## 3 Results and Discussion
### Vertical Variation of Ammonia Concentration and Air Temperature
#### 3.3.3 Ammonia and Temperature in Cross Section C  
With the wind direction at 90\({}^{\circ}\), the ammonia concentration is similar to the previous sections. That is, the decrease in concentration is from 15.4 to 7.5 ppm, only 0.5 and 0.2 ppm higher than in sections A and B, respectively. With the wind direction at 45\({}^{\circ}\), the ammonia concentration in this section decreases from 15.4 to 5.8 ppm. When the wind direction is at 0\({}^{\circ}\), the ammonia concentration decreases from 15.4 to 12 ppm, which is equivalent to the smallest ammonia variation of the three sections analyzed. The temperature in this section ranges from 19.8 \({}^{\circ}\)C to 20.6, 21.5, and 21.3 \({}^{\circ}\)C for the wind direction at 0\({}^{\circ}\), 45\({}^{\circ}\), and 90\({}^{\circ}\), respectively (Figures 5C and 6C). Managing the environment inside the farm passively presents specific difficulties among the variables analyzed: wind speed, temperature, and gas concentration (ammonium). For temperature and humidity control, a critical aspect is the orientation of the windows in relation to the wind direction, as described by [PERSON] et al. (1998), [PERSON] et al. (2000), and [PERSON] (2007). Previous results indicate that even when the ventilation rate in different facilities is the same, the critical factor to consider is the position of the windows that can help remove the gas concentration that originates in the manure area. By managing the ventilation rate, temperature control is achieved in the cage area and in the three simulated wind directions. When the wind direction angle is 0\({}^{\circ}\), it is feasible to efficiently remove the volume of air, and consequently, temperatures ranging from 21 \({}^{\circ}\)C with a longitudinal gradient of \(\pm\)1 \({}^{\circ}\)C are obtained. However, the maximum reduction in the concentration of gases, in this case ammonium, occurs when the wind direction is simulated with an angle of 45\({}^{\circ}\) with respect to the \(z\) axis. The difficulty in managing ammonium gas does not depend only on the ventilation rate but also on the generation rate in the floor area (source) due to temperature levels, as reported by [PERSON] et al. (2015) and [PERSON] et al. (2016). Due to the interaction of factors that determine the farm environment, it is necessary to integrate other climatic variables, such as relative humidity and the concentration of gases such as CO\({}_{2}\), for better control of the rabbits' health. However, according to the objective set in this work, ammonium levels have been observed distributed mainly in the cage area as a function of the wind direction with respect to the farm. It stands out that although it is true that a difference is observed with respect to the simulated wind direction, the difference in ammonium concentration ranges from 2 ppm (Figure 7), so there is a relationship with the results found by [PERSON] et al. (2016), [PERSON] et al. (2019), [PERSON] et al. (2007), and [PERSON] et al. (2018) regarding the variables that influence the concentration of gases and their interaction with the ventilation rate and temperature. Figure 6: Air temperature in cross sections A, B, and C.  
Figure 7 show the dynamics of the ammonia concentration in the rabbit zone along the cages. Computational fluid dynamics modeling is a robust tool for prediction and design in physical processes involving fluids. In rabbit farming facilities, climate control is a critical activity due to the production of ammonia by the rabbits themselves. As an example, the quality of semen for insemination depends on climatic control, which consequently implies the health of the rabbit. The contribution of this research is the construction and validation of a model capable of predicting the environmental dynamics on the farm as well as knowing the levels of ammonium and temperature at the level of the rabbit cage.