24 research outputs found
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Application of neural network in metal adsorption using biomaterials (BMs): a review
With growing environmental consciousness, biomaterials (BMs) have garnered attention as sustainable materials for the adsorption of hazardous water contaminants. These BMs are engineered using surface treatments or physical alterations to enhance their adsorptive properties. The lab-scale methods generally employ a One Variable at a Time (OVAT) approach to analyze the impact of biomaterial modifications, their characteristics and other process variables such as pH, temperature, dosage, etc., on the removal of metals via adsorption. Although implementing the adsorption procedure using BMs seems simple, the conjugate effects of adsorbent properties and process attributes implicate complex nonlinear interactions. As a result, artificial neural networks (ANN) have gained traction in the quest to understand the complex metal adsorption processes on biomaterials, with applications in environmental remediation and water reuse. This review discusses recent progress using ANN frameworks for metal adsorption using modified biomaterials. Subsequently, the paper comprehensively evaluates the development of a hybrid-ANN system to estimate isothermal, kinetic and thermodynamic parameters in multicomponent adsorption systems
Per- and polyfluoroalkyl substances : removal from recycled and impaired waters using ion exchange process
The full abstract for this thesis is available in the body of the thesis, and will be available when the embargo expires.Applied Science, Faculty ofChemical and Biological Engineering, Department ofGraduat
Anion exchange resins for the removal of microcystins from surface water
Harmful algal blooms have markedly increased in frequency over the past two decades, due to rising global temperatures and chemical runoff produced by modern farming practices. Cyanobacteria, also known as the blue green algae, are an essential part of the aquatic food chain. Cyanobacterial toxins, which are released from the algal biomass, can contaminate drinking, recreational and agricultural water reserves. Such environmental and health hazards pose a serious threat to communities and many aquatic ecosystems. In particular, small, shallow lakes that are sources of drinking water for rural communities have been particularly affected by elevated levels of algal toxins. Conventional water treatment systems are inefficient in removing these toxins, and may produce hazardous by-products. Additionally, the effectiveness of chemical oxidants, like chlorine and ozone, is hindered by the presence of natural organic matter (NOM) and inorganic ions in the contaminated water. Such challenges reveal the need for alternative treatment technologies capable of removing algal toxins.
Anionic ion exchange (IX) resins offer a promising and cost-effective treatment alternative for natural waters affected by high algal content and high dissolved organic carbon (DOC) levels. This research investigates the efficiency of strongly basic ion exchange resins for the removal of microcystin-LR (MCLR), the most common toxin released from the algal biomass, inorganic ions, and NOM from natural water sources. We focused specifically on optimizing resin dosage, resin regeneration, and scaling up such procedures for particular source waters. Our results showed that the resin exhibited an excellent adsorption capacity of 3850 µg/L, removing more than 80% of the MCLR within 10 minutes at examined resin dosages (10 to 1000 mg/L; 1mL of resin = 221 mg). Additionally, we examined the influence of operating parameters such as pH and adsorption capacity of the resin, as well as the impact of NOM fractions on the uptake of MCLR. The charge density and molecular weight of the source water NOM were found to play a major competitive role in the uptake of Microcystin-LR. The results of this study bring the promising potential of IX resins for the removal of Microcystins and NOM from surface waters to light.Applied Science, Faculty ofChemical and Biological Engineering, Department ofGraduat