The Dynamics of Interbank Networks (original) (raw)
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2013
On-line monitoring of wastewater parameters is a major scientific and technical challenge because of the great variability of wastewater characteristics and the extreme physical-chemical conditions that endure the sensors. Wastewater treatment plant managers require fast and reliable information about the input sewage and the operation of the different treatment stages. There is a great need for the development of sensors for the continuous monitoring of wastewater parameters. In this sense, several optical systems have been evaluated. This article presents an experimental laboratory-based approach to quantify commonly employed urban wastewater parameters, namely biochemical oxygen demand in five days (BOD 5), chemical oxygen demand (COD), total suspended solids (TSS), and the ratio BOD 5 :COD, with a visible and short wave near infrared (V/SW-NIR) spectrometer (400-1000 nm). Partial least square regression (PLSR) models were developed in order to quantify the wastewater parameters with the recorded spectra. PLSR models were developed for the full spectral range and also for the visible and near infrared spectral ranges separately. Good PLSR models were obtained with the visible spectral range for BOD 5 (RER = 9.64), COD (RER = 10.88), and with the full spectral range for the TSS (RER = 9.67). The results of this study show that V/SW-NIR spectroscopy is a suitable technique for on-line monitoring of wastewater parameters.
Monitoring Urban Wastewaters’ Characteristics by Visible and Short Wave Near-Infrared Spectroscopy
Water, 2013
On-line monitoring of wastewater parameters is a major scientific and technical challenge because of the great variability of wastewater characteristics and the extreme physical-chemical conditions that endure the sensors. Wastewater treatment plant managers require fast and reliable information about the input sewage and the operation of the different treatment stages. There is a great need for the development of sensors for the continuous monitoring of wastewater parameters. In this sense, several optical systems have been evaluated. This article presents an experimental laboratory-based approach to quantify commonly employed urban wastewater parameters, namely biochemical oxygen demand in five days (BOD 5), chemical oxygen demand (COD), total suspended solids (TSS), and the ratio BOD 5 :COD, with a visible and short wave near infrared (V/SW-NIR) spectrometer (400-1000 nm). Partial least square regression (PLSR) models were developed in order to quantify the wastewater parameters with the recorded spectra. PLSR models were developed for the full spectral range and also for the visible and near infrared spectral ranges separately. Good PLSR models were obtained with the visible spectral range for BOD 5 (RER = 9.64), COD (RER = 10.88), and with the full spectral range for the TSS (RER = 9.67). The results of this study show that V/SW-NIR spectroscopy is a suitable technique for on-line monitoring of wastewater parameters.
Estimation of salinity wastewater using near infrared spectroscopy
2013
The visible and near infrared spectroscopy is a fast, and inexpensive non-destructive technique for the prediction of concentrations of salts in wastewater. Conventional chemical methods are usually used which are very accurate but take time and require special techniques for sampling, storing and pretreatment of wastewater. In this work we studied the spectral characteristics of water and the effect of salts on the perturbations in the water absorption bands. The generation of multiple regression models with principal components (PCR) was carried out on standard solutions with composition of salts similar to that of wastewater samples taken along the drainage channel network of the Mexico City Metropolitan Area. The spectral signatures were obtained in situ and laboratory using a portable highresolution spectroradiometer (ASD FieldSpect3). The prediction model generated showed high precision in the estimation of salinity in wastewater, a coefficient of determination of 89.6% and a ...
Wastewater salinity assessment using near infrared spectroscopy
The visible and near infrared spectroscopy is a fast and inexpensive non-destructive technique for the prediction of concentrations of salts in wastewater. Conventional chemical methods are usually used, which are very accurate, take more time and require special techniques for sampling, storing and pretreatment of wastewater. In this work we studied the spectral characteristics of water and the effect of salts on the perturbations in the water absorption bands. The generation of multiple regression models with principal components was carried out on standard solutions with composition of salts similar to that of wastewater samples taken along the drainage channel network of the Mexico City Metropolitan Area. The spectral signatures were obtained in situ and in the laboratory using a portable high-resolution spectroradiometer (ASD FieldSpec 3). The prediction model generated showed high precision in the estimation of salinity in wastewater, a coefficient of determination of 89.6% and a low root mean square error of 0.12‰. Other compounds, which are not discussed here, cause distortion of the absorption bands of water at wavelengths less than 900 nm or near the visible region, while our results showed distortions in the water spectrum at higher wavelengths (>1,000 nm).
