Cross-linked chitosan/zeolite as a fixed-bed column for organic micropollutants removal from aqueous solution, optimization with RSM and artificial neural network

Advanced technologies in water treatment: Chitosan and its modifications as effective agents in the adsorption of contaminants

Chitosan, derived from the abundant biopolymer chitin, has emerged as a promising option for water treatment due to its intrinsic bioavailability. This review emphasizes the notable characteristics of chitosan, which allow for various modifications, expanding its applications. The polymer's effectiveness in adsorbing contaminants, particularly in advanced water treatment technologies, is highlighted. The review underscores the potential of chitosan-based hybrid materials, including nanocomposites, hydrogels, membranes, films, sponges, nanoparticles, microspheres, and flakes, as innovative alternatives to traditional chemical-based adsorbents. The advantages of using these materials in wastewater treatment, especially in removing heavy metals, dyes, and emerging compounds, are explored. The study delves into the mechanisms involved in wastewater treatment with chitosan, emphasizing the interactions between the polymer and various contaminants. Additionally, the application of chitosan as a contaminant removal agent in a post-pandemic context is addressed, considering the challenges related to waste management and environmental preservation. The analysis highlights the potential contribution of chitosan in mitigating environmental impacts post-pandemic, offering practical solutions for treating contaminated effluents and promoting sustainability. The study addresses current obstacles and prospects for chitosan-based wastewater treatment, emphasizing its promising role in sustainable water management.

Modelling and optimization of membrane process for removal of biologics (pathogens) from water and wastewater: Current perspectives and challenges

As one of the 17 sustainable development goals, the United Nations (UN) has prioritized "clean water and sanitation" (Goal 6) to reduce the discharge of emerging pollutants and disease-causing agents into the environment. Contamination of water by pathogenic microorganisms and their existence in treated water is a global public health concern. Under natural conditions, water is frequently prone to contamination by invasive microorganisms, such as bacteria, viruses, and protozoa. This circumstance has therefore highlighted the critical need for research techniques to prevent, treat, and get rid of pathogens in wastewater. Membrane systems have emerged as one of the effective ways of removing contaminants from water and wastewater However, few research studies have examined the synergistic or conflicting effects of operating conditions on newly developing contaminants found in wastewater. Therefore, the efficient, dependable, and expeditious examination of the pathogens in the intricate wastewater matrix remains a significant obstacle. As far as it can be ascertained, much attention has not recently been given to optimizing membrane processes to develop optimal operation design as related to pathogen removal from water and wastewater. Therefore, this state-of-the-art review aims to discuss the current trends in removing pathogens from wastewater by membrane techniques. In addition, conventional techniques of treating pathogenic-containing water and wastewater and their shortcomings were briefly discussed. Furthermore, derived mathematical models suitable for modelling, simulation, and control of membrane technologies for pathogens removal are highlighted. In conclusion, the challenges facing membrane technologies for removing pathogens were extensively discussed, and future outlooks/perspectives on optimizing and modelling membrane processes are recommended.

A review on the lignocellulosic derived biochar-based catalyst in wastewater remediation: Advanced treatment technologies and machine learning tools

Wastewater disposal in the ecosystem affects aquatic and human life, which necessitates the removal of the contaminants. Eliminating wastewater contaminants using biochar produced through the thermal decomposition of lignocellulosic biomass (LCB) is sustainable. Due to its high specific surface area, porous structure, oxygen functional groups, and low cost, biochar has emerged as an alternate contender in catalysis. Various innovative advanced technologies were combined with biochar for effective wastewater treatment. This review examines the use of LCB for the synthesis of biochar along with its activation methods. It also elaborates on using advanced biochar-based technologies in wastewater treatment and the mechanism for forming oxidizing species. The research also highlights the use of machine learning in pollutant removal and identifies the obstacles of biochar-based catalysts in both real-time and cutting-edge technologies. Probable and restrictions for further exploration are discussed.

