Treatment of Synthetic Olefin Plant Wastewater at Various Salt Concentrations in a Membrane Bioreactor

The objective of this study was to investigate the effect of salt concentration on performance of a membrane bioreactor (MBR) for treating an olefin plant wastewater. For this purpose, a lab‐scale submerged MBR with a flat‐sheet ultrafiltration membrane was used for treatment of synthetic wastewater according to oxidation and neutralization unit of olefin plant. The synthetic wastewater was adjusted to have 500 mg/L chemical oxygen demand (COD). Trials on different concentrations of sodium sulfate (Na₂SO₄) (0–20 000 ppm) in the feed were conducted under aerobic conditions in the MBR. The results showed that increasing the salt concentrations causes an increase in the effluent COD, phenol, and oil concentrations. These results are due to reduction of the membrane filtration efficiency and also decline in the microbial activity that it is indicated by decreasing the sOUR in MBR. But in all the trials, the effluent COD and oil concentration was well within the local discharge limit of 100 and 10 mg/L, respectively. These results indicate that the MBR system is highly efficient for treating the olefin plant wastewater, and although high salt concentrations decreased organic contaminant removal rates in the MBR, the effluent still met the discharge limits for treating the olefin plant wastewater.     

Performance Evaluation of a Full‐Scale Extended Aeration System in Al‐Bireh City,Palestine

Major challenges attributed to dysfunctional wastewater treatment facilities in developing countries include lack of commitment and poor informed decision making by the higher municipal administration. This paper presents how process monitoring and control during full scale operation ensures sustainability of civic infrastructures like Al‐Bireh wastewater treatment plant (AWWTP). It is written from the perspective of practical process selection to evaluate the performance of AWWTP, a single‐sludge nitrification–denitrification process with aerobic sludge stabilization. Process monitoring data (July 2000–April 2007) from available monthly operating reports were analyzed and evaluated. Additional data on microbiological analysis and information about facility unit operations were gathered through review of published local literature and interviews with AWWTP personnel. Influent and effluent data evaluated were the chemical oxygen demand (COD), biological oxygen demand (BOD), total nitrogen (TN), and total phosphorus (TP). Despite annual and seasonal variations in AWWTP influent for COD, BOD, TN, and TP, the Palestinian wastewater reuse requirements for restricted irrigation were met. Process design and proper facility operation have direct impacts on effluent quality. The study concludes that regardless of the design capacity and process type, adequate administrative and operational management dictate the sustainability of AWWTP and reuse schemes.     

Prediction of Chemical Oxygen Demand (COD) Based on Wavelet Decomposition and Neural Networks

The chemical oxygen demand (COD) parameter of a wastewater treatment plant is predicted based on wavelet decomposition, entropy, and neural networks (NN) for rapid COD analysis. This paper also describes the usage of wavelet and NNs for parameter prediction. Data from a wastewater treatment plant in Malatya, Turkey, were used. This dataset consists of daily values of influents and effluents for a year. To reduce the dimension of input parameters and to decrease the NN training time, wavelet decomposition and entropy were used. Test results were presented graphically. The test results of the trained model were found to be closer to the measured COD values.     

Dynamic Treatment Response of Olive Mills Wastewater Using Series of Adsorption Steps

Olive mills wastewater (OMW) is a critical environmental problem in the Mediterranean area due to its extremely high levels of COD and phenols. In this study, a group of adsorption experiments were conducted to investigate the dynamic response of the pH, COD, phenols, TSS, TDS, and TS concentrations of pretreated OMW, using different concentrations of activated carbon as adsorbent. The pretreatment included sedimentation and filtration of OMW. The pretreated OMW was then subjected to adsorption. A series of adsorption steps in stirred batch vessels were studied, namely, one stage, two‐stage countercurrent, and three‐stage countercurrent adsorption systems. A combined two‐ two‐stage countercurrent adsorption steps were also studied. Experimental results showed that such treatment protocols were promising. For example, a treatment protocol composed of a three‐stage countercurrent adsorption process using activated carbon of concentration of 24 g/L of OMW was able to reduce the COD from 60 000 mg/L down to 22 300 mg/L, while phenols were reduced from 450 to 15 mg/L.     

