WATER AND WASTEWATER
Year:2014 | Volume:25 | Issue:4 (92)|Papers Count:15

With the growing industrial and social development through time, toxic substances such as phenol and its derivatives are increasingly released into the environment from a variety of sources. The present study aims to investigate the effects of molasses on phenol removal. For this purpose, five pilot scale batch reactors (5 Erlenmeyer flasks equipped with the air and gas diffusion control system) were used in the laboratory scale. The volumes of the reactors were kept constant with a final volume content of 550 ml in each reactor. Phenol with a fixed concentration of 100 mg/l was tested under anaerobic conditions in each reactor in contact with beet molasses (organic matter used as the auxiliary substrate) with COD concentrations of 10000, 5000, 2000, 1000, and 500 mg/l over 5 retention times (10, 20, 30, 40, and 50 days). All the sampling and testing procedures were performed according to the standard methods. The results showed that in all the five experimental reactors, increasing retention time was accompanied by a continuous decline in initial phenol and COD concentrations.However, for each retention time, increasing COD concentration led to a decrease in COD removal efficiency such that increasing the initial COD concentration up to a certain level was associated with an increase in chemical oxygen demanding materials, but beyond this range, COD removal decreased slowly. It was also found that phenol removal increased with increasing retention time but it was not proportional to the concentration of the biodegradable COD. After 50 days of contact with 1000 mg/l of the supporting substrate, phenol removal in the reactors reached 98.62%. Another finding of the study was the fact that the highest phenol removal was achieved when 1000-2000 mg/l of biodegradable COD was used over 50 days of retention time.

Nitrate is one of the most important groundwater pollutants with such different sources as chemical fertilizers, pesticides, or domestic and industrial wastewater. In this research, the optimal operation of groundwater wells in aquifers with nitrate pollution is investigated using simulation and optimization techniques. For the simulation part, an artificial neural network (ANN) model is developed, and for the optimization model, the particle swarm optimization (PSO) is used. Considering the high nitrate concentration in Karaj area and its increase in recent years, the northern part of this aquifer is selected as a case study to apply the proposed methodology. A seasonal ANN model is developed with input layers including well discharge in the current and previous seasons, nitrate concentration in the previous season, aquifer thickness, and well coordinates, all selected based on sensitivity analysis. The results of PSO algorithm shows that nitrate concentration can be controlled by increasing or decreasing well discharge in different zones. Therefore, it is possible to reduce nitrate concentration in critical areas by changing the spatial distribution of groundwater extractions in different zones keeping the total discharge constant.

High performance liquid chromatography (HPLC/UV-VIS) was used to detect and measure chlorophylls a and b in Karaj, Taleghan, and Latian dam reservoirs. For this purpose, samples were collected in duplicates during 2012 to 2013. The calibration graphs were found to be linear with good correlation coefficients (r>0.999) for chlorophylls a and b. Average values of chlorophylls a and b, respectively, were 4.5 and 0.028 mg/l at Karaj, 2.4, 0.04 mg/l at Taleghan, and 3 and 0.03 at Latian; in some case, the average values were below the detection limit (LOD). Also, HPLC was found to be valid and effective for determining chlorophylls a and b in natural water samples at levels as low as mg/l.

Wastewaters containing dyes are qualitatively dangerous and toxic. Researchers have, therefore, concentrated on simple and efficient methods for their treatment. The present study investigates the preparation of adsorbents from waste materials and evaluation of their performance in removing dyes from aqueous solutions. For this purpose, activated carbon is prepared from pomegranate residuals by phosphoric acid (37%) activation and used to remove the reactive blue 19 from aqueous solutions. Furthermore, the activated carbon thus obtained is characterized in terms of its morphological and textural properties, and the effects of such operation parameters as contact time, initial pH, adsorbent dose, and initial dye concentration on dye removal efficiency are evaluated.Results indicate the high surface area (SBET) of the pomegranate-based activated carbon (572.53 m2/g) and its maximum dye removal efficiency (98.16%) for a contact time of 5 minutes, at an initial pH of 11 with 3.5 gr/L of the adsorbent in an aqueous solution with an initial dye concentration of 300 mg/L. Finally, adsorption isotherm studies (Langmuir, Freundlich, and Temkin) and kinetic studies (the pseudo first-order, pseudo-secondorder, Elovich and intraparticle diffusion kinetic models) are performed to show that the adsorption process follows a Langmuir isotherm equation (R2=0.955) and the pseudo-second order kinetic model (R2=0.997).

