# Urban Overheating Impact: A Case Study on Building Energy Performance
## 3 Results and Discussion
### Effects of Different Climatic Scenarios on BES  
The second part of the study investigated the influence of various meteorological data on the annual heating and cooling energy needs of a sample building using the dynamic software TRNSYS. For this purpose, the meteorological parameters acquired by the Rome, Fiumicino and Ciampino stations in 2019 were used. The results were then compared with those obtained by applying the Typical Meteorological Years of the IGDG collection, related to Fiumicino and Ciampino (respectively defined as \"TMY Fiumicino\" and \"TMY Ciampino\") and the climatic data provided by the Italian standard UNI 10349, which was updated in 2016. By means of a statistical analysis, UNI 10349 provides a typical year composed of data that best represent the typical climatic conditions of a specific location. The meteorological data acquired by the Rome station in 2019 were used as a reference sample year for the comparison of the results of the energy simulations conducted on the same building model but thermally stressed with the other climatic years. Although the climatic data of both 2019 and 2020 were available, only the climatic data related to 2019 were considered due to the very small differences between the two years. Furthermore, considering as reference 2019 allowed to exclude any effect correlated to the international pandemic of SARS-CoV-2 in terms of heat anthropogenic sources. Figure 8 shows the comparison of average monthly temperatures between the sample year and the law standard. It can be observed that the temperature trends of UNI 10349 and the sample year are quite similar from July to December. The sample year is characterized by slightly higher temperatures except for January, March and April, during which an inversion of the trend of the two curves can be noticed, with negative temperature differences equal to \(-0.46\), \(-0.65\) and \(-3.13\,^{\circ}\)C, respectively. Overall, the temperature differences range from \(-3.13\) to \(3.60\,^{\circ}\)C, relating to the months of May and June. Figure 9 shows the wind speed and relative humidity comparison between the sample year and the law standard. Figure 8: Sample year and UNI10349 temperature comparison. The wind speeds reported in UNI 10349 are standardized based on the \"wind zone\" that splits Italy into distinct zones with varying wind speed values. With an average wind speed of 6.1 km/h and a predominant south-west wind direction, Rome is classified as a \"C\" zone. This is greater than the values reported in the sample year, which vary from 1.2 to 3.1 km/h, with an average value equal to 2.4 km/h. The patterns of the relative humidity values of the Italian standard and the sample year may also be seen in Figure 9. Except for January (+15%), March (+6%) and December (+6%), UNI 10349 exhibits lower values (from 11% to 40%) than the sample year. Since the weather stations do not measure solar radiation, these data were obtained from the TMYs of the IGDG collection, inside TRNSYS using the \"Type 109-TMY2\", specifically considering the TMY of Ciampino and Fuumicino. In detail, Type 109-TMY2 was used both for the extrapolation of solar radiation values in the energy simulations relating to Rome (Rome, 2019), Ciampino (Ciampino, 2019) and UNI 10349 and as a complete source of data in the energy model called \"TMY Ciampino\". The same procedure was followed for the simulations related to Fuumicino. The TMY of Fuumicino derived from the IGDG collection was used both for the acquisition of the missing solar radiation data in the simulation model relating to the year 2019 and as a complete climate file for the simulation of the model \"TMY Fiumicino\". During the energy simulation through TRNSYS, the wind speed values corresponding to each dataset were also used to compute the external convective heat transfer coefficients, using the well-known correlation \(h_{c}=4\cdot v+4\), where \(v\) is the wind speed expressed in m/s ([PERSON] et al., 2019; [PERSON] et al., 2019).