Variation of current density with time as a novel method for efficient electrochemical treatment of real dyeing wastewater with energy savings

Yao, Jiachao; Lv, Sini; Wang, Zeyu; Hu, Liyong; Chen, Jun

doi:10.1007/s11356-022-18927-3

Cited by 8 publications

(2 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[3][4][5]. However, the addition of external carbon sources requires a profound understanding of the COD components of the influent water in the local wastewater treatment plant (WWTP), as well as the kinetics of degradation and utilization processes [6,7].…”

Section: Introductionmentioning

confidence: 99%

Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Zhang,

Guo,

Luo

et al. 2024

Water

View full text Add to dashboard Cite

The rapid identification of the amount and characteristics of chemical oxygen demand (COD) in influent water is critical to the operation of wastewater treatment plants (WWTPs), especially for WWTPs in the face of influent water with a low carbon/nitrogen (C/N) ratio. Given that, this study carried out batch kinetic experiments for soluble chemical oxygen demand (SCOD) and nitrogen degradation for three WWTPs and established machine learning (ML) models for the accurate prediction of the variation in SCOD. The results indicate that four different kinds of components were identified via parallel factor (PARAFAC) analysis. C1 (Ex/Em = 235 nm and 275/348 nm, tryptophan-like substances/soluble microbial by-products) contributes to the majority of internal carbon sources for endogenous denitrification, whereas C4 (230 nm and 275/350 nm, tyrosine-like substances) is crucial for readily biodegradable SCOD composition according to the machine learning (ML) models. Furthermore, the gradient boosting decision tree (GBDT) algorithm achieved higher interpretability and generalizability in describing the relationship between SCOD and carbon source components, with an R2 reaching 0.772. A Shapley additive explanations (SHAP) analysis of GBDT models further validated the above result. Undoubtedly, this study provided novel insights into utilizing ML models to predict SCOD through the measurements of the excitation–emission matrix (EEM) in specific Ex and Em positions. The results could help us to identify the degradation and transformation relationship between different kinds of carbon sources and nitrogen species in the wastewater treatment process, and thus provide a novel guidance for the optimized operation of WWTPs.

show abstract

Section: Introductionmentioning

confidence: 99%

Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Zhang,

Guo,

Luo

et al. 2024

Water

View full text Add to dashboard Cite

show abstract

“…In recent years, various methods such as the electrochemical method [11], photocatalytic degradation [12], and adsorption [13,14] have been developed for the removal of dyes. In these methods, adsorption has been regarded as the most promising approach due to various advantages such as simple steps, low cost, and high efficiency [15,16].…”

Section: Introductionmentioning

confidence: 99%

Fabrication of highly crystalline covalent organic framework for solid‐phase extraction of three dyes from food and water samples

Wang

Tao

Wang

et al. 2023

J of Separation Science

View full text Add to dashboard Cite

The harm caused by dye pollution in water or excessive dyes in food has seriously threatened human health, and thus the monitor and removal of the dyes in environmental water and food are of great signi cance. In present study, covalent organic framework (namely COF-TFTP), which was fabricated at room temperature by using 1,3,5-tris(p-formylphenyl) benzene and 1,3,5-tris(4-aminophenyl)benzene as building blocks, was employed as an adsrobent for solid-phase extraction (SPE) of dyes including congo red, methyl blue and direct red 80 for the rst time. The physicochemical properties of COF-TFTP were investigated by using SEM, TEM, XRD, XPS and so on. The results revealed that COF-TFTP showed uniform spherical structure, high crystallinity, satisfactory surface area, and good thermal stability. The results of adsorption experiments indicated that COF-TFTP had good adsorption capacities for congo red, methyl blue and direct red 80 (284.10, 177.62 and 55.25 mg⋅g − 1 ) and the adsorption equilibrium can be achieved in a relatively short time (15 min). Further, to achieve the best adsorption effects of COF-TFTP, the in uence parameters including pH, ionic strength, type of desorption solvent, the COF-TFTP dosage in SPE column, were optimized in turn. Finally, under the optimal SPE conditions, COF-TFTP based SPE was applied to the adsorption of congo red and methyl blue in food samples (e.g. pork and sh), to the adsorption of three dyes in water samples. The recoveries of dyes in environmental water samples (71.50-86.84%) and food samples (68.50-88.95%) were satisfactory, revealing the unique applicability of COF-TFTP in sample pretreatment eld.

show abstract

Application of Anodic Oxidation in Diazinon Degradation

Santos

Marques

Alsina

et al. 2022

Water Air Soil Pollut

View full text Add to dashboard Cite

Variation of current density with time as a novel method for efficient electrochemical treatment of real dyeing wastewater with energy savings

Cited by 8 publications

References 43 publications

Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Insightful Analysis and Prediction of SCOD Component Variation in Low-Carbon/Nitrogen-Ratio Domestic Wastewater via Machine Learning

Fabrication of highly crystalline covalent organic framework for solid‐phase extraction of three dyes from food and water samples

Application of Anodic Oxidation in Diazinon Degradation

Contact Info

Product

Resources

About