A universal model to predict DOC removal by coagulation based on UV-Visible absorption spectrum

IF 12.4 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research Pub Date : 2025-07-04 DOI:10.1016/j.watres.2025.124160

Yang Deng, Hanzhe Wang, Lei Zheng, Zhongli Liu, Gregory V. Korshin, Mingquan Yan

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Abstract

Dissolved organic matter (DOM) universally present in drinking water reacts with chlorine-based disinfectants to form disinfection byproducts (DBPs) such as trihalomethanes (THMs), haloacetic acids (HAAs) and other potentially more toxic compounds. Given that DOM removal is the primary goal of drinking water treatment, establishing models to predict DOM removal by coagulation is crucial for intelligent control in drinking water treatment plants (DWTPs). However, due to the lack of online methods for characterizing DOM reactivity in coagulation, predicting its performance for various water sources and variations of applicable seasonal conditions remains a great challenge. This study demonstrates that while DOC removal exhibits significant variations, it is primarily determined by the maximum DOC concentration removable by coagulation (DOC_max), the alkalinity in source waters, coagulant type and its dosage. The main finding of this study is that DOC_max can be determined based on the properties of absorbance Band A₃, identified as a deconvoluted Gaussian band within the Ultraviolet-Visible (UV-Vis) absorbance spectra of DOM, with the Band A₃ maximum near 350 nm (R² = 0.84). This result allows developing a universal model that accurately predicts, based on UV-Vis absorbance spectra of source waters, DOC removal by coagulation for a wide range of source conditions, alkalinity, and coagulant dosage (R² = 0.93). These insights can be used to develop smart dosing systems for control of coagulation in DWTPs.

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基于紫外可见吸收光谱预测混凝去除DOC的通用模型

饮用水中普遍存在的溶解有机物（DOM）与氯基消毒剂发生反应，形成消毒副产物（dbp），如三卤甲烷（THMs）、卤乙酸（HAAs）和其他潜在毒性更大的化合物。鉴于DOM去除是饮用水处理的首要目标，建立预测混凝去除DOM的模型对于饮用水处理厂（dwtp）的智能控制至关重要。然而，由于缺乏表征DOM在混凝过程中的反应性的在线方法，预测其在各种水源和适用季节条件变化中的性能仍然是一个很大的挑战。本研究表明，虽然DOC去除率存在显著差异，但主要由混凝去除最大DOC浓度（DOCmax）、源水体碱度、混凝剂类型和投加量等因素决定。本研究的主要发现是DOCmax可以根据DOM紫外-可见（UV-Vis）吸收光谱中A3波段的性质来确定，A3波段在350 nm附近最大（R2 = 0.84）。这一结果可以建立一个通用模型，根据源水的UV-Vis吸收光谱，准确预测在广泛的源条件、碱度和混凝剂用量下混凝去除DOC的效果（R2 = 0.93）。这些见解可用于开发智能加药系统，以控制dwtp中的凝血。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Water Research 环境科学-工程：环境

CiteScore

20.80

自引率

9.40%

发文量

1307

审稿时长

38 days

期刊介绍： Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.