• Ballarini, I., Piro, M., Corrado, V., Pernigotto, G., Borelli, G., & Gasparella, A. (2025). ”A methodology for the assessment of the Urban Heat Island effect by exploiting the urban archetype approach”, in C. Zilio et al. (Eds.) Proceedings of the 15th REHVA HVAC World Congress – CLIMA 2025, Lecture Notes in Civil Engineering, volume 763, Springer Nature, pp. 1179–1191. https://doi.org/10.1007/978-3-032-06810-1_118

Abstract:

Population in urban areas experiences local warming with temperatures higher than in surrounding rural areas due to the Urban Heat Island (UHI) effect, which determines risks for human health, and increases in energy consumption. In the literature, it is reported that accurately quantifying the UHI effect at a wider territorial scale is challenging, due to difficulties in acquiring climatic data at microscale and modelling the drivers of UHI while considering the interactions between buildings and their surroundings.

This work, developed in the framework of the PRIN2022–PNRR CRiStAll (Climate Resilient Strategies by Archetype-based Urban Energy Modelling) project, aims to overcome this research gap by coupling Urban Building Energy Modelling with urban archetypes, representative urban context configurations at microscale derived by varying urban canyon parameters and assuming building archetypes of different climatic zones, use categories, and construction periods.

The methodology presented in the paper is applied to create urban archetypes for the city of Torino (Italy). Key metrics of the urban context are assessed and the UHI effect is evaluated by means of Urban Weather Generator. Energy simulations are then carried out using CitySim Pro to quantify the effect of the UHI on the energy behaviour of buildings at the urban scale. The urban archetype approach is effective for getting outcomes both at a finer spatial resolution, due to the modelling of climatic data at microscale, and with larger spatial coverage, due to the adoption of a bottom-up model that allows mapping of urban areas.

• Manzan, M., Ramezani, A. (2026). “Climate Change and Health Conditions in a Social House Building in Trieste”, In: Zilio et al. (Eds) Proceedings of the 15th REHVA HVAC World Congress – CLIMA 2025. Lecture Notes in Civil Engineering, volume 763, Springer Nature, pp. 964-974. https://doi.org/10.1007/978-3-032-06810-1_97

Abstract:

In this paper we present a study concerning the effect of external high temperatures on interior living conditions in a social housing building. The construction, located in Trieste, is characterized by uninsulated walls and low performance windows. However, since the building is under refurbishment, simulations also considered the effect of new improved thermal characteristics. People health was considered through the application of a biophysical model, and the use of electrical ventilators as a mitigation strategy was also included. The building model has been developed using DesignBuider code and the simulation were performed with EnergyPlus software. The model has been validated using internal temperatures measured during hot summer weeks in 2024. Three external conditions for simulations were used, a current reference year obtained using a local weather station data and two future weather data obtained from GCM-RCM projections to highlight the effects of possible future more severe conditions. The results show that the internal environment during a hot period can become dangerous for the people and can lead to heat stress conditions with values of skin wettedness nearing and surpassing the limit of 0.7 especially for future weather conditions. However, the use of ventilators can provide mitigation reducing skin wettedness below values of 0.5. As an alternative the use of an air conditioning system guaranteeing comfort conditions was assessed but the simulations highlighted that future temperatures could led to an increase of cooling energy up to19%.

• Borelli, G., Battini, F., Pernigotto, G., & Gasparella, A. (2025). “Influence of Urban Microclimate on the Energy Performance of Buildings of Complex Shapes in Different District Layouts and Climates”. Presented at the 9th International Building Physics Conference (IBPC 2024), 25–27 July 2024, Toronto, Canada. Published in: Berardi, U. (ed.) Multiphysics and Multiscale Building Physics. Lecture Notes in Civil Engineering, vol 553. Springer, Singapore. https://doi.org/10.1007/978-981-97-8309-0_45

Abstract:

Urban Building Energy Modelling UBEM tools usually adopt conventional weather data that do not consider the impact of the urban context on the local climate conditions, e.g., the Urban Heat Island effect. In this study, the influence of the use of urban microclimate data on UBEM results was investigated considering a set of 5 synthetic district morphologies composed of buildings with complex shapes. Each base district, characterized by 2 envelope compositions and 2 window-to-wall ratios, was simulated in both heating- and cooling-dominated climates. Moreover, for each district scenario simulations were performed with EnergyPlus using both a standard rural weather file and a microclimatic one generated with the Urban Weather Generator tool. Results were compared in terms of annual district heating and cooling needs and peak loads. As a whole, the microclimatic weather files showed increased ambient temperatures, resulting in an overall reduction in heating needs and an increase in the cooling ones, supporting the need to include microclimate in UBEM calculations.

• Borelli, G., Ballarini, I., Corrado, V., Gasparella, A., & Pernigotto, G. (2024). “Assessment and mapping of the urban heat island effect: a preliminary analysis on the impact on urban morphology for the city of Turin, Italy”. In Proceedings of BSA 2024, 26–28 June 2024, Bolzano, Italy. https://doi.org/10.13124/9788860462022_64

Abstract:

