为实现奶牛场氨气减排, 改善生态环境, 需要在线监测氨挥发浓度并准确揭示氨排放特征。 采用开放式可调谐半导体激光吸收光谱 (TDLAS) 技术设计了开放式氨气在线监测系统, 结合反演式气体扩散技术开展相关研究, 于2013年秋季和冬季在保定市某奶牛厂进行了氨排放浓度在线监测和排放特征分析工作。 监测结果表明, 秋季氨气浓度峰值为6.11×10-6%, 冬季氨气浓度峰值为6.56×10-6%, 氨浓度具有日变化趋势, 基本呈白天浓度低, 夜晚浓度高的特点。 由反演气体扩散模型得到秋冬季氨排放特征, 氨排放峰值均出现在中午, 秋季氨排放速率为1.48～130.6 kg/head/hr, 冬季氨排放速率为0.004 5～43.32 kg/head/hr, 秋季的排放速率高于冬季, 说明奶牛场尺度下的氨排放存在一定的季节性差异。 该方法可以有效获得大范围、 高灵敏、 免采样、 快速气体排放特征结果, 为奶牛厂的氨排放监测和科学养殖提供技术支持。

It needs on-line monitoring of ammonia concentration on dairy feedlot to disclose ammonia emissions characteristics accurately for reducing ammonia emissions and improving the ecological environment. The on-line monitoring system for ammonia concentration has been designed based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology combining with long open-path technology, then the study has been carried out with inverse dispersion technique and the system. The ammonia concentration in-situ has been detected and ammonia emission rules have been analyzed on a dairy feedlot in Baoding in autumn and winter of 2013. The monitoring indicated that the peak of ammonia concentration was 6.11×10-6 in autumn, and that was 6.56×10-6 in winter. The concentration results show that the variation of ammonia concentration had an obvious diurnal periodicity, and the general characteristic of diurnal variation was that the concentration was low in the daytime and was high at night. The ammonia emissions characteristic was obtained with inverse dispersion model that the peak of ammonia emissions velocity appeared at noon. The emission velocity was from 1.48 kg/head/hr to 130.6 kg/head/hr in autumn, and it was from 0.004 5 kg/head/hr to 43.32 kg/head/hr in winter which was lower than that in autumn. The results demonstrated ammonia emissions had certain seasonal differences in dairy feedlot scale. In conclusion, the ammonia concentration was detected with optical technology, and the ammonia emissions results were acquired by inverse dispersion model analysis with large range, high sensitivity, quick response without gas sampling. Thus, it’s an effective method for ammonia emissions monitoring in dairy feedlot that provides technical support for scientific breeding.