Generation and emission of particulate matter (PM) from dairy farming have a potential effect on the health and welfare of the animals, farm workers and even the neighbors. Monitoring accuracy of the PM concentration depends much on the number and location of sampling points as well as the sampling interval (SI). Most PM studies used intermittent sampling methods, such as sampling the concentration for a couple of days in a season or in several seasons, which were unable to accurately reflect the actual PM concentration level and variation inside the intensive dairy building. To determine the reasonable SI of PM sensors, this study developed an Internet of Things (IoT)-based monitoring system for PM concentration in an intensive naturally ventilated dairy barn, in which a 17-point continuous concentration monitoring of PM less than 2.5 μm in aerodynamic diameter (PM_2.5) and the total suspended particulate (TSP) was carried out in autumn and winter, and its 5-minute mean values were regarded as relatively true values (RTV). Using error analysis, the daily averaged PM concentration with 30 min and 1, 2, 3, 6, 12 h SI in autumn and winter and the hourly mean PM concentration with 10, 15, 20, 30 min and 1 h SI during the day (05:00-23:00), night (23:00-05:00) and daily management periods (05:00-07:00, 13:00-15:00, 21:00-23:00) were first computed, respectively; then their relative errors ( E_r ) with RTV were counted within 5% and 10% range; and finally, the maximum accepted SI for daily and hourly mean PM concentration measurements were determined based on acceptance criteria in bioanalytical method (66.7%).The results showed that within 5%, when the SI for TSP concentration were set within 2 h (in autumn) and 1h (in winter), and they were within 3 h (in autumn) and 1 h (in winter) for PM_2.5 measuring, respectively. It can accurately obtain the daily average PM concentration of the naturally ventilated dairy barn in autumn and winter. When the SI were at 20 min (in autumn) and 15 min (in winter) in daytime, and 30 min (in autumn) and 15 min (in winter) in nighttime for the TSP measurements, and 30 min for PM_2.5 daytime and nighttime (in autumn and winter), an accurate monitoring could be obtained on hourly mean PM concentration and its fluctuations. When the sampling interval for TSP was 10 min, and the interval for PM_2.5 was on 20 min in autumn and winter, respectively, the measurement data can reflect the impact of daily management on the PM concentration inside the barn. The findings of this study can be applied as a standardized procedure to continuously track the PM concentration in an intensive naturally ventilated dairy barn.

Particulate matter (PM) concentration can be real-time monitored to assess the environmental risks and make emission reduction measures in dairy barns. However, a great challenge is remained on arranging as few sampling points as possible to accurately monitor the PM concentration in an intensive barn, particularly with the rapid development of large dairy barns in China. This study aims to design an appropriate monitoring layout with the optimal PM sampling number and location. An online monitoring system was built to continuously detect the PM concentration inside a naturally ventilated dairy barn using the Internet of Things (IoT) and sensing technologies. A total of 17 sampling points were set inside three relatively independent sections of the investigated barn. The total suspended particle (TSP) and PM_2.5 concentrations were monitored in real time for the six months during the field test. The uniformity of PM concentration was evaluated on the spatial distribution of PM concentration among the three sections and the difference in sampling heights. The systematical clustering and error analysis were also performed on the sampling of PM concentration. The optimal sampling was determined to compare the measurement with the six regular ones under three environmental controls (namely, EC1: Fans and spraying, EC2: Fans, EC3: No fans and no spraying). The average PM concentration from the 17 sampling points was treated as the true value during data analysis. Results showed that no significant difference was found for the TSP and PM_2.5 concentration among the three measuring sections of the barn (P>0.05). TSP concentration sampled at the height of 9.0 m was significantly lower than that at the 1.5 and 2.5 m heights (P<0.05). There was no statistical difference in the PM_2.5 concentration among different sampling heights (P>0.05). The concentrations of TSP and PM_2.5 sampled at the height of 2.5 m were uniformly distributed among three sections of the barn. The sampling point setting down the ridge opening (approximately 9.0 m above the floor surface) was necessary for the TSP concentration monitoring. In TSP and PM_2.5 concentrations, the sum of absolute errors between the true values and the optimized sampling under three ECs were 6.4%-22.6% and 4.7%-14.2%, respectively, indicating all smaller than those of six regular monitoring (P<0.05). Generally, the number of PM sampling points was appropriately reduced to consider the monitoring costs and practical operability. The final PM monitoring was determined with the optimized sampling number and location in a naturally ventilated dairy barn. Six PM sampling points were set inside a dairy barn: one sampling point 1.0−2.0 m down the ridge openings in the central of the barn, two sampling points at a 2.5 m height above the cubicles, and three sampling points distributed at milking alley, feed delivery alley and manure alley at a 2.5 m height, respectively. Among them, the three sampling points down the ridge opening and above the cubicles should be diagonally arranged along the barn. The final PM sampling can be expected to achieve both the accuracy and economy of PM real-time monitoring for a naturally ventilated dairy barn.

