Housing and Mobility Demands of Individual Households and their Life Cycle Assessment

Abstract

Household consumption, apart from governmental consumption, is the main driver of worldwide economy. Attached to each household purchase are economic activities along the preceding supply chain, with the associated resource use and emissions. A method to capture and assess all these resource uses and emissions is life cycle assessment. We developed a model for the life cycle assessment of housing and land-based mobility (excluding air travel) consumption of individual households a small village in Switzerland. Statistical census and dwelling register data are the foundations of the model. In a case study performed on a midsized community, we found a median value of greenhouse gas emissions of 3.12 t CO2 equiv and a mean value of 4.30 t CO2 equiv per capita and year for housing and mobility. Twenty-one percent of the households in the investigated region were responsible for 50% of the total greenhouse gas emissions, meaning that if their emissions could be halved the total emissions of the community would be reduced by 25%. Furthermore, a cluster analysis revealed that driving factors for large environmental footprints are demands of large living area heated by fossil energy carriers, as well as large demands of motorized private transportation.

Household carbon emission research: an analytical review of measurement, influencing factors and mitigation prospects

“…Lee and Lee (2014), for example, note the mitigating effects of compact and transit friendly cities in the United States, while Saner et al (2013) consider the emissions of household consumption of housing and transportation (excluding air travel) in Switzerland, revealing a 4.30 tonnes CO 2 emission equivalent per person per year. In China, Dai et al (2012) point to the need for more careful design of Chinese city layouts to reduce unnecessary transport service demand; Qin and Han's (2013) studies confirm that higher building density, mixed land-use patterns, proximity to public transport and jobshousing balance are important HCE reducing planning parameters; while Ye et al (2013), after eliminating socio-economic factors, find HCEs are reduced by green spaces and water bodies e a result that needs to be taken into account in urban planning, especially in coastal cities.…”

Greenhouse Gas Emissions Quantification and Reduction Efforts in a Rural Municipality

“…Part of the deviation of Zernez's CF from the national average may also be explained by different methodological approaches, such as different GHG emission factors or different reference years. The areas of housing and mobility were double‐checked with the model of Saner and colleagues () and revealed to be consistent with the model results (for further results, see the Supporting Information on the Web).…”

“…Whereas this unique data set enabled the exemplification of how a rural community can quantify and reduce its GHG emissions, we attempt to develop a detailed bottom‐up consumption model based on nation‐wide data in follow‐up research. This model will build upon the ideas of Saner and colleagues () and on the detailed insights of the present study. The planned model will allow for computing the CBF on different aggregation levels and will thus enable comparisons between different municipalities and cities.…”

“…In addition, an independent alternative approach was followed by applying Saner and colleagues’ () model to Zernez in order to assess the consumption‐related CF in the areas of residential energy and mobility (see the Supporting Information on the Web). This model is able to determine housing and land‐based mobility demand of individual households.…”

Using life cycle sustainability assessment to trade off sourcing strategies for humanitarian relief items

“…Sustainability assessment methods such as life cycle assessment have been extensively applied in the building sector (e.g., Saner et al 2013;Cabeza et al 2014), energy and waste management (Quek and Balasubramanian 2014), packaging (Von Falkenstein et al 2010), and the food and agri-food sector (Amani and Schiefer 2011). To the best of our knowledge, Oberhofer et al (2015) conducted the only LCA in the humanitarian sector, when they analyzed the supply chain of the French Red Cross 1 to calculate the carbon footprint of three commonly used relief items (blanket, plastic sheet, and jerry can).…”