Fluorine recovery from low-concentration fluorine wastewater by flow-electrode capacitive deionization and fluid bed crystallization (FCDI-FBC): Preconcentration and high-quality fluorite pellets formation

IF 12.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2025-05-01 Epub Date: 2025-01-31 DOI:10.1016/j.watres.2025.123228
Jing Yang , Hui Gong , Shuqian Chai , Danyang Zhu , Kejin Chen , Qinpei Liu , Xiaoguang Liu , Xiaohu Dai
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Abstract

Fluorine (F), critical for various industries, faces resource scarcity due to limited reserves of its primary source, fluorite (CaF₂). While fluorine-containing wastewater from industrial processes represents a valuable potential resource, recovering fluorine from low-concentration wastewater remains challenging. This study introduces a cyclic "preconcentration + recovery" system combining flow-electrode capacitive deionization (FCDI) and fluidized bed crystallization (FBC) to address this gap. FCDI preconcentrates fluorine ions into high-concentration brine, and FBC facilitates the formation of high-purity fluorite crystals. Experimental parameters influencing FCDI efficiency - such as influent fluoride concentration, electrode solution composition, and flow rate - were systematically evaluated. Additionally, the cyclic operation was modeled to enhance the whole recovery rate across multiple cycles. The experimental results demonstrated that FCDI achieves an 83.90% fluoride removal rate under optimal conditions with energy-efficient operation. FBC produces fluorite crystals of up to 97.20% purity, classified as acid-grade. The integrated FCDI-FBC system achieves a fluoride recovery rate of 64.40% in single operation mode, with further improvements in cyclic mode. The proposed system offers a sustainable and economically feasible solution to fluorine recovery from low-concentration wastewater, representing a significant step toward the sustainable utilization of non-renewable fluorite resources.

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流动电极电容去离子和流化床结晶(fdi - fbc)回收低浓度氟废水中的氟:预富集和高质量萤石球团形成
氟(F)对各行业至关重要,但由于其主要来源萤石(CaF 2)储量有限,面临资源短缺的问题。虽然工业过程产生的含氟废水是一种宝贵的潜在资源,但从低浓度废水中回收氟仍然具有挑战性。本研究引入了一种结合流动电极电容去离子(FCDI)和流化床结晶(FBC)的循环“预富集+回收”系统来解决这一空白。fdi将氟离子预浓缩成高浓度卤水,FBC有利于形成高纯度萤石晶体。系统地评估了影响FCDI效率的实验参数,如进水氟浓度、电极溶液组成和流速。此外,还对循环作业进行了建模,以提高多个循环的总采收率。实验结果表明,在最优条件下,fdi除氟率达到83.90%,运行节能。FBC生产的萤石晶体纯度可达97.20%,属酸级。fdi - fbc一体化系统在单工况下氟回收率可达64.40%,循环工况下氟回收率进一步提高。该系统为从低浓度废水中回收氟提供了可持续和经济可行的解决方案,代表了不可再生萤石资源可持续利用的重要一步。
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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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