles, rather than solely focus on improving physical infrastructure and adopting new technologies.[5]. However, there is general agreement across the literature that socioeconomic variables have an opposing effect to urban density on the volume of carbon emissions. Thus, as an environmental impact of high versus low density living, the overall CF depends on the relative strength of the opposing drivers, which is in turn determined by a country's specific socioeconomic and infrastructural circumstances at the location level [5]. In China, income and subjective personal-level variables (such as happiness and security) were found to have an important effect on household carbon emissions [12]. In Finland, socioeconomic variables such as income play a much more significant role than urbanity in determining carbon emissions volumes, thus leading to a larger CF in urban areas where the positive impacts of population density are outweighed by increased rates of consumption [4,8,10]. This is also observed in the case of energy, where urban Australian households consume more total energy than rural households despite requiring less direct energy [13]. Conversely, results from Germany indicate that the significant carbon savings effect of density do offset the environmental impacts of increased consumption in urban areas [7]. Therefore, specific local features can contribute differently to consumption patterns, which in turn lead to varying overall CFs.As described, the relationship between urbanity, socioeconomic variables, and GHG emissions has been examined to varyin...