Artificial intelligence and structural design of inorganic hollow fiber membranes: Materials chemistry

A key challenge is to produce the uniform morphology and regular pore design of inorganic hollow fiber membranes (HFMs) due to involvement of multiple parameters including, fabrication process and materials chemistry. Inorganic HFMs required technical innovations via novel structural design and artificial intelligence (AI) to produce the uniform structure and regular pore design. Therefore, this review aims at critical analysis on the most recent and relevant approaches to tackle the issues related to tune the morphology and pore design of inorganic HFMs. Structural design and evaluation of routes towards the dope suspension, spinning, and sintering of inorganic HFMs are critically analysed. AI, driving forces and challenges involved for harnessing of materials are revealed in this review. AI programs used for the prediction of pore design and performance of HFMs have also been explained in this review. Overall, this review will provide the understanding to build the equilibrium in spinning and sintering processes to control the design of micro-channels, and structural properties of inorganic HFMs. This review has great significance to control the new design of membranes via AI programs. This review also explain the inorganic membrane efficiency as algal-bioreactor.

Wastewater treatment by using microalgae: Insights into fate, transport, and associated challenges

The remediation of wastewater with microalgae is a new topic that concentrates on devising a cost-effective and environmentally beneficial method. Multiple microalgae and bacterial consortiums have recently been evaluated to determine if they can purify effluent from various sources. Critical to a system's efficacy is its ability to remove nutrients such as nitrogen (N) and phosphorus (P) and heavy metals such as arsenic (As), lead (Pb), and copper (Cu). This study compared traditional wastewater treatment systems to microalgae-based systems for treating different types of wastewater. The research investigates the potential for microalgae to cleanse wastewater. The research also evaluates wastewater parameters, methods, and scientific techniques for extracting nutrients and heavy metals from polluted water. According to the literature, Microalgae can remove between 98.7% and 100% of nitrogen (N), phosphorous (P), and heavy metals from various effluents. The paper concludes by discussing the difficulties of using microalgae to remediate wastewater. The elimination of nutrients from the effluent is influenced by biomass production, osmotic capacity, temperature, pH, and O2 concentration. Therefore, a "pilot" study is recommended to investigate contaminants.

Artificial intelligence in wastewater treatment: A data-driven analysis of status and trends

Wastewater treatment is a complex process that involves many uncertainties, leading to fluctuations in effluent quality and costs, and environmental risks. Artificial intelligence (AI) can handle complex nonlinear problems and has become a powerful tool for exploring and managing wastewater treatment systems. This study provides a summary of the current status and trends in AI research as applied to wastewater treatment, based on published papers and patents. Our results indicate that, at present, AI is primarily used to evaluate removal of pollutants (conventional, typical, and emerging contaminants), optimize models and process parameters, and control membrane fouling. Future research will likely continue to focus on removal of phosphorus, organic pollutants, and emerging contaminants. Moreover, analyzing microbial community dynamics and achieving multi-objective optimization are promising directions of research. The knowledge map shows that there may be future technological innovation related to predicting water quality under specific conditions, integrating AI with other information technologies and utilizing image-based AI and other algorithms in wastewater treatment. In addition, we briefly review development of artificial neural networks (ANNs) and explore the evolutionary path of AI in wastewater treatment. Our findings provide valuable insights into potential opportunities and challenges for researchers applying AI to wastewater treatment.

Chitin and chitosan derived from crustacean waste valorization streams can support food systems and the UN Sustainable Development Goals

Crustacean waste, consisting of shells and other inedible fractions, represents an underutilized source of chitin. Here, we explore developments in the field of crustacean-waste-derived chitin and chitosan extraction and utilization, evaluating emerging food systems and biotechnological applications associated with this globally abundant waste stream. We consider how improving the efficiency and selectivity of chitin separation from wastes, redesigning its chemical structure to improve biotechnology-derived chitosan, converting it into value-added chemicals, and developing new applications for chitin (such as the fabrication of advanced nanomaterials used in fully biobased electric devices) can contribute towards the United Nations Sustainable Development Goals. Finally, we consider how gaps in the research could be filled and future opportunities could be developed to make optimal use of this important waste stream for food systems and beyond.

