Carbon mitigation in domains of high consumer lock-in

Abstract

As climate policy needs to address all feasible ways to reduce carbon emissions, there is an increasing focus on demand-side solutions. Studies of household carbon footprints have allocated emissions during production to the consumption of the produced goods, and provided an understanding of what products and consumer actions cause significant emissions. Social scientists have investigated how attitudes, social norms, and structural factors shape salient behavior. Yet, there is often a disconnect as emission reductions through individual actions in the important domains of housing and mobility are challenging to attain due to lock-ins and structural constraints. Furthermore, most behavioral research focuses on actions that are easy to trace but of limited consequence as a share of total emissions. Here we study specific alternative consumption patterns seeking both to understand the behavioral and structural factors that determine those patterns and to quantify their effect on carbon footprints. We do so utilizing a survey on consumer behavioral, attitudinal, contextual and socio-demographic factors in four different regions in the EU. Some differences occur in terms of the driving forces behind behaviors and their carbon intensities. Based on observed differences in mobility carbon footprints across households, we find that the key determining element to reduced emissions is settlement density, while car ownership, rising income and long distances are associated with higher mobility footprints. For housing, our results indicate that changes in dwelling standards and larger household sizes may reduce energy needs and the reliance on fossil fuels. However, there remains a strong need for incentives to reduce the carbon intensity of heating and air travel. We discuss combined effects and the role of policy in overcoming structural barriers in domains where consumers as individuals have limited agency.

Happier with less? Members of European environmental grassroots initiatives reconcile lower carbon footprints with higher life satisfaction and income increases

“…Even individuals with pro-environmental orientations may be ineffective at reducing their CF due to the dominant influence of socio-economic factors on consumption levels [28][29][30] . Particularly, they may focus on behaviors that are easy to adopt, but have relatively small impact 28,31 e.g., recycling.…”

“…Particularly, they may focus on behaviors that are easy to adopt, but have relatively small impact 28,31 e.g., recycling. Typically, the available voluntary lifestyle changes are often limited to consumption of less harmful goods or "green consumption" 10,32 , and constrained by institutional, infrastructural and behavioral lock-ins 30,33,34 . Furthermore, only a massive adoption of lifestyle changes would represent a serious contribution towards keeping within 1.5°C trajectories 35,36 .…”

“…The GLAMURS (Green Lifestyles, Alternative Models and Upscaling Regional Sustainability) 1 project applied an interdisciplinary approach to research the main obstacles and prospects for sustainable lifestyles in Europe at national 20 , regional 2 and individual levels 30 -including participatory modelling with stakeholders to quantify the potential of lifestyle changes 35 . Empirically, the project conducted action research with grassroots initiatives 56 and applied a comprehensive survey to compare the lifestyles of non-members with the lifestyles of members of local sustainability-oriented grassroots initiatives 56 .…”

“…Compared to regional official statistics, our non-member sample appear to over-represent females and younger people. Females are generally associated with lower food-and transportrelated emissions 30 meaning that we may misestimate the average emission levels in these domains. Age is positively associated with food-and housing-related emissions, and negatively associated with mobility emissions 30 .…”

“…Females are generally associated with lower food-and transportrelated emissions 30 meaning that we may misestimate the average emission levels in these domains. Age is positively associated with food-and housing-related emissions, and negatively associated with mobility emissions 30 . See SI1 for a detailed discussion on the representativeness of our nonmember samples.…”