Urban Heat Island (UHI) effects, intensified by growing urbanization, significantly impact thermal comfort and energy demand in cities. To accurately model these effects in building performance and urban energy simulations, precise weather data and boundary conditions are essential. Although weather stations in city centers are increasingly used to develop typical meteorological years, they often fail to capture the microclimate variations across urban areas. New tools and methods are thus needed to help building professionals and municipalities assess UHI severity, use more representative weather data, and evaluate the impact of buildings on the urban microclimate. Among available tools for UHI impact assessment, Computational Fluid Dynamics (CFD) models offer detailed analysis but are computationally intensive and impractical for largescale, year-round studies. Conversely, equivalent RC networks are more computationally efficient but still require extensive inputs, limiting their widespread use in large cities. This research introduces a new workflow using correlations to estimate UHI effects from rural weather data. The MIT Urban Weather Generator (UWG) was used to simulate UHI in representative districts, with the results employed to develop correlations for mapping local microclimates across urban areas. The proposed methodology is preliminary applied to the Italian city of Turin, focusing primarily on the correlation between urban morphology and the UHI phenomena (i.e., paying attention to those variables with the most significant effects on the local urban microclimate, according to the literature). The UHI impact has been quantified in terms of differential heating and cooling degree-days with respect to the rural environment. Results prove that with a training set of about 5 % of the city, modelled in detail with UWG, developed correlations appear robust enough to describe the phenomenon for residential districts of Turin.

• Piro M., Ballarini I., Tootkaboni M.P., Corrado V., Pernigotto G., Borelli G., Gasparella A. 2026. “The Urban Heat Island Under Climate Change: Analysis of Representative Urban Blocks in Northwestern Italy”, Energies 19(3): 660. https://doi.org/10.3390/en19030660

Abstract:

Urban populations are exposed to elevated local temperatures compared to surrounding rural areas due to the urban heat island (UHI) effect, which increases health risks and energy demand. The literature highlights that accurately quantifying UHIs at broader territorial scales remains challenging because of limited microscale climate data availability and, at the same time, the difficulty of increasing the spatial coverage of the outcomes. Within the PRIN2022-PNRR CRiStAll (Climate Resilient Strategies by Archetype-based Urban Energy Modeling) project, this work addresses these limitations by coupling Urban Building Energy Modeling with archetype-based representation of urban form and high-resolution climatic data. Urban archetypes are defined as representative microscale configurations derived from combinations of urban canyon geometries and building typologies, accounting for different climatic zones, use categories, and construction periods. The proposed methodology was applied to the city of Turin (Italy), where representative urban blocks were identified and modeled to evaluate key urban context metrics under short-, medium-, and long-term climate scenarios. The UHI effect was assessed using Urban Weather Generator, while energy simulations were performed with CitySim. The urban archetype approach enables both fine spatial resolution and extensive spatial coverage, supporting urban-scale mapping.

• Da Silva M.A., Borelli G., Gasparella A., Pernigotto G. 2026. “Confronting Land Surface Temperature and Ground Station Data for Urban Heat Island Assessment and Urban Building Energy Modeling—A Case Study for Northern Italy”, Energies 19(3): 724. https://doi.org/10.3390/en19030724

Abstract:

Data scarcity limits robust assessment of urban overheating and its implications for building energy use, especially in complex-terrain cities such as those in mountain environments. In this context, Land Surface Temperature (LST) from thermal remote sensing can be used to map urban hotspots at high spatial resolution. Nevertheless, it does not provide the full set of hourly atmospheric variables required to run building energy simulations aimed at quantifying their impact and defining mitigation measures. Given these premises, this study proposes a methodology combining satellite-derived LST with ground meteorological measurements to assess Urban Heat Island (UHI) patterns and quantify how measured weather data selection affects urban building energy modeling (UBEM) outcomes. After selecting as a case study Bolzano, an Alpine city in Northern Italy, ECOSTRESS LST (2019–2025, May–August) was first processed and quality-screened to (1) compute ΔLST (urban–rural) and (2) identify diurnal and spatial overheating patterns across the building stock. Second, four measured weather datasets—one rural station and three urban stations located in the city core, in the industrial district, and in the urban edge—were used as boundary conditions in an EnergyPlus-based UBEM parametric campaign for 253 residential buildings, covering multiple envelope insulation levels and window-to-wall ratios. Results show strong diurnal asymmetry in surface overheating, with the largest contrasts in the afternoon and prominent industrial hotspots. Ground measurements confirm persistent intra-urban microclimatic differences, and the choice of measured weather dataset causes systematic shifts in simulated cooling demand and thermal comfort. The study highlights the need for weather data selection strategies based on microclimatic context rather than simple proximity, improving representativeness in UBEM applications for Alpine and other heterogeneous urban environments.

• Manzan M., Ramezani A., Corona J.J. 2025. “The Impact of Climate Change on Economic Uncertainty in the Renovation of a Social Housing Building”, Energies 18(10): 2562. https://doi.org/10.3390/en18102562

Abstract:

The renovation of buildings impacts various factors; one of them is the economic aspect, which has a significant influence on the decision-making process in building refurbishment, especially in social housing. An often-neglected aspect of renovation is the influence of climate change. Typically, historical climate data are used to estimate the building’s future energy needs. However, due to climate change, this approach may fail to accurately represent future environmental conditions, resulting in miscalculations in energy consumption and costs. This study analyzed a building archetype obtained from the TABULA webtool with the characteristics of a social house building located in Trieste. Dynamic simulations were performed using DesignBuilder and EnergyPlus software and future climate models (the GERICS_CNRM-CM5 and GERICS_IPSL-CM5A-MR models obtained from the EURO-CORDEX database). The projected energy needs of the renovated building and its economic effects were compared with current scenarios, and due to the uncertainties in economic parameters, the outcome is expressed in terms of percentiles of the Net Present Value (NPV). The results of this study show that since temperature increases in the future, the need for energy in the heating period reduces, while the need for cooling increases, directly affecting the statistical distribution of the NPV.