Simultaneous Analysis of Natural Free Estrogens and Their Conjugates in Wastewater by GC‐MS

A solid‐phase extraction (SPE)‐gas chromatography (GC)‐mass spectrometry (MS) analytical method was developed for the simultaneous analysis of natural free estrogens and their conjugates in wastewater samples. Natural free estrogens and their conjugates in wastewater were successfully separated by the oasis hydrophilic‐lipophilic balance solid phase extraction (Oasis HLB SPE) method, and the conjugates were initially enzyme hydrolyzed by β‐glucuronidase or arylsulfatase from Helix pomatia prior to derivatization. N‐methyl‐N‐(tert‐butyldimethylsilyl)trifluoroacetamide (MTBSTFA) plus 1% tert‐butyldimetheylchlorosilane (TBDMCS) was chosen as the derivatization reagent, and the most appropriate conditions of derivatization were determined to be at 95°C for 90 min. The recovery ratios of nine target chemicals were determined by spiking them in 1 L of ultra‐purified water or the influent of a wastewater treatment plant (WWTP). The recovery ratios of six out of nine for the analytes ranged from 73.3–114.9% with relative standard deviations (RSD) from 1.6–19.9%. The established method was successfully applied to environmental wastewater samples which were collected from one municipal wastewater treatment plant (WWTP) in Osaka, Japan, for the determination of natural free estrogens and their conjugates. In the influent sample, E1, E2, E1‐3S, E3‐3S, and E1‐3G were detected at concentrations of 16.6, 9.6, 8.2, 21.9, and 3.2 ng L^–1, respectively. However, only E1 was detected at a high concentration of 44 ng L^–1 in the effluent sample, suggesting that it is the dominant natural free estrogen in the effluent.     

Characteristics of organic matter as indicators of pollution from small‐scale livestock and nitrate contamination of shallow groundwater in an agricultural area

The main purpose of this study was to examine the hydrogeochemical factors leading to nitrate contamination of shallow groundwater in an agricultural area. Another purpose was to identify relationships between variations in organic matter levels (as estimated by the BOD and COD parameters) of groundwater that transports effluent from small‐scale livestock holdings. Major cations, anions, BOD and COD of organic matter and total coliforms were analysed. It was found that groundwaters beneath cultivated areas and areas carrying livestock had higher concentrations of calcium, nitrate and chloride than did freshwater. Above all, the nitrification process increased concentrations of nitrate. Nitrate levels were depressed in some places where the groundwater was low in dissolved oxygen. Groundwaters affected by livestock activities showed high concentrations of organic matter (BOD, COD) and high microbial concentrations (as indicated by total coliforms). The COD/BOD ratio increased in the downward direction. It was inferred that this was due to the faster loss of easily biodegradable organic matter compared with non‐biodegradable organic matter proceeding away from a discharge. Accordingly, it is possible to trace effluent in a small area back to a point source by monitoring the COD/BOD ratio of groundwater. Copyright © 2003 John Wiley & Sons, Ltd.     

Predicting catchment flow in a semi‐arid region via an artificial neural network technique

A model of rainfall–runoff relationships is an essential tool in the process of evaluation of water resources projects. In this paper, we applied an artificial neural network (ANN) based model for flow prediction using the data for a catchment in a semi‐arid region in Morocco. Use of this method for non‐linear modelling has been demonstrated in several scientific fields such as biology, geology, chemistry and physics. The performance of the developed neural network‐based model was compared against multiple linear regression‐based model using the same observed data. It was found that the neural network model consistently gives superior predictions. Based on the results of this study, artificial neural network modelling appears to be a promising technique for the prediction of flow for catchments in semi‐arid regions. Accordingly, the neural network method can be applied to various hydrological systems where other models may be inappropriate. Copyright © 2004 John Wiley & Sons, Ltd.     

