## 4 Analysis of Results and Discussion
### Divergence of DA and DAp According to Room Location  
The last analysis quantifies the divergence of DA and DAp according to the different climate conditions of the room location: London UK, with mainly overcast skies and Madrid, Spain, with predominantly clear skies. It could be assumed that the differences of the climate conditions will affect to the use of daylight during the summer season, where DAp is ignoring most of the days in its calculation process. Figure 7 shows the results for both metrics according to the room location. As in the previous trials, the first and second rows show the room sections with a window-to-wall ratio of 30%, third and fourth rows show medium-size openings with a relative surface of 45% and the last two rows describe the results for large windows which correspond to a ratio of 60%. Odd columns represent  
Figure 6: Quantification of DA and DAp in the calculation models according to room reflectance. bright rooms, with inner surfaces with a high reflectance value, while even columns show dark rooms. In addition, odd rows describe the results for an illuminance threshold of 300 lx, while even rows show the quantification of the metrics for the upper requirement of 500 lx. Finally, the left columns describe the results for windows facing North, while right columns represent the opposite orientation. As in previous studies, labels located in the left-top of the room sections describe the calculation model in accordance with parameters defined in Table 2.  
As deduced from Figure 7, study cases located in Madrid with an illuminance requirement of 300 lx show a not significant difference between DA and DAP, due to the fact that both metrics achieve very high values, mainly with medium-size or large windows. Quantifying this assertion, it can be observed that the mean deviation for Madrid location,  
Figure 7: Quantification of DA and DAP in the calculation models according to room location. with mainly clear skies, is 3.8%, with a standard deviation of 1.3%. These values slightly increase for a threshold of 500 lx, where the mean deviation goes up to 5.6%, keeping a standard deviation of 2.9%. Therefore, it can be deduced that the difference between DA and DAp is almost negligible for locations with a predominance of clear skies and rooms with sufficient access to daylight. The opposite case occurs for the London scenario. The divergence of both studied metrics increases considering a location with predominantly overcast skies and therefore poorer access to daylight. As deduced from Figure 7, the mean deviation between DA\({}_{300}\) and DAP300[243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253,  
The analysis of the results was carried out considering a set of simulation hypotheses generated from the base case study. They were defined by combining three variable characteristics (windows-to-wall ratio, orientation, room reflectance) in two different locations (Madrid, with mainly clear sky conditions, and London, with mainly overcast sky conditions), using two illuminance thresholds (300 and 500 lx). The divergence between the DA and DAp results according to windows size is noticeable, increasing in an almost constant way when the illuminance threshold is higher or when the access to natural light is poorer (a mean deviation of 7.5% with a 300 lx threshold and 10.6% for 500 lx, in the case of an opening size of 30%), and showing the maximum difference at the back of the room (a maximum divergence of 18.5% and 22%, respectively). When the variable under study is the windows orientation, North models show a bigger divergence between both metrics than those to the South. This happens especially in the area close to the back of the room, given that DAp provides a more accurate approach to the real use of daylight in this seasonal use space when the access to natural light is poorer. The mean deviation for windows facing North is 8.0% with a threshold of 300 lx and 12.5% for 500 lx, while these values decrease when the window is facing South, with 5.2% and 5.6% respectively.