The biofilter system is one of the methods commonly used for the removal of hydrogen sulfide as the main source of odors emitted from wastewater facilities. The system is based on using the contaminant material as bedding to feed microorganisms. To achieve the desirable removal efficiency, it is, therefore, essential to create the proper conditions for the bacteria to grow on the bedding. In this study, a pilot-scale biofilter made of compost and woodchip (with a compost/woodchip ratio of 5: 1) was used as the bedding material at Khorrmabad wastewater pumping station to investigate the performance of the system under real conditions. The experiment was carried out over 75 days during which time the input and output H2S concentrations were measured on a regular basis. Moisture was adjusted between 40% and 60% throughout the experiment to provide optimal conditions for bacterial growth. The results showed that the concentration of H2S emitted from the pumping station during 24 hours varied greatly between 0 and 48 PPM. The maximum adsorption capacity of the biological bedding was recorded at 2.874 g/m3. hr and the mean efficiency of H2S removal including the startup time was 89%. The mean performance efficiency during the biological activity after the startup was recorded at 98%.

Soil pollution, in general, and heavy metals contamination, in particular, are problems of modern life. In this context, surveying contaminated soils becomes essential for keeping away human food chains from dangerous heavy metals. This study was conducted to evaluate soil Cd-contamination in part of the arable lands in Bizaa, west of Shiraz. Soil samples were randomly collected from an area of 800, 000 m2, prepared, and analyzed for Cd concentration. Analysis of variograms showed that the structural component moderately dominated the randomized component and that the range of special dependency was 2300 m. Ordinary kriging was used for mapping and estimation variances were calculated. Based on the Cd contamination standard threshold (3mg/Kg), the map thus prepared indicated that about 80 percent of the study area was polluted and that the hot point was located in the southern stretches of the study area. The non-existence of industrial activities and the absence of point Cd distribution indicated that soil pollution in the area must have been caused by human activities such as farming. The excessive consumption of chemical fertilizers, especially phosphates, in agricultural activities and sludge application seem to be the main suspects of soil Cd contamination. Further investigation is needed into the agricultural history of the area to determine the main causes of Cd contamination in this area.

This study investigates the potential use of date-palm leaf (Phoenix dactylifera) ash as an inexpensive adsorbent for the removal of Pb (II) ions. For this purpose, the variables pH, Pb (II) ion concentration, adsorbent dosage, and temperature in the batch system were investigated. The results obtained showed that the optimum pH for the removal of Pb (II) ions from aqueous solutions was equal to 5. Adsorption efficiencies obtained were 99.46, 91.47, 80.49, 69.62, 57.34, and 51.29%, respectively, for Pb (II) concentrations of 50, 100, 150, 200, 250, and 300 mg/l using 0.5 g/l of the adsorbent with a retention time of 60 minutes at 20dC. Increasing the adsorbent dosage from 0.1 to 2 g/l led to increased adsorption rate. Also, thermodynamic investigations showed that the adsorption process was dependent on temperature such that the order of decreasing removal efficiency followed the temperature order 40oC>30oC>20oC. Based on the Langmuir model, the value for the constant b was 0.152 and maximum Pb removal was 31.5%. It was concluded that date-palm leaf ash has a good potential for use as an adsorbent to remove toxic heavy metals like lead from aqueous solutions.

Sludge dewatering and disposal form important steps of water treatment processes. The rising costs of raw material and limitations in resources have led to increasing interest in waste reuse solutions. The main objective of this study was to investigate the feasibility of using water treatment plant sludge in brick making. For this purpose, samples of bricks with different sludge to clay ratios were prepared for analysis. Results show that higher sludge/clay ratios led to increasing number of bricks pores and enhanced water absorption capacity while the compressive strength, density, and brick weight reduced. The recommended minimum brick compressive strength of 80 Kg/m2 was achieved with a sludge/clay ratio of 42%, which also led to a brick water absorption of 24% while its acceptable maximum limit is 20%. This rather small excess water absorption can be ignored in the case of load-bearing walls for the favorable compressive strength achieved although water absorption is an important parameter for face bricks. In another part of this study, different sludge/clay ratios were tested to obtain a variety of brick colors suitable for use as face bricks. A final advantage of the bricks made is the reduced brick weight and, thereby, building weight which.

The use of pozzolanic materials as a replacement for cement is nowadays of great significant due to the improvements gained in the properties of cement-based materials and the costs it saves. On the other hand, sewage sludge is harmful to both the environment and the human health and its safe disposal is highly desirable.Based on these considerations, this study investigates the use of sewage sludge ash as an artificial pozzolan to produce self-compacting cement-based materials, an initiative that has come to be evaluated as a revolution in the concrete industry. The objective of the study is to accelerate the performance of sewage sludge ash by utilizing nano-silica particles. For this purpose, 10 mix designs were employed for self-compacting mortar and concrete made up of binary and ternary cementitious blends of sewage sludge ash (0%, 5%, 10%, 15%, and 20%) and nano-silica (0% and 1%). The results show that the rheological and mechanical properties of the samples declined as a result of adding sewage sludge ash, but their durability characteristics improved with only small percentage volumes of sewage sludge ash addition. Moreover, nano-silica addition was observed to improve the mechanical properties and durability of self-compacting mortar and concrete. Finally, the reactivity of sewage sludge ash increased and its performance was improved in the presence of nano-silica.

