*3.1. Model Application*

In the selected district, 1228 buildings were analyzed. Of these buildings, 1097 were classified as potential rooftop renovation opportunities, distinguishing three types of smart solutions: Green roof technology, high-reflectance strategy, and energy production from ST collectors and PV modules.

According to [23], in order to give a priority of interventions, critical areas with the worst air quality conditions were identified as priority areas for the installation of green roof technologies (Figure 6a, red areas) to mitigate the UHI e ffect. The other areas, with mainly residential buildings, were considered for solar energy production using ST collectors and PV panels. Solar technologies were dimensioned considering residential and nonresidential demand. Figure 6b shows the rooftop classification, distinguishing these three types of smart solutions.

The main characteristics of the buildings selected as potential are indicated in Table 5. It is possible to observe that, thanks to the typical urban mix of Turin, the retrofit measures are well distributed within the district and, moreover, there is a consistent potential. For this reason, it is important to encourage the buildings' renovation – in this case the rooftop renovation—especially in consolidated urban contexts where energy e fficiency measures to intervene on buildings are limited.

**Figure 6.** District of Turin with a dimension of 1 km2: (**a**) Building block classification according to three classes of air quality conditions (green, good; yellow, acceptable, red, bad) [23]; (**b**) analysis of roof potential and feasibility of smart solutions: Green, high-reflectance, and solar roofs.



#### *3.2. Smart Roof Solutions' Assessment*

This subsection describes the main results obtained from the use of three smart solutions: Green roof technology, high-reflectance roof strategy, and solar energy technology. The aim was to harness the potential of urban rooftops in a district in the city of Turin.

## 3.2.1. Green Roof Technology

In the district analyzed, 64,712 m<sup>2</sup> of roofs were identified as potential green roofs. Referring to Equation (3), the energy savings for heating and cooling seasons were quantified for a district in Turin. In this scenario, potential roofs were renovated using green roof technologies. The thermal transmittance with green technologies is equal to 0.24 <sup>W</sup>/m<sup>2</sup>/<sup>K</sup> (according to Italian Decree 26/6/2015) and the solar absorptance of a green roof surface is 0.87 [48,56]. The energy savings after the installation of green roofs was equal to 5669 MWh/year, which corresponds to 8.4% of space heating consumptions of residential buildings. The energy savings during cooling season was equal to 662 MWh/year. Figure 7 describes the energy savings at block-of-building scale, distinguishing heating and cooling seasons.

Thermal conditions were investigated using some parameters calculated at block-of-building scale from satellite images (Section 2.1.). These parameters are the *NDVI* and the *LST* and allow us to describe the UHI e ffect and the local-climate characteristics of the urban environment. An analysis at blocks-of-building scale was made, and Figure 8a shows the variation of *LST* before and after the installation of green roof technologies. According to the literature review [34,35], the *LST* and the air temperature tend to decrease more or less rapidly as the green areas increase, depending also on the type of urban morphology. Increasing the green roofs' areas of 64,712 m2, on average, the *LST* in the district tends to decrease by 1 ◦C (Figure 8b).

**Figure 7.** Green roofs' potential assessment at block-of-building scale: (**a**) Heating and (**b**) cooling primary energy savings in MWh/year.

**Figure 8.** Green roofs' potential assessment at block-of-building scale: (**a**) Thermal condition assessment, Land Surface Temperature (*LST)* variation before and after the installation of green roof technologies; (**b**) correlation between the *LST* variation and the quota of green roof area.

The feasibility of green roof technology was assessed considering requirements the Ministerial Decree 26/06/2015. The roofs' albedo in the district analyzed varied between 0.05 and 0.26 (for a few buildings, mainly industrial, the albedo was around 0.33) [23]. After retrofit measures with green roofs, the roof albedo criterion was respected due to the installation of passive cooling technology.

## 3.2.2. High-Reflectance Roof Strategy

Starting with 500 low buildings located in the district of Turin, 417 were selected as potential for the renovation of rooftop with white color (high-reflectance roof). Of these 417 potential buildings, which corresponded to an area of almost 45,000 m2, 313 had a slope less than 8.5◦ and 104 had a higher slope (on average, had slope of 8.8◦, see Table 5). Figure 9 shows the *SRI* values calculated for each block of buildings. The *SRI* values are weighted according to the m<sup>2</sup> of each roof. Figure 9 shows the *SRI* roof values at block-of-building scale, before (Figure 9a) and after (Figure 9b) the use of high-reflectance roof strategy on 417 potential roofs. From the results, it emerged that it is possible to obtain an increase in *SRI* of almost 30 and a reduction of *Ts* of over 10 ◦C. Therefore, these indicators could help designers and consumers to choose the proper materials for sustainable buildings and communities.

The feasibility of high-reflectance roof strategy was assessed according to the Italian Decree 11/01/2017 and the environmental protocols. The *SRI* prerequisites (*SRI* > 0.29) were respected.

**Figure 9.** Solar Reflectance Index (*SRI*) (%) values of existing roof at block-of-building scale: (**a**) Before (**b**) and after high-reflectance strategy.
