Electrochemical nitrite sensing using mass transfer signal with a catalyst-free small-sized rotating disk electrode for wastewater monitoring

IF 12.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2025-06-01 Epub Date: 2025-02-21 DOI:10.1016/j.watres.2025.123346
Fengjun Yin , Xiaohui Yang , Shun Lu , Hanlin Zhang , Ying Zhao , Sha Wang , Cheng Song , Yongzhi Li , Zhaoming Chen , Hong Liu
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Abstract

Electrochemical nitrite sensing (ENS) is a competitive method for online monitoring in the intelligent control of biological nitrogen removal process. However, its popularity is extremely low due to complex wastewater interference and low sensor durability. Here, we developed a novel ENS method that utilizes the mass transfer signal (MTS) of the nitrite oxidation reaction (NOR), making detection accuracy dependent solely on mass transfer process. These features enabled us to design a catalyst-free, small-sized glassy carbon rotating disk electrode for accurate MTS determination with exceptional durability. The linearity of MTS versus nitrite concentration surpasses that of conventional differential pulse voltammetry and amperometry. The method has a wide linear range of 100 μM–100 mM, a detection limit of 28 μM, and a high sensitivity of 1638 μA mM-1 cm-2. Importantly, solution pH and coexisting buffers show no significant effect on MTS determinations as long as pH does not exceed 10. Excellent immunity to interference from ionic strength, temperature, COD, inert salts, metal ions, dissolved oxygen, and hydrogen peroxide was observed. While reducing substances capable of oxidation reactions do cause interference, they are not common in environmental samples. Finally, a self-designed detection system requiring a sample volume of 4 mL was used for wastewater testing. The results demonstrate good capability for nitrite detection during practical wastewater treatment processes, although relative error increases with the complexity and content of organic pollutants in the wastewater. Overall, this ENS method holds great potential for achieving rapid, stable, and low-cost nitrite sensing in environmental applications.

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基于传质信号的小型圆盘电极亚硝酸盐电化学传感废水监测
电化学亚硝酸盐传感(ENS)是生物脱氮过程智能控制中一种具有竞争力的在线监测方法。然而,由于复杂的废水干扰和传感器耐久性低,其普及率极低。在这里,我们开发了一种新的ENS方法,利用亚硝酸盐氧化反应(NOR)的传质信号(MTS),使检测精度仅依赖于传质过程。这些特点使我们能够设计一种无催化剂,小尺寸的玻璃碳旋转圆盘电极,用于精确的MTS测定,具有卓越的耐用性。MTS与亚硝酸盐浓度的线性关系优于传统的差分脉冲伏安法和安培法。该方法线性范围为100 μM - 100 mM,检出限为28 μM,灵敏度为1638 μA mM-1 cm-2。重要的是,只要pH不超过10,溶液pH和共存缓冲液对MTS的测定没有显著影响。对离子强度、温度、COD、惰性盐、金属离子、溶解氧和过氧化氢的干扰具有良好的免疫力。虽然能够进行氧化反应的还原性物质确实会引起干扰,但它们在环境样品中并不常见。最后,采用自行设计的检测系统,样本量为4 mL进行废水检测。结果表明,该方法在实际废水处理过程中具有良好的亚硝酸盐检测能力,但相对误差会随着废水中有机污染物的复杂性和含量的增加而增加。总的来说,这种ENS方法在环境应用中实现快速、稳定和低成本的亚硝酸盐传感具有很大的潜力。
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来源期刊
Water Research
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.
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