| 光谱学与光谱分析 |
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| Study on Ammonia Emission Rules in a Dairy Feedlot Based on Laser Spectroscopy Detection Method |
| HE Ying1，2，3, ZHANG Yu-jun1，3, YOU Kun1，3, WANG Li-ming1，3, GAO Yan-wei1，3, XU Jin-feng1，3, GAO Zhi-ling4, MA Wen-qi4 |
1. Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
2. University of Science and Technology of China, Hefei 230026, China
3. Key Laboratory of Optical Monitoring Technology for Environment，Anhui Province，Hefei 230031, China
4. College of Resources and Environmental Science, Agricultural University of Hebei, Baoding 071000, China |
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Abstract 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.
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Received: 2014-10-11
Accepted: 2015-02-08
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Corresponding Authors:
HE Ying
E-mail: heying@aiofm.ac.cn
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