A voltammetric electronic tongue as tool for water quality monitoring in wastewater treatment plants

Campos, Inmaculada; Alcañíz, Miguel; Aguado, Daniel; Barat, R.; Ferrer, J.; Gil, Luisa Fernanda Muriel; Marrakchi, Mouna; Martínez‐Máñez, Ramón; Soto, Juán; Vivancos, José-Luis

doi:10.1016/j.watres.2012.02.029

Cited by 96 publications

(53 citation statements)

References 24 publications

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“…6) during both seasons. The higher population density results in higher organic contaminant discharge, such as food waste, human sewage and industrial wastes, which contribute to increased COD concentrations (Xu et al, 2005;Campos et al, 2012;Mohseni-Bandpei and Yousefi, 2013;Sivri et al, 2014). …”

Section: Interpretation Of Water Quality and Predicting Variablesmentioning

confidence: 99%

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

Chen

Mei

Dahlgren

et al. 2016

Science of The Total Environment

163

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• The modified GWR models had higher R 2 and reflected the actual spatial features.• A manual variable excluding-selecting method is explored to avoid multicollinearity.• Influences of the dominant indicator on water quality varied with space and seasons.• Protection policies need consider sitespecific conditions and seasonal variations. G R A P H I C A L A B S T R A C Ta b s t r a c t a r t i c l e i n f o As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2~5 9.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use Contents lists available at ScienceDirectScience of the Total Environment j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / s c i t o t e n v conditions within each watershed to optimize mitigation strategies for contrasting land-use characteristics and seasonal variations.

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Section: Interpretation Of Water Quality and Predicting Variablesmentioning

confidence: 99%

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

Chen

Mei

Dahlgren

et al. 2016

Science of The Total Environment

163

View full text Add to dashboard Cite

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“…This electronic device and measurement system has been described in detail in previous papers working with glyphosate [18] [29] and has been successfully used in food [38][39] [40], water analyses [41] and the determination of environmental parameters [42].…”

Section: Electrochemical Measurementmentioning

confidence: 99%

Glyphosate detection with ammonium nitrate and humic acids as potential interfering substances by pulsed voltammetry technique

Gil

Laguarda-Miró

Camino

et al. 2013

Talanta

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ElsevierMartínez Gil, P.; Laguarda Miró, N.; Soto Camino, J.; Masot Peris, R. (2013) AbstractPulsed voltammetry has been used to detect and quantify glyphosate on buffered water in presence of ammonium nitrate and humic substances. Glyphosate is the most widely used herbicide active ingredient in the world. It is a non-selective broad spectrum herbicide but some of its health and environmental effects are still being discussed. Nowadays, glyphosate pollution in water is being monitored but quantification techniques are slow and expensive. Glyphosate wastes are often detected in countryside water bodies where organic substances and fertilizers (commonly based on ammonium nitrate) may also be present. glyphosate also forms complexes with humic acids so these compounds have also been taken into consideration. The objective of this research is to study the interference of these common pollutants in glyphosate measurements by pulsed voltammetry. The statistical treatment of the voltammetric data obtained lets us discriminate glyphosate from the other studied compounds and a mathematical model has been built to quantify glyphosate concentrations in a buffer despite the presence of humic substances and ammonium nitrate. In this model, the coefficient of determination (R 2 ) is 0.977 and the RMSEP value is 2.96x10 -5 so the model is considered statistically valid.

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“…Due to the versatility of electronics tongues and noses, there is a lot of research interest in their development for a wide range of applications, such as food industry (milk, wine, beer, fish, etc.) [27][28][29][30][31][32][33], environmental analyses, water quality monitoring, etc. [27,[34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

“…[27][28][29][30][31][32][33], environmental analyses, water quality monitoring, etc. [27,[34][35][36][37]. For instance, Campos et al [27] show an electronic tongue that is able to analyze COD (Chemical Oxygen Demand), BOD (Biochemical Oxygen Demand), ammonia (NH4-N), orthophosphate (PO3-P), sulphate (SO4-S), acetic acid (HCA) and alkalinity (Alk) from an array of metallic electrodes and using a partial least squares (PLS) analysis.…”

Section: Introductionmentioning

confidence: 99%

Feasibility Study of a Simple and Low-Cost Device for Monitoring Trihalomethanes Presence in Water Supply Systems Based on Statistical Models

Rivadeneyra

García-Ruiz

Delgado-Ramos

et al. 2014

Water

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This paper describes a new method for predicting trihalomethanes (THMs) presence in networks of water supply systems, using a low-cost device that permits a fast monitoring of concentrations without need of complex analysis made in laboratories. This method, based on statistical models, allows the estimation of THM concentration by monitoring parameters whose determination is direct and easy, and therefore, THM presence can be carried out in real-time. These parameters values are introduced in a multiple regression model resulting in the concentration of THMs levels. This model has taken into account parameters compulsory in water quality analysis and it has been shown that six parameters are enough to determine accurately THM concentration. In addition, the feasibility of a low-cost device that directly gives THM concentration is demonstrated. This device can be easily designed to be transported to different points of the water supply network where it is intended to make control campaigns.

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A voltammetric electronic tongue as tool for water quality monitoring in wastewater treatment plants

Cited by 96 publications

References 24 publications

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

Glyphosate detection with ammonium nitrate and humic acids as potential interfering substances by pulsed voltammetry technique

Feasibility Study of a Simple and Low-Cost Device for Monitoring Trihalomethanes Presence in Water Supply Systems Based on Statistical Models

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