Integrated Electro-Ozonation and Fixed-Bed Column for the Simultaneous Removal of Emerging Contaminants and Heavy Metals from Aqueous Solutions

In the current study, an integrated physiochemical method was utilized to remove tonalide (TND) and dimethyl phthalate (DMP) (as emerging contaminants, ECs), and nickel (Ni) and lead (Pb) (as heavy metals), from synthetic wastewater. In the first step of the study, pH, current (mA/cm2), and voltage (V) were set to 7.0, 30, and 9, respectively; then the removal of TND, DMP, Ni, and Pb with an electro-ozonation reactor was optimized using response surface methodology (RSM). At the optimum reaction time (58.1 min), ozone dosage (9.4 mg L−1), initial concentration of ECs (0.98 mg L−1), and initial concentration of heavy metals (28.9 mg L−1), the percentages of TND, DMP, Ni, and Pb removal were 77.0%, 84.5%, 59.2%, and 58.2%, respectively. For the electro-ozonation reactor, the ozone consumption (OC) ranged from 1.1 kg to 3.9 kg (kg O3/kg Ecs), and the specific energy consumption (SEC) was 6.95 (kWh kg−1). After treatment with the optimum electro-ozonation parameters, the synthetic wastewater was transferred to a fixed-bed column, which was filled with a new composite adsorbent (named BBCEC), as the second step of the study. BBCEC improved the efficacy of the removal of TND, DMP, Ni, and Pb to more than 92%.

The Role of Zeolite Structure in Its β-cyclodextrin Modification and Tetracycline Adsorption from Aqueous Solution: Characteristics and Sorption Mechanism

Modification of zeolites with organic compounds is of increasing interest due to their significant potential in removing emerging pollutants from water. In this work, zeolites from fly ash with three different structure types, NaX (faujasite), NaA (Linde A) and NaP1 (gismondine), were modified with β-cyclodextrin (β-CD), and their adsorption efficacy towards tetracycline (TC) antibiotic in aqueous solutions have been studied. To assess the effect of modification on the zeolites, they were subjected to chemical, mineralogical and surface analyses using X-ray diffraction (XRD), thermogravimetry (TG), scanning electron microscope (SEM), N2 adsorption/desorption isotherm, Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). The maximum adsorption capacity for NaX-CD, NaA-CD and NaP1-CD was around 48, 60, and 38 mg/g, respectively. The fastest adsorption rate was observed for NaP1-CD, which achieved adsorption equilibria after 200 min, while for NaX-CD and NaA-CD it was established after around 24 h. The kinetic data were best described by the Elovich model, followed by pseudo-second order, while the Sips and Redlich-Peterson models were the most suitable to describe the adsorption isotherms. Based on the adsorption data as well as FTIR and XPS results, TC adsorption efficacy is strongly related to the amount of CD attached to the mineral, and hydrogen bonding formation probably plays the major role between CDs and adsorbate.

Stabilization of flavin mononucleotide by capturing its "tail" with porous organic polymers for long-term photocatalytic degradation of micropollutants

Flavin mononucleotide (FMN) produces photo-induced reactive oxygen species (ROS), making it a bio-based and sustainable photosensitizer for micropollutant degradation. However, the rapid self-degradation of FMN under light poses challenges in practical applications. We propose for the first time to use porous organic polymer (POP) structures as particles and in situ grown on nanofibrous membranes to capture the ribityl side chain ("tail") of FMN by electrostatic-driven guest-host interaction. By restraining the free bending mode of FMN in POP, its self-degradation is highly inhibited, showing a prolonged half-life (102.7 and 79.7 times to that in solution and in β-cyclodextrin, respectively) without any impact on the ROS production even after 16 h of UVA irradiation. As a proof-of-concept, the photocatalytic degradation efficiency of FMN-POP complexes can be achieved at 58-93% against micropollutants under UVA. The stabilization of FMN by the "tail" capture in the POP allows its photocatalytic degradation function to be continuously online.

