SUMMARYLittering is a packaging-related problem where the environmental, social and economic aspects of sustainability meet. Litter is likely to be harmful for wildlife, looks untidy and is expensive to clean up. Research into reducing litter has focused primarily on the litterer and on the surroundings in which the littering occurs, but the infl uence of the littered object has so far been ill addressed. This research focused on understanding how the characteristics of an object infl uence its probability of being littered and how this insight can be used to improve the design of these objects, in particular packaging. Both eco-feedback and scripting approaches were examined in four experimental setups. It was found that the design of a packaging does have a signifi cant infl uence on waste behaviour of consumers. However, applying this insight to packaging design in order to reduce littering was found to be less than straightforward.

already acknowledge the impact of the PSS concept on sustainability, although there is no

No abstract

Building simulations are often used to predict energy demand and to determine the financial feasibility of the low-carbon projects. However, recent research has documented large differences between actual and predicted energy consumption. In retrofit projects, this difference creates uncertainty about the payback periods and, as a consequence, owners are reluctant to invest in energy-efficient technologies. The differences between the actual and the expected energy consumption are caused by inexact input data on the thermal properties of the building envelope and by the use of standard occupancy data. Integrating occupancy patterns of diversity and variability in behaviour into building simulation can potentially foresee and account for the impact of behaviour in building performance. The presented research develops and applies occupancy heating profiles for building simulation tools in order create more accurate predictions of energy demand and energy performance. Statistical analyses were used to define the relationship between seven most common household types and occupancy patterns in the Netherlands. The developed household profiles aim at providing energy modellers with reliable, detailed and ready-to-use occupancy data for building simulation. This household-specific occupancy information can be used in projects that are highly sensitive to the uncertainty related to return of investments.

a b s t r a c tLarge differences between the expected and actual energy consumption have been found in energy efficient dwellings. Research has shown that these differences are partially caused by occupant behaviour. The financing and payback periods of low carbon technologies are often uncertain because of the impact of the occupants on building performance. This translates into a reluctance to invest in deep renovation projects. The goal of this design-inclusive research project is to develop a solution for zero energy renovation that reduces the uncertainty on building performance cause by occupants' behaviour by reducing the uncertainty in design decisions and energy calculations. This investigation focuses on the identification of building type specific occupants and their characteristics, requirements and living practices. This paper presents the user research approach developed for the renovation process. The approach consists of statistical analysis of Dutch households, a monitoring campaign in the area of study and co-creation research through mock-ups, enactments and interviews. Case studies results are presented to highlight the effect of different household types on energy consumption and occupants' requirements, and point at the importance of taking into account household typology and socio-economic characteristics in energy calculations or building simulations, as well as occupant requirements in the design process.