Degradation of 2-chlorophenol by Fenton and photo-Fenton processes

The photodegradation of a specific organic pollutant using the Fenton and the photo-Fenton processes has been examined in aqueous solution. The applications of the Fenton process and the photo-Fenton process to the degradation of 2-chlorophenol (2-CP) were investigated. The dependence on the following experimental conditions had been evaluated: initial pH (1.0–9.0), hydrogen peroxide (0.67–2 mM), ferrous ions (0.1–2 mM), initial concentration of 2-CP (0.1–2 mM). The optimal experimental conditions were 1 mM H₂O₂, 1 mM ferrous ion and pH 3.0. Under the optimal conditions, the degradation efficiency of 2-CP in the photo-Fenton process was enhanced 4% more than that of the Fenton process. Experimental results about the degradation of 2-CP show that UV irradiation improves the degradation efficiency of the Fenton process. The major intermediate formed during the degradation of 2-CP was p-benzoquinone.     

Fenton氧化降解焦化废水的影响特性及动力学模型

为研究Fenton试剂氧化降解焦化废水的影响特性及动力学机理,采用小试烧杯实验考察初始COD、H2O2投加量、Fe2+投加量和反应温度等因素对处理效果的影响。结果表明,原水COD为260 mg/L、H2O2投加量为666mg/L、Fe2+投加量为200 mg/L、温度为298 K时,COD去除率达到89.53%;反应初始阶段COD氧化降解的表观反应动力学模型与实验数据得到较好的拟合,因此该动力学模型能较好地预测Fenton试剂对焦化废水的氧化降解情况;反应总级数为2.001 7,其中H2O2的反应分级数(0.568 5)高于Fe2+的反应分级数(0.494 0),说明Fenton氧化降解COD过程中H2O2浓度的影响比Fe2+的大;较低的反应活化能说明反应较易进行。     

Modeling and optimization of cross-flow ultrafiltration using hybrid neural network-genetic algorithm approach

Precise modeling flux decline under various operating parameters in cross-flow ultrafiltration (UF) of oily wastewaters and afterward, employing an appropriate optimization algorithm in order to optimize operating parameters involved in the process model result in attaining desired permeate flux, is of fundamental great interest from an economical and technical point of view. Accordingly, this current research proposed a hybrid process modeling and optimization based on computational intelligence paradigms where the combination of artificial neural network (ANN) and genetic algorithm (GA) meets the challenge of specified-objective based on two steps: first the development of bio-inspired approach based on ANN, trained, validated and tested successfully with experimental data collected during the polyacrylonitrile (PAN) UF process to treat the oily wastewater of Tehran refinery in a laboratory scale in which the model received feed temperature (T), feed pH, trans-membrane pressure (TMP), cross-flow velocity (CFV), and filtration time as inputs; and gave permeate flux as an output. Subsequently, the 5-dimensional input space of the ANN model portraying process input variables was optimized by applying GA, with a view to realizing maximum or minimum process output variable. The results obtained validate the estimates of the ANN–GA technique with a good accuracy. Finally, the relative importance of the controllable operation factors on flux decline is determined by applying the various correlation statistic techniques. According to the result of the sensitivity analysis based on the correlation coefficient, the filtration time was the most significant one, followed by T, CFV, feed pH and TMP.     

Cost analysis for the degradation of highly concentrated textile dye wastewater with chemical oxidation H2O2/UV and biological treatment

The efficiency and cost‐effectiveness of H₂O₂/UV for the complete decolorization and mineralization of wastewater containing high concentrations of the textile dye Reactive Black 5 was examined. Oxidation until decolorization removed 200–300 mg g^?1 of the dissolved organic carbon (DOC). The specific energy consumption was dependent on the initial dye concentration: the higher concentration required a lower specific energy input on a weight basis (160 W h g^?1 RB5 for 2.1 g L^?1 versus 354 W h g^?1 RB5 for 0.5 g L^?1). Biodegradable compounds were formed, so that DOC removal could be increased by 30% in a following biological stage. However, in order to attain 800 mg g^?1 overall mineralization, 500 mg g^?1 of the DOC had to be oxidized in the H₂O₂/UV stage. A cost analysis showed that although the capital costs are much less for a H₂O₂/UV stage compared to ozonation, the operating costs are almost double those of ozonation. Thus, while H₂O₂/UV can compete with ozonation when the treatment goal only requires decolorization, ozonation is more cost‐effective in this case when mineralization is desired. Copyright © 2006 Society of Chemical Industry     

Graphene/Fe3O4 nanocomposite: Interplay between photo-Fenton type reaction,and carbon purity for the removal of methyl orange

