The implementation of poultry houses with enhanced control over environmental variables represents a solution to the growing demands for production and animal welfare. This study assessed the internal environment of dark-house poultry houses for broilers on a weekly basis throughout a production cycle. Data were collected over six weeks, from March to April 2016 involving 40,000 Cobb500^TM broilers. A Hobo^® datalogger continuously monitored the temperature (°C), relative humidity (%), dew point temperature (°C), and black globe temperature (°C) at 15 min intervals. The indices analyzed included the temperature and humidity index (THI), the black globe and humidity index (BGHI), and enthalpy (H). In the first week, both the THI and BGHI indicated favorable conditions for the birds, with the THI ranging from 72.4 to 80 and the BGHI from 77 to 81.6. Between the second and fifth weeks, the THI conditions varied between thermal comfort and discomfort, from 56.6 to 72. In the sixth week, all indices indicated discomfort, reflecting increased metabolism and population density. The dark-house system demonstrated a feed efficiency of 51%, an accumulated mortality rate of 1.97%, and a total production of 99,873 kg of meat. The study highlights the importance of continuously monitoring and adjusting environmental conditions to optimize production and enhance bird welfare.

A deeper understanding of gas emissions in milk production is crucial for promoting productive efficiency, sustainable resource use, and animal welfare. This paper aims to analyze ammonia and greenhouse gas emissions in dairy farming using bibliometric methods. A total of 187 English-language articles with experimental data from the Scopus and Web of Science databases (January 1987 to April 2024) were reviewed. Publications notably increased from 1997, with the highest number of papers published in 2022. Research mainly focuses on ammonia and methane emissions, including quantification, volatilization, and mitigation strategies. Other gases like carbon dioxide, nitrous oxide, and hydrogen sulfide were also studied. Key institutions include the University of California–Davis and Aarhus University. Bibliometric analysis revealed research evolution, identifying trends, gaps, and future research opportunities. This bibliometric analysis offers insights into emissions, air quality, sustainability, and animal welfare in dairy farming, highlighting areas for innovative mitigation strategies to enhance production sustainability. This research contributes to academia, enhancing agricultural practices, and informing environmental policies. It is possible to conclude that this research is a valuable tool for understanding the evolution of research on gas emissions in dairy cattle facilities, providing guidance for future studies and interventions to promote more sustainable production.

The dairy sector plays a fundamental role in the economic development of numerous regions by creating jobs and sustaining the livelihoods of millions of people. However, concerns related to animal welfare and environmental sustainability—particularly greenhouse gas (GHG) emissions—persist in intensive dairy systems. This study aimed to measure and assess the presence of GHGs, such as methane (CH₄) and carbon dioxide (CO₂), in a compost barn facility, using spatial variability tools to analyze the distribution of these gasses at different heights (0.25 m and 1.5 m) relative to the animals’ bedding. Data were collected over five consecutive days using a prototype equipped with low-cost sensors. Geostatistical analysis was performed using R, and spatial distribution maps were generated with Surfer 13^®. Results showed elevated CH₄ concentrations at 0.25 m, exceeding values typically reported for similar systems values (60–117 ppm), while CO₂ concentrations remained within the expected range (970–1480 ppm), suggesting low risk to animals, workers, and the environment. The findings highlight the importance of continuous environmental monitoring to promote sustainability and productivity in confined dairy operations.

This study characterizes a compost-bedded pack barn of a dairy cattle farm in terms of CO₂ emissions approximately 20 min after tilling under stable atmospheric conditions. Emission fluxes were calculated with the bLS model WindTrax, assessing modeled CO₂ concentrations at two altitudes (5.0 m and 10.0 m ABGL) by comparing them with those measured by a UAV-based system at the same two altitudes. The UAV-based system was equipped with a low-cost self-engineered MSP (multi-sensor platform) containing an NDIR sensor for measuring concentrations and detecting environmental conditions, which were measured both by MSPs and commercial sensors. The input data were provided by the same sensors positioned on the ground (1.5 m ABGL), upwind and downwind with respect to the emission source. A sensitivity analysis of atmospheric stability in the bLS model yielded differences between median calculated emission fluxes for stable and unstable conditions from −0.020 to 0.034 g ∙ m⁻² ∙ s⁻¹. Mean percentage errors gave overestimates of 8–39% and 13–21% 5.0 m and 10.0 m ABGL. The RMSE also indicated overestimates ranging from 44 to 275 ppm. This is the first study to validate concentrations calculated by a bLS model at two altitudes by using a UAV-based system on a compost-bedded pack barn.