Oil refinery wastewater treatment using coupled electrocoagulation and fixed film biological processes

Oil refinery wastewater was treated using a coupled treatment process including electrocoagulation (EC) and a fixed film aerobic bioreactor. Different variables were tested to identify the best conditions using this procedure. After EC, the effluent was treated in an aerobic biofilter. EC was capable to remove over 88% of the overall chemical oxygen demand (COD) in the wastewater under the best working conditions (6.5 V, 0.1 M NaCl, 4 electrodes without initial pH adjustment) with total petroleum hydrocarbon (TPH) removal slightly higher than 80%. Aluminum release from the electrodes to the wastewater was found an important factor for the EC efficiency and closely related with several operational factors. Application of EC allowed to increase the biodegradability of the sample from 0.015, rated as non-biodegradable, up to 0.5 widely considered as biodegradable. The effluent was further treated using an aerobic biofilter inoculated with a bacterial consortium including gram positive and gram negative strains and tested for COD and TPH removal from the EC treated effluent during 30 days. Cell count showed the typical bacteria growth starting at day three and increasing up to a maximum after eight days. After day eight, cell growth showed a plateau which agreed with the highest decrease on contaminant concentration. Final TPHs concentration was found about 600 mgL⁻¹ after 30 days whereas COD concentration after biological treatment was as low as 933 mgL⁻¹. The coupled EC-aerobic biofilter was capable to remove up to 98% of the total TPH amount and over 95% of the COD load in the oil refinery wastewater.     

Short-term prediction of influent flow in wastewater treatment plant

Predicting influent flow is important in the management of a wastewater treatment plant (WWTP). Because influent flow includes municipal sewage and rainfall runoff, it exhibits nonlinear spatial and temporal behavior and therefore makes it difficult to model. In this paper, a neural network approach is used to predict influent flow in the WWTP. The model inputs include historical influent data collected at a local WWTP, rainfall data and radar reflectivity data collected by the local weather station. A static multi-layer perceptron neural network performs well for the current time prediction but a time lag occurs and increases with the time horizon. A dynamic neural network with an online corrector is proposed to solve the time lag problem and increase the prediction accuracy for longer time horizons. The computational results show that the proposed neural network accurately predicts the influent flow for time horizons up to 300 min.     

Evaluation of a Novel Control Method on Biofilm Parameters in an Aerated Submerged Fixed‐bed Biofilm Reactor

One of the critical technological parameter in operation of aerated submerged fixed‐bed biofilm reactor (ASFBBR) is the control over process of biofilm detachment. Both, an excessive growth of biomass with its accumulation in the bioreactor and an exceeded biofilm detachment rate, cause serious operational and technological problems. The studies presented in this paper demonstrate that in an ASFBBR reactor with a PVC bed carrier media, an effective way to maintain a proper shear stress acting on the biofilm and causing its detachment could be an internal recirculation of wastewater instead of backwashing with wastewater or air flushing. In case of polishing of oil‐refinery wastewater with average COD loading rate equal to 9 g COD/(m² day), the minimum value of the hydraulic loading rate in such reactor is 1.9 m³/(m² h), at which there was no excessive growth of biofilms. Despite a significant decrease of the biofilms thickness and amount of biomass in the reactor, there was no significant decline in the efficiency of pollutant removal from oil‐refinery wastewater, which made it possible to obtain the quality of effluent at the outlet of the bioreactor significantly below the water permits and standards.     