Graphene/Fe₃O₄ nanocomposites obtained via soft chemical methodis have been characterized for their crystallinity, morphology, microstructure,optical bandgap, vibrational modes and magnetic properties. Graphenesheets decorated with magnetite nanoparticles are employed to investigatetheir photocatalytic response against methyl orange. The study revealsthat the conducting nature of graphene, engineered bandgap and photoFenton like reaction synergistically govern the efficient photocatalyticactivity of nanocomposite. Interestingly, it is observed that methylorange can be completely removed i.e., upto 99.24% by graphene/Fe₃O₄ nanocomposite, whereas the removal efficiency is 43% for Fe₃O₄ nanoparticles, alone. The presence of graphene endows the delay in chargecarriers' recombination whereas, photo Fenton like reaction stimulatesthe generation of reactive oxygen species. This ultimately leads to thehighly enhanced photocatalytic activity and complete removal of methylorange. The magnetically separable photocatalyst, presented in thiswork, offers great prospects for fast and economical decontamination of dye polluted water.     

Modeling and performance monitoring of multivariate multimodal processes

A multimodal modeling and monitoring approach based on maximum likelihood principal component analysis and a component‐wise identification of operating modes are presented. Analyzing each principal component individually allows separating components describing the variation within the individual modes from those capturing variation which the modes commonly share. On the basis of the former set, a Gaussian mixture model produces a statistical fingerprint that describes the production modes. The advantage of the component‐wise analysis is a simple identification of the mixture model parameters, which does not rely on the computationally cumbersome expectation maximization. The proposed method diagnoses abnormal process conditions by defining statistics relating to the components describing (1) between‐cluster variation, (2) within cluster variation, and (3) model residuals. The article demonstrates the benefits of this approach over existing work by an application to a continuous stirred tank reactor (CSTR) simulator and the analysis of recorded data from a furnace and a chemical reaction process. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1557–1569, 2013     

The mechanism and application of the electro‐Fenton process for azo dye Acid Red 14 degradation using an activated carbon fibre felt cathode

BACKGROUND: The discharge of azo dyes into the environment poses concerns due to their limited biodegradability. The electro‐Fenton process (EF) is a good method to effectively degrade these dyes. The aim of this work was to study the mechanism and the feasibility of the EF reaction using an activated carbon fibre (ACF) cathode. In this study, two methods were used to measure the reactive species generated in anodic oxidation (AO), anodic oxidation with electrogenerated H₂O₂ (AO‐H₂O₂) and the EF process. Acid Red 14 (AR14) was chosen as a model pollutant. The effects of the operational parameters, pH and initial concentrations were investigated. A short‐term biodegradability test was also carried out to evaluate the EF process from a biological point of view. RESULTS: After 2 h EF reaction 118.7 µmol L^?1?OH were produced, which was much higher than that of the AO‐H₂O₂ (63.2 µmol L^?1) process. H₂O₂ is largely generated and Fe³⁺ efficiently reduced on the high surface area of the ACF cathode. The EF process provides more effective degradation of AR14 than the conventional Fenton process, and its current efficiency is significantly affected by the initial pH and the initial AR14 concentration. Following EF treatment, the biodegradability of AR14 is significantly increased. CONCLUSION: The higher formation of ^?OH in the EF process suggests it is an effective method for pollutant removal. This process also leads to increased biodegradability, which is expected to facilitate subsequent biological treatment. Copyright © 2010 Society of Chemical Industry     

Probabilistic monitoring of chemical processes using adaptively weighted factor analysis and its application

As a probabilistic statistical method, factor analysis (FA) has recently been introduced into process monitoring for the probabilistic interpretation and performance enhancement of noisy processes. Generally, FA methods employ the first several factors that are regarded as the dominant motivation of the process for process monitoring; however, fault information has no definite mapping relationship to a certain factor, and useful information might be suppressed by useless factors or submerged under retained factors, leading to poor monitoring performance. Weighted FA (WFA) for process monitoring is proposed to solve the problem of useful information being submerged and to improve the monitoring performance of the GT² statistic. The main idea of WFA is firstly building a conventional FA model and then using the change rate of the GT² statistics (RGT²) to evaluate the importance of each factor. The important factors tend to have larger RGT² values, and the larger weighting values are then adaptively assigned to these factors to highlight useful fault information. Case studies on both a numerical process and the Tennessee Eastman process demonstrate the effectiveness of the WFA method. Monitoring results indicate that the performance of the GT² statistic is improved significantly compared with the conventional FA method.     

