首页 | 本学科首页   官方微博 | 高级检索  
     


Identification of Odor Causing Compounds in a Commercial Dairy Farm
Authors:Mingming Lu  Prabhat Lamichhane  Fuyan Liang  Eric Imerman  Ming Chai
Affiliation:(1) Department of Civil and Environmental Engineering, University of Cincinnati, P.O. Box 210071, Cincinnati, OH 45221, USA;(2) Agricultural, Natural Resources and Community Development Office, The Ohio State University, 217 Elm St., Columbus, OH 43140, USA
Abstract:The odorous air emissions from confined animal feeding operations (CAFOs), such as swine, poultry and dairy farms, are increasingly raising community complaints. Odorous emissions can result in health damages, psychological discomforts and adverse aesthetic effects in the community. However, these emissions are not well characterized up to now due to the lack of legislation, the limitations in sampling and instrumentation techniques, and the complexity of the emissions themselves. This study is aimed at the development of a high volume sampler and sorbent assembly to identify the odor causing compounds from a diary CAFO. The sorbent was custom designed to target the potential compounds that may exist in a dairy farm and was validated in laboratory with a synthetic odor from the swine manure. The actual samples at the diary farm were collected in spring and summer of 2005. The sorbents were solvent extracted and individual odor compounds were identified using GC–MS (gas chromatography–mass spectroscopy). The data obtained indicated that high volume sampling can shorten the sampling time from days to within 4 h. Both volatile organic compounds (VOCs) and volatile fatty acids (VFAs) have been identified from the dairy farm, such as phenol, methylphenol, 4-ethyl phenol, indole, methyl indole, benzyl alcohol, hexanoic acid, valeric acid and iso-valeric acid, together with some nitrogen containing compounds that have not been reported before.
Keywords:Concentrated animal feeding operations (CAFOs)  Volatile fatty acids (VFAs)  Odor causing compounds  High volume sampler  GC–  MS
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号