Removal of Organic Pollutants from Wastewater Using Wood Fly Ash as a Low‐Cost Sorbent

In this study, untreated and treated wood fly ash (WA) was used as a low‐cost sorbent in batch sorption tests to investigate the removal of organic pollutants from a real wastewater generated by cleaning/washing of machinery in a wood‐laminate floor industry in Sweden. The experiments focused on the effect of the WA dosage and particle size on the removal efficiency for organic compounds. With a WA dosage of 160 g L^?1 and a particle size less than 1 mm, the reductions of chemical oxygen demand (COD), biologic oxygen demand, and total organic carbon were 37 ± 0.4, 24 ± 0.4, and 30 ± 0.3%, respectively. Pre‐treatment of WA with hot water improved the COD removal efficiency by absorption from 37 ± 0.4 to 42 ± 1.6% when the same dosage (160 g L^?1) was applied. Sorption isotherm and sorption kinetics for COD using untreated WA can be explained by Freundlich isotherm and pseudo‐second‐order kinetic models. Intra‐particle diffusion model indicates that pore diffusion is not the rate‐limiting step for COD removal. Based on the experimental data, WA could be used as an alternative low‐cost sorption media/filter for removal of organic compounds from real industrial wastewater.     

Removal of Natural Free Estrogens and their Conjugates in a Municipal Wastewater Treatment Plant

Removal of natural free estrogens and estrogen conjugates in a municipal wastewater treatment plant (WWTP) was investigated and analyzed by GC‐MS, in which estrogen conjugates were first transformed to their corresponding free estrogens with an acid solvolysis procedure before their analysis. Natural free estrogens, E1‐3‐sulfate (E1‐3S), and E3‐3‐sulfate (E3‐3S) were detected with high concentrations in both the influent and effluent of the primary settling tank (PS), while no estrogen glucuronides were detected in any of the monitored wastewater samples. Regarding their removal efficiencies, all were almost completely removed, except for E1 with only a minor decrease. The estrogenic/androgenic removal of the same WWTP was also evaluated with estrogen receptor (androgen receptor) (ER (AR))‐binding assays, in which the removal efficiencies for E2 equivalents (EEQ) or testosterone equivalents (TEQ) were 68.5 and 72.2%. In addition, the chemically calculated EEQ from natural estrogens were about 20.6–39.3% that of the ER‐binding assay, in which E3 contributed the biggest proportion in both the influent and PS, while the calculated value of E1 increased from only 6.7% in the influent to as high as 20.6% in the effluent.     

Supervised neural network recognition of habitat zones of rice invertebrates

This study aimed to evaluate effectiveness and performance of several supervised neural network models and make pattern recognition on invertebrate habitat zones. Probabilistic, general regression, and linear neural networks, and discriminant analysis were used to recognize both known and unknown invertebrate habitat zones. The results showed that neural network models were better than traditional discriminant analysis in the recognition of known habitat zones. There was not distinctive variation in recognition from different neural network models. Sensitivity analysis indicated that the learning rate of the neural network would influence recognized results. An unknown invertebrate species from Lepidoptera was recognized to be soil-dweller (dryland) by both neural network models and discriminant analysis. In sensitivity analysis it was additionally recognized to be the type of plant canopy (terrestrial). Overall the species was estimated to be a soil-dweller (dryland) or live on plant canopy (terrestrial). It was concluded that neural network models can perform better than conventional statistic models in pattern recognition, but a comprehensive comparison among various models is necessary in order to achieve a high reliable recognition and prediction. Furthermore, sensitivity analysis can lead to an in-depth grasp on the mechanism in the recognition and is thus needed.     

Determination of Real COD in Highly Chlorinated Wastewaters

In order to determine the interference caused by chloride ions in Chemical Oxygen Demand (COD) measurements, synthetically prepared samples with various COD and chloride concentrations were analyzed. In addition, statistical analyses of the results were performed to calculate the real COD caused by the presence of organic substances in chlorinated wastewaters. The results of regression analyses showed good correlation between chloride concentrations and COD levels. A mathematical model is proposed on the basis of the statistical analyses. To calculate the real COD value of a wastewater sample, firstly, the chloride and interfered (or apparent) COD concentrations should be measured and then interference due to the chloride is calculated using the model equation proposed in this study. The real COD value was found by subtracting the COD due to chloride from the apparent COD. The reliability of the proposed model was also validated on real domestic wastewater samples, which were mixed with real seawater in various volumetric ratios to generate a range of salinity concentrations. These real saline samples gave good estimates of real COD with the results indicating that the proposed model can be used with acceptable confidence.     

