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Comparison of modelling accuracy with and without exploiting automated optical monitoring information in predicting the treated wastewater quality

Tomperi, Jani; Leiviskä, Kauko (2017-05-27)

 
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URL:
https://doi.org/10.1080/09593330.2017.1331267

Tomperi, Jani
Leiviskä, Kauko
Informa
27.05.2017

Tomperi, J., Leiviskä, K. (2017) Comparison of modelling accuracy with and without exploiting automated optical monitoring information in predicting the treated wastewater quality. Environmental Technology, 39 (11), 1442-1449. doi:10.1080/09593330.2017.1331267

https://rightsstatements.org/vocab/InC/1.0/
© 2017 Informa UK Limited, trading as Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis in Environmental Technology on 27 May 2017, available online: https://doi.org/10.1080/09593330.2017.1331267
https://rightsstatements.org/vocab/InC/1.0/
doi:https://doi.org/10.1080/09593330.2017.1331267
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe201901031214
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Abstract

Traditionally the modelling in an activated sludge process has been based on solely the process measurements, but as the interest to optically monitor wastewater samples to characterize the floc morphology has increased, in the recent years the results of image analyses have been more frequently utilized to predict the characteristics of wastewater. This study shows that the traditional process measurements or the automated optical monitoring variables by themselves are not capable of developing the best predictive models for the treated wastewater quality in a full-scale wastewater treatment plant, but utilizing these variables together the optimal models, which show the level and changes in the treated wastewater quality, are achieved. By this early warning, process operation can be optimized to avoid environmental damages and economic losses. The study also shows that specific optical monitoring variables are important in modelling a certain quality parameter, regardless of the other input variables available.

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