Enhanced coagulation and adsorption were investigated in separate and combined processes to alleviate problems created by high levels of NOM (15 mg L-1) and ammonia (2.5 mg L-1NH4-N) in dam water. Raw water acidification to pH 6.2 with optimised enhanced coagulation in jar tests achieved effective (68%) DOC reduction and satisfactory residual turbidity, aluminium, and colour, however removed only 5% ammonia. Adsorption on the nano-adsorbent (termed ACZ) led to 45% DOC reduction and excellent 58% ammonia removal in 30 min. Concurrent enhanced coagulation and complementary adsorption using only 80 mg L-1 alum and 150 mg L-1 ACZ doses showed high performance with 76% ammonia, 90% DOC, and 95% trihalomethanes formation potential (THMFP) reduction in 20 min time. Concurrent treatment can be simply implemented utilising readily available rapid mixers and flocculators, and operated on demand. Preadsorption and consecutive enhanced coagulation using the same alum and ACZ doses resulted in slightly better DOC but reduced (61%) ammonia removal. The results showed that concurrent treatment could safely resolve a challenging operational problem. ACZ combines the distinct advantages of zeolite and activated carbon in a single product, and may find additional uses in removing taste and odour, heavy metals, and synthetic organic matter from ground and surface waters. (C) 2019 Elsevier B.V. All rights reserved.

Activated carbons are the most widely used adsorbents; however, producing high‐performance mesoporous activated carbons with simple technology still remains a challenge. In this research, waste macadamia nut shell (MNS) was explored as precursor for preparing mesoporous activated carbons by carbon dioxide activation. The material characteristics of MNS‐based activated carbon (MAC) were thoroughly examined in comparison with a premium‐grade commercial activated carbon (CAC). MAC and CAC had specific surface areas of 830 and 1,299 m2 g−1, respectively. Although CAC had a predominantly microporous structure, about 74% of the pore volume of MAC is composed of mesopores. Adsorption performances were evaluated in batch experiments using methylene blue model pollutant and demonstrated 135 and 181 mg g−1 saturation capacities for MAC and CAC, respectively. Non‐linear regression found that the fractal‐like pseudo first‐order model accurately described sorption kinetics, and intraparticle diffusion was the rate‐limiting step. Among 6 established isotherm models, the Liu equilibrium model showed the best statistics. Thermodynamic analysis verified that the process was favourable and involved physisorption. These results show that valuable mesoporous activated carbons can be prepared from the biowaste MNS with simple production technology to suit environmental and industrial applications.

Novel activated carbon-zeolite composite adsorbent was prepared from macadamia shell bio-waste and synthetic zeolite X using hydrothermal treatment. Characterisation studies revealed mainly mesoporous structure with 418 m(2).g(-1) BET surface area with faujasite clusters on the carbon carrier. Sorption capacity for methylene blue model pollutant increased from 85 to 97 mg.g(-1 )with the temperature increase from 25 to 45 degrees C, and improved with increasing pH. Nonlinear regression analyses found accurate fit to the pseudo-first-order kinetics model and intra-particle diffusion rate controlling mechanism. Excellent fits to the Jovanovic isotherm model indicated monolayer coverage on chiefly homotattic surfaces with variable potential. The thermodynamic analysis confirmed spontaneous and endothermic physisorption process. The spent adsorbent was regenerated with 20% capacity loss over five reuse cycles. Although the adsorbent was developed for ammonia, heavy metal and organic matter removal from water sources, the results also indicate good performance in cationic dye removal from wastewaters. (C) 2018 The Chemical Industry and Engineering Society of China. and Chemical Industry Press. All rights reserved.

Nanosorbents have been increasingly used for targeted contaminant removal; however, handling and separation of spent sorbents from treated water remains a challenge. To address these drawbacks, a hybrid magnetic nanosorbent was prepared from waste macadamia nut shell and magnetite nano particles. The novel nanosorbent had primarily meso- and macroporous structure with 70 m(2) g(-1) specific surface area. Batch sorption tests using methylene blue model pollutant found sorption capacities increasing from 33 to 42 mg g(-1) with temperature in the 25-45 degrees C range. Nonlinear regression analyses found that process kinetics was accurately described by a fractal-like pseudo first order model. The isotherms showed excellent fits to the Langmuir model and implied monolayer adsorption mechanism. The thermodynamic parameters confirmed that the process was spontaneous, endothermic, and involved physisorption. The point of zero charge was 7.4, which is advantageous in the removal of anionic aquatic pollutants. The ferrimagnetic sorbent had 48 emu g(-1) saturation and 0.65 emu g(-1) remanence that allowed easy handling and rapid separation by magnetic field. Spent sorbents were effectively regenerated by acidic wash for subsequent reuse over four cycles. The intrinsic characteristics of the magnetite/carbon nanosorbent befit tailored water and wastewater treatment applications. (C) 2017 Elsevier Ltd. All rights reserved.

