Development of an Optical Method to Monitor Nitrification in Drinking Water

Nitrification is a common issue observed in chloraminated drinking water distribution systems, resulting in the undesirable loss of monochloramine (NH<sub>2</sub>Cl) residual. The decay of monochloramine releases ammonia (NH<sub>3</sub>), which is converted to nitrite (NO<...

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Autores principales:	Sharif Hossain, David Cook, Christopher W. K. Chow, Guna A. Hewa
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	optical nitrification monitoring UV-Vis absorbance spectra spectrophotometric analysis of nitrate and nitrite spectral compensation drinking water nitrification monitoring Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/78d3de3c223849eb828e16563e8e46c8
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spelling	oai:doaj.org-article:78d3de3c223849eb828e16563e8e46c82021-11-25T18:57:09ZDevelopment of an Optical Method to Monitor Nitrification in Drinking Water10.3390/s212275251424-8220https://doaj.org/article/78d3de3c223849eb828e16563e8e46c82021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7525https://doaj.org/toc/1424-8220Nitrification is a common issue observed in chloraminated drinking water distribution systems, resulting in the undesirable loss of monochloramine (NH<sub>2</sub>Cl) residual. The decay of monochloramine releases ammonia (NH<sub>3</sub>), which is converted to nitrite (NO<sub>2</sub><sup>−</sup>) and nitrate (NO<sub>3</sub><sup>−</sup>) through a biological oxidation process. During the course of monochloramine decay and the production of nitrite and nitrate, the spectral fingerprint is observed to change within the wavelength region sensitive to these species. In addition, chloraminated drinking water will contain natural organic matter (NOM), which also has a spectral fingerprint. To assess the nitrification status, the combined nitrate and nitrite absorbance fingerprint was isolated from the total spectra. A novel method is proposed here to isolate their spectra and estimate their combined concentration. The spectral fingerprint of pure monochloramine solution at different concentrations indicated that the absorbance difference between two concentrations at a specific wavelength can be related to other wavelengths by a linear function. It is assumed that the absorbance reduction in drinking water spectra due to monochloramine decay will follow a similar pattern as in ultrapure water. Based on this criteria, combined nitrate and nitrite spectra were isolated from the total spectrum. A machine learning model was developed using the support vector regression (SVR) algorithm to relate the spectral features of pure nitrate and nitrite with their concentrations. The model was used to predict the combined nitrate and nitrite concentration for a number of test samples. Out of these samples, the nitrified sample showed an increasing trend of combined nitrate and nitrite productions. The predicted values were matched with the observed concentrations, and the level of precision by the method was ± 0.01 mg-N L<sup>−1</sup>. This method can be implemented in chloraminated distribution systems to monitor and manage nitrification.Sharif HossainDavid CookChristopher W. K. ChowGuna A. HewaMDPI AGarticleoptical nitrification monitoringUV-Vis absorbance spectraspectrophotometric analysis of nitrate and nitritespectral compensationdrinking water nitrification monitoringChemical technologyTP1-1185ENSensors, Vol 21, Iss 7525, p 7525 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	optical nitrification monitoring UV-Vis absorbance spectra spectrophotometric analysis of nitrate and nitrite spectral compensation drinking water nitrification monitoring Chemical technology TP1-1185
spellingShingle	optical nitrification monitoring UV-Vis absorbance spectra spectrophotometric analysis of nitrate and nitrite spectral compensation drinking water nitrification monitoring Chemical technology TP1-1185 Sharif Hossain David Cook Christopher W. K. Chow Guna A. Hewa Development of an Optical Method to Monitor Nitrification in Drinking Water
description	Nitrification is a common issue observed in chloraminated drinking water distribution systems, resulting in the undesirable loss of monochloramine (NH<sub>2</sub>Cl) residual. The decay of monochloramine releases ammonia (NH<sub>3</sub>), which is converted to nitrite (NO<sub>2</sub><sup>−</sup>) and nitrate (NO<sub>3</sub><sup>−</sup>) through a biological oxidation process. During the course of monochloramine decay and the production of nitrite and nitrate, the spectral fingerprint is observed to change within the wavelength region sensitive to these species. In addition, chloraminated drinking water will contain natural organic matter (NOM), which also has a spectral fingerprint. To assess the nitrification status, the combined nitrate and nitrite absorbance fingerprint was isolated from the total spectra. A novel method is proposed here to isolate their spectra and estimate their combined concentration. The spectral fingerprint of pure monochloramine solution at different concentrations indicated that the absorbance difference between two concentrations at a specific wavelength can be related to other wavelengths by a linear function. It is assumed that the absorbance reduction in drinking water spectra due to monochloramine decay will follow a similar pattern as in ultrapure water. Based on this criteria, combined nitrate and nitrite spectra were isolated from the total spectrum. A machine learning model was developed using the support vector regression (SVR) algorithm to relate the spectral features of pure nitrate and nitrite with their concentrations. The model was used to predict the combined nitrate and nitrite concentration for a number of test samples. Out of these samples, the nitrified sample showed an increasing trend of combined nitrate and nitrite productions. The predicted values were matched with the observed concentrations, and the level of precision by the method was ± 0.01 mg-N L<sup>−1</sup>. This method can be implemented in chloraminated distribution systems to monitor and manage nitrification.
format	article
author	Sharif Hossain David Cook Christopher W. K. Chow Guna A. Hewa
author_facet	Sharif Hossain David Cook Christopher W. K. Chow Guna A. Hewa
author_sort	Sharif Hossain
title	Development of an Optical Method to Monitor Nitrification in Drinking Water
title_short	Development of an Optical Method to Monitor Nitrification in Drinking Water
title_full	Development of an Optical Method to Monitor Nitrification in Drinking Water
title_fullStr	Development of an Optical Method to Monitor Nitrification in Drinking Water
title_full_unstemmed	Development of an Optical Method to Monitor Nitrification in Drinking Water
title_sort	development of an optical method to monitor nitrification in drinking water
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/78d3de3c223849eb828e16563e8e46c8
work_keys_str_mv	AT sharifhossain developmentofanopticalmethodtomonitornitrificationindrinkingwater AT davidcook developmentofanopticalmethodtomonitornitrificationindrinkingwater AT christopherwkchow developmentofanopticalmethodtomonitornitrificationindrinkingwater AT gunaahewa developmentofanopticalmethodtomonitornitrificationindrinkingwater
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Development of an Optical Method to Monitor Nitrification in Drinking Water

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