As climate change raises temperatures, projecting future building energy demand is crucial for adaptation, mitigation, and resilient infrastructure and energy systems. This is intensified by Europe's ageing population, including Norway, where more elderly residents will increase demand for elderly housing and vulnerability to thermal stress. This study examines how climate change affects the energy demand while ensuring thermal comfort of the elderly in newly built elderly housing in Baerum Municipality, Norway. Urban Building Energy Modelling was used to simulate heating and cooling energy demand in two elderly housing complexes under Intergovernmental Panel on Climate Change Assessment Report 5 climate scenarios, Representative Concentration Pathways (RCP 2.6 and RCP 8.5) for the 2030s-2060s. Custom weather datasets included a 2023 Actual Meteorological Year (AMY) for calibration, a Typical Meteorological Year (TMY) baseline, and future weather files for different greenhouse gas trajectories. Contemporary and projected extreme weather data were generated to assess building energy performance under current and severe climate conditions. The RCP 8.5 scenario is projected to reduce heating demand by up to 19% by the 2060s, while the RCP 2.6 scenario reduces it by about 9% relative to historical data from 2000 to 2020. Peak cooling demand is forecasted to increase by 34% by the 2060s with more frequent and longer cooling events. This indicates a growing need for infrastructure improvements to meet future energy demands. Understanding these shifts in energy demand is crucial for preparedness to ensure the well-being and thermal comfort of elderly populations.

Sweden's housing stock, designed predominantly for winter thermal performance, is increasingly exposed to summer heat extremes following record heatwaves in 2014, 2018, and 2022. Despite projections of intensifying heat risk and the near-total absence of mechanical cooling in Swedish residential buildings, no prior study has delivered a nationally comprehensive, indicator-based compound risk assessment integrating hazard, exposure, and vulnerability at the municipal scale. This study addresses that gap through an integrated framework covering all 290 Swedish municipalities, combining GIS-based climate data processing, standardised Poisson regression for empirical indicator selection, and CA-Markov land cover projections under RCP 2.6, 4.5, and 8.5 scenarios to 2040. Thermal hazard is characterised through maximum seasonal air temperature, consecutive summer days, and tropical day frequency derived from UERRA-HARMONIE reanalysis and SMHI regional projections; vulnerability is constructed from seven demographic, socioeconomic, and built environment indicators; and exposure is represented by SCB municipal population forecasts. The composite index is externally validated against observed 2018 excess summer mortality across all 290 municipalities, with the equal-weighted specification outperforming PCA-and regression-beta-weighted alternatives (Pseudo R2 = 0.117, p = 0.007); the index is interpreted as a spatial prioritisation tool rather than a mortality prediction model. The 2040 projections are framed as a counterfactual stress test, applying projected thermal forcing to a fixed sociodemographic baseline. Results identify a pronounced south-north risk gradient, with Stockholm, Go & uml;teborg, Malmo & uml;, Burlo & uml;v, and Solna remaining persistently classified as high risk under every scenario. By 2040, over 230 of 290 municipalities are reclassified to medium risk or above, driven primarily by committed demographic ageing rather than emissions pathway, with RCP 2.6 and RCP 8.5 producing near-identical patterns. Elderly fraction, low-income share, building density, and vegetation proximity emerge as the significant mortality predictors, providing an evidential basis for spatially targeted adaptation centred on green-blue infrastructure, equity-oriented cooling access, and differentiated heat-health warning systems.

The transition toward a circular and climate-neutral construction sector is critical to achieving the EU 2050 goals. Especially, when the construction sector accounts for approximately 40% of global resource consumption and 36% of greenhouse gas emissions. Achieving circularity and net-zero emissions by mid-century requires not only technical innovation but also regulatory, economic, and cultural realignment across value chains. Current regulatory frameworks and market practices remain largely linear, with limited integration of life-cycle carbon performance and circularity principles. This study explores how a shared long-term vision can guide systemic transformation, using participatory foresight and expert validation to define measurable pathways for the sector’s evolution. This study employs a backcasting methodology - working backwards from a desired 2050 end state—to identify the enabling actions, governance models, and knowledge mechanisms required today.

There exist different circularity indicators and lifecycle assessment (LCA) methodologies to calculate resource efficiency and environmental impacts of the building sector. But they largely operate within single-lifecycle boundaries and lack a consistent approach for assessing material across multiple lifecycles in existing buildings. This study addresses this gap by adapting the Material Circularity Indicator (MCI) assessment approach for the renovation of buildings (MCIRENO), which accounts for successive lifecycles of the materials generated from the renovation. The MCIRENO is integrated with the Circular Footprint Formula (CFF) to provide a methodological operational unified framework for evaluating circularity and environmental impacts. Using a systematic selection process, seven end-of-life-cycle allocation methodologies were compared to identify the CFF's point of integration with MCIRENO. In the framework, the MCIRENO incorporates extended lifetimes and reuse potential, while CFF allocates environmental burdens and credits across multiple loops using standardized factors. The framework is validated with an empirical example of façade brick using seven scenarios and probabilistic uncertainty analysis of key parameters. The analyses reveal that material recoverability drives the degree of circularity and is sensitive towards varying scenarios. Similarly, environmental outcomes remain scenario-dependent and primarily driven by avoided virgin material production. The combined results are sensitive to contextual and scenario-specific assumptions. The approach offers a structured framework to jointly evaluate multicycle circularity and environmental impacts of inert materials. Future research across heterogeneous materials and renovation complexity can strengthen the robustness of the proposed framework.

