Treatment of phenol formaldehyde production wastewater by electrooxidation-electrofenton successive processes

ABSTRACT

Treatments of phenol formaldehyde producing wastewater (PFPW) by electrooxidation (EO) and electro-Fenton (EF) successive processes were carried out in a batch electrolytic reactor using graphite (Gr) and stainless steel (Ss) electrodes. After the completion of the EO process, the wastewater was further treated with EF process. The influence of operating variables such as current density, operating time, initial pH_i and H₂O₂ concentration was evaluated for removals of phenol, TOC and COD in PFPW. Gr/Gr, Gr/Ss or Ss/Ss and Ss/Gr electrode pair were used as anode and cathode. The best removal efficiency in the EO process was obtained with Gr/Gr (93%) as compared to Gr/Ss (82%), Ss/Ss (63%) and Ss/Gr (55%). The removal efficiencies for the EO process using Gr-Gr electrode pair were obtained as 93% for phenol, 61% for COD and 44% for TOC at initial pH_i 7,5 g/L of NaCl, 50 mA/cm² and 5 h. In the EF process, the removal efficiencies at pH_i 3,5 mA/cm² and 30 mM H₂O₂ and 45 min were 100% for phenol, 76% for COD and 59% for TOC. This study provided that the successive processes are an effective method for the removal of phenolic compounds from the wastewater.     

Toxicity and Biodegradability Behavior of Xenobiotic Chemicals Before and After Ozonation: A Case Study with Commercial Textile Tannins

Ozonation of a natural tannin (NT; COD_o?=?1195 mg/L; TOC_o?=?342 mg/L; BOD_5,o?=?86 mg/L) and a synthetic tannin ST; COD_o?=?465 mg/L; TOC_o?=?55 mg/L; BOD_5,o?=?6 mg/L) being frequently applied in the polyamide dyeing process was investigated. Synthetic wastewater samples containing these tannins individually were prepared and subjected to ozonation at varying ozone doses (625– 1250 mgO₃/L wastewater), at pH?=?3.5 (the application pH of tannins) and pH?=?7.0 at an ozone dose of 1125 mgO₃/L wastewater. The collective environmental parameters COD, TOC, BOD₅, UV₂₅₄ and UV₂₈₀ (UV absorbance at 254 nm and 280 nm, representing aromatic and unsaturated moieties, respectively) were followed during ozonation. Changes in the biodegradability of the tannins were evaluated in terms of BOD₅ measurements conducted before and after ozonation. In addition, activated sludge inhibition tests employing heterotrophic biomass were run to elucidate the inhibitory effect of raw and ozonated textile tannins towards activated sludge biomass. Partial oxidation (45% COD removal at an ozone dose of 750 mg O₃/L wastewater and pH?=?3.5) of ST was sufficient to achieve elimination of its inhibitory effect towards heterotrophic biomass and acceptable biodegradability improvement, whereas the inhibitory effect and biodegradability of NT could not be reduced via ozonation under the same reaction conditions.     

Enhanced multiclass SVM with thresholding fusion for speech-based emotion classification

As an essential approach to understanding human interactions, emotion classification is a vital component of behavioral studies as well as being important in the design of context-aware systems. Recent studies have shown that speech contains rich information about emotion, and numerous speech-based emotion classification methods have been proposed. However, the classification performance is still short of what is desired for the algorithms to be used in real systems. We present an emotion classification system using several one-against-all support vector machines with a thresholding fusion mechanism to combine the individual outputs, which provides the functionality to effectively increase the emotion classification accuracy at the expense of rejecting some samples as unclassified. Results show that the proposed system outperforms three state-of-the-art methods and that the thresholding fusion mechanism can effectively improve the emotion classification, which is important for applications that require very high accuracy but do not require that all samples be classified. We evaluate the system performance for several challenging scenarios including speaker-independent tests, tests on noisy speech signals, and tests using non-professional acted recordings, in order to demonstrate the performance of the system and the effectiveness of the thresholding fusion mechanism in real scenarios.     

Effects of Mn and Gd Co-substituted into ZnO on Structural and Magnetic Properties

We have worked on the structural and magnetic properties of Zn_0.99?xMn_0.01Gd _x O _δ (for x = 0.02, 0.03, and 0.04) compounds prepared by using a sol–gel method. The x-ray diffraction, scanning electron microscopy, and energy dispersive x-ray spectroscopy were used to understand the structural properties of the samples. We observed that co-substitution of Mn (1 %) and Gd (2–4 %) into the ZnO does not change the hexagonal structure. Scanning electron microscope (SEM) images show us that the grain size decreases with the increasing amount of the Gd into the ZnO matrix. The magnetic properties of the samples have been investigated by using magnetic hysteresis and DC susceptibility measurements. The ZMG1 sample shows a weak ferromagnetic behavior at room temperature, whereas the ZMG2 and ZMG3 samples exhibit a paramagnetic nature. Furthermore, it is also found that the magnetizations of the samples decrease with increasing Gd content in the ZnMnO system due to the enhancing interaction between Gd ³⁺ ions. We summarize that the co-substitution of Mn and Gd into the ZnO generates a room-temperature ferromagnetism, but it still needs more work to obtain strong and high coercivity magnetic loops for applications.     

