Mobility, food and housing: responsibility, individual consumption and demand-side policies in European deep decarbonisation pathways

Abstract

The Brundtland Commission report ‘Our Common Future’ highlighted that residents in high-income countries lead lifestyles incompatible with planetary boundaries. Three decades later, consumption-related greenhouse gas (GHG) emissions have continued to increase. To achieve ‘well below 2°C’ and 1.5 °C goals, consumption-related emissions must be substantially reduced in the coming decades. This paper provides insights on how to pursue 1.5 °C pathways through changes in household consumption. It draws on original data gathered in the project ‘HOusehold Preferences for reducing greenhouse gas Emissions in four European High Income Countries’ (HOPE) to analyse policies targeting and affecting direct and indirect GHG emissions in three household consumption categories (mobility, housing and food) in four countries (France, Germany, Norway and Sweden) and four medium-sized cities. This paper demonstrates discrepancies and similarities between current governmental policy approaches in the four countries and household perceptions of consumption changes with respect to policy mechanisms, responsibilities and space for acting on mitigation. Current demand-side policy strategies rely heavily on instruments of self-governance and nudging behaviour. Whilst some of our data suggests that households broadly accept this, it also suggests that governments could more actively lead and steer demand-side mitigation via adjusting and supplementing a comprehensive list of 20 climate policy measures currently in place in one or more of the case countries. The paper concludes by suggesting areas for more effective policy change and household-level climate change mitigation to feed the next update of climate pledges under the Paris Agreement.

Appendices

Appendix 1

This paper does not make any attempts to give quantified estimates of the GHG reduction impact of existing demand-side climate policies, nor make assumptions about the impact policies have on climate mitigation in terms of quantified GHG-emission reductions as this would be beyond the scope of our research. Neither existing mitigation policies nor the NDCs would keep emissions on track with an emission pathway compatible with the 1.5 °C goal (Millar et al. 2017; Rogelj et al. 2015; Schleussner et al. 2016; UNEP 2017, p. 14). The full potential of demand-side mitigation is not being taken advantage of. This is made apparent by several factors: (1) the current emission gap, (2) research demonstrating that increased demand-side mitigation is necessary to close the emission gap (Dietz et al. 2009) and (3) the uncertainty about voluntary mitigation occurring without stronger political interference (Berthoû 2013; Asdal and Jacobsen 2009; Miller and Rose 1995; Howell 2009). Our research has therefore focused on identifying existing space in demand-side mitigation policies as this provides an opportunity for policymakers to put in place incremental policy changes that can take advantage of the mitigation potential in targeting household consumption. To this end, it is necessary to consider whether there is a match between the roles of responsibility implicit in the policies and the readiness of the policy target (in our case, households) to take on such responsibility for mitigation action. By focusing on the implicit or explicit role of responsibility inherent in each policy approach, we are then able to highlight the subjectification effect of consumption-oriented policies for the discretion and agency of governed subjects (households), as outlined above.

The research method used for household data collection in the HOPE project has been elaborated elsewhere (Herrmann et al. 2017), but a few key attributes deserve more explicit mentioning. We have three sources of household data: mapping of household-related carbon footprints, the output from a household simulation game and interviews with households. In addition, we have mapped current household-related climate policy measures.

Three-hundred-nine households in four mid-sized European cities—Communauté du Aix-en-Provence, France; Mannheim, Germany; Bergen, Norway; and Umeå, Sweden—participated in the study. Three interactions provided information on household behaviour in the following areas: food, housing, mobility and other consumption. Interaction 1 calculated households’ carbon footprints (Herrmann et al. 2017, pp. 3–4). Interaction 2 was a simulation game with the goal to reduce household GHG emissions by 50% until 2030, in order to represent the idea of ambitious near-term demand-side mitigation compatible with 1.5 °C pathways (Sanderson et al. 2016; Rogelj et al. 2015). Households were first asked to reduce their GHG emissions voluntarily by 50%. If they failed to reduce sufficiently in the ‘voluntary’ scenario, households were asked to imagine they were ‘forced’ to reduce their emissions by 50%. For interaction 3, in-depth interviews were conducted with a subsample of households using an interview guide (Herrmann et al. 2017, p. 7). This paper uses a small part of the interview data, analysing interviewees’ answers to the following question: ‘Who do you consider responsible for climate mitigation?’ The interviews were audio recorded, transcribed verbatim⁴ and subjected to a qualitative content analysis where emerging themes were identified in the data (Bryman 2012). Fifty statements relating to this question were analysed. The results are presented along with quotes illustrating the themes resulting from the qualitative content analysis.

The results from the household study were contrasted with results from a policy mapping. For this paper, ‘policy’ includes only the tangible output of political processes (Knill and Tosun 2012; Treib et al. 2007), such as strategy documents and legislative acts by public bodies, thus excluding voluntary initiatives by private entities or persons. The policy mapping identified any policy that affects household GHG emissions either directly or indirectly. The scope of our analysis is limited to ‘demand-side’ policies, including policies that might directly affect demand for goods or services. We have excluded supply-side policies (i.e. regulations to reduce GHG emissions from production and minimum energy efficiency standards as these target the producer, and not the consumer) unless they fall into a grey-area (i.e. city planning for mobility or fuel mix regulations). Policy data was gathered through the Odyssee-Mure database, official reports to international organisations and government databases from the national, regional and local levels of government. EU policies were assumed implemented at subsidiary levels of government and therefore not mapped separately.⁵

Our database includes 250 policies. They were coded along the dimensions shown in Table 1, and every policy was summarised in a separate policy sheet (Table 3).

Table 3 Policy coding scheme

Appendix 3 offers a breakdown of the policies for analytical purposes and to create an overview of the consumption categories addressed by policies as well as the logic these policies use. The ‘technologies of government’ were identified and coded in the categories ‘policy instrument’. The objective of the coding was to identify the strategies and practices employed to achieve a stated policy objective. Keeping in line with the IPCC’s policy categories, policies were coded according to the policy categories used in the Fifth Assessment Report (IPCC 2014, pp. 239–241)⁶: Economic Instruments, Information Policies, Public Goods and Services and Regulatory Approaches. International agreements or agreements between local governing bodies were counted if they resulted in tangible policies that affect private households as defined above. Policies that combine for example regulations and subsidies were counted twice, once per policy category.

After coding the policies, a generalised typology of rationalities was used to assess and analyse the logics and rationalities of government across the four country cases and between the different consumption sectors (outlined in Table 2). The IPCC’s policy categories can be integrated with the rationalities of government (Table 2). We would expect that market-oriented governance largely operates through policy instruments belonging to ‘Information Policies’ or ‘Economic Instruments’, and command-and-control governance generally uses either ‘Regulatory Approaches’ or ‘Public Goods and Services’. We summarised the policy results in tables in Appendix 3 by adding the number of policy measures in each category and showing the relative distribution of these across the policy categories. These figures must be used with great caution since individual policies have varying impact on GHG reductions, and they are for our purposes only meant to serve as indications of the broader policy approach ().

Table 4 Governmentality framework

Appendix 2

Table 5 Median carbon footprint before, during and after the simulation game measured in kg CO₂e per year and CU by sector

Appendix 3

Table 6 IPCC-policy category breakdown by consumption category for each country

Table 7 Consumption subsector breakdown of policies per consumption category for each country

Table 8 Targeted household behaviour change per country (efficiency, reduction, substitution)

Table 9 Targeted household behaviour change per consumption subsector (efficiency, reduction, substitution)

Table 10 IPCC policy categories broken down for each consumption subsector