Simultaneous capturing of mixed contaminants from wastewater using novel one-pot chitosan functionalized with EDTA and graphene oxide adsorbent

The emergence of inorganic and organic contaminants has raised great concerns owing to their adverse impact on human health and ecological security. Herein, first time one-pot process was applied for chitosan (CS) functionalization using graphene oxide (GO) and ethylenediaminetetraacetic acid (EDTA) for simultaneous capturing of toxic inorganic (lead (Pb²⁺) and cadmium (Cd²⁺)) and organic (ciprofloxacin (CIP) and sildenafil (SDF)) contaminants from wastewater. In this approach, we believe that CS would work as a backbone, GO would capture both inorganic and organic contaminants via electrostatic interactions, while EDTA would make complexation with heavy metals. Various parameters including pH, reaction time, concentration, reusability etc. were evaluated to achieve the best experimental result in monocomponent system. The prepared adsorbent displayed an excellent monolayer adsorption capacity of 351.20 and 264.10 mg g^-1 for Pb²⁺ and Cd²⁺, respectively, while a heterogeneous sorption capacity of 75.40 and 40.90 mg g^-1 for CIP and SDF, respectively. The kinetics data fitted well to Pseudo-second order (PSO) kinetics model for both types of contaminants and gave faster interaction towards metal ions (higher k₂) than organic contaminants. Experimental results showed excellent adsorption efficiencies at environmental levels in the capturing of both inorganic and organic contaminants at the same time from polluted water. The capturing mechanism of both types of contaminants was explained by elemental mapping, EDS, and FT-IR spectra. Overall, easy synthesis, excellent capturing capacity, and reusability imply that the prepared adsorbent has a sufficient potential for the treatment of co-existing toxic contaminants in water.

A comprehensive review of the circulation of microplastics in aquatic ecosystem using scientometric method

Nowadays, the extensive application of microplastics (MPs) has led to the gradual accumulation of toxicity in aquatic environment and caused potential harm to aquatic organisms and human life, which has become a hot issue of worldwide concern. Although MPs show inert or sublethal toxicity in many cases, its long-term existence can still cause harmful ecological effects. However, to our knowledge, there is a lack of comprehensive literature on the current research hotspots, circulation process, and future development trend of MPs in aquatic ecosystem. This study aims to comprehend the current research hotspots and future development trend in the field of the MPs in aquatic ecosystem using scientometric method. And the circulation process of MPs in aquatic ecosystem is also investigated. The results indicate the most of the current publications on MPs in aquatic ecosystems focus on the formation and harmful properties of MPs. The current research hotspots mainly include the causes of the formation of MPs, the extent of contamination, deposition phenomena, and the toxicity and harm caused to aquatic organisms and humans after ingestion. And the future trends in the researches related to MPs mainly include the study of microplastic cycling processes in aquatic and terrestrial ecosystems, as well as the effective collection of microplastics and their conversion into valuable carbon sources. This review has filled in the knowledge gap in the field of MPs research in aquatic ecosystem to some extent and plays a guiding role in the future researches.

Synthesis of new composite based on TiO2 immobilized in glass fibers for photo-catalytic degradation of chlorobenzene in aqueous solutions

In this study photo-catalytic degradation of chlorobenzene from aqueous solutions using CQD decorated Fe-doped TiO₂ immobilized in Glass Fibers (GF) was investigated. Characteristics of the synthesized photo-catalyst were determined by EF-SEM, EDX, BET, XRD, FTIR, and DRS analysis. Additionally, DRS analysis demonstrated adding CQD to the TiO₂-Fe reduced its band gap energy from 2.96 eV to 2.91eV, while that was 3.10 eV for undoped TiO₂. Among that three photo-catalysts, GF/CQD_(4.5 wt%) decorated Fe-TiO₂ composite had performance nearly 100.0%, when pH was 5 and low concentration of chlorobenzene. In addition, GF/CQD_(4.5 wt%) decorated Fe-TiO₂ composite show it could be well applied for five times and with a little reduction on the performance. Also, no detectable Fe found to be released from the composite. Minimum inhibitory concentration (MIC) for E. coli bacteria was 12.2 mg L^-1 of chlorobenzene residual. Our findings show the catalyst was successful for chlorobenzene removal in the wastewater effluent. In conclusion, present hybrid composite could successfully and safely remove chlorobenzene from synthetic aqueous solution.

