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An Alternative Approach of the E-Nose Training Phase in Odour Impact Assessment
Odour emissions are causing serious nuisance for the population, especially in the surrounding of waste water treatment plants (WWTP) and solid waste treatment plants. Extended exposure to odours generate undesirable reactions ranging from emotional stresses such as unease, discomfort, headaches, or...
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Published in: | Chemical engineering transactions 2012-09, Vol.30 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | Odour emissions are causing serious nuisance for the population, especially in the surrounding of waste water treatment plants (WWTP) and solid waste treatment plants. Extended exposure to odours generate undesirable reactions ranging from emotional stresses such as unease, discomfort, headaches, or depression to physical symptoms. Odour emission characterization is currently discussed in international literature for opportune implementation. Measurement of emissions can be achieved using different methods (analytical, sensorial and/or senso-instrumental) that have different advantages and problems. Among these techniques, there is a growing interest towards the environmental applications of electronic noses. Electronic nose is the only technique that allows continuous monitoring of odours. However, at present there are several limitations affecting the application of electronic nose in the environmental sector. The study investigates the electronic nose potentialities in the environmental sector. Scope of this research activity is to investigate an alternative method to build training data set necessary to distinguish different odour sources generated by solid waste treatment facilities through electronic nose application. The proposed methodology is based on the straightforward application of the electronic nose directly in field with the aim to reduce the time to build the complete data set. Results highlight the great efficiency of the proposed approach to reduce the time to build the complete data set, to maximize the electronic nose capability of operating a qualitative classification of odour sources. |
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ISSN: | 2283-9216 |
DOI: | 10.3303/CET1230024 |