Turbidity Compensation Research Articles

A novel turbidity compensation method for water measurements by UV/Vis and fluorescence spectroscopy

The study presented here addresses the influence of turbidity on UV/Vis spectroscopy measurements of water bodies, a factor that affects the accurate identification and quantification of substances. The novelty of the developed turbidity compensation method is its applicability over the entire UV/Vis spectrum (250 – 900 nm), enabling the accurate detection of substances which appear in the UV/Vis spectrum at higher wavelengths (e.g. chlorophylls), and at high turbidity amounts. Commonly used approaches for turbidity compensation bases on the relationship before and after its correction through mapping functions or subtracting the turbidity-related absorbance from the original spectrum. However, these methods usually consider only certain wavelength ranges, such as 200 – 400 nm, and often reach limitations when applied to real water samples due to increase of turbidity. A significant improvement in our method was achieved by simultaneous determination of turbidity in the sample using scattered light measurement at 850 nm. This information was then applied to generate a turbidity-compensation curve, which was then used to correct the absorption spectrum according to Lambert-Beer’s law. The experimental results show that this novel method reduces the root mean square error (RMSE) from 0.5935 mg L–1 to 0.0218 mg L–1 of the rhodamine B predictions. For better comparability, COD measurements were also carried out and an RMSE of 0.3096 mg L–1 and an R2 of 0.979 were obtained. In summary, it corrects the absorbance deviation caused by turbidity, improves the accuracy of substance prediction and works even at low substance concentrations in turbid solutions or for realistic measurements.

Improved boosting and self-attention RBF networks for COD prediction based on UV-vis.

Chemical Oxygen Demand (COD) is crucial for assessing water quality. Compared to traditional chemical detection methods, UV-vis spectroscopy for measuring COD offers advantages such as speed, reduced consumption of materials, and no secondary pollution. Considering the impact of suspended particles in water, this paper proposes an optimized boosting model based on a combination strategy for turbidity compensation, using absorption spectra obtained from reservoir water samples via UV-vis. A self-attention mechanism is introduced into the radial basis function (RBF) network, resulting in a COD detection model based on the saRBF framework. This model facilitates comprehensive optimization of the entire process, from turbidity compensation of the original absorption spectrum to the subsequent COD prediction. Experimental results show that the proposed COD measurement model achieves a coefficient of determination of 0.9267, a root mean square error of 1.2669, and a mean absolute error of 1.0097, outperforming other COD measurement models. This work provides a new approach for turbidity compensation and COD detection research.

A straightforward approach utilizing an exponential model to compensate for turbidity in chemical oxygen demand measurements using UV-vis spectrometry.

Recently, ultraviolet-visible (UV-vis) absorption spectrometry has garnered considerable attention because it enables real-time and unpolluted detection of chemical oxygen demand (COD) and plays a crucial role in the early warning of emerging organic contaminants. However, the accuracy of detection is inevitably constrained by the co-absorption of organic pollutants and turbidity at UV wavelengths. To ensure accurate detection of COD, it is necessary to directly subtract the absorbance caused by turbidity from the overlaid spectrum using the principle of superposition. The absorbance of COD is confined to the UV range, whereas that of turbidity extends across the entire UV-vis spectrum. Therefore, based on its visible absorbance, the UV absorbance of turbidity can be predicted. In this way, the compensation for turbidity is achieved by subtracting the predicted absorbance from the overlaid spectrum. Herein, a straightforward yet robust exponential model was employed based on this principle to predict the corresponding absorbance of turbidity at UV wavelengths. The model was used to analyze the overlaid absorption spectra of synthetic water samples containing COD and turbidity. The partial least squares (PLS) method was employed to predict the COD concentrations in synthetic water samples based on the compensated spectra, and the corresponding root mean square error (RMSE) values were recorded. The results indicated that the processed spectra yielded a considerably lower RMSE value (9.51) than the unprocessed spectra (29.9). Furthermore, the exponential model outperformed existing turbidity compensation models, including the Lambert-Beer law-based model (RMSE = 12.53) and multiple-scattering cluster method (RMSE = 79.34). Several wastewater samples were also analyzed to evaluate the applicability of the exponential model to natural water. UV analysis yielded undesirable results owing to filtration procedures. However, the consistency between the compensated spectra and filtered wastewater samples in the visible range demonstrated that the model is applicable to natural water. Therefore, this proposed method is advantageous for improving the accuracy of COD measurement in turbid water.