A Review of the Modeling of Adsorption of Organic and Inorganic Pollutants from Water Using Artificial Neural Networks

The application of artificial neural networks on adsorption modeling has significantly increased during the last decades. These artificial intelligence models have been utilized to correlate and predict kinetics, isotherms, and breakthrough curves of a wide spectrum of adsorbents and adsorbates in the context of water purification. Artificial neural networks allow to overcome some drawbacks of traditional adsorption models especially in terms of providing better predictions at different operating conditions. However, these surrogate models have been applied mainly in adsorption systems with only one pollutant thus indicating the importance of extending their application for the prediction and simulation of adsorption systems with several adsorbates (i.e., multicomponent adsorption). This review analyzes and describes the data modeling of adsorption of organic and inorganic pollutants from water with artificial neural networks. The main developments and contributions on this topic have been discussed considering the results of a detailed search and interpretation of more than 250 papers published on Web of Science ® database. Therefore, a general overview of the training methods, input and output data, and numerical performance of artificial neural networks and related models utilized for adsorption data simulation is provided in this document. Some remarks for the reliable application and implementation of artificial neural networks on the adsorption modeling are also discussed. Overall, the studies on adsorption modeling with artificial neural networks have focused mainly on the analysis of batch processes (87%) in comparison to dynamic systems (13%) like packed bed columns. Multicomponent adsorption has not been extensively analyzed with artificial neural network models where this literature review indicated that 87% of references published on this topic covered adsorption systems with only one adsorbate. Results reported in several studies indicated that this artificial intelligence tool has a significant potential to develop reliable models for multicomponent adsorption systems where antagonistic, synergistic, and noninteraction adsorption behaviors can occur simultaneously. The development of reliable artificial neural networks for the modeling of multicomponent adsorption in batch and dynamic systems is fundamental to improve the process engineering in water treatment and purification.

Progress and challenges of contaminate removal from wastewater using microalgae biomass

The utilization of microalgae in treating wastewater has been an emerging topic focussed on finding an economically sustainable and environmentally friendly approach to treating wastewater. Over the last several years, different types of con microalgae and bacteria consortia have been experimented with to explore their potential in effectively treating wastewater from different sources. The basic features considered while determining efficiency is their capacity to remove nutrients including nitrogen (N) and phosphorus (P) and heavy metals like arsenic (As), lead (Pb), and copper (Cu). This paper reviews the efficiency of microalgae as an approach to treating wastewater from different sources and compares conventional and microalgae-based treatment systems. The paper also discusses the characteristics of wastewater, conventional methods of wastewater treatment that have been used so far, and the technological mechanisms for removing nutrients and heavy metals from contaminated water. Microalgae can successfully eliminate the suspended nutrients and have been reported to successfully remove N, P, and heavy metals by up to 99.6 %, 100 %, and 13%-100 % from different types of wastewater. However, although a microalgae-based wastewater treatment system offers some benefits, it also presents some challenges as outlined in the last section of this paper. Performance in eliminating nutrients from wastewater is affected by different parameters such as temperature, biomass productivity, osmotic ability, pH, O₂ concentration. Therefore, the conducting of pilot-scale studies and exploration of the complexities of contaminants under complex environmental conditions is recommended.

