4.7 Article

Pollution parameters evaluation of wastewater collected at different treatment stages from wastewater treatment plant based on E-nose and E-tongue systems combined with chemometric techniques

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ELSEVIER
DOI: 10.1016/j.chemolab.2022.104593

Keywords

Wastewater; Electronic nose; Voltammetric electronic tongue; Water quality control; Chemometric techniques

Funding

  1. Ministry of Higher Education, Scientific Research and Executives Training (CNRST of Morocco) [2015-87]
  2. Federal Ministry of Education and Research (Germany) [2015-87]

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Wastewater contains harmful chemicals and heavy metals, which are detrimental to the environment and health. Therefore, it is important to use sensitive, simple, fast, accurate, and portable tools for water quality control. This study evaluated the pollution parameters of wastewater using an electronic nose and electronic tongue combined with chemometric techniques. The results showed that these simple, portable, and inexpensive tools are suitable for wastewater analysis.
Wastewater contains harmful chemicals and heavy metals that are known to cause various environmental and health problems. Therefore, the water quality control using sensitive, simple, fast, accurate, and portable tools is of great importance. This study aimed to evaluate the pollution parameters of wastewaters collected at different treatment stages from a wastewater treatment plant (WWTP) that treats domestic and industrial wastewaters by using an electronic nose (E-nose) and a voltammetric electronic tongue (E-tongue) combined with chemometric techniques. Water and wastewater pollution parameters determination were performed using inductively coupled plasma optical emission spectrometry for the determination of cations, and anions by using ion chromatography. Chemometric techniques, such as Principal Component Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to process the E-nose and Etongue datasets to describe the similarities between the samples. In addition, Partial Least Squares Regression (PLSR) model was constructed using electronic sensing data to simultaneously predict the concentration values of physicochemical parameters. The obtained correlation coefficient, for training and testing sets, is higher than 0.91 for the prediction of the concentration of all physicochemical parameters, except for iron (Fe) which remains 0.84. These results suggest that simple, portable, and inexpensive tools such as electronic nose and tongue are suitable for wastewater analysis.

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