A COD measurement method with turbidity compensation based on a variable radial basis function neural network.

In recent years, ultraviolet-visible spectrometry has been widely used to measure sewage's chemical oxygen demand (COD). However, most methods that use UV-vis spectroscopy for COD measurement have not eliminated the influence of turbidity. Therefore, this article proposes a new COD measurement method using UV-vis spectroscopy. This method includes a new turbidity compensation algorithm and an algorithm for COD measurement using a variable radial basis function (VRBF) neural network. Our turbidity compensation algorithm first utilizes principal component analysis (PCA) to extract the characteristic wavelengths of the spectrum. Then, turbidity is used to fit the absorbance difference caused by turbidity at the characteristic wavelength, and a turbidity compensation model is obtained. The turbidity compensation model is used to remove the influence of turbidity from the absorbance spectrum, thereby compensating for its effect on the COD measurement. Secondly, the VRBF neural network model is used to measure the COD concentration. The results show that, compared with the traditional partial least squares regression model, the R2 coefficient of determination increases from 0.27 to 0.88, and the root-mean-square deviation decreases from 5.56 to 1.69. Compared with the improved bagging algorithm and MLP algorithm, this method can measure COD concentration from absorption spectra faster, more directly, and more accurately.

Deep learning–based turbidity compensation for ultraviolet-visible spectrum correction in monitoring water parameters

Ultraviolet-visible spectroscopy is an effective tool for reagent-free qualitative analysis and quantitative detection of water parameters. Suspended particles in water cause turbidity that interferes with the ultraviolet-visible spectrum and ultimately affects the accuracy of water parameter calculations. This paper proposes a deep learning method to compensate for turbidity interference and obtain water parameters using a partial least squares regression approach. Compared with orthogonal signal correction and extended multiplicative signal correction methods, the deep learning method specifically utilizes an accurate one-dimensional U-shape neural network (1D U-Net) and represents the first method enabling turbidity compensation in sampling real river water of agricultural catchments. After turbidity compensation, the R2 between the predicted and true values increased from 0.918 to 0.965, and the RMSE (Root Mean Square Error) value decreased from 0.526 to 0.343 mg. Experimental analyses showed that the 1D U-Net is suitable for turbidity compensation and provides accurate results.

High sensitivity and wide range chlorophyll-a determination by simultaneous measurement of absorbance and fluorescence using a linear CCD

In the determination of chlorophyll with the fluorescence method in the natural water, the suspended particles and colloids will seriously interfere with the incident light and the fluorescence. Based on the analysis of the interaction between light and the measured substances, a high sensitivity, wide range of chlorophyll-a concentration measurement strategy, which combines optical information of fluorescence and absorbance with the CCD integration time transformation method, is proposed. Correspondingly, a novel algorithm, which can significantly correct the attenuation of incident light due to the absorption of suspended particles and the deviation of detected fluorescence caused by the scattered light and reflected light, is proposed to realize turbidity compensation. For verification, a self-designed compact optical experimental device consisting of a single LED and a linear CCD was set up to obtain the fluorescence spectrum and absorbance spectrum simultaneously. The experimental results demonstrate that the compensation strategy can commendably compensate for the impact of the suspended particles. The relative error of chlorophyll-a measurement is less than 5%, even in a high turbidity environment. Furthermore, the minimum detection limit is significantly reduced from conventional 0.01 μg/L to 0.0025 μg/L in the range of 0.0025–130 μg/L with the CCD integration time transformation method, which improves the measurement sensitivity. This device and method have the potential to be applied to the in situ online measurement of chlorophyll-a concentration in natural water.

A Novel Hybrid Strategy for Detecting COD in Surface Water

The prediction of chemical oxygen demand (COD) by ultraviolet–visible absorption spectrum is a common method. Many researchers use the absorbance at the characteristic wavelength to establish COD prediction models. However, selecting the characteristic wavelength is a problem. In this paper, the extreme values of absorption spectrum change rate, was proposed as a new characteristic parameter to determine the characteristic wavelengths. On this basis, a novel hybrid strategy for detecting COD in surface water was proposed. We first proposed to combine the first derivative method with the permutation entropy method (FDPE) to determine the characteristic wavelengths. Then we used partial least square (PLS) to establish a COD prediction model. Experimental results demonstrated the linear correlation coefficient (R2) of the FDPE_PLS was above 0.99 without turbidity interference. Secondly, a dual-wavelength method (DWM) was proposed to determine the turbidity values. The DWM used slopes of absorbance values at 400 nm and 600 nm to predict the turbidity values. Compared with the single-wavelength method, the DWM improves the measurement accuracy of turbidity. Finally, a new turbidity compensation method was proposed to compensate for the interference in the first derivative spectrum. After compensation, FDPE_PLS can predict COD concentrations accurately, whose R2 was 0.99.