The performance of constructed wetlands for,wastewater treatment: a case study of Splash wetland in Nairobi Kenya

The performance of a constructed wetland for wastewater treatment was examined for four months (December 1995 to March 1996). The study area, hereby referred to as the Splash wetland, is approximately 0·5 ha, and is located in the southern part of Nairobi city. Splash wetland continuously receives domestic sewage from two busy restaurants. Treated wastewater is recycled for re‐use for various purposes in the restaurants. Both wet and dry season data were analysed with a view of determining the impact of seasonal variation on the system performance. The physical and chemical properties of water were measured at a common intake and at series of seven other points established along the wetland gradient and at the outlet where the water is collected and pumped for re‐use at the restaurants. The physico‐chemical characteristics of the wastewater changed significantly as the wastewater flowed through the respective wetland cells. A comparison of wastewater influent versus the effluent from the wetland revealed the system's apparent success in water treatment, especially in pH modification, removal of suspended solids, organic load and nutrients mean influent pH = 5·7 ± 0·5, mean effluent pH 7·7 ± 0·3; mean influent BOD₅ = 1603·0 ± 397·6 mg/l, mean effluent BOD₅ = 15·1 ± 2·5 mg/l; mean influent COD = 3749·8 ± 206·8 mg/l, mean effluent COD = 95·6 ± 7·2 mg/l; mean influent TSS = 195·4 ± 58·7 mg/l, mean effluent TSS = 4·7 ± 1·9 mg/l. As the wastewater flowed through the wetland system dissolved free and saline ammonia, NH₄⁺, decreased from 14·6 ± 4·1 mg/l to undetectable levels at the outlet. Dissolved oxygen increased progressively through the wetland system. Analysis of the data available did not reveal temporal variation in the system's performance. However, significant spatial variation was evident as the wetland removed most of the common pollutants and considerably improved the quality of the water, making it safe for re‐use at the restaurants. Copyright © 2001 John Wiley & Sons, Ltd.     

Surveillance of Invasive Bacterial Pathogens and Human Enteric Viruses in Wastewater Final Effluents and Receiving Water Bodies – a Case Study from Durban,South Africa

The physico‐chemical characteristics and microbial composition of the final effluents of two municipal wastewater treatment plants in South Africa were assessed between July and September 2009. The impact of the treated final effluents on the receiving water bodies was also evaluated. The temperature across all sampling points ranged between 14 and 22°C, while pH varied from 6.9 to 7.6. High levels of turbidity, chemical oxygen demand (COD), ammonia, nitrate, nitrite and orthophosphate (PO₄) were observed in many cases. Turbidity of the samples was in the range of 2.2–288.6 NTU. The concentrations (mg/L) of other physico‐chemical parameters are as follows: COD (9.33–289); ammonia (0.000340–45.4); nitrate (0.062–539); nitrite (0.021–22.6); PO₄ (5.3–33.2). The microbial quality of the effluents discharged from the plants did not comply with the limits set by the South African guidelines with respect to pathogens such as Salmonella, Shigella, Escherichia coli, total coliform, faecal coliform, enterococci, faecal streptococci, and viral particles for effluents intended for discharge into receiving watersheds. This study revealed an undesirable impact on the physico‐chemical and microbial qualities of the receiving water bodies as a result of the discharge of inadequately treated effluents from the wastewater treatment facilities. This poses a health risk to several rural communities which rely on the receiving water bodies primarily as their sources of domestic water and recreational purposes. There is therefore a need for the intervention of appropriate regulatory agencies in South Africa to ensure compliance of treatment facilities with wastewater effluent quality standards.     