Photo-catalytic degradation of bisphenol-a from aqueous solutions using GF/Fe-TiO2-CQD hybrid composite

In this photocatalytic study, removal of bisphenol-A from aqueous solution was studied using the GF/Fe-TiO2-CQD composite. Due to its health and environmental effects, this compound should be disposed of sources that are mainly industrial wastewater. The phis-chemical properties of the composite were determined by traditional analyzes of EF-SEM, EDX, BET, XRD, FTIR and DRS. In this study, different ratios of CQD in the composite (1.5, 4.5 and 7.5 wt%), pH, and bisphenol-A concentration as variable parameters were investigated. All analyzes, EF-SEM, EDX, BET, XRD, FTIR, show that the GF/Fe-TiO2-CQD composite is well coated on glass fibers (GF) and all the elements in the catalyst are present. On the other hand, DRS analysis showed that CQD reduces the band gap of Fe-TiO2 from 2.96 eV to 2.91 eV, it was 3.10 eV for TiO2. Among different catalysts, GF/Fe-TiO2-CQD4.5wt% has the best performance. The results showed that for GF/Fe-TiO2-CQD4.5wt%, optimum for the process was at pH = 6 in low concentration of bisphenol-A. The first order model for the photocatalytic degradation process were well studied. In addition, GF/Fe-TiO2-CQD4.5wt% showed that it can be used many times with a minimal reduction in performance. As a result, the GF/Fe-TiO2-CQD4.5wt% composite can successfully remove bisphenol-A form in synthetic aqueous solution. However, it is necessary to further studies to applied that for real water source in water and wastewater treatment plants.

Gold(III) recovery from aqueous solutions by raw and modified chitosan: A review

Chitosan, a prestigious versatile biopolymer, has recently received considerable attention as a promising biosorbent for recovering gold ions, mainly Au(III), from aqueous solutions, particularly in modified forms. Confirming the assertion, this paper provides an up-to-date overview of Au(III) recovery from aqueous solutions by raw (unmodified) and modified chitosan. A particular emphasis is placed on the raw chitosan and its synthesis from chitin, characteristics of raw chitosan and their effects on metal sorption, modifications of raw chitosan for Au(III) sorption, and characterization of raw chitosan before and after modifications for Au(III) sorption. Comparisons of the sorption (conditions, percentage, capacity, selectivity, isotherms, thermodynamics, kinetics, and mechanisms), desorption (agents and percentage), and reusable properties between raw and modified chitosan in Au(III) recovery from aqueous solutions are also outlined and discussed. The major challenges and future prospects towards the large-scale applications of modified chitosan in Au(III) recovery from aqueous solutions are also addressed.

Removal of Pharmaceutical Micropollutants with Integrated Biochar and Marine Microalgae

Using microalgae to remove pharmaceuticals and personal care products (PPCPs) micropollutants (MPs) have attracted considerable interest. However, high concentrations of persistent PPCPs can reduce the performance of microalgae in remediating PPCPs. Three persistent PPCPs, namely, carbamazepine (CBZ), sulfamethazine (SMT) and tramadol (TRA), were treated with a combination of Chaetoceros muelleri and biochar in a photobioreactor during this study. Two reactors were run. The first reactor comprised Chaetoceros muelleri, as the control, and the second reactor comprised Chaetoceros muelleri and biochar. The second reactor showed a better performance in removing PPCPs. Through the response surface methodology, 68.9% (0.330 mg L-1) of CBZ, 64.8% (0.311 mg L-1) of SMT and 69.3% (0.332 mg L-1) of TRA were removed at the initial concentrations of MPs (0.48 mg L-1) and contact time of 8.1 days. An artificial neural network was used in optimising elimination efficiency for each MP. The rational mean squared errors and high R2 values showed that the removal of PPCPs was optimised. Moreover, the effects of PPCPs concentration (0-100 mg L-1) on Chaetoceros muelleri were studied. Low PPCP concentrations (<40 mg L-1) increased the amounts of chlorophyll and proteins in the microalgae. However, cell viability, chlorophyll and protein contents dramatically decreased with increasing PPCPs concentrations (>40 mg L-1).

