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

Chen, Xiaowei; Yin, Guisheng; Zhao, Nanjing; Gan, Tingting; Yang, Ruifang; Xia, Meng; Feng, Chuanqi; Chen, Yunan; Huang, Yao

doi:10.1016/j.saa.2020.118827

Cited by 27 publications

(14 citation statements)

References 5 publications

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“…Indirect multivariate methods showed an important improvement in calibration compared to the direct methods. These results support the findings from previous studies that recommended the use of the PLSR method to infer solutes concentrations (Aguerssif et al, 2008; Carré et al, 2017; Chen et al, 2021; Garcia Rodriguez et al, 1998; Khatri et al, 2020; Xu et al, 2014). This is likely because using the whole spectrum allows accounting for interferences (e.g., suspended solids) in light absorbance of stream water (Shi et al, 2020, 2021).…”

Section: Discussionsupporting

confidence: 91%

High‐frequency multi‐solute calibration using an in situUV–visible sensor

Pesántez

Birkel

Mosquera

et al. 2021

Hydrological Processes

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Monitoring the temporal variation of solute concentrations in streams at high temporal frequency can play an important role in understanding the hydrological and biogeochemical behaviour of catchments. UV-visible spectrometry is a relatively inexpensive and easily used tool to infer those concentrations in streams at high temporal resolution. However, it is not yet clear which solutes can be modelled with such an in-situ sensor. Here, we installed a UV-visible spectrometer probe (200-750 nm) in a high-altitude tropical Páramo stream to record the wavelength absorbance at a 5-min temporal resolution. For calibration, we simultaneously sampled stream water at a 4-h frequency from February 2018 to March 2019 for subsequent laboratory analysis. Absorbance spectra and laboratory-determined solute concentrations were used to identify the best calibration method and to determine which solute concentrations can be effectively inferred using in situ spectrometry through the evaluation of six calibration methods of different mathematical complexity. Based on the Nash-Sutcliffe efficiency (NSE) and Akaike information criterion metrics, our results suggest that multivariate methods always outperformed simpler strategies to infer solute concentrations. Eleven out of 21 studied solutes (Al, DOC, Ca, Cu, K, Mg, N, Na, Rb, Si and Sr) were successfully calibrated (NSE >0.50) and could be inferred using UVvisible spectrometry even with a reduced daily sampling frequency. It is worth noting that most calibrated solutes were correlated with wavelengths (WLs) in the low range of the spectra (i.e., UV range) and showed relatively good correlation with DOC. The latter suggests that estimation of metal concentrations could be possible in other streams with a high organic load (e.g., peat dominated catchments). In situ operation of spectrometers to monitor water quality parameters at high temporal frequency (sub-hourly) can enhance the protection of human water supplies and aquatic ecosystems as well as providing information for assessing catchment hydrological functioning.

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Section: Discussionsupporting

confidence: 91%

High‐frequency multi‐solute calibration using an in situUV–visible sensor

Pesántez

Birkel

Mosquera

et al. 2021

Hydrological Processes

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“…Related works can be found, but they are related to Wastewater Treatment Plants and not directly applied to the estimation of COD in wastewater coming from the different processes involved in leather production. Most of the works found in the literature exploit Multi-linear Regression to provide COD estimation from spectroscopy [16][17][18][19]. Others used Artificial Neural Networks as a machine learning model to find the correlation between the absorption spectrum and COD [18,20].…”

Section: Related Workmentioning

confidence: 99%

Estimation of COD from UV-Vis Spectrometer Exploiting Machine Learning in Leather Industries Wastewater

Cardia¹,

Chessa²,

Franceschi³

et al. 2023

World Congress on Civil, Structural, and Environmental Engineering

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We present a method for the analysis of wastewater in the context of the leather industry. In this context, the determination of the Chemical Oxygen Demand parameter is essential for the determination of the degree of water pollution. Conventional methods for measuring it require time-consuming laboratory analysis, sample preparation and the usage of toxic chemicals. The proposed method is based on machine learning and soft sensing, employing nonspecific sensors to derive the quality indicators of wastewater. In particular, we leverage ultraviolet and visible spectroscopy measurements, that provide wastewater absorbance, that is the quantity of light absorbed by a solution, to estimate Chemical Oxygen Demand. We stress that, after deployment, our approach does not require any (timeexpensive) laboratory analyses, and hence it can be used to implement systems of real-time monitoring of wastewater in a leather production context.

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“…The result shows that at the wavelength of 270 nm, the concentration of COD shows the best linearity with the absorption magnitude, and the adjusted R-Square value at this wavelength is beyond 0.99. To further evaluate the performance of the system in the wavelength of visible band (400~700 nm), the solution was selected as an analyte sample, due to the absorption of turbidity that occurs both at the ultra-violet band and the visible band of the spectrum [35]. The turbidity solution was diluted from the Formazine solution at the concentration of 400 NTU and divided into nine groups at the concentration range from 8 NTU to 40 NTU.…”

Section: Signal Quality Evaluation For Absorption Spectrummentioning

confidence: 99%

A Design of Real-Time Data Acquisition and Processing System for Nanosecond Ultraviolet-Visible Absorption Spectrum Detection

et al. 2022

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Ultraviolet-visible absorption spectroscopy is widely used to monitor water quality, and rapid optical signal detection is a key technology in the process of spectrum measurement. In this paper, an ultrafast spectrophotometer system that can achieve spectrum data acquisition in a single flash of the xenon lamp (within 200 ns) is introduced, and a real-time denoising method for the spectrum is implemented on a field programmable gate array (FPGA) to work cooperatively with the nanosecond spectrum acquisition system, in order to guarantee the quality of the spectrum signals without losing running speed. The hardware of the data acquisition and processing system are constructed on a Xilinx Spartan 6 FPGA chip and its peripheral circuit, including an analog to digital converter and a complementary metal-oxide-semiconductor transistor (CMOS) sensor’s diver circuit. An oversampling method that is suitable for the CMOS sensor’s output is proposed, which works on the CMOS sensor’s dark current noise and readout noise. Another moving-average filter method is designed adaptively, which works on the low-frequency component to filter out the residual spectrum noise of the spectrum signal. The implementation of the filter on the FPGA has been optimized by using a pipelined structure and dual high-speed random-access memory (RAM). As a result, the CMOS linear image sensor successfully captured the spectrum of xenon flash light at the readout clock frequency of 500 kHz and the processing manipulation to the full UV-Vis spectrum data was accomplished at a sub-microsecond speed performance. After the digital filter and oversampling technology were implemented, the coefficient of variation of the measurements reduced from 9.57% to 1.74%, while the signal noise ratio (SNR) of the absorption spectrum increased nine times, compared to the raw data of the CMOS sensor’s output. The tests towards different analyte samples were conducted, and the system shows good performance on distinguishing different concentrations of different analyte solutions on both ultra-violet and visible spectrum bands. The present work showcases the potential of the CMOS sensor’s technique for the fast detection of contaminated water containing nitrate and organic compounds.

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

Cited by 27 publications

References 5 publications

High‐frequency multi‐solute calibration using an in situUV–visible sensor

High‐frequency multi‐solute calibration using an in situUV–visible sensor

Estimation of COD from UV-Vis Spectrometer Exploiting Machine Learning in Leather Industries Wastewater

A Design of Real-Time Data Acquisition and Processing System for Nanosecond Ultraviolet-Visible Absorption Spectrum Detection

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