Synthesis and application of phenylcarbamodithioate compound for steel protection

Phenyldithiocarbamate compound has been synthesized and studied as corrosion inhibitor for steel. Dithiocarbamate (DTC) compounds with linear alkyl groups are good inhibitors, but their stability is quite low in acidic solutions. It should be noted that long-term stability is important for practical applications, in order to avoid excess use of chemicals. So, we have synthesized phenyl substituted DTC which offers strong inhibition efficiency and extra stability. This new inhibitor is chemically adsorbed on steel through its DTC group, while the aromatic ring provides extra stability and long-term efficiency. For the assessment of corrosion kinetics, we have utilized potentiodynamic and ac impedance studies; also solution assay analysis was realized with atomic absorption spectroscopy. It was revealed that inhibitor exhibits remarkably high efficiency, even under elevated temperature conditions. At 55 °C temperature conditions, i_corr value decreased from 5050 to 154 μA cm^?2, with the addition of 500 ppm inhibitor. The long-term stability of inhibitor was also tested and 85.93% efficiency was obtained after three days of exposure period for 500 ppm concentration.     

Efficiency of Gold Nano Particles on the Autoxidized Soybean Oil Polymer: Fractionation and Structural Analysis

Polyunsaturated plant oils have gained great interest as monomers to produce biodegradable polymers obtained from renewable resources due to the limited existing sources of petroleum oil and environmental issues. Soybean oil was autoxidized by exposure to atomospheric oxygen at room temperature with or without the presence of gold nanoparticles (Au NPs) 5–41 days. When the autoxidation process was catalyzed with Au NPs, the molecular weight of the oxidized oil was increased in 5 days. In contrast to this, without Au NPs, the oxidized oil was still a fluidized liquid. Autoxidized soybean oil polymer in toluene solution with gold NP showed a surface plasmon resonance at λ_max = 540 nm in a UV–VIS spectrometer and a fluorescence emission spectrum at λ_max = 450 nm, when it was irradiated at λ_max = 390 nm. The higher molecular weight of the polymeric oils was successively fractionated by the extraction from the solvent‐non‐solvent mixture CHCl₃/petroleum ether with the volume ratio of 5:15. Three polymeric oils fractions with different molecular weight (ca 1000, 4000, and 40,000 g/mol) were obtained. GC–MS analysis, ¹H‐NMR and GPC techniques were used in the structural analysis of the fractionated polymeric oils.     

The impact of a realistic packet traffic model on the performance of surveillance wireless sensor networks

It is quite common to see that classical periodic or Poisson packet traffic models are used for evaluating the performance of wireless sensor networks (WSNs). However, these models may not be appropriate for modeling the data traffic resulting from a particular application. Furthermore, they may be overestimating the performance of a WSN. In this paper, we show the significance of using a realistic and application-specific packet traffic model by comparing the performance of a well-known WSN protocol under the Surveillance WSN packet traffic model (SPTM), as well as under periodic and binomial traffic models. A packet traffic framework specific to surveillance applications is proposed which is then used for deriving SPTM analytically. In order to be adaptable and flexible, SPTM incorporates a probabilistic and parametric sensor detection model. Simulation results show that to employ an application-specific packet traffic model has significant impact on the performance evaluation of the WSN and ordinary traffic models may overestimate the capacity of the WSN.     

Multi-machine earliness and tardiness scheduling problem: an interconnected neural network approach

This paper addresses the problem of scheduling a set of independent jobs with sequence-dependent setups and distinct due dates on non-uniform multi-machines to minimize the total weighted earliness and tardiness, and explores the use of artificial neural networks as a valid alternative to the traditional scheduling approaches. The objective is to propose a dynamical gradient neural network, which employs a penalty function approach with time varying coefficients for the solution of the problem which is known to be NP-hard. After the appropriate energy function was constructed, the dynamics are defined by steepest gradient descent on the energy function. The proposed neural network system is composed of two maximum neural networks, three piecewise linear and one log-sigmoid network all of which interact with each other. The motivation for using maximum networks is to reduce the network complexity and to obtain a simplified energy function. To overcome the tradeoff problem encountered in using the penalty function approach, a time varying penalty coefficient methodology is proposed to be used during simulation experiments. Simulation results of the proposed approach on a scheduling problem indicate that the proposed coupled network yields an optimal solution which makes it attractive for applications of larger sized problems.     

A Survey of Handover Techniques for Wireless ATM Networks

This paper provides a review and comprehensivecomparison of existing handover schemes proposed forwireless ATM networks. Existing schemes include thoseproposed by NEC, Olivetti, Bell Labs, Cambridge, Stanford, CMU, Berkeley, Michigan, VTT, andColumbia. We highlight the methodologies employed by thevarious schemes and reveal their differences. We discussissues related to the effect of ATM switch architectures on mobility implementation and on futurehandover paradigms.     

Determining optimum tilt angles and orientations of photovoltaic panels in Sanliurfa, Turkey

The performance of a photovoltaic (PV) panel is affected by its orientation and its tilt angle with the horizontal plane. This is because both of these parameters change the amount of solar energy received by the surface of the PV panel. A mathematical model was used to estimate the total solar radiation on the tilted PV surface, and to determine optimum tilt angles for a PV panel installed in Sanliurfa, Turkey. The optimum tilt angles were determined by searching for the values of angles for which the total radiation on the PV surface was maximum for the period studied. The study also investigated the effect of two-axis solar tracking on energy gain compared to a fixed PV panel. This study determined that the monthly optimum tilt angle for a PV panel changes throughout the year with its minimum value as 13° in June and maximum value as 61° in December. The results showed that the gains in the amount of solar radiation throughout the year received by the PV panel mounted at monthly optimum tilt angles with respect to seasonal optimum angles and tilt angel equal to latitude were 1.1% and 3.9%, respectively. Furthermore, daily average of 29.3% gain in total solar radiation results in an daily average of 34.6% gain in generated power with two-axis solar tracking compared to a south facing PV panel fixed at 14° tilt angle on a particular day in July in Sanliurfa, Turkey.