# Urban Overheating Impact: A Case Study on Building Energy Performance
## 2 Materials and Methods  
Rome is a densely built Italian city of about 4 million inhabitants as a result of a constant urban expansion over time. The city is located 24 km from the Tyrrhenian coast and it is characterized by temperate climatic conditions and hot summer seasons, with maximum average temperatures higher than 30 \({}^{\circ}\)C.  
To assess the aim of this study, data from different meteorological stations were used: two airport meteorological stations and one urban station (Figure 1). Specifically, Fiumicino and Ciampino airport stations were selected as they are two rural areas typically also present in the climate data sheets of the dynamic energy modeling software, while the area of the Rome station was selected as it represented a typical neighborhood of the city, densely built and with high population density. This selection made the quantification of the UHI phenomenon realistic and reliable. The airport stations are reference weather stations for the Meteorological Service of the Military Air Force and for the World Meteorological Organization (WMO, Geneva, Switzerland) [33]. The methodological approach of this research can be divided into two main parts:  
1. Acquisition and processing of climatic data of the stations selected for the evaluation of the impact of the UHI in Rome;  
2. Different climatic conditions' effects on building energy performance. Starting from this, the first part of the research is characterized by the following steps:  
* The biennial meteorological data obtained from two airports near the city (Fiumicino and Ciampino airports) and in a densely built Rome neighborhood were examined and compared considering the same time interval (from January 2019 to December 2020), evaluating the differences in terms of temperature, wind velocity and relative humidity of the three different areas;
* Monthly average maximum and minimum temperatures were processed and used for evaluating the Urban Heat Island Intensity (UHII) in Rome. In order to quantify the UHI phenomenon, the day and night UHI intensity was used, calculated according to the following expressions: \[UHII_{day}=Tmax_{urban\ area}-Tmax_{rural\ area}\] (1) \[UHII_{night}=Tmin_{urban\ area}-Tmin_{rural\ area}\] (2)  
Figure 1: Locations of the weather stations. where \(UHII_{day}\) and \(UHII_{night}\) are the intensity indices of the UHI phenomenon, diurnal and nocturnal, respectively, \(Tmax_{urban\ area}\) and \(Tmin_{urban\ area}\) are the maximum monthly temperatures recorded during the day and the minimum monthly temperatures recorded at night by the selected Rome station and \(Tmax_{rural\ area}\) and \(Tmin_{rural\ area}\) are the maximum monthly temperatures recorded during the day and the minimum monthly temperatures recorded at night by the rural stations (in this case, one Fiumicino and one Ciampino). On the other hand, the second part of the research is characterized by the following steps:  
* Analysis of the influence of the different actual weather data recorded in 2019 by the selected stations of Rome, Fiumicino and Ciampino on the annual heating and cooling energy needs of a detached building, through the dynamic software TRNSYS;
* Comparison between the annual heating and cooling energy needs obtained using the TMY available for building energy simulations in Rome, UNI 10349:2016 and actual climatic data in 2019 in order to quantify the differences due to the use of unrealistic climate files. The stations selected in this study belong to the Davis Vantage Vue model. In particular, the accuracies of the sensors for measuring wind speed and direction, external temperatures and humidity are, respectively, 3 km/h or 5%, 3\({}^{\circ}\), 0.5 \({}^{\circ}\)C and 3%. In terms of resolution, the control unit is characterized by values equal to 1 km/h for wind speed, 1\({}^{\circ}\) for wind direction, 0.1 \({}^{\circ}\)C for external temperature and 1% for relative humidity. Furthermore, Table 1 provides information on their positioning.