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Contaminated gases emissions from livestock industry are becoming one of the most significant contributors to the increasingly serious environmental pollution. To find a way to reduce gases emissions, it is essential to reveal the factors that can affect the gases emissions. In this study, the concentrations of typical gases (including ammonia (NH 3), carbon dioxide (CO 2), hydrogen sulfide (H 2 S), and sulfur dioxide (SO 2)) generated from naturally-ventilated dairy cow barns were detected through the sample-data method in Tianjin, northern China. Indoor environmental conditions, such as temperature (T) and relative humidity (RH), were measured simultaneously. After applying the carbon dioxide mass balance method, ammonia, hydrogen sulfide and sulfur dioxide emissions were determined. The correlation analysis and regression analysis between the climate condition and gas emissions were conducted to assess the data collected in dairy cow barns during the whole study period. There was a significant relationship between environmental conditions and gas emissions. NH 3 , H 2 S and SO 2 emissions from the building are in the range of 0.98-2.36 g/LU• h, 0-0.034 g/LU• h, and 0-0.069 g/LU• h, respectively. The numerical analysis shows that the NH 3 emission is highly correlated with the temperature and relative humidity. The ventilation rate shows a positive correlation with all the three gases.

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Ventilation and heating can be necessary for pig production during winter in China. However, it is challenging to balance the ventilation rate and heat loss due to the ventilation. Therefore, it is essential to design the minimum ventilation and heating load properly in order to reduce energy loss. In this paper, a VBA (Visual Basic for Applications) model based on energy balance is established. Meteorological data, pig body masses, outdoor temperatures, feeding densities, and building envelope thermal insulance factors were involved in the model. A model pig house with a length and width of 110 m × 15 m was used to investigate the ventilation, heating time, load, and power consumption in different climate zones, i.e., Changchun, Beijing, Nanning, Wuhan, and Guiyang, representing five major climate regions in China. Based on the simulation results, the models of minimum ventilation and heating load were fitted. The results showed that there is a logarithmic relationship between the minimum ventilation volume and body mass, R2 = 0.9673. The R2 of heating load models for nursery pigs and fattening pigs were 0.966 and 0.963, respectively, considering the feeding area, the outside temperature, the body masses of the nursery and fattening pigs, and the thermal insulance factor of the enclosure. The heating requirements of commercial pig houses within the same building envelope followed the trend in Changchun > Beijing > Guiyang > Wuhan > Nanning. Increasing the building envelope’s thermal insulance factor or using precision heating could reduce the pig house’s power consumption. The analysis of the heating load and energy consumption of winter pig houses in various climate regions provided a reference for precise environmental control and the selection of building thermal insulance factors in China.

Abstract. A wash cycle using an alkaline solution with a dissolved chemical detergent is a standard clean-in-place (CIP) process for cleaning milking systems. However, long-term chemical use may corrode equipment and create difficulties in wastewater treatment. This study investigated the potential for using alkaline electrolyzed oxidizing (EO) water as an alternative to alkaline chemical detergent for removal of microorganisms and adenosine triphosphate (ATP) on milking system materials. Laboratory trials were performed based on a Box-Behnken response surface design to assess the cleaning effect of alkaline EO water on three materials typically used in milking systems: stainless steel, rubber gasket, and polyvinyl chloride (PVC) hose. Results showed that alkaline EO water treatment was generally enhanced with increased treatment time, temperature, and pH, and their interaction effects were also observed in ATP removal. However, treatment time did not have a dominant role in cleaning PVC hose. Response surface models were developed to reliably predict detected microorganisms and relative light units (RLU) on the three materials after alkaline EO water treatment. Based on the response surface models, the three parameters for alkaline EO water cleaning were optimized as treatment time of 10.0 min, temperature of 61.8°C, and pH of 12, after which microorganisms and RLU were nearly undetectable. Alkaline EO water treatment with the optimized parameters had an equivalent or better cleaning ability compared to the commercial detergent, suggesting its potential as a cleaning and bacteria removal agent for milking systems. Keywords: Alkaline electrolyzed oxidizing water, Cleanliness, Milking system, Response surface model.