Activated sludge process monitoring through in situ near-infrared spectral analysis
Water Science & Technology, 2008
The application of near infrared (NIR) spectroscopy for industrial process monitoring is achieving increasing importance over the last twenty years. In fact, the real time monitoring capacity of NIR spectroscopy is a very important feature for process monitoring, prediction and control as it allows a fast evaluation of the state of the process. However, the application of NIR spectroscopy in wastewater treatment processes is still to be explored. Although some applications of the technique for wastewater monitoring have been reported in the literature, there is still a need for more investigation related with applications, limitations and advantages of the technique when compared with other methods.
INMATEH Agricultural Engineering
Groundwater quality in agricultural area is highly affected by human activities. To determine groundwater quality, several methods are widely applied. Yet, most of them are based on standard laboratory analysis which is normally time consuming, expensive, and involve chemical materials from which may cause another environmental pollution. Thus, a rapid, effective and simple alternative method is required to assess groundwater quality. Fourier transform near-infrared spectroscopy (FT-NIRS) is considered to be employed due to its advantages. The main purpose of the present study, is to evaluate the feasibility of FT-NIRS technology in assessing groundwater quality parameters: total dissolved solids (TDS) and Sulfate concentration (SC). Transmission spectra data were acquired for groundwater samples from 8 different wells in wavelength range from 1000 to 2500 nm. Spectra data were corrected by multiplicative signal correction (MSC), while TDS and SC prediction models were established b...
Artificial Neural Network and Near Infrared Light in Water pH and Total Ammonia Nitrogen Prediction
International Journal of Integrated Engineering
Water quality plays an important role in aquaculture. The operation of a freshwater aquaculture fish farming is highly dependent on the ability to understand, monitor, and control the physical and chemical constituents of the water. pH and total ammonia nitrogen (TAN) levels are two critical water quality parameters that affect fish growth rate and health. However, pH and TAN levels are affected by uncontrollable factorse.g.weather, temperature, and biological processes occurring in the water. Therefore, it is important to monitor changes in pH and TAN levels frequently to maintain optimal conditions for freshwater habitats. Near infrared spectroscopy (NIR) has been extensively investigated as an alternative measurement approach for rapid quality control without sample preparation. Therefore, this research aims to evaluate the feasibility of machine learning combined with NIR light in predicting the water pH and TAN values of a fish farming system. The proposed system contains three...
Spectral Analysis Review, 2014
Although near infrared (NIR) spectroscopy has been evaluated for numerous applications, the number of actual on-line or even on-site industrial applications seems to be very limited. In the present paper, the attempts to produce on-line predictions of the chemical oxygen demand (COD) in wastewater from a pulp and paper mill using NIR spectroscopy are described. The task was perceived as very challenging, but with a root mean square error of prediction of 149 mg/l, roughly corresponding to 1/10 of the studied concentration interval, this attempt was deemed as successful. This result was obtained by using partial least squares model regression, interpolated reference values for calibration purposes, and by evenly distributing the calibration data in the concentration space. This work may also represent the first industrial application of on-line COD measurements in wastewater using NIR spectroscopy.
In situ near Infrared Monitoring of Activated Dairy Sludge Wastewater Treatment Processes
Journal of Near Infrared Spectroscopy, 2008
A sequential batch reactor (SBR) for aerobic treatment of dairy residues (activated sludge process) was monitored on-line by near infrared (NIR) spectroscopy. NIR spectra in the wavelength range of 900–1700 nm were acquired in situ with a transflectance probe. Measured in situ NIR spectra allowed the development of multivariate statistical process control models for supervision of the SBR process. The directly acquired spectra permitted characterisation of the different SBR operation stages and the detection of process disturbances. Calibration models based on partial least squares regression were developed for three process parameters: total solids (TS), total suspended solids (TSS) and chemical oxygen demand (COD). Model errors were estimated as root mean squared errors of cross-validation. The cross-validation errors obtained were 0.066 g TS L−1, 0.075 g TSS L−1 and 86.6 mg O2 L−1 respectively. Results demonstrated the viability of NIR spectroscopy as an alternative method for mo...