Identifying major contributing sources to odour annoyance using a non-specific gas sensor array

Article


Sohn, Jae Ho, Pioggia, Giovanni, Craig, Ian P., Stuetz, Richard M. and Atzeni, Michael G.. 2009. "Identifying major contributing sources to odour annoyance using a non-specific gas sensor array." Biosystems Engineering. 102 (3), pp. 305-312. https://doi.org/10.1016/j.biosystemseng.2008.12.010
Article Title

Identifying major contributing sources to odour annoyance using a non-specific gas sensor array

ERA Journal ID3455
Article CategoryArticle
AuthorsSohn, Jae Ho (Author), Pioggia, Giovanni (Author), Craig, Ian P. (Author), Stuetz, Richard M. (Author) and Atzeni, Michael G. (Author)
Journal TitleBiosystems Engineering
Journal Citation102 (3), pp. 305-312
Number of Pages8
Year2009
PublisherElsevier
Place of PublicationUnited Kingdom
ISSN1537-5110
1537-5129
Digital Object Identifier (DOI)https://doi.org/10.1016/j.biosystemseng.2008.12.010
Web Address (URL)http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%237168%232009%23998979996%23932063%23FLA%23&_cdi=7168&_pubType=J&_auth=y&_acct=C000052720&_version=1&_urlVersion=0&_userid=1472215&md5=5d7fdf6fc02cf4f3e4478ae6fc2647cf
Abstract

Identification of major contributors to odour annoyance in areas with multiple emission sources is necessary to address and resolve odour disputes. In an effort to develop an appropriate tool for this task, odour samples were collected on-site at a piggery and an abattoir (the major odour sources in the area) and at surrounding off-site areas, then analysed using a commercial non-specific chemical sensor array to develop an odour fingerprint database. The developed odour fingerprint database was analysed using two pattern recognition algorithms including a partial least squares-discriminant analysis (PLSDA)
and a Kohonen self-organising map (KSOM). The KSOM model could identify odour samples sourced from the piggery shed 15, piggery pond 8, piggery pond 9, abattoir, motel and others with mean percentage values of 77.5, 65.0, 90.2, 75.7, 44.8 and 64.6%,respectively.

Keywordsodour; chemical sensor; partial least squares-discriminant analysis; pattern recognition algorithms; self-organising maps
ANZSRC Field of Research 2020469999. Other information and computing sciences not elsewhere classified
340108. Sensor technology (incl. chemical aspects)
401199. Environmental engineering not elsewhere classified
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Byline AffiliationsDepartment of Primary Industries and Fisheries, Queensland
University of Pisa, Italy
Department of Agricultural, Civil and Environmental Engineering
University of New South Wales
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