Lack of an efficient sewer network in urban areas threatens public health and may give rise to contagious diseases. Various optimization methods have been developed for use in designing sewers networks in response to a number of requirements such as the high costs of constructing sewer networks, financial limitations, the presence of both discrete and continuous decision variables, and the nonlinear time complexity of such design problems. In this study, the particle swarm optimization algorithm (PSO) with the capability of “fly-back” mechanism equipped with the harmony search (HPSO) is used for the optimization of sewers network designs. The objective function consists of minimizing the excavation and embedding costs of commercial pipes. The flyback mechanism and the harmony memory method are used to prevent leaving out variables from the feasible space of the problem in an attempt to enhance model efficiency. Model constraints are satisfied at two levels, which leads to the desirable convergence of the PSO algorithm as compared to the conventional penalty methods in alternative evolutionary algorithms. In order to determine the admissible decision variables, the Manning equation is used as a hydraulic model. The performance of the proposed algorithm is shown by presenting two examples of sewer networks. Compared to the PSO algorithm used in sewer network optimization models, the proposed model exhibits a tangible improvement in cost reduction and a higher computational stability.

Rainfall is one of the factors involved in increasing soil moisture. Soil moisture, in turn, is a key parameter in the rise and fall of water in the soil which plays an important role in the rainfall-runoff process. It, therefore, requires to be carefully investigated in order to determine its effect on peak flood discharge. One method commonly used for this purpose is the CN-NRCS (curve-number method). Based on this approach, the sum of rainfalls during the 5 days preceding the flood event is taken to represent the soil moisture conditions prior to the event. Given the fact that natural phenomena are always associated with different degrees of uncertainty due to the involvement a multitude of factors, an efficient method for investigating their behavior is the Adaptive Neuro- Fuzzy Intelligent System (ANFIS). Here, we used ANFIS for determining the effect of rainfalls over the five days prior to the flood event in order to predict the maximum daily flood discharge. The model employed the two training algorithms of Back Propagation and Hybrid, which were then tested using different statistical tests and the results were analyzed for each model. The results indicate that the hybrid method outperformed the back propagation method. The best correlation coefficient of the 5-day model was 0.985 and the RMSE (Root Mean Squared Error) was 0.162 in the hybrid method.

There are complex and nonlinear causal relationships among the different quality and quantity parameters of wastewater and return activated sludge, which is one of the most important parameters in the operation of activated sludge wastewater treatment plants. On the other hand, Artificial Neural Networks (ANNs) have advantages such as the ability to identify and extract complex and nonlinear causal relations using simple mathematical formulas, high generalizing power, and high speed that make them capable of being used as a powerful software in the operation of wastewater treatment plants. In this study, the application of artificial neural networks (ANNs) for determining the amount of return activated sludge in Torbat Heydarieh wastewater treatment plant is investigated based on one-year inlet flow data. The different parameters involved in this process such as inlet flow and temperature, inlet and outlet total suspended solids, inlet and outlet BOD5 and COD, MLSS, and the amount of return activated sludge were collected and applied to MLP and RBF artificial neural networks (ANNs). Results showed that MLP is capable of estimating the return activated sludge required in conventional biological wastewater treatment systems such as extended aeration and that its estimation accuracy is above 93%.

In this study, an adaptive neuro-fuzzy inference system (ANFIS) is employed to model the activated sludge wastewater treatment process at Mobin Petrochemical Company. The correlation coefficients between the input variables and the output variables were calculated to determine the one input with the highest influence on the output (the quality of the outlet flow) in order to compare three neuro-fuzzy structures with different numbers of parameters. The predictions of the neuro-fuzzy models were compared with those of multilayer artificial neural network models with a similar structure. The comparison indicated that both methods provided flexible, robust, and effective models for the activated sludge system. Moreover, the mean squared errors of the neuro-fuzzy and the neural network models were obtained as 5.14 and 6.59, respectively, which indicates the superior performance of the former.

Implementation and operation of municipal wastewater collection systems is an essential part of qualitative water resource management. In this paper, the most appropriate alternative among a set of limited of wastewater collection systems was selected using different quantitative and qualitative attributes. Moreover, the impact of risk attitudes of decision makers (DMs) on selection of the most preferred alternative was evaluated. As a case study the best alternative was examined using four MADM methods including Simple Additive Weighting (SAW), Compromise Programming (CP), TOPSIS, and Hybrid Weighted Averaging (HWA) to validate the application of RBMADM methods in wastewater collection systems. Then, the impact of selection of MADM method on the final outcome was studied and the results were compared.