Turbidity compensation method based on Mie scattering theory for water chemical oxygen demand determination by UV-Vis spectrometry.

In view of the problem that chemical oxygen demand (COD) measurement in water using UV-Vis spectrometry was easily affected by turbidity, this paper proposed an analytical method for determining the complex refractive index of particles in water based on Lambert-Beer's law and K-K (Kramers-Kronig) relationship. The obtained complex refractive index was used to establish the turbidity compensation model in the COD characteristic spectral region, and the COD concentration inversion were achieved by using the PLS algorithm. The results show that the turbidity compensation method based on Mie scattering theory can improve the accuracy of COD measurement by UV-Vis spectroscopy. Compared with before turbidity compensation, R2 (determination coefficient) between true values and predicted values of COD increased from 0.2274 to 0.9629, and RMSE (root mean square error) of predicted values decreased from 21.73 to 3.12mgL-1. Compared with 350nm PC, derivative method, and improved MSC method, the turbidity compensation method for COD measurement based on Mie scattering theory is simple, fast, and highly accurate. And the calculated spectrum can represent the scattering characteristics of the measured spectrum. The average relative error between the fitted spectrum and the original normalized spectrum in the 55 mixed solutions was 0.52%, and the maximum relative error was 6.65%. This method can be useful for online COD measurement. Graphical abstract.

Simultaneous determination of nitrate, chemical oxygen demand and turbidity in water based on UV-Vis absorption spectrometry combined with interval analysis.

In this paper, a new method for simultaneous determination of nitrate, COD and turbidity in water based on UV-Vis absorption spectrometry combined with interval analysis was studied. By analyzing the spectral absorption characteristics of nitrate, COD, and turbidity standard solutions and the mixtures of them, the absorption spectra in the range of 225-260nm, 260-320nm and 320-700nm were selected as the characteristic spectra of nitrate, COD and turbidity, respectively. Multiplicative scatter correction was employed to compensate turbidity of the absorption spectra of the mixture solutions in the wavelength range of 225-320nm. Then, the spectra after turbidity compensation in the range of 225-260nm was compensated for COD using the method of spectral difference. The original spectra in the range of 320-700nm, the turbidity compensated spectra in the range of 260-320nm, and the COD compensated spectra in the range of 225-260nm were analyzed by PLS algorithm in order to calculate the concentrations of nitrate, COD and turbidity in the mixture solutions. The results showed that this method could simultaneously and accurately determine the concentrations of nitrate, COD and turbidity. After interval analysis, all the correlation coefficients (R2) between the predicted values and the true values of nitrate, COD and turbidity were higher than 0.9, and root mean square error (RMSE) of predicted values were between 0.696 and 2.337.

High precision wide range online chemical oxygen demand measurement method based on ultraviolet absorption spectroscopy and full-spectrum data analysis

In this paper, a new method for high precision and wide range measurement of chemical oxygen demand (COD) based on ultraviolet absorption spectroscopy without reagent is proposed. The reasons for limiting measurement range and the main factors affecting the measurement accuracy are analyzed. A novel method of selecting different calibration wavelengths according to COD value to expand the measurement range and the turbidity compensation strategy based on full-spectrum data analysis to improve accuracy in wide measurement range are proposed and realized by an automatic wavelength selection calibration algorithm. Experiments were conducted to verify our idea with the self-developed micro UV–vis spectrophotometer (with a spectral range of 200–750 nm and a resolution of 5 nm) with a 10mm-path-length sample cell. By comparing various algorithms, the Savitzky-Golay (SG) convolution smoothing algorithm and the orthogonal signal correction (OSC) algorithm were chosen to compensate the additional absorption owing to turbidity. The experimental results show that the algorithm can automatically select the optimal characteristic wavelengths according to the spectral data and the measurement range of COD is enormously expanded from 10–150 mg/L to 1–1000 mg/L. The linear correlation coefficient (R2) of model is above 0.9995 and the relative error of measurement is less than 5%. This method can be used for in-situ and online COD measurement.

