Ammonia (NH₃) concentration has seldom been used for environmental control of weaner buildings despite its impact on environment, animal welfare, and workers’ health. This paper aims to determine the effects of setpoint temperature (ST) on the daily evolution of NH₃ concentration in the animal-occupied zone. An experimental test was conducted on a conventional farm, with ST between 23 °C and 26 °C. NH₃ concentrations in the animal-occupied zone were dependent on ST insofar as ST controlled the operation of the ventilation system, which effectively removed NH₃ from the building. The highest NH₃ concentrations occurred at night and the lowest concentrations occurred during the daytime. Data were fitted to a sinusoidal model using the least squares setting (LSS) and fast Fourier transform (FFT), which provided R² values between 0.71 and 0.93. FFT provided a better fit than LSS, with root mean square errors (RMSEs) between 0.09 ppm for an ST of 23 °C and 0.55 ppm for an ST of 25 °C. A decrease in ST caused a delay in the wave and a decrease in wave amplitude. The proposed equations can be used for modeling NH₃ concentrations and implemented in conventional controllers for real-time environmental control of livestock buildings to improve animal welfare and productivity.

This paper aims to study the evolution of CO₂ concentrations and emissions on a conventional farm with weaned piglets between 6.9 and 17.0 kg live weight based on setpoint temperature, outdoor temperature, and ventilation flow. The experimental trial was conducted during one transition cycle. Generally, the ventilation flow increased with the reduction in setpoint temperature throughout the cycle, which caused a reduction in CO₂ concentration and an increase in emissions. The mean CO₂ concentration was 3.12 g m^–3. Emissions of CO₂ had a mean value of 2.21 mg s⁻¹ per animal, which is equivalent to 0.195 mg s⁻¹ kg⁻¹. A potential function was used to describe the interaction between 10 min values of ventilation flow and CO₂ concentrations, whereas a linear function was used to describe the interaction between 10 min values of ventilation flow and CO₂ emissions, with r values of 0.82 and 0.85, respectively. Using such equations allowed for simple and direct quantification of emissions. Furthermore, two prediction models for CO₂ emissions were developed using two neural networks (for 10 min and 60 min predictions), which reached r values of 0.63 and 0.56. These results are limited mainly by the size of the training period, as well as by the differences between the behavior of the series in the training stage and the testing stage.

Measuring animal activity is useful for monitoring animal welfare in real time. In this regard, passive infrared detectors have been used in recent years to quantify piglet activity because of their robustness and ease of use. This study was conducted on a commercial farm in Northwest Spain during six complete breeding cycles. The hourly average activity of weaned piglets with a body mass of 6–20 kg was recorded and further analyzed by using a multiplicative decomposition of the series followed by a wavelet analysis. Finally, the real series were compared to the theoretical models of activity. Results showed a high level of movement immediately after weaning and a sustained level of activity throughout the cycles. The daily behavior of the piglets followed a clear circadian pattern with several peaks of activity. No differences in behavior were observed between spring–summer cycles and autumn–winter cycles. Single-peak models achieved the best predictive results. In addition, the installed sensors were found to underestimate mild activity.