Abstract
The provision of decent housing is both a global social priority and a productive activity with long-term environmental implications. Investigating the unequal distribution of housing resources and their associated greenhouse gas emissions, from heating to materials, construction, and use, allows us to foreground housing as a key site of socio-ecological inequalities in today's economies. This paper develops a model for assessing such inequalities as they relate to the overall use of materials and energy in the provision and operation of housing. Our interdisciplinary and multidimensional analysis of housing consumption in the Netherlands brings together income, urban form, building age, tenure, and housing typology, and includes patterns of mobility and daily use. We draw on a unique combination of sources—register data about the Dutch population and housing stock, a mobility survey, and life cycle inventory data—to reveal that a) the carbon footprint per person differs starkly between richest and poorest groups; b) the low-density locations and income of richer households drive mobility emissions; c) rental units show larger carbon footprints related to lower quality housing stock; and d) suburbanization offsets emissions-saving investments in owner-occupied stock. We end by calling for further interdisciplinary research into ways to provide socially just and environmentally sustainable housing, and policy interventions to tackle excess in housing consumption, invest in social rental stock, and foster density in planning policies.
Scope and analytical approach
The study examines housing consumption in the Netherlands in 2019 and 2023. It looks beyond building energy use to include emissions from construction materials and mobility associated with where people live and the type of housing they occupy. The analysis combines register data on the population and housing stock, mobility survey data and life cycle inventory data. It compares per-person footprints across income and housing-tenure groups, while also considering dwelling size, building characteristics and urban context.
Key findings
In the authors’ predictive analysis, household income is the strongest predictor of total per-person housing carbon footprints. More floor area per person is also associated with a higher footprint, while social housing is associated with lower footprints than owner-occupied or private-rental homes. The study further links low-density and suburban living with higher mobility emissions. It highlights a potential trade-off: efficiency improvements in owner-occupied homes can be offset by suburbanisation and the travel patterns associated with it. The findings show why housing emissions need to be considered alongside household resources, tenure and urban form.
Policy relevance
The authors call for further interdisciplinary work and policy measures that address excess in housing consumption, invest in social rental housing, and support density in planning. Their analysis treats housing as both a social need and a source of environmental pressures across materials, building operation and mobility. This broader boundary helps connect housing policy with carbon-reduction goals.