A ventilation system can often dominate a controllable environment in a pig house. A vertical ventilation system with roof and manure pit exhaust fans has been introduced into some newly built pig houses in Northern China, in order to improve the microclimate environment. However, it is still unclear on the adaptability of this ventilation system in cold seasons. This study aims to evaluate the suitability of the ventilation system in northern China. A field measurement was also performed in the newly built pig house using the vertical ventilation pattern in Inner Mongolia. The pig house was equipped with air inlets on the sidewalls, while there was no ceiling inside. Two independent units (U1 and U3) of the pig house were selected for the experiment. Portable monitoring unit (PMU) and particulate concentration monitoring unit (PCMU), internet of things (IoT)-based environmental monitoring devices, were developed to continuously measure indoor temperature, relative humidity, carbon dioxide (CO₂), ammonia (NH₃) and total suspended particulate matter (TSP) concentrations in autumn and winter. Ventilation rate was also recorded with the feed intake, feed conversion ratio, mortality, initial and final average weight of the pigs. Then, the adaptability of the vertical ventilation was evaluated in the extremely cold climate using the indoor thermal, air quality and spatial uniformity of the pig house with production performance. Results show that the average temperature and relative humidity during measurement were 22.7 ℃ and 59.6% in the ranges of 18.2-29.2 ℃ and 38.6%-82.1%, respectively. Meanwhile, the average ventilation rate fluctuated at 0.34-0.39 m³/(h∙kg). Seasonal means of NH₃, CO₂ and TSP concentrations were 6.5 mg/m³, 2200 mg/m³ and 2915 μg/m³, which were fluctuated in 3.1-12.3 mg/m³, 1244-3 400 mg/m³, 1563-4215 μg/m³, respectively. The thermal and air quality environment of the pig house was generally controlled in a suitable state for pigs. While effective environmental temperature was 27.1-30.7 ℃ in the pig house during the nursery period, indicating mild heat stress to the pigs with a duration of 12.9% of the measurement. The Non-uniformity Coefficient of temperature, relative humidity, and NH₃, CO₂, and TSP concentrations in the pig house were 0.01, 0.15, 0.45, 0.03, and 0.15, respectively. Meanwhile, the maximum differences in the temperature, relative humidity, and NH₃, CO₂, and TSP concentrations in the indoor space were 1.5 ℃, 32.8%, 4.8 mg/m³, 445 mg/m³, and 1296 μg/m³, respectively, indicating the relatively uniform distribution in the environment. Average ventilation rates of U1 and U3 units in the nursery period were 0.35 and 0.39 m³/(h∙kg), respectively, which were 0.34 and 0.35 m³/(h∙kg) during the fattening period. Generally, the ventilation of the pig house fully met the minimum demands in northern China in cold seasons. Moreover, the concentrations of NH₃ and CO₂ in pig houses were 50% and 52% lower than those without manure pit fans in Europe. There were also comparable daily weight gain (842 vs. 818 g/d), feed conversion ratio (2.68 vs. 2.79), and mortality rate (1.68% vs. 1.31%) of the pigs in the U1 and U3 test units. The thermal environment and air quality of the experimental pig house were suitable for the production performance of the pigs. In conclusion, the tested pig house was equipped with roof and manure pit exhaust fans but without ceiling settings, where the thermal and air quality environment was maintained in a suitable state in autumn and winter. Generally, the production performance of pigs was also achieved under such an environment.