**5. Conclusions**

The introduction of the Climate Based Daylight Modelling (CBDM) concept has questioned the robustness of the traditional practice of relying on static (i.e., fixed) sky conditions to appraise daylight levels within buildings. This paper advanced the knowledge about the use of recently developed CBDM metrics by proposing a detailed daylight analysis of a school building located in Agira (Italy), a town that experiences sunny and clear-sky conditions for most of the year.

Hourly simulations, run using the Radiance-based DIVA software for a calibrated daylight model, allowed to identify the main issues of rooms presenting different orientation, shape, function, and furniture, and helped to inform the design of the required shading and re-directing devices.

More in detail, the calculation of the spatial Daylight Autonomy (*sDA*) metrics revealed good daylight availability for all of the rooms analysed (with values always higher than 90%), but on the other hand the Annual Sunlight Exposure (*ASE*) calculation evidenced a risk of glare occurrence especially for the gym (*ASE* = 68.2%). This happens because of the large glazed surfaces that are oriented due to both west and east, since they expose the room to direct sunlight in the morning (from east) and in the afternoon (from west). Glare risks have been confirmed by the calculation of the simplified Daylight Glare Probability (*DGPs*) metrics for some observers' position and by the number of hours when the Useful Daylight Illuminance (*UDI*) metric is above the upper threshold of 2000 lux (which happens for around 23% of the occupied hours in the standard and computer classrooms).

Based on these outcomes, retrofit solutions that are aimed at reducing and re-directing direct sunlight, such as external overhangs, light shelves, louvers, and reflective ceilings, have been designed and their efficacy tested by calculating all of the static and dynamic metrics again. The results showed that, despite a reduction in daylight levels in proximity of the windows, as shown by lower *sDA* values than in the base case, higher illuminance values were expected at the bottom of the rooms.

In this way, the useful *UDI* metrics keeps above 90% in all rooms, the *ASE* metrics is close to the threshold of acceptability of 10% (except for the computer classroom) and the *UR* significantly improves in all rooms.

However, it must be pointed out that a design that was carried out using CBDM metrics appears in contrast with what would be suggested if considering the average Daylight Factor (*aDF*) metrics alone, as it is usually done in common design practice. In fact, all of the proposed design solutions lower the *aDF* values if compared to the existing scenario, which are already below the minimum threshold, as prescribed by the Italian regulations for classrooms. This would likely sugges<sup>t</sup> a designer to bring in more daylight by increasing the glazed surfaces; however, such a choice would actually be wrong in relation to the sunny hours, which are much more frequent than cloudy hours in Southern Italy.

These outcomes rebate the need of performing more accurate and dynamic daylight simulations using recorded (i.e., varying) rather than fixed sky conditions to correctly inform the design process.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2071-1050/10/8/2653/s1, Figure S1: Hourly luminance distribution for a typical user of the standard classroom, computer classroom and gym, respectively, during 7 December from 7 a.m. to 5:30 p.m.

**Author Contributions:** Conceptualization, Methodology and Writing, V.C.; Writing—review and editing and Data Curation, G.E.; Supervision and Resources, L.M.; Investigation and Visualization, F.P.N.

**Acknowledgments:** The authors would like to warmly thank all the teachers and pupils of the 'Guglielmo Marconi' elementary school in Agira (Italy) for their kind support throughout the measurement campaign.

**Conflicts of Interest:** The authors declare no conflict of interest.
