Jannat A, Johnson Amanda, Manriquez D
AgNext, Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523.
AgNext, Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523.
J Dairy Sci. 2025 Aug;108(8):8567-8581. doi: 10.3168/jds.2025-26372. Epub 2025 May 16.
This study aimed to describe air quality dynamics in a commercial dairy farm focusing on 2 locations: a tunnel-ventilated barn (TVB) and a milking parlor (MKP). Assessed air quality components included carbon monoxide (CO), carbon dioxide (CO), methane (CH), ammonia (NH), particulate matter 2.5 µg/m (PM2.5), total volatile organic compounds (VOC), and temperature-humidity index (THI), which were continuously monitored from August 16 to December 22, 2023, using a multiple air quality sensor platform. Descriptive analysis revealed significant hourly variability in the air quality dynamics during the study period. Mixed-effects models revealed no significant differences in the overall CO and THI measurements between the barn and milking parlor. However, the location significantly influenced overall concentrations of other air components including CO, CH, PM2.5, VOC, and NH. Overall comparisons between TVB and MKP showed that the TVB had a higher overall CO concentration mean during the observation period compared with the MKP (LSM ± SEM; 640 ± 9.02 vs. 612 ± 9.01 ppm), while the MKP recorded highest CH levels (11.03 ± 0.52 vs. 8.87 ± 0.52 ppm). In the TVB, the NH levels ranged from 0.401 to 44.9 ppm, whereas no NH was detected in the MKP. The MKP recorded higher overall PM2.5 compared with the TVB (5.51 ± 0.31vs. 3.21 ± 0.31µg/m). The VOC levels exhibited higher overall means in the TVB compared with the MKP (153 ± 2.18 vs. 144 ± 2.16 ppm) but were characterized by substantial variability in both locations. Temporal trends suggested that the monitored air components might be influenced by farm activities such as feeding, cleaning, and milking as identifiable peaks we observed at specific hours of the day. We identified hourly pattern dynamics of CO, CO, CH, NH, PM2.5, VOC, and THI within the TVB and the MKP. Understanding these dynamics provides the opportunity to develop mitigation strategies for enhancing air quality within dairy facilities.
本研究旨在描述一家商业奶牛场的空气质量动态，重点关注两个地点：一个隧道通风牛舍（TVB）和一个挤奶厅（MKP）。评估的空气质量成分包括一氧化碳（CO）、二氧化碳（CO₂）、甲烷（CH₄）、氨（NH₃）、细颗粒物2.5微克/立方米（PM2.5）、总挥发性有机化合物（VOC）和温湿度指数（THI），使用多空气质量传感器平台于2023年8月16日至12月22日对其进行连续监测。描述性分析显示，在研究期间空气质量动态存在显著的每小时变化。混合效应模型显示，牛舍和挤奶厅之间的总体CO和THI测量值没有显著差异。然而，该位置对包括CO₂、CH₄、PM2.5、VOC和NH₃在内的其他空气成分的总体浓度有显著影响。TVB和MKP之间的总体比较表明，在观察期内，TVB的总体CO浓度平均值高于MKP（最小二乘均值±标准误；640±9.02 vs. 612±9.01 ppm），而MKP记录到的CH₄水平最高（11.03±0.52 vs. 8.87±0.52 ppm）。在TVB中，NH₃水平范围为0.401至44.9 ppm，而在MKP中未检测到NH₃。与TVB相比，MKP记录到的总体PM2.5更高（5.51±0.31 vs. 3.21±0.31微克/立方米）。与MKP相比，TVB中的VOC水平总体平均值更高（153±2.18 vs. 144±2.16 ppm），但在两个地点都表现出很大的变异性。时间趋势表明，监测到的空气成分可能受到农场活动的影响，如喂食、清洁和挤奶活动，我们在一天中的特定时间观察到了可识别的峰值。我们确定了TVB和MKP内CO、CO₂、CH₄、NH₃、PM2.5、VOC和THI的每小时模式动态。了解这些动态为制定改善奶牛场设施空气质量的缓解策略提供了机会。
