The public housing stock across the European Union is generally constituted of old buildings (built prior to 1980) with high energy demand and indoor thermal comfort issues, which could be exacerbated by climate change. The aim of this paper was to quantify the impact of climate change on the energy demand of the public housing building stock. A neighbourhood located in Bari (south Italy) is considered as representative of a common construction typology of late 1970s in Italy. Energy models were created and calibrated with real-time data collected from utilities’ bills. The results showed a medium to strong correlation between age and energy consumption (r = 0.358), but no evident correlation between the number of tenants and energy consumption, although a significantly low energy consumption was found in apartments occupied by more than five tenants. An energy penalty of about 7 kWh/m² of heating energy consumption for every 10 years of increase in the average age of tenants was calculated. Moreover, the impact of future weather scenarios on energy consumptions was analysed and an average annual energy penalty of 0.3 kWh/m² was found.

User behaviour can significantly affect indoor thermal comfort conditions, as well as energy consumption, especially in existing buildings with high thermal masses where natural cross ventilation is the main strategy to reduce cooling loads. The aims of this paper were: (i) to compare how behavioural changes evaluated by means of rule-based and stochastic models lead to changes in indoor thermal comfort levels, and (ii) to define the patterns of indoor thermal comfort in historic residential buildings in future scenarios. To this end, a historic building located in Molfetta (Southern Italy) was analysed using a dynamic energy simulation engine in five weather scenarios (Typical Meteorological Year, current extreme weather file 2018, predicted weather files for 2020, 2050, and 2080 generated by morphing method), and stochastic and rule-based models for window openings were adopted and compared. The results showed that the stochastic model was more accurate than the rule-based one, resulting in a reduction of discomfort conditions during the summer period between 30% and 50% in all climate scenarios. However, although the differences between predicted discomfort levels using rule-based and stochastic models tended to increase, discomfort levels still appeared to be not acceptable in the 2050 and 2080 scenarios due to the rising temperature driven by climate change.

The association between elevated temperatures and increased mortality and morbidity risk is well-documented. This represents a significant public health concern, particularly in the Eastern Mediterranean and Middle East (EMME) region, which has been identified as a climate change hotspot exhibiting substantial warming, drying, and more frequent heat waves. Mitigation and adaptation strategies can reduce temperatures and enhance thermal comfort in urban areas, thereby alleviating the heat-induced health burden. Building upon prior research, this study aims to quantify the potential impact of Nicosia's most effective heat mitigation scenarios on heat-related risk over a six-month period, spanning from April 15th to October 15th, 2020.To accomplish this, the Weather Research and Forecasting (WRF) model is coupled with the Multilayer BEP/BEM scheme to simulate the effects of heat mitigation strategies on temperatures, outdoor thermal comfort as measured by the Universal Thermal Comfort Index (UTCI), and energy-use for space heating and cooling. Then, statistical and machine learning methods, such as the well-established Distributed Lag Non-Linear Models (DLNMs) and Generalized Additive Models (GAMs) trained on historical data, are used to estimate the relative risks and attributable fractions of mortality associated with temperature fluctuations for each scenario throughout the study period. The considered strategies include (i) adopting cool roofs to minimize heat absorption, (ii) planting trees and expanding green areas within the city, (iii) combining cool roofs and urban trees, and (iv) combining urban trees with total roof coverage by photovoltaic panels to increase renewable energy generation.This research can provide valuable insights to policymakers and urban planners on addressing climate change impacts in city regeneration projects by quantifying and comparing the benefits of these scenarios in terms of mortality alleviation.

Urbanization has become a dominant factor in shaping local climate dynamics, manifesting profound impacts on the environment and human well-being. This effect is even more important over areas that are expected to become vulnerable to climate change in the future. Cyprus, which is located in the eastern Mediterranean and Middle East (EMME) region, is considered as a climate change “hot-spot”.In this study, we employ the Weather Research and Forecasting (WRF) regional climate model driven by ERA5 reanalysis dataset coupled with different available urban parametrization schemes to simulate prevailing climatic conditions over the EMME and the island of Cyprus. The main objective of this research is to investigate the performance of -different in complexity- urban canopy models in simulating urban heat island over our region of interest, the capital city of Nicosia. The outcome of this investigation is the definition of the most suitable model set-up to be used over the area of Cyprus.The simulations are performed at 1 km horizontal resolution for the year 2021, a year that Cyprus experienced a prolonged heatwave during summer, with 12 consecutive days of temperatures exceeding 40 degrees Celsius. We examine the seasonal variability of urban climate properties in Nicosia during this year.The outcomes of this study provide valuable insights into the complex interactions between urbanization and climate. Understanding how different urban parametrization influence seasonal climate dynamics and selecting the best performing scheme aims in better representation of the local climatic conditions which can be further used in mitigation and adaptation assessments of the impacts of the ongoing global climate change.