The livestock sector significantly contributes to atmospheric emissions of various pollutants, such as ammonia (NH₃) and particulate matter of diameter under 2.5 µm (PM2.5) from activity and barn management. The objective of this study was to evaluate the reliability of low-cost sensors integrated with an IoT system for monitoring PM2.5 concentrations in a dairy barn. To this end, data acquired by a PM2.5 measurement device has been validated by using a high-precision one. Results demonstrated that the performances of low-cost sensors were highly correlated with temperature and humidity parameters recorded in its own IoT platform. Therefore, a parameter-based adjustment methodology is proposed. As a result of the statistical assessments conducted on this data, it has been demonstrated that the analysed sensor, when corrected using the proposed correction model, is an effective device for the purpose of monitoring the mean daily levels of PM2.5 within the barn. Although the model was developed and validated by using data collected from a dairy barn, the proposed methodology can be applied to these sensors in similar environments. Implementing reliable and affordable monitoring systems for key pollutants is crucial to enable effective mitigation strategies. Due to their low cost, ease of transport, and straightforward installation, these sensors can be used in multiple locations within a barn or moved between different barns for flexible and widespread air quality monitoring applications in livestock barns.

Livestock farming has been identified as a significant contributor to atmospheric pollution, underscoring the necessity for the design and management of housing systems to adopt mitigation strategies. In the context of civil engineering, green wall systems are proving to be effective solutions for air filtration and purification. Nevertheless, research related to their application in livestock buildings is limited. This study focuses on the design, implementation, and performance evaluation of a modular, mobile green wall system that has been specifically developed to test PM2.5 concentrations’ reduction in naturally ventilated, free-stall dairy barns in the Mediterranean region. To this end, PM2.5 concentrations and climatic parameters have been measured before and after the application of the green wall system. Based on one-way analysis of variance, PM2.5 concentrations after the application were significantly lower (p < 0.001) than those before the mitigation strategy. The results of this study showed that the overall efficacy of the green wall reached 44%. The implementation of green wall systems offers a promising strategy to improve air quality in livestock facilities and to design aesthetically pleasing barns with a positive impact on the surrounding landscape.