## 3 Results and Discussion
### Phase 1: Perform CFD Simulations  
As indicated in the previous section, the study was performed in four scenarios. They were those corresponding to the same living space of 9.4 m\({}^{2}\) with a unique occupant in soft sorting activities (minor than 6 MET), but in the following conditions:  
* Cross-ventilation: space with door and window opened. * Outdoor-ventilation: space with door closed and window opened. * Indoor-ventilation: space with door opened and window closed. * No-ventilation: space with door and window closed. \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Third Calibration**} & **Before Adjustment** & **After Adjustment** \\ \cline{2-3}  & **2.9497\(x-1120.8\)** & **\(y=2.9713x-1150.3\)** \\ \hline MAE & 29.29 ppm & 27.45 ppm \\ ME & \(-13.94\) ppm & 0.01 ppm \\ RMSE & 35.17 ppm & 32.17 ppm \\ MAPE & 3.11\% & 3.03\% \\ FIT & 90.23\% & 90.96\% \\ R\({}^{2}\) & & 99.31\% & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Statistical parameters related to the errors of the third calibration. Figure 9: Research framework scheme. The hygrometric comfort conditions were considered acceptable in all simulations, with temperature (T) ranging between 17 \({}^{\circ}\)C and 25 \({}^{\circ}\)C and relative humidity (RH) between 40% and 70%. The room faces southeast (taking the plane of the window as a reference). As the characteristic wind in this area comes from the east, ventilation with an open window was satisfactory. Figure 10 shows the working space employed in the research. The room was modelled with Ansys 2021 R2 version software. The main parameters considered in the simulations was the mass flow of incoming and outgoing air through the different openings and the concentration (or mass flow) of CO\({}_{2}\) from the metabolic exhalation of the occupant in the working space. Among four scenarios, cross-ventilation had the highest air renewal. This example could be extrapolated to public spaces that require a high air renewal rate to keep CO\({}_{2}\) levels low. Therefore, the location of measurement points was based on this scenario, as it was the most unfavourable. In this scenario, static and transitional tests were performed. For this purpose, an inlet air mass flow rate of 0.008 kg/s for each hourly renewal considered, depending on the scenario, was defined. Figure 11 shows the zones in the space where vortices are formed. It must be noted that these points were not suitable for the placement of the CO\({}_{2}\) sensors for IAQ control. On the other hand, in the case of no-ventilation (Scenario 4), the same mass flow of air was considered and there was an increase of exhaled metabolic CO\({}_{2}\). The permeability of the door and window allowed for pressure balancing through minimal air renewal, which was considered. Figure 12 shows the simulation of this scenario for a period of 9 h. As can be observed, as time progressed, the CO\({}_{2}\) concentration in the working space became uniform, being higher in the areas close to the CO\({}_{2}\) emitter. To decide a good sensor location in each of the four scenarios, the parameters for the mass flow of air from the concentration of CO\({}_{2}\) emitted by the people in the room measured and the ventilation were used. The amount of CO\({}_{2}\) reflected in all simulations performed was 0.0004 kg/s. However, the mass flow of air from the ventilation varied according to the scenario considered. Among all of them, the highest mass air flow came from the highest air renewal (Scenario 1, cross ventilation) with three renewals per hour, corresponding to a volumetric flow rate of 20 L/s per person. By studying the behavior of the turbulent flow by CFD, the vortices in the room were observed. These points were not suitable for sensor placement. On the contrary, in Scenario 4 (no ventilation), there was no air flow that caused  
Figure 10: Working space for the research. vortices and the CO\({}_{2}\) concentration increased progressively, uniformly filling the volume tested.