Intensifying transition metal ion removal and recovery from acidic wastewater via electrodialysis (ED) -based process

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Petric Marc Ruya , Miguel Perdigão Silva , Geert Reyniers , Gracia Angelly Ruya , Siew Shee Lim , I Gede Wenten , Xing Yang
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Abstract

Industrial use of critical metals such as cobalt (Co) and manganese (Mn) generates metal-containing wastewater. Sustainable and effective solutions are yet to be developed to recover these elements in reusable forms, mainly due to the low metal ion concentration and presence of organics (e.g., in green plastic production). Thus, this study aimed to explore the feasibility of metal ion recovery from synthetic wastewater containing metal ions (e.g., Mn2+, Co2+) and high content of organic acid using electrodialysis (ED)-based process, with a specific focus to understand the fundamental performance constrains and find effective routes to intensify the recovery efficiency. The parametric study in the conventional ED demonstrated that the choice of more electrically conductive receiving solution greatly promoted the metal ion transport rate (ITR) by ∼26 % and reduced the energy consumption to 0.0045 kWh/kg metal recovered; while an optimal applied voltage of 1 V was chosen to avoid energy penalty through water splitting. Nevertheless, inherent limitations to further improvement of mass transfer of metal ions were identified in conventional ED. To this end, the adverse effect of concentration polarization was overcome by applying a pulsed electric field (PEF) in ED, reaching Co2+ ITR of 0.537mg·cm-2·h-1, which was 40 % higher than the optimal in conventional ED. Also, the competitive ion (H+ from acetic acid in this study) transport was found to impede the effective transfer of metal ions across the membrane. Thus, a novel integration of ED with a pretreatment method (i.e., super critical water gasification (SCWG)) was proposed to remove the acid for significantly intensifying the metal ion recovery with 50 % shorter treatment time, which was simulated to demonstrate the potential of energy self-sufficiency. The findings highlight the importance of advancing beyond traditional process optimization to address the complexities of real-world wastewater treatment, contributing to the development of unconventional and more sustainable treatment technologies and closed-loop industrial solutions.

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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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