# Advances on Water Quality Detection by UV-Vis Spectroscopy
## 4 Research Status and Progress of Main Water Quality Parameters  
### Research Status of COD in Water  
COD is a very important parameter in water quality detection. COD refers to the amount of oxidant consumed by the reducing substances in the oxidized one liter water sample under certain conditions, expressed in milligrams per liter. It reflects the degree of pollution caused by adding reducing substances to water [33].  
Because it is easily influenced by human factors or machine equipment in the process of data acquisition, many researchers preprocess the spectral data before establishing the COD prediction model. [PERSON] et al. [34] collected spectral data in the samples to be tested by the UV-Vis spectrum, preprocessed the data by using the wavelet transform method, reduced the dimension of the data by using a local linear embedding (LLE) method, and finally established a prediction model based on SVR. [PERSON] et al. [35] used a smoothing algorithm, empirical mode decomposition algorithm, and wavelet analysis to reduce the noise of UV-Vis spectrum data, and obtained six potential variables from PLSR modeling as the input of a partial least squares support vector machine (LS-SVM) to establish a COD prediction model. [PERSON] et al. [36] used a competitive adaptive reweighting algorithm (CARS) to obtain the characteristic wavelength of the UV-Vis spectrum and used ELM to model, which can accurately and rapidly detect the COD content in aquaculture water. [PERSON] et al. [37] used the UVE-SPA variable selection algorithm to obtain the UV-Vis spectrum characteristic wavelength, which when combined with LS-SVM modeling, quickly and accurately measured COD concentrations in aquaculture water. [PERSON] et al. [38] accurately determined COD by combining UV-Vis spectroscopy and multivariate calibration and established a calibration model of COD values by using the partial least squares method (PLS). To improve the prediction performance of COD content in water, [PERSON] et al. [39] used variable pathlength UV-Vis spectroscopy combined with PLSR model to achieve high-precision monitoring of COD in wastewater.  
While studying the use of UV-Vis spectroscopy to detect COD of water quality, many researchers also noticed that the scattering caused by turbidity has an impact on the UV-Vis absorption spectrum of the water sample, such as baseline drift and nonlinear uplift of spectral lines [40; 41]. Turbidity seriously interferes with the output accuracy of the COD detection model. [PERSON] et al. [42] studied the influence of temperature and turbidity on COD detection. The single temperature parameter required a long-span change to have a significant impact on the UV absorbance data of COD detection of waterquality but the turbidity parameter caused the deviation in COD measurement. Finally, the non-linear compensation model was used to effectively suppress the influence of turbidity in water; [PERSON] et al. [43] used the normalization technique to estimate the turbidity and dynamically simulated its absorption spectrum. The absorption peak in the mixed solution to shift blue was caused by hydrogen bonds; thus, a numerical fitting curve to describe the relationship between the blue shift and the turbidity was established, and then the position of the peak was corrected. After the turbidity compensation process, the coefficient of determination was 0.99 and the predicted RMSE was only 2.42 mg/L, which highlights the potential of this method in improving the accuracy of COD measurement based on the UV-Vis spectrum. [PERSON] et al. [44] simultaneously determined COD and turbidity concentration by UV-Vis in the wavelength range of 200-1100 nm. The PLS method was used to analyze the regression, and relatively reliable detection results were obtained.