The Impact of Social Factors and Consumer Behavior on Carbon Dioxide Emissions in the United Kingdom

Abstract

In this article we apply geodemographic consumer segmentation data in an input−output framework to understand the direct and indirect carbon dioxide (CO 2 ) emissions associated with consumer behavior of different lifestyles in the United Kingdom. In a subsequent regression analysis, we utilize the lifestyle segments contained in the dataset to control for aspects of behavioral differences related to lifestyles in an analysis of the impact of various socioeconomic variables on CO 2 emissions, such as individual aspirations and people's attitudes toward the environment, as well as the physical context in which people act.This approach enables us to (1) test for the significance of lifestyles in determining CO 2 emissions, (2) quantify the importance of a variety of individual socioeconomic determinants, and (3) provide a visual representation of "where" the various factors exert the greatest impact, by exploiting the spatial information contained in the lifestyle data.Our results indicate the importance of consumer behavior and lifestyles in understanding CO 2 emissions in the United Kingdom. Across lifestyle groups, CO 2 emissions can vary by a factor of between 2 and 3. Our regression results provide support for the idea that sociodemographic variables are important in explaining emissions. For instance, controlling for lifestyles and other determinants, we find that emissions are increasing with income and decreasing with education. Using the spatial information, we illustrate how the lifestyle mix of households in the United Kingdom affects the geographic distribution of environmental impacts.

How Does the Environmental Load of Household Consumption Depend on Residential Location?

“…There is little information available about the spatial variations in household consumption concerning non-energy commodities, taking into account socio-economic differences between households. Some authors have claimed that the effect of location could be either missing [61], minor [51], or partly favoring urban living [63].…”

“…With rising income the consumption of direct and in particular indirect energy is increasingly related to pleasure [3,59,60]. Wealthier households are more prone to adopt carbon-intensive lifestyles [15,61]. Income differences are one of the main drivers of residential segregation [62] that also affects the spatial variation of carbon load from final consumption.…”

Comparing the Gtap-Mrio and Wiod Databases for Carbon Footprint Analysis

“…This interest was preceded by a growing concern over different issues related to climate policy such as the debate on how to allocate the responsibility for emissions between producers and consumers (Munksgaard and Pedersen, 2001) (Peters, 2008), the transfer of emissions between countries through international trade (Peters and Hertwich, 2008) or the identification of the impacts of the consumption habits of a country (Hertwich and Peters, 2009) and (Baiocchi, et al, 2010).…”

The Distribution of Material Footprints in Germany

“…We employ the EASI demand 2 Utilising between-country heterogeneity, studies find affluence, measured as income or final demand, to be the principle driver of material footprints (Wiedmann et al, 2015;Pothen, 2017;Pothen and Welsch, 2017) 3 The energy footprint of households, also known as energy requirements, has been estimated since the 1970s (Herendeen and Tanaka, 1976;Herendeen, 1978). Other studies on energy and carbon footprints of households include Wier et al (2001) for Denmark, Weber and Matthews (2008) for the USA, Druckman and Jackson (2009) and Baiocchi et al (2010) for the UK, Girod and De Haan (2010) for Switzerland, Steen-Olsen et al (2016) for Norway, and Lenzen et al (2006) for Australia, Brazil, Denmark, India as well as Japan. Hertwich (2005) provides an overview.…”