A turbidity compensation method for COD measurements by UV–vis spectroscopy

In water quality detection by ultraviolet-visible (UV–vis) spectroscopy, the detection equipment faces diverse water bodies. It is easy to be interfered by turbidity caused by suspended solid particles (SSP), resulting in a nonlinear rise of the whole spectrum and a significant decrease in measurement accuracy of chemical oxygen demand (COD). A turbidity compensation algorithm for UV–vis spectroscopy based on Lambert-Beer’s law for fitting the absorbance caused by turbidity in the whole spectrum region is studied. According to the additivity of absorbance, a few absorbance spectra of turbidity were obtained by filtering and difference method. They are then used as base spectra to linearly fit the absorbance spectrum of any turbidity value water. Finally, turbidity compensation of all samples in the whole region is realized by the subtraction method. Compared with 350 nm proportional compensation (350 nm PC) and multiplicative scatter correction (MSC), the compensated spectra of the method proposed in this paper are in the best coincidence with the filtered spectra by a 0.45 um filter membrane. Partial least squares (PLS) method is used to establish the COD prediction model of the raw spectra and compensated spectra of the three methods. The results show that the Rpred of the proposed method is the biggest and the RMSEP is the smallest. The experimental results show that the proposed turbidity compensation method can effectively correct the absorption spectrum without affecting the absorption characteristics of water samples. Furthermore, improving the accuracy of COD measurement by UV–vis spectroscopy.

Novel method of turbidity compensation for chemical oxygen demand measurements by using UV–vis spectrometry

In recent years, ultraviolet–visible spectroscopy has been widely used for chemical oxygen demand (COD) measurements of water. However, turbidity in water can cause measurement deviations, so it is very important to compensate for the impact of turbidity. In this study, a novel method of turbidity compensation is proposed. The absorption spectra of standard solutions and their mixture were sampled in the wavelength range from 220 to 750nm. We used a normalization technique to estimate the turbidity and dynamically simulate the absorption spectra of the turbidity. In addition, hydrogen bonds made the absorption peak blue shift in the mixture solutions. We established a numerical fitting curve to describe the relation between the blue shift and turbidity, and then we corrected the peak position. Furthermore, turbidity particles decreased the absorption peak of organic molecules. We introduced an impact index kN(λ) to describe the peak height reduction, and experiments demonstrated that kN is negatively associated with the absorbance of the standard COD solution. After the process of turbidity compensation, the root mean square errors (RMSEs) of the predictions were very small, which highlights the potential of this method for improving the accuracy of COD measurements based on ultraviolet–visible spectrum.

Ultrafast turbidity compensation in the optical therapeutic window by three-wave mixing phase conjugation

Imaging by phase conjugation through diffusing media is performed by using parametric amplification in a type II crystal, at a wavelength included in the therapeutic window. By nature, the method ensures imaging in a time far below the decorrelation time of in vivo biological tissues. A systematic comparison of performance with direct imaging is provided.

Frequency-selective absorbance detection: Refractive index and turbidity compensation with dual-wavelength measurement

A frequency-selective absorbance detection approach and its applications are described. First, a digital signal processor–lock-in amplifier (DSP–LIA)-based absorbance detector was evaluated. Compared to a simple operational amplifier (TL082CP)-based detector, the DSP–LIA-based detector showed lower noise levels, but the relative advantage was reduced under very low photocurrent levels (down to few nA). A 7 cm pathlength flow cell with this commercial LIA-based detector exhibited excellent Beer's law linearity ( r 2 = 0.9999) and a noise level of 7 micro absorbance units (μAU). The limit of detection (LOD, S/ N = 3) for methyl orange (MO) was 7 nM with this detector. Finally, as a more affordable alternative to an LIA, a balanced demodulator integrated circuit chip was used to fabricate a dual wavelength–frequency-selective LED-based absorbance detector. This device successfully compensated refractive index (RI) effect and turbidity effect in test flow systems. The LOD for MO with this system was 8 nM.

Automatic u.v.-control system for relative evaluation of organic water pollution

The research of correlation between u.v. absorbance and organic matter content has been carried out for a long-term observation. The positive results enabled the construction of u.v. analyser for continuous absorbance measurements at 254nm. The instrument performance has been used in river reaches with organic pollution and in effluents from municipal and industrial sewage works, especially with humic, lignin and phenolic matter content. At present the u.v. analyser with automatical turbidity compensation for some types of water is tested. The application of u.v. control system under work conditions is significant for detecting the instant relative concentration changes of organic component in the tested water and for indicating harmful situations. For information the results of absorbance, oxidability and conversion factors are given.