Residential buildings are central to Europe’s energy transition as climate change alters heating and cooling demand and increases risks related to thermal discomfort. In Sweden single family houses account for approximately 43 percent of the building stock and 40 percent of residential energy use while in neighboring Nordic countries demographic ageing increases the importance of ensuring adequate thermal comfort in elderly housing. Understanding how future climate conditions affect residential energy demand across different residential typologies and urban contexts is therefore essential for building and energy system planning. This study applies Urban Building Energy Modelling to examine future residential energy demand and thermal comfort under climate change through two parallel studies conducted in Nordic cities. The first study analyses district heated single family houses in Växjö Sweden represented by two villas and two townhouses. The second study focuses on newly built elderly housing in Baerum Norway. Both studies use a Python based UBEM framework with EnergyPlus as the simulation engine and are driven by consistent climate scenario assumptions. Future climate impacts are evaluated using Representative Concentration Pathway scenarios RCP 2.6 RCP 4.5 and RCP 8.5 across midcentury time horizons. Baseline simulations rely on local measured weather data and Typical Meteorological Year files while future typical and extreme weather datasets are generated using Meteonorm version 8.1. Model calibration and validation are conducted using measured energy data where available. Results from both cities are analysed simultaneously at monthly and hourly resolutions to assess seasonal energy demand shifts and changes in peak loads. Across both residential typologies heating demand consistently declines while cooling demand and peak cooling events increase under higher emission scenarios. However, the magnitude and timing of these changes differ between single family housing and elderly housing reflecting differences in building design occupancy patterns and thermal sensitivity. The findings demonstrate how Urban Building Energy Modelling enables cross context interpretation of future residential energy demand and provides evidence to support HVAC design district heating planning and policies addressing thermal comfort in Nordic cities.

More than 70 percent of Sweden's detached houses are aging and in need of renovation, creating an opportunity to improve their energy efficiency through targeted measures. Currently, renovation strategies are often chosen based on their immediate advantages, such as compatibility with existing climate conditions and thermal comfort. However, as climate projections indicate potential shifts in weather patterns, which may change heating and cooling demand, it becomes crucial to consider climate change pattern considering future climate scenarios when choosing energy measures. This paper aims to investigate the available energy measures in the renovation process of detached houses and categorize them based on their appropriateness for future climate change, considering their energy performance and thermal comfort. The authors will employ an Urban Building Energy Modeling (UBEM) tool with a physics-based approach to simulate building heating and cooling energy consumption. Future energy consumption of buildings will be analyzed under "Representative Concentration Pathway" (RCP) scenarios for 2030, 2040, and 2050. Six detached houses in Växjö, Sweden, have been selected as case studies for this research. The outputs from the UBEM model of the case study buildings will be calibrated based on 2018 weather data and corresponding energy bills, and the calibrated models will be validated using 2019 weather data. The calibration process uses a Monte Carlo Markov Chain (MCMC) algorithm based on monthly heating energy consumption data. The performance of different energy measures in the case study buildings will be investigated based on yearly heating and cooling energy consumption under different RCP scenario. The expected results of this study are to identify the most appropriate energy measures based on the forecasted energy performance and to analyze their effectiveness in addressing the change in cooling demand. This study could be beneficial for detached house owners, municipalities, and all decision-makers involved in building renovations, enabling smarter renovation decisions.

Sweden’s average temperature has increased by 1.9 °C since the late 19th century and is projected to rise by another 3–5 °C by the end of the century. As urbanisation amplifies heat stress, there is an urgent need to assess Surface Urban Heat Island (SUHI) risks, especially in high-latitude regions like Sweden, where such studies are limited. This study maps SUHI hazards, exposure, and vulnerability across Sweden to identify high-risk municipalities, focusing on residents in Single-Family Houses (SFHs). MODIS-derived land surface temperature (LST) data (2015–2022) were used to estimate SUHI intensity (hazard). Population density and building footprint data informed exposure, while vulnerability was measured using a Composite Vulnerability Index (CVI) based on social and physical indicators, including population demographics and building-related characteristics. All indicators and risk components were normalised, weighted using entropy and PCA, and integrated through geospatial analysis to produce a 1 km resolution national SUHI risk map, validated using heat-related mortality data. Results indicate that high-risk areas are concentrated in major cities. 12 high-risk municipalities contain 14 % of all SFHs built before 1975, and 18 medium-risk municipalities contain 8 %, together accounting for 22 % of the national pre-1975 SFH stock. Residents of these SFHs represent nearly half of those living in pre-1975 SFHs nationwide. These findings highlight the urgent need for climate-smart renovations with strategies like reflective roofing, increased greenery, and soft financing for urban adaptation planning in northern climates.

