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

Hu, Yingtian; Wen, Yizhang; Wang, Xiaoping

doi:10.1016/j.snb.2015.12.078

Cited by 58 publications

(17 citation statements)

References 5 publications

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“…This process is known as turbidity or particle compensation. Several particle compensation techniques exist in the literature [ 27 , 28 , 29 , 30 ]. The software equipped with the spectrophotometer has a built-in function to do this operation for different water types (i.e., drinking water, wastewater, etc.).…”

Section: Methodsmentioning

confidence: 99%

Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach

Hossain

Chow

Hewa

et al. 2020

Sensors

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The spectra fingerprint of drinking water from a water treatment plant (WTP) is characterised by a number of light-absorbing substances, including organic, nitrate, disinfectant, and particle or turbidity. Detection of disinfectant (monochloramine) can be better achieved by separating its spectra from the combined spectra. In this paper, two major focuses are (i) the separation of monochloramine spectra from the combined spectra and (ii) assessment of the application of the machine learning algorithm in real-time detection of monochloramine. The support vector regression (SVR) model was developed using multi-wavelength ultraviolet-visible (UV-Vis) absorbance spectra and online amperometric monochloramine residual measurement data. The performance of the SVR model was evaluated by using four different kernel functions. Results show that (i) particles or turbidity in water have a significant effect on UV-Vis spectral measurement and improved modelling accuracy is achieved by using particle compensated spectra; (ii) modelling performance is further improved by compensating the spectra for natural organic matter (NOM) and nitrate (NO3) and (iii) the choice of kernel functions greatly affected the SVR performance, especially the radial basis function (RBF) appears to be the highest performing kernel function. The outcomes of this research suggest that disinfectant residual (monochloramine) can be measured in real time using the SVR algorithm with a precision level of ± 0.1 mg L−1.

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Section: Methodsmentioning

confidence: 99%

Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach

Hossain

Chow

Hewa

et al. 2020

Sensors

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“…PXRD analysis (Figure S8, Supporting Information) indicates that the structure of Eu‐ade‐MOF after 8‐oxo‐dG detection maintains intact, ruling out the possibility that the luminescence responses were triggered by the transformation of the material's framework. The UV–vis spectra of Eu‐ade‐MOF shows an absorption peak at 267 nm for ade (Figure S9, Supporting Information) that shifts to 255 nm in the [Eu‐ade‐MOF‐8‐oxo‐dG] adduct, indicating the formation of H‐bonds between ade and 8‐oxo‐dG . The hydrogen‐bonding interaction can greatly restrict the intramolecular rotations (IMR) in Eu‐ade‐MOF, thus suppressing the non‐radiative decay and ET loss from the organic framework‐to‐Eu.…”

Section: Resultsmentioning

confidence: 99%

Concurrent Modulation of Competitive Mechanisms to Design Stimuli‐Responsive Ln‐MOFs: A Light‐Operated Dual‐Mode Assay for Oxidative DNA Damage

Hao

2019

Adv Funct Materials

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The identification of biomolecules for disease diagnosis requires facile analytical technologies with high precision and reliability. Several signal transduction pathways have inspired the development of various bioanalytical systems. However, most systems are greatly limited by a single-mechanism/ mode assay, which easily results in false-positive/negative results. Herein, a multiple-mechanism-driven optical biosensor for 8-oxo-2′-deoxyguanosine (8-oxo-dG), an early pathological signature of DNA lesions and various diseases, is designed by assembling adenine as a recognition element, mellitic acid as energy donors and Eu 3+ as signal reporters into one metalorganic framework (MOF) system. Significantly, by regulating the delicate competition between the different mechanisms, the fabricated single platform (Eu-ade-MOF) concurrently provides two switchable approaches for rapid qualitative (30 s and 4 min) and quantitive (ppb level) recognition of 8-oxo-dG in both complex artificial and real human urine environments. Compared with those single-mechanism/mode-driven detections, this light-operated dual-mode analysis system can inherently boost the analysis reliability and largely minimize the chances of false negatives/positives for a non-invasive diagnosis of DNA damage and related diseases. This work represents the first effort in designing a luminescent sensor coupling multiple mechanisms in a single interface to determine DNA damage degree and provides a new approach for developing multimode analysis platforms for human health monitoring.

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“…The dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) contents were measured with a total organic carbon analyzer (TOC-V CPN, Shimadzu, Kyoto, Japan). COD Mn was determined via UV-VIS spectrometry [17]. Sediment water content was measured by drying the wet sediment to a constant weight at 105 • C. Loss on ignition (LOI) was obtained by igniting the dried sediment at 550 • C for 4 h [18].…”

Section: Sampling and Measurementsmentioning

confidence: 99%

Methane Levels of a River Network in Wuxi City, China and Response to Water Governance

Yan

Xue

2020

Water

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The majority of rivers are a CH4 source that accounts for an important proportion of annual global emissions. However, CH4 evasion from urban river networks has received disproportionately less attention than their contribution. The effect of water governance on water quality and CH4 emission in urban areas remains unclear. Water quality, CH4 concentrations, and fluxes from a river network in Binhu District, Wuxi City, and their response to water governance were analyzed in this study. CH4 concentrations in the investigated rivers ranged from 0.05 μmol L−1 to 16.37 μmol L−1 (2.47 ± 4.5 μmol L−1, medium 0.23 μmol L−1), and CH4 diffusive fluxes were 75.55 ± 171.78 μmol m−2 h−1 with a medium of 6.50 μmol m−2 h−1. CH4 concentration showed a significant correlation with water quality parameters, especially for NH3–N (r = 0.84, p < 0.001). Significant differences in water quality and CH4 levels were found between sites that had conducted water management and those that continued to exhibit poor water quality. Our analysis showed that rivers under water governance have a positive tendency toward water ecological restoration, and a significant decrease in CH4 efflux to the air can be achieved after extensive and intensified water governance.

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

Cited by 58 publications

References 5 publications

Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach

Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach

Concurrent Modulation of Competitive Mechanisms to Design Stimuli‐Responsive Ln‐MOFs: A Light‐Operated Dual‐Mode Assay for Oxidative DNA Damage

Methane Levels of a River Network in Wuxi City, China and Response to Water Governance

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