Anwendung einfacher Konservierungsverfahren für Wasseruntersuchungen

Samples taken from the influent and effluent of a biological wastewater treatment plant were immediately analysed and investigated at different intervals within four weeks after sampling. They were stored in the dark at 277 and 293 K and at pH 2 and pH 12 each. None of the measures resulted in a correct stabilization or preservation of the samples: orthophosphate cannot be stabilized by any measure, the total phosphate needs not be stabilized, the COD gives values which are still useful only at pH 2 and 277 K, TOC and DOC do not show useful results with none of the applied techniques, equally insufficient are the results for ammonium- and nitrate-ions. In addition, differences occur in the behaviour of the samples taken from the influent and effluent. In agreement with the results published in the literature, the chemical analysis has to be carried out within 6 h after sampling.     

Long‐lead seasonal rainfall forecasting using time‐delay recurrent neural networks: a case study

A temporal artificial neural network‐based model is developed and applied for long‐lead rainfall forecasting. Tapped delay lines and recurrent connections are two different components that are used along with a static multilayer perceptron network to design a time‐delay recurrent neural network. The proposed model is, in fact, a combination of time‐delay and recurrent neural networks. The model is applied in three case studies of the Northwest, West, and Southwest basins of Iran. In addition, an autoregressive moving average with exogenous inputs (ARMAX) model is used as a baseline in order to be compared with the time‐delay recurrent neural networks developed in this study. Large‐scale climate signals, such as sea‐level pressure, that affect the rainfall of the study area are used as the predictors in the models, as well as the persistence between rainfall data. The results of winter‐spring rainfall forecasts are discussed thoroughly. It is demonstrated that in all cases the proposed neural network results in better forecasts in comparison with the statistical ARMAX model. Moreover, it is found that in two of three case studies the time‐delay recurrent neural networks perform better than either recurrent or time‐delay neural networks. The results demonstrate that the proposed method can significantly improve the long‐lead forecast by utilizing a non‐linear relationship between climatic predictors and rainfall in a region. Copyright © 2007 John Wiley & Sons, Ltd.     

Simulating and predicting river discharge time series using a wavelet‐neural network hybrid modelling approach

Accurate simulation and prediction of the dynamic behaviour of a river discharge over any time interval is essential for good watershed management. It is difficult to capture the high‐frequency characteristics of a river discharge using traditional time series linear and nonlinear model approaches. Therefore, this study developed a wavelet‐neural network (WNN) hybrid modelling approach for the predication of river discharge using monthly time series data. A discrete wavelet multiresolution method was employed to decompose the time series data of river discharge into sub‐series with low (approximation) and high (details) frequency, and these sub‐series were then used as input data for the artificial neural network (ANN). WNN models with different wavelet decomposition levels were employed to predict river discharge 48 months ahead of time. Comparison of results from the WNN models with those of the ANN models alone indicated that WNN models performed a more accurate prediction. Copyright © 2011 John Wiley & Sons, Ltd.     

Semi‐Micro Reflux Procedure for Minimization of Chloride Interference by COD Determination

In this study, a semi‐micro procedure for the COD (Chemical Oxygen Demand) was undertaken to allow the measurement of effluent samples with a high chloride content. It was found that the COD values for standard and effluent samples, corresponded closely to those obtained using the standard method of Burns and Marshall. When the method was applied to samples of industrial wastewater, with a very high chloride content, the recommended procedure proved to be accurate and precise, with RSDs of 6% and 4.3% for the standard and effluent solutions, respectively. The required amount of hazardous reagents was similar to that found in the standard closed reflux method. It was also possible to determine the total amount of oxidized halides. The use of this low‐cost, laboratory‐made system made it unnecessary to acquire an expensive, imported analytical system, while maintaining a high level of accuracy in the determinations.