Odor and Odorous Chemical Emissions from Animal Buildings: Part 4. Correlations Between Sensory and Chemical Measurements

dc.contributor.author Akdeniz, Neslihan
dc.contributor.author Jacobson, Larry
dc.contributor.author Hetchler, Brian
dc.contributor.author Bereznicki, Sarah
dc.contributor.author Heber, Albert
dc.contributor.author Koziel, Jacek
dc.contributor.author Cai, Lingshuang
dc.contributor.author Zhang, Shicheng
dc.contributor.author Parker, David
dc.contributor.department Department of Agricultural and Biosystems Engineering (ENG)
dc.date 2018-02-13T04:40:08.000
dc.date.accessioned 2020-06-29T22:38:12Z
dc.date.available 2020-06-29T22:38:12Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2012
dc.date.embargo 2013-01-03
dc.date.issued 2012-01-01
dc.description.abstract <p>This study supplemented the National Air Emissions Monitoring Study (NAEMS) with one year of comprehensive measurements of odor emission at five swine and four dairy buildings. The measurements included both standard human sensory measurements using dynamic forced-choice olfactometry and chemical analysis of the odorous compounds using gas chromatography-mass spectrometry. In this article, multilinear regressions between odor and gas concentrations (a total of 20 compounds including H2S, NH3, and VOCs) were investigated. Regressions between odor and gas emission rates were also tested. It was found that gas concentrations, rather than emission rates, should be used to develop multilinear regression models. For the dairy sites, H2S, NH3, acetic acid, propanoic acid, 2-methyl propanoic, and pentanoic acids were observed to be the compounds with the most significant effect on sensory odor. For the swine sites, in addition to these gases, higher molecular weight compounds such as phenol, 4-methyl phenol, 4-ethyl phenol, and 1H-indole were also observed to be significant predictors of sensory odor. When all VOCs were excluded from the model, significant correlations between odor and H2S and NH3 concentrations were still observed. Although these coefficients of determination were lower when only H2S and NH3 were used, they can be used to predict odor variability by up to 83% when VOC data are unavailable.</p>
dc.description.comments <p>This article is from <em><a href="http://elibrary.asabe.org/abstract.asp?aid=42496&t=3&dabs=Y&redir=&redirType=" target="_blank">Transactions of the ASABE</a> </em>55, no. 6 (2012): 2347–2356.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_pubs/238/
dc.identifier.articleid 1237
dc.identifier.contextkey 3562722
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_pubs/238
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/983
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_pubs/238/Koziel_2012_OdorOdorousChemical_Part4.pdf|||Fri Jan 14 22:49:35 UTC 2022
dc.subject.disciplines Agriculture
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.subject.keywords Dairy
dc.subject.keywords Emission rate
dc.subject.keywords Multilinear regression
dc.subject.keywords Odor concentration
dc.subject.keywords Swine
dc.subject.keywords Volatile organic compound
dc.title Odor and Odorous Chemical Emissions from Animal Buildings: Part 4. Correlations Between Sensory and Chemical Measurements
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 76fc5589-51f8-4f3c-885c-e25d8037d641
relation.isOrgUnitOfPublication 8eb24241-0d92-4baf-ae75-08f716d30801
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