Building energy assessment is essential to accomplish the sustainable energy targets of new and present buildings. Retrofitting of the existing buildings by assessing them through energy models is the most prominent method. Studies revealed that there is still blank information about the building stocks, and these affect the valuation of building energy efficiency policies. Literature also recommends that the existing energy models are too complex and unreliable to predict the energy use. Reliability of such energy models would improve through a better alignment of the input parameters and the model assumptions. The authors hypothesized that the reliability of models would be improved through identification of the most relevant energy use parameters for the building stocks in different regions and models. One of the most commonly accepted methods for detecting the most dominant input parameters is sensitivity analysis, though its shortcomings include the need for a large number of data samples and long computing time. In this research, the Energy, Carbon, and Cost Assessment for Buildings Stocks (ECCABS) model is adopted to identify the most important parameters of the presented model. The research team uses the model that has been validated by studies conducted for the UK building stock. Moreover, by assessing the feasibility study with the stepwise regression to identify the significant input parameters have been discussed. Results show that stepwise regression method could produce the same results compared to sensitivity analysis. This paper also indicates that stepwise regression is considerably faster and less computationally intensive compared to common sensitivity analysis methods.

The increasing world population and climate change are major concerns for the supply of water needs. Understanding user behavior facilitates the development of effective strategies of domestic water management. This research applied a questionnaire survey and data analysis methods to analyze the water consumption behavior of tenants in a multicultural urban area, dominated by immigrants of different ethnic origins, in the city of Växjö in Sweden. Results showed that the majority of the studied participants perceived themselves to be environmentally friendly. They reported to be engaged in water conservation activities quite often, but analysis showed that they did not have accurate perceptions of their water consumption. Positive attitudes towards water conservation and self-reported water conservation activities significantly but negatively influenced respondents’ actual water consumption, i.e., water consumption was higher. Subjective norms did not have a significant influence. The results also revealed that individual measurement and debit positively influenced, i.e., reduced, actual water consumption. Therefore, water management systems should include an individual measurement and debit system combined with a visualization system to enable tenants to monitor the quantity and cost of their water consumption.

Alabastern, a multicultural rental housing area in the Växjö city of Sweden, was identified as poor at recycling household waste compared to other housing areas in the town. In this paper, a qualitative and quantitative analysis is conducted to understand the underlying causes of waste recycling behaviour of the tenants. Results showed that majority of the studied participants perceived themselves to be environmentally friendly. They reported that they recycled household waste quite often, but it was the other tenants who did not sort their waste properly. The respondents identified the causes of the improper waste recycling as lack of attitude and awareness, limitation of communication, sense of insecurity, lack of means to transport bulky waste, limitation of the recycling room, and inadequate action by the housing company Växjöbostäder.