ABSTRACT:Residential buildings account for about one third of the final energy demand in Norway. Many costeffective measures for reducing heat losses in buildings are known and their gradual implementation may make the building sector one of the largest contributors to climate change mitigation.To estimate the sectoral reduction potential we model a complete transformation of the dwelling stock by 2050 by both renovation and re-construction with different energy standards. We propose a new dynamic stock model with an optimization routine to identify and prioritize buildings with the highest energy saving potential. The sectoral boundary is extended by including the energy and carbon footprint of the construction industry. 3Despite an expected population growth of almost 50% between 2000 and 2050, sectoral carbon emissions may drop between 30 and 40% compared to emissions in 2000 for scenarios where the stock is completely transformed by either re-construction or ambitious renovation. Due to the lower upstream impact, renovation to passive house standard allows sectoral emissions to decline faster and is therefore preferable from the viewpoint of carbon emissions.Transformation however, is not sufficient to achieve emission reduction of 50% or more as required on average to limit global warming to 2°C, because hot water generation, appliances, and lighting will dominate the sectoral footprint once the stock has been transformed. A first estimate on the impact of energy efficiency and lifestyle changes in the non-heating part of the sector reveals a maximal reduction potential of ca. 75%.

To cope with present and future challenges, a growing number of water utilities in Sweden, Europe and elsewhere initiate various forms of inter-municipal cooperations creating a new regional level of drinking water governance. In order to reach viable decisions of alternative ways forward, there is an international consensus that sustainability needs to be addressed in water supply planning, design and decision-making. There are, however, few decision aids focusing on assessing the sustainability of inter-municipal cooperations and the inter-municipal policies and interventions that regional decision-makers are faced with. This paper presents a decision support model based on a combination of cost-benefit analysis and multi-criteria decision analysis for assessing the sustainability of regional water supply interventions, including formations of inter-municipal cooperations. The proposed decision support model integrates quantitative and semi-quantitative information on sustainability criteria. It provides a novel way of presenting monetized benefits and costs, capturing utilitarian aspects of alternative interventions, with non-monetized social and environmental effects, capturing aspects based in the deontological theories of moral ethics. The model is based on a probabilistic approach where uncertainties are defined by statistical probability distributions. A case study is used to exemplify and evaluate model application in decision situations regarding regionalization, (de)centralization, source water quality and redundancy. All evaluated alternatives were expected to contribute to a slightly improved social sustainability, whereas the results were more varying in the economic and environmental domains. A structured and transparent treatment of uncertainties facilitates a better understanding of the results as well as communication between decision-makers, stakeholders and the community.

Several countries promote a regionalization of the drinking water sector; however, few decision support tools are adapted to the intermunicipal level to aid in regional decisions. The aim of this paper is to describe and demonstrate a probabilistic cost-benefit analysis approach to assess the societal effects of regional water supply interventions to constitute support for decision makers. A special focus is given to the quantification of effects on consumers' health, water supply reliability, and operation and maintenance costs. The uncertainties of the quantified values are represented by probability distribution functions and analyzed by means of Monte Carlo simulations. The proposed approach was demonstrated in the Göteborg region in Sweden, for which five alternative interventions were evaluated. In conclusion, the proposed approach facilitates the identification and prioritization of societal effects so that costs and benefits normally overlooked in evaluation processes can be explicitly considered and addressed. The paper provides a transparent handling of uncertainties and enables a structured approach to improve decision makers' ability in making informed choices on regional water supply alternatives.