Urban Building Energy Modelling (UBEM) has become an essential tool for analysis and planning renovation strategies as well as predicting future energy use patterns both at building and district levels. To aid urban planning effectively, digital solutions such as UBEM should support informed urban planning decisions by analysing various renovation scenarios, including energy use, occupant comfort, and climate resilience, while ensuring accuracy without excessive complexity. A critical input for physics-based UBEM tools is building geometry, which can be represented at different levels of detail (LoD). Striking a balance between accuracy and the costs and time required for data generation necessitates examining the influence of LoD in building geometry. This research aims to investigate the extent to which the LoD in building geometry can influence the accuracy of results. To achieve this, four LoD of building geometry were defined for 9 different detached single-family houses in Sweden, and their effect on model performance was assessed with and without calibration using the Monte Carlo Markov Chain (MCMC) algorithm. The calibration used simulated heating demand and utility bill data, optimising for Coefficient of Variation of the Root Mean Square Error (CVRMSE) and Normalised Mean Bias Error (NMBE) indices. The results indicate that, without calibration, models with differing geometric LoDs can exhibit significant performance discrepancies, with variations of up to 19.7% in the CVRMSE and 22.5% in NMBE observed between high and low geometric detail levels. However with calibration, the differences between models with varying geometric LoDs were substantially reduced, with average CVRMSE and NMBE decreasing to 2.9% and 0.9%, respectively, well within ASHRAE Guideline thresholds. The findings offer useful guidance for academic and societal stakeholders working to improve energy modeling in urban planning. By identifying effective LoDs and calibration methods, this research enables cost-efficient UBEM applications, supporting better decisions for sustainable urban development.

Single-family houses (SFHs) make up 43% of Sweden's building stock and contribute to 40% of the country's residential energy consumption.  Many of these houses, being old, are not only key contributors to residential energy consumption but may also be highly vulnerable to the impacts of climate change. Investigating how climate change affects the thermal energy demand and comfort in SFHs is essential for developing strategies that enhance energy efficiency, improve occupants’ thermal comfort, and ensure the resilience.  This study will assess the impact of climate change on energy demand and thermal comfort in single-family houses (SFHs) in Sweden supported by district heating.

This study will analyze future energy demand under three "Representative Concentration Pathway" (RCP) scenarios—RCP 2.6, RCP 4.5, and RCP 8.5—for the years 2030, 2040, and 2050. These scenarios will be used to explore energy consumption trends, seasonal variations, and changes in peak demand, with comparisons made against the typical and extreme weather years. Monthly analyses will provide insights into seasonal variations and overall energy consumption patterns, while hourly analyses will focus on peak-demand dynamics to guide HVAC system sizing and the development of energy supply strategies. To achieve these objectives, a case study will be conducted in Växjö, Sweden, involving two townhouses and two villas as representative of Sweden's single-family housing stock. The Urban Building Energy Modeling (UBEM) tool, developed using Python and employing EnergyPlus as the simulation engine, will be utilized for the analysis. Future weather data for the simulations will be generated using Meteonorm version 8.1, while baseline data will be sourced from local weather stations. The simulations will be calibrated and validated by comparing the results with actual energy consumption patterns of the SFHs. By integrating multiple climate scenarios and focusing on energy demand and thermal comfort, this study aims to provide actionable insights for stakeholders in the building sector. The findings will likely support the development of effective strategies to adapt SFHs to climate change, enhancing their resilience, energy efficiency, and occupant comfort.

Energy poverty has evolved into a topic of global concern affecting both developing and developed countries. Energy poverty deprives the potential of numerous women to participate in family, communal, and economic activities. While energy poverty is a commonly studied subject, the existing literature often overlooks its gender dimension, specifically the effects on women. This systematic review aims to fill the current research lacuna by shedding light on the multifaceted consequences faced by women due to energy poverty. To this end, numerous articles from Scopus and Web of Science are fully analysed. The findings demonstrate the impacts on multiple aspects of women’s lives, such as health, emotional well-being, income, increased workload, and the perpetuation of inequality. Though the challenges seem a bit different in the Global South and North from a boarder perspective, coherent policies that enhance women’s empowerment with economic opportunities could minimize the potential risk of energy poverty. The review underlines the urgency of integrating a gender perspective, emphasising the necessity of interdisciplinary methods that connect energy and gender studies differently in both the Global North and South. The finding also highlights the role of socio-economic conditions, cultural norms, and the division of labour in increasing women’s vulnerability. This review highlights the crucial significance of gender-inclusive approaches in understanding and tackling energy poverty.