Journal article
Determination of the relationship between sewage odour and BOD by neural networks
Environmental modelling & software : with environment data news, Vol.20(7), pp.843-850
2005
DOI: 10.1016/j.envsoft.2004.04.012
Abstract
Sewage treatment works are one of the major sources that cause atmospheric odour pollution. Due to the increase in environmental concerns, there is a growing number of complaints on odour nuisance. In order to determine the boundaries of legal standards, reliable and efficient odour measurement methods need to be defined. An electronic nose was used for the purpose of characterising sewage odours. Samples collected at different locations of a wastewater treatment plant were classified using an Artificial Neural Network (ANN) trained with a back-propagation algorithm. Additionally, the same method was used to determine the relation between sewage sample odours and their related Biochemical Oxygen Demand (BOD) values. The overall results have indicated that ANNs can be used to classify the sewage samples collected from different locations of a wastewater treatment plant. Moreover, the electronic nose output could be used as an indicator in monitoring the biochemical activities of wastewaters.
Details
- Title: Subtitle
- Determination of the relationship between sewage odour and BOD by neural networks
- Creators
- Guleda Onkal-Engin - Department of Environmental Engineering, Gebze Institute of Technology, Gebze, 41400 Kocaeli, TurkeyIbrahim Demir - Department of Environmental Engineering, Gebze Institute of Technology, Gebze, 41400 Kocaeli, TurkeySeref N Engin - Department of Electrical Engineering, Yildiz Technical University, Besiktas, 34349 Istanbul, Turkey
- Resource Type
- Journal article
- Publication Details
- Environmental modelling & software : with environment data news, Vol.20(7), pp.843-850
- DOI
- 10.1016/j.envsoft.2004.04.012
- ISSN
- 1364-8152
- eISSN
- 1873-6726
- Publisher
- Elsevier Ltd
- Language
- English
- Date published
- 2005
- Academic Unit
- Electrical and Computer Engineering; Civil and Environmental Engineering; Injury Prevention Research Center
- Record Identifier
- 9983992068602771
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