Membrane backflush with air or permeate is commonly employed to reduce fouling in immersed micro– and ultrafiltration (MF/UF). Membrane plants traditionally rely on simple timer control automation to initiate periodic backflushes for membrane cleaning. In this study, a closed–loop (feedback) type backflush controller was evaluated experimentally with a bench–scale hollow fibre immersed MF/UF membrane – flocculation hybrid system.The controller showed an unexpected behaviour at low fouling rates, which was manifested in significantly varying filtration periods. The investigation identified the cause in the use of a constant stabilisation lag parameter.The role of this control parameter was to determine the reversible component of fouling in real–time, which is a difficult problem in transient flow conditions that characterise the start of filtration periods. The resulting error became significant at low fouling rates and impaired effective control.Based on this insight, we propose alternative, more robust control parameters, which can provide improved backwash control solutions for MF/UF membrane applications.

The term “photocatalysis” refers to a chemical transformation or the acceleration of a chemical reaction in the presence of light and a photocatalyst (Kisch 1989). The various types of photocatalysts listed in the literature can be classified into three groups (Sakata 1989): 1. Dye molecules used as homogeneous photocatalysts; 2. Semiconductors used as heterogeneous photocatalysts (HP); and 3. A combination of dye and semiconductor species known as dye sensitised photocatalysts.

In this study, nitrogen doped and nitrogen/silver co-doped TiO2 photocatalsysts were fabricated using a sol-gel method at room temperature. The obtained gels were neutralized, washed with pure water, and calcined at 400 degrees C for 4 h. The photocatalysts were characterized by scanning and transmission electron microscopy, X-ray diffracticin, diffuse reflectance spectroscopy, X-ray photoelectron spectroscopy, and BET specific surface area. The results showed that spherical particles with anatase structure were produced after annealing at 400 degrees C. N is (400 eV) and Ag 3d (367.3 eV) states indicated that nitrogen doping and silver co-doping were in the form of NO bonds and AgO, respectively. The photocatalytic activity of photocatalysts was investigated using a batch reactor system exposed to artificial solar irradiation. Both nitrogen and silver/nitrogen co-doped materials were effective in the photocatalytic degradation of hexamethyl pararosaniline chloride. (C) 2013 Elsevier Ltd. All rights reserved.

In this study, Degussa P25 TiO2 was partially dissolved in a mixture of hydrogen peroxide and sodium hydroxide at high pH. The fabrication of nanofibres proceeded by the hydrothermal treatment of the solution at 80 degrees C. This was followed by acid wash in HCl at pH 2 for 60 min, which resulted in the formation of hydrogen-titanate nanofibres. The nanofibres were annealed at 550 degrees C for 6 h to produce crystalline anatase nanofibres. The nanofibres were characterised for physico-chemical modifications and tested for the adsorption and photocatalytic degradation of methylene blue as a model water pollutant. An average specific surface area of 31.54 m(2)/g, average pore volume of 0.10 cm(3)/g and average pore size of 50 angstrom were recorded. The nanofibres were effective adsorbents of the model pollutant and adsorbents and good photocatalysts under simulated solar light illumination. No reduction in photocatalytic activity was observed over three complete treatment cycles, and the effective separation of nanofibres was achieved by gravity settling resulting in low residual solution turbidity. (c) 2013 Elsevier Ltd. All rights reserved.

Potassium-rich titanate nanofibers were produced by digesting TiO2 in concentrated KOH solutions under hydrothermal conditions. The nanofibers were characterized by scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, and thermogravimetric analysis. A hexatitanate structure was assigned, in contrast to the trititanate structure usually resulting from NaOH treatment of TiO2. The potassium cations could be exchanged with others, such as sodium, hydrogen, and ammonium. The potassium-rich hexatitanate was found to be photocatalytic in its as-synthesized condition. The thermal stability of the fibers during calcination was followed in situ using X-ray diffraction and was found to be strongly dependent on the chemical composition. The potassium-rich titanate converted to anatase at only 480 degrees C, whereas the hydrogen- and ammonium-rich materials had to be heated to over 600 degrees C before conversion took place. Conversion was notably slowest in the ammonium-rich material. Surprisingly, the sodium-rich hexatitanate did not form anatase at temperatures up to 800 degrees C and instead recrystallized.

