Particulate matter (PM) emitted from livestock and poultry production contributes to atmospheric aerosol loading, affecting animal health and the surrounding atmospheric environment. However, developing and optimizing remediation technologies require a better understanding of air pollutant concentrations, the emission plumes, and the mechanism of emission. Previous studies have primarily focused on indoor air pollution research, while outdoor research is relatively rare. Field test research is not only costly but also consumes extensive amounts of time. The application of computational fluid dynamics (CFD) technology can save a lot of measurement time and repetitive labor, in order to better understand the diffusion fundamentals and spatial and temporal distribution differences of PM. This study monitored the PM concentrations of different particle sizes inside and outside a layer house with negative pressure ventilation in Northeast China during the summer of 2021. These data were also used to validate the three-dimensional simulation of the PM concentrations inside and outside of the layer house in various scenarios of wind directions at different times by CFD technology. Through correlation analysis, it is found that temperature was positively correlated with PM1 and PM2.5, and relative humidity and wind speed were negatively correlated with PM, which has a greater impact on PM10 and total suspended particulate (TSP). The particle size was proportional to the diffusion distance and diffusion height, time, and wind direction both have an impact on the spread of PM. Considering the environmental conditions in Northeast China, increasing the height of the fan by 1 m was suggested to reduce the diffusion of PM concentration. In addition, the diffusion patterns and transport paths in this study provide valuable information for improving control measures to minimize the influence of PM on both animal health and air quality.

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In this paper, triaxial loading and unloading tests under different loading and unloading conditions are carried out to explore the deformation and failure characteristics of hard rock marble, and the acoustic emission (AE) information of the test process is monitored synchronously to obtain the AE distribution characteristics. The test results show that: (1) when the unloading rate of confining pressure is small, the yield of rock is more obvious, the failure peak value is higher, and the Poisson effect is more obvious under loading and unloading, while when the unloading rate is larger, it shows multi-stage failure; (2) there is a linear relationship between strain deflection stress compliance and unloading rate. With the increase of unloading rate, the circumferential and volumetric compliance increases and the axial compliance decreases; (3) the smaller the unloading rate is, the greater the confining pressure is, and a large number of tensile microcracks in the main shear plane of rock form a shear zone, while the higher the unloading rate is, the smaller the confining pressure is, and the main shear plane runs through; (4) AE counts can characterize the damage degree of marble during loading and unloading. When the confining pressure is low, the damage peak of AE signals increases sharply, and the overall damage increases with the increase of unloading rate, and when the confining pressure is high, AE signals increases gradually. The overall damage decreases with the increase of unloading rate, and a “pre-peak to post-peak” lag effect can occur in the general rock failure.