Gases emissions estimation and analysis by using carbon dioxide balance method in natural-ventilated dairy cow barns

Abstract

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.

Effect of the Milking Frequency on the Concentrations of Ammonia and Greenhouse Gases within an Open Dairy Barn in Hot Climate Conditions

“…This is due to the fact that the main source of CO 2 and CH 4 can be attributed to enteric fermentation and respiration [35]. In detail, eructation from cows has been reported as the major source for CH 4 release in ruminants [36]. Moreover, for the same kind of housing system under study, it was found that the CO 2 released from manure was less than 5% of the total CO 2 production due to the absence of the deep-litter [37].…”

Behavior recognition and fuel consumption prediction of tractor sowing operations using smartphone

“…The correlation result between v t and v t+k is shown in Figure 2. The correlation between v t and v t+k is negatively correlated with k. When k is 15 s, the correlation coefficients under the three driving modes are 0.92, 0.90, and 0.91, which are all greater than 0.9, showing a strong correlation (p<0.01) [15] . When k is 20 s, the correlation coefficients in the three driving modes are 0.90, 0.87, and 0.90, respectively, which are slightly lower than when k is 15 s, but the correlation coefficients in both manual and unmanned driving modes are still greater than 0.9.…”

Emission Characteristics of Fine Particles in Relation to Precursor Gases in Agricultural Emission Sources: A Case Study of Dairy Barns

“…The average wind speed, relative humidity, and temperature were 2.2 m/s, 32%, and 27.6 • C, respectively. Zou et al, (2020) reported that the emission rates from naturally ventilated dairy barns in North China were approximately 1.52 g/AU/h (1 to 8 ppm) for ammonia, 0.001 g/AU/h for hydrogen sulfide, and 0.002 g/AU/h for sulfur dioxide, respectively [35]. In another study from Canada, the emission rates from a dairy barn were approximately 26.5 to 97.5 mg/min (2.1 to 7.8 mg/AU/h) for PM 2.5 and 0.45 to 1.78 g/AU/h (1.9 to 3.1 ppm) for ammonia, respectively [36].…”

“…Bjerg et al, (2012) reported that NH 3 emissions were higher in the morning (before noon) because animals urinated more at this time [37]. NH 3 emissions were lower at night because of reduced feeding and defecation [35]. Other studies also showed that ammonia concentrations during the daytime were lower than those during the nighttime.…”