Biodegradable iron chelate for H2S abatement: Modeling and optimization using artificial intelligence strategies

A batch reactor process for the abatement of a common pollutant, namely, H₂S using Fe³⁺-malic acid chelate (Fe³⁺-MA) catalyst has been developed. Further, process modeling and optimization was conducted in the three stages with a view to maximize the H₂S conversion: (i) sensitivity analysis of process inputs was performed to select the most influential process operating variables and parameters, (ii) an artificial neural network (ANN)-based data-driven process model was developed using the influential process variables and parameters as model inputs, and H₂S conversion (%) as the model output, and (iii) the input space of the ANN model was optimized using the artificial immune systems (AIS) formalism. The AIS is a recently proposed stochastic nonlinear search and optimization method based on the human biological immune system and has been introduced in this study for chemical process optimization. The AIS-based optimum process conditions have been compared with those obtained using the genetic algorithms (GA) formalism. The AIS-optimized process conditions leading to high (≈97%) H₂S conversion, were tested experimentally and the results obtained thereby show an excellent match with the AIS-maximized H₂S conversion. It was also observed that the AIS required lesser number of generations and function evaluations to reach the convergence when compared with the GA.     

Simultaneous degradation of 2,4,6-trinitrophenyl-N-methylnitramine (Tetryl) and hexahydro-1,3,5-trinitro-1,3,5 triazine (RDX) in polluted wastewater using some advanced oxidation processes

Here we report the study on the utilization of several advanced oxidation processes such as electro-oxidation and Fenton process in simultaneous treatment of two nitramine explosives: 2,4,6-trinitrophenyl-N-metylnitramine (Tetryl) and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). The preliminary tests indicated that the electrolytic method using a TiO₂/IrO₂/RuO₂-coated electrode could rapidly degrade Tetryl but not RDX. While the addition of certain amount of H₂O₂ induced an increase of Tetryl degradation yield but had insignificant effect on RDX decomposition, the use of Fenton's reagent showed an enhanced efficiency in degradation of both nitramines. It can be concluded that among tested processes, Fenton process is the most effective for treatment of nitramine-containing wastewaters.     

Combination of photocatalytic and photoelectro-Fenton/citrate processes for dye degradation using immobilized N-doped TiO2 nanoparticles and a cathode with carbon nanotubes: Central composite design optimization

In this report, commercial TiO₂ nanoparticles were doped with nitrogen by a manual grinding method using urea. The prepared catalyst was characterized by X-ray diffraction (XRD), diffuse reflectance spectra (DRS), and transmission electron microscopy (TEM). N-doped TiO₂ was immobilized on ceramic plates by methyl tri-methoxy silane. Next, multi-walled carbon nanotubes (CNTs) were stabilized on carbon paper to fabricate the cathode. Scanning electron microscopy (SEM) was employed to confirm stabilization of the CNTs. The prepared cathode and immobilized catalyst were utilized for the degradation of C.I. Direct Red 23 (DR23) by the photoelectro-Fenton (PEF) process in the presence of citrate (Cit) combined with a photocatalytic process. The coupled PEF/Cit/N-TiO₂ process could be performed under visible light, not only due to the formation of iron–citrate complexes, but also because of the incorporation of nitrogen to the crystalline structure of TiO₂ and the generation of TiO₂ complexes with electrogenerated H₂O₂. Results demonstrated that the degradation efficiency of DR23 (20 mg/L) using the identical operational conditions, followed a decreasing order of: PEF/Cit/N-TiO₂ > PEF/Cit > PEF > EF > N-TiO₂. Eventually, a model was developed by the central composite design (CCD) method, describing the degradation efficiency as a function of the operational parameters.     

Slaughterhouse wastewater treatment by combined anaerobic baffled reactor and UV/H2O2 processes

Combined processes of biological anaerobic baffled reactor (ABR) and UV/H₂O₂ at a laboratory scale were studied to treat a synthetic slaughterhouse wastewater. In this study, the total organic carbon (TOC) loadings of 0.2-1.1 g/(L day) were used. The results revealed that combined processes had a higher efficiency to treat the synthetic slaughterhouse wastewater. Up to 95% TOC removal was obtained for an influent concentration of 973.3 mgTOC/L at the hydraulic retention time (HRT) of 3.8 days in the ABR and 3.6 h in the UV photoreactor. Meanwhile, up to 97.7% and 96.6% removal of chemical oxygen demand (COD) and 5-day carbonaceous biochemical oxygen demand (CBOD₅) were observed in the ABR for the same influent concentration, respectively. Comparatively, for an influent concentration of 157.6 mgTOC/L, the UV/H₂O₂ process alone with the TOC loading of 0.06-1.9 g/(L h) was also studied, in which, up to 64.3%, 83.7%, and 84.3% of TOC, COD, and CBOD₅ removal were observed, respectively, at the HRT of 2.5 h with hydrogen peroxide (H₂O₂) concentration of 529 mg/L. It was found that individual ABR and UV/H₂O₂ processes enhanced the biodegradability of the treated effluent by an increased CBOD₅/COD ratio of 0.4 to 0.6. An optimum H₂O₂ dosage of 3.5 (mgH₂O₂)/(mgTOC_in h) was also found for the UV/H₂O₂ process.