Effective Adsorption of Reactive Black 5 onto Hybrid Hexadecylamine Impregnated Chitosan-Powdered Activated Carbon Beads

In this study, hexadecylamine (HDA) impregnated chitosan-powder activated carbon (Ct-PAC) composite beads were successfully prepared and applied to adsorption of the anionic dye reactive black 5 (RB5) in aqueous solution. The Ct-PAC-HDA beads synthesized with 0.2 g powdered activated carbon (PAC) and 0.04 g HDA showed the highest dye removal efficiency. The prepared beads were characterized using Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). Various adsorption parameters, i.e., adsorbent dosage, pH, and contact time, which affect the adsorption performance, were studied in a series of batch experiments. The obtained adsorption data were found to be better represented by Freundlich (R2 = 0.994) and pseudo-second-order (R2 = 0.994) models. Moreover, it was ascertained that the adsorption of RB5 onto Ct-PAC-HDA beads is pH-dependent, and the maximum Langmuir adsorption capacity (666.97 mg/g) was observed at pH 4. It was also proved that Ct-PAC-HDA beads were regenerable for repeated use in the adsorption process.

Zwitterion composite chitosan-epichlorohydrin/zeolite for adsorption of methylene blue and reactive red 120 dyes

In this research, an attempt to develop zwitterion composite adsorbent is conducted by modifying chitosan (CHS) with a covalent cross-linker (epichlorohydrin, ECH) and an aluminosilicate mineral (zeolite, ZL). The zwitterion composite adsorbent of chitosan-epichlorohydrin/zeolite (CHS-ECH/ZL) is performed multifunctional tasks by removing two structurally different cationic (methylene blue dye, MB), and anionic (reactive red 120 dye, RR120) dyes from aqueous solutions. The surface property, crystallinity, morphology, functionality, and charge of the CHS-ECH/ZL are analyzed using BET, XRD, SEM, FTIR, and pH_pzc, analyses, respectively. The influence of pertinent parameters namely CHS-ECH/ZL dosage (0.02-0.5 g), solution pH (4-10), temperature (303-323K), initial dye concentration (30-400 mg/L), and contact time (0-600 min) on the MB and RR120 removal are tested. The research findings revealed that the adsorption isotherm at equilibrium well explained in according to the Freundlich isotherm model, and the recorded adsorption capacities of CHS-ECH/ZL are 156.1 and 284.2 mg/g for MB and RR120 respectively at 30 °C. The mechanism of MB and RR120 adsorption onto the CHS-ECH/ZL indicates various types of interactions namely, electrostatic interaction, hydrogen bonding, and Yoshida H-bonding in addition to n-π interaction. Overall, this research introduces CHS-ECH/ZL composite as an eco-friendly zwitterion adsorbent with good applicability towards the two structurally different cationic and anionic dyes from aqueous environment.

Chitosan Modified Zeolite Molecular Sieve Particles as a Filter for Ammonium Nitrogen Removal from Water

Drinking water containing a high amount of ammonium-nitrogen (NH₄⁺-N) is not effectively removed by conventional treatment processes and can cause eutrophication. In this research, a composite adsorbent based on chitosan crosslink with zeolite molecular sieve (CTS-ZMS) was prepared for NH₄⁺-N removal through dynamic adsorption filter experiments. Effect of bed depth (30, 50 and 70 cm), flow rate (32, 49 and 65 mL/min), initial pH value (4.5, 6.5 and 8.5) and influent NH₄⁺-N concentration (3, 5 and 7 mg/L) was examined by using a filter column packed with CTS-ZMS particles. The Thomas model was applied to study the breakthrough curves and adsorption capacity. The optimal process parameters of the aforementioned factors were obtained at bed depth of 70 cm, flow rate of 32 mL/min, pH of 6.5 and initial NH₄⁺-N concentration of 7 mg/L. Scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and Fourier Transform Infrared Spectroscopy (FTIR) were investigated to analyze the structure and morphology of the CTS-ZMS adsorbents before and after 3 months running. The EDS and FTIR results showed Na⁺ and the active functional groups of -OH, -NH₂ and -COO⁻ on CTS-ZMS adsorbent particles reacted with ammonium nitrogen. The results of this study supported the use of CTS-ZMS to improve drinking water filtration processes by increasing ammonium nitrogen reductions.