In this study we present the effects of non-metal (nitrogen) and metal/non-metal (silver/nitrogen) dopants on titanium dioxide (TiO2) in synthesising visible-light reactive photocatalysts. Nanopowders of TiO2-N and TiO2-N–Ag were synthesised using a simple procedure at room temperature. For nitrogen doping, a dispersion of Degussa P-25 was treated with ammonium hydroxide. The obtained modified catalyst was further treated with silver nitrate powder to facilitate silver-nitrogen co-doping. The produced catalysts were characterised using X-ray diffraction, X-ray photoelectron spectroscopy, and specific surface area measurements. Scanning electron microscopy/energy dispersive X-ray and transmission electron microscopy were adapted to detect changes in the morphology and in the chemical composition of synthesised catalysts. The results show that both the morphology and appearance of catalysts were modified to yield nanopowders of yellowish color and relatively high specific surface area. Methylene blue (MB) dye was used as a model aquatic contaminant in 23mg/L concentration to study the performance of these novel photocatalysts in an aerobic mixed batch reactor system under white light irradiation. Both nitrogen and nitrogen-silver co-doping lead to visible light sensitivity and the new catalysts showed remarkable activities in the decolorisation of MB.

Photocatalysis over metal oxide semiconductors is an effective way to reduce or eliminate the impact of aquatic and airborne pollutants. Titania (TiO2) photocatalyst is able to degrade many toxic and recalcitrant compounds under UV light illumination. Since UV light accounts for only about 5% of the solar energy, the more significant visible light fraction (45%) remains unused. Here we report the synthesis of non-metal (nitrogen) and metal/non-metal (silver/nitrogen) co-doped photocatalysts that are reactive both in the UV and visible range. Nitrogen doped and nitrogen/silver co-doped TiO2 nanoparticles were fabricated using a sol-gel production method at a relatively low temperature. The obtained gels were neutralised, washed with pure water, dried in oven, and calcined at 400 °C for 4 hours. Morphology changes were monitored using a scanning electron microscope. The photocatalysts were characterised by X-ray diffraction, X-ray photoelectron spectroscopy, and BET specific surface area. The results showed that spherical particles of anatase structure were produced after annealing at 400°C. The photocatalytic activity of these novel catalysts was investigated using a batch reactor system exposed to artificial solar irradiation. Both nitrogen and silver/nitrogen co-doped materials were effective in the photocatalytic degradation of hexamethyl pararosaniline chloride.

Mesoporous Na-titanate microspheres were fabricated by a simple low temperature hydrothermal synthesis. Microspheres were obtained after treating TiO2 (Degussa P-25) with a mixture of sodium hydroxide (NaOH) and hydrogen peroxide (H2O2) at 25°C and 80°C. The as-prepared powders were characterised by X-ray diffraction, N2 adsorption–desorption measurements and scanning electron microscope/energy dispersive X-ray spectroscopy. The as-prepared microspheres were calcined at 550°C to investigate the effect of calcination on morphology and characteristics. Microspheres were tested for the adsorption and photodecomposition of methylene blue (MB) under ultraviolet light. The results revealed that microspheres with average diameter of 700nm were formed by self-assembly of tiny TiO2 nanoparticles during the reaction at 25°C, whereas spherical aggregation of nanofibres was detected in powders produced at 80°C. Calcination of samples had low impact on morphology, adsorption and photocatalytic degradation of MB. These novel materials are effective adsorbents of MB, and also capable of its photodecolorisation.

In this study, different processes such as flocculation with ferric chloride (FeCl(3)) and deep bed filtration (sand filtration and dual media filtration) as a pre-treatment were used for seawater desalination. The performance of these pre-treatments was determined in terms of silt density index (SDI) and modified fouling index by using microfilter (MF-MFI), ultrafilter (UF-MFI), and nanofilter (NF-MFI) membrane. MFI and SDI indicated that deep bed filtration with in-line flocculation was better pre-treatment than flocculation alone as colloidal particles are removed after this pretreatment. UF-MFI and NF-MFI indicated that these pretreatment cannot remove dissolved organic matter as the fouling reduction was smaller. Detailed molecular weight distribution (MWD) of seawater organic matter was examined after different pretreatments. MWD of the initial seawater mainly ranged from 1510 Da to 130 Da. Deep bed filtration with in-line flocculation removed relatively large molecular weight of organic matter (1510-1180 Da), while the small molecular weights (less than 530 Da) were not removed.

Hybrid membrane filtration processes involve complex physical, chemical and biological phenomena, thus their mechanistic modelling is challenging. The chief advantages of statistical and artificial neural networks (ANN) models (data-driven models) are that they do not require assumptions and simplifications to establish relationships from data. This paper investigates the characteristics and performance of several data-driven methods to model a hybrid membrane system. The focus is on the application of regression analysis and artificial intelligence based methods to a steady-state system. Among empirically based approaches, ANN neural networks methods were found to be very useful to predict permeate quality and membrane fouling. In the past multivariate nonlinear regression had barely been investigated for process modelling in water and waste water treatment. In this study polynomial multivariate nonlinear regression showed a superior performance. Multivariate parametric nonlinear models could match the performance of the nonparametric ANN models in the empirical modelling of complex systems, especially when combined with advanced optimization methods. This paper gives the methodology of how one could optimize a membrane hybrid system using ANN, validating it with one set of data. The same procedure/methodology can be applied to similar systems.