A Simple Approach to Predicting the Reliability of Small Wastewater Treatment Plants

The treatment performance of small wastewater treatment plants (WWTPs) is not well understood, and their ecological impact may be underestimated. Growing evidence suggests they play a critical role in ensuring sustainable wastewater management, meaning they can no longer be neglected. The aim of thi...

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Main Authors: Joshua T. Bunce, David W. Graham
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:Water
Subjects:
Online Access:https://www.mdpi.com/2073-4441/11/11/2397
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spelling doaj-524417ee9a8249209037759563d14c462020-11-25T01:40:26ZengMDPI AGWater2073-44412019-11-011111239710.3390/w11112397w11112397A Simple Approach to Predicting the Reliability of Small Wastewater Treatment PlantsJoshua T. Bunce0David W. Graham1School of Engineering, Newcastle University, Newcastle Upon Tyne NE1 7RU, UKSchool of Engineering, Newcastle University, Newcastle Upon Tyne NE1 7RU, UKThe treatment performance of small wastewater treatment plants (WWTPs) is not well understood, and their ecological impact may be underestimated. Growing evidence suggests they play a critical role in ensuring sustainable wastewater management, meaning they can no longer be neglected. The aim of this study was to provide new data, understanding, and analytical approaches to improve the management of existing small WWTPs. A one-year sampling campaign was performed in the rural UK, and we found the effluent quality from twelve small versus three larger WWTPs was significantly poorer (<i>p</i> &lt; 0.05) across a range of performance parameters. Specifically, mean removal rates at the small plants were 67.3 &#177; 20.4%, 80 &#177; 33.9%, and 55.5 &#177; 30.4% for soluble chemical oxygen demand (sCOD), total suspended solids (TSS), and NH<sub>4</sub>-N (&#177; standard deviation), respectively, whereas equivalent rates for larger plants were 73.3 &#177; 17.6%, 91.7 &#177; 4.6%, and 92.9 &#177; 3.7%. A random forest classification model was found to accurately predict the likelihood of smaller WWTPs becoming unreliable. Importantly, when condensed to the three most &#8216;important&#8217; predictors, the classifier retained accuracy, which may reduce the data requirements for effective WWTP management. Among the important predictors was population equivalence, suggesting the smallest WWTPs may require particularly stringent management. Growing awareness of the need for sustainable wastewater and water resources management makes this new approach both timely and widely relevant.https://www.mdpi.com/2073-4441/11/11/2397decentralizedwastewateroperationsclassification
collection DOAJ
language English
format Article
sources DOAJ
author Joshua T. Bunce
David W. Graham
spellingShingle Joshua T. Bunce
David W. Graham
A Simple Approach to Predicting the Reliability of Small Wastewater Treatment Plants
Water
decentralized
wastewater
operations
classification
author_facet Joshua T. Bunce
David W. Graham
author_sort Joshua T. Bunce
title A Simple Approach to Predicting the Reliability of Small Wastewater Treatment Plants
title_short A Simple Approach to Predicting the Reliability of Small Wastewater Treatment Plants
title_full A Simple Approach to Predicting the Reliability of Small Wastewater Treatment Plants
title_fullStr A Simple Approach to Predicting the Reliability of Small Wastewater Treatment Plants
title_full_unstemmed A Simple Approach to Predicting the Reliability of Small Wastewater Treatment Plants
title_sort simple approach to predicting the reliability of small wastewater treatment plants
publisher MDPI AG
series Water
issn 2073-4441
publishDate 2019-11-01
description The treatment performance of small wastewater treatment plants (WWTPs) is not well understood, and their ecological impact may be underestimated. Growing evidence suggests they play a critical role in ensuring sustainable wastewater management, meaning they can no longer be neglected. The aim of this study was to provide new data, understanding, and analytical approaches to improve the management of existing small WWTPs. A one-year sampling campaign was performed in the rural UK, and we found the effluent quality from twelve small versus three larger WWTPs was significantly poorer (<i>p</i> &lt; 0.05) across a range of performance parameters. Specifically, mean removal rates at the small plants were 67.3 &#177; 20.4%, 80 &#177; 33.9%, and 55.5 &#177; 30.4% for soluble chemical oxygen demand (sCOD), total suspended solids (TSS), and NH<sub>4</sub>-N (&#177; standard deviation), respectively, whereas equivalent rates for larger plants were 73.3 &#177; 17.6%, 91.7 &#177; 4.6%, and 92.9 &#177; 3.7%. A random forest classification model was found to accurately predict the likelihood of smaller WWTPs becoming unreliable. Importantly, when condensed to the three most &#8216;important&#8217; predictors, the classifier retained accuracy, which may reduce the data requirements for effective WWTP management. Among the important predictors was population equivalence, suggesting the smallest WWTPs may require particularly stringent management. Growing awareness of the need for sustainable wastewater and water resources management makes this new approach both timely and widely relevant.
topic decentralized
wastewater
operations
classification
url https://www.mdpi.com/2073-4441/11/11/2397
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