A Turbidity-Compensation Method for Nitrate Measurement Based on Ultraviolet Difference Spectroscopy

• Published in: Molecules (Basel, Switzerland) Switzerland), 2022-12, Vol.28 (1), p.250
• Main Authors: Dong, Jing, Tang, Junwu, Wu, Guojun, Li, Ruizhuo
• Format: Article
• Language: English
• Subjects: Absorbance; Absorption; Absorption spectra; Accuracy; Algorithms; Analysis; Chemical oxygen demand; Compensation; Composition; difference spectrum; Laboratories; Methods; nitrate; Nitrates; partial least squares; Phytoplankton; Prediction models; Properties; Spectroscopy; Spectrum analysis; Turbidity; turbidity compensation; Ultraviolet spectra; ultraviolet spectroscopy; Water analysis; Water sampling; Water turbidity; Wavelengths
• ISSN: 1420-3049; 1420-3049
• DOI: 10.3390/molecules28010250

To solve the problem that turbidity in water has a significant effect on the spectra of nitrate and reduces the accuracy of nitrate detection, a turbidity-compensation method for nitrate measurement based on ultraviolet difference spectra is proposed. The effect of turbidity on the absorption spectra of nitrate was studied by using the difference spectra of the mixed solution and a nitrate solution. The results showed that the same turbidity had different effects on the absorbance of different concentrations of nitrate. The change in absorbance due to turbidity decreased with an increase in the nitrate concentration at wavelengths from 200 nm to 230 nm, although this change was constant when the wavelength was greater than 230 nm. On the basis of this characteristic, we combined the residual sum of squares (RSS) and interval partial least squares (iPLS) to select wavelengths of 230-240 nm as the optimal modeling interval. Furthermore, the turbidity-compensation model was established by the linear fitting of the difference spectra of various levels of turbidity. The absorption spectra of the nitrate were extracted by subtracting the turbidity-compensation curve from the original spectra of the water samples, and the nitrate concentration was calculated by using a partial least squares (PLS)-based nitrate-prediction model. The experimental results showed that the average relative error of the nitrate predictions was reduced by 50.33% to 1.33% by the proposed turbidity-compensation method. This indicated that this method can better correct the deviation in nitrate's absorbance caused by turbidity and improve the accuracy of nitrate predictions.