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Construction activities have been a primary cause for depleting natural resources and are associated with stern environmental impact. Developing concrete mixture designs that meet project specifications is time-consuming, costly, and requires many trial batches and destructive tests that lead to material wastage. Computational intelligence can offer an eco-friendly alternative with superior accuracy and performance. In this study, coal waste was used as a recycled additive in concrete. The flexural strength of a large number of mixture designs was evaluated to create an experimental database. A hybrid artificial neural network (ANN) coupled with response surface methodology (RSM) was trained and employed to predict the flexural strength of coal waste-treated concrete. In this process, four influential parameters including the cement content, water-to-cement ratio, volume of gravel, and coal waste replacement level were specified as independent input variables. The results show that concrete incorporating 3% recycled coal waste could be a competitive and eco-efficient alternative in construction activities while attaining a superior flexural strength of 6.7 MPa. The RSM-modified ANN achieved superior predictive accuracy with an RMSE of 0.875. Based on the experimental results and model predictions, estimating the flexural strength of concrete incorporating waste coal using the RSM-modified ANN model yielded superior accuracy and can be used in engineering practice to save the effort, cost, and material wastage associated with trial batches and destructive laboratory testing while producing mixtures with enhanced flexural strength.
Farshad Dabbaghi; Maria Rashidi; Moncef Nehdi; Hamzeh Sadeghi; Mahmood Karimaei; Haleh Rasekh; Farhad Qaderi. Experimental and Informational Modeling Study on Flexural Strength of Eco-Friendly Concrete Incorporating Coal Waste. Sustainability 2021, 13, 7506 .
AMA StyleFarshad Dabbaghi, Maria Rashidi, Moncef Nehdi, Hamzeh Sadeghi, Mahmood Karimaei, Haleh Rasekh, Farhad Qaderi. Experimental and Informational Modeling Study on Flexural Strength of Eco-Friendly Concrete Incorporating Coal Waste. Sustainability. 2021; 13 (13):7506.
Chicago/Turabian StyleFarshad Dabbaghi; Maria Rashidi; Moncef Nehdi; Hamzeh Sadeghi; Mahmood Karimaei; Haleh Rasekh; Farhad Qaderi. 2021. "Experimental and Informational Modeling Study on Flexural Strength of Eco-Friendly Concrete Incorporating Coal Waste." Sustainability 13, no. 13: 7506.
Air pollution in metropolises is one of the serious problems of human life. Tehran is one of the cities facing air pollution problem. Urban managers concern about choosing different management methods to control air pollution. In this study, a combination of fuzzy systems and neural networks has been used to select the most suitable scenario for controlling SO2 pollution. According to the method presented in this paper, 8 input data categories such as wind speed, precipitation, temperature, pressure, humidity, gas oil consumption, gasoline consumption and urban green space levels have been used as independent parameters and SO2 pollutant concentration has been considered as the dependent parameter. The contribution of each meteorological station to the meteorological data was determined by Thiessen Polygon Method. Then, using adaptive neural fuzzy inference systems, modeling was done in Sugeno Method and the least root mean square error (3.19) was determined for the model. Then, by changing each of the independent parameters, the effect of each of these independent parameters on SO2 pollutant was measured. The results showed that the parameters of pressure, urban green space, gasoline consumption, gas oil consumption, temperature, wind speed and humidity, respectively, had the greatest effect on reducing the SO2 concentration. Since the parameters of gasoline and gas oil consumption as well as the area of green space are changeable by different policies and by human decisions, the concentration of SO2 pollutant can be controlled by reducing the consumption of gasoline and gas oil and increasing the green space in Tehran.
Mohammad Ebrahimi; Farhad Qaderi. Determination of the most effective control methods of SO2 Pollution in Tehran based on adaptive neuro-fuzzy inference system. Chemosphere 2020, 263, 128002 .
AMA StyleMohammad Ebrahimi, Farhad Qaderi. Determination of the most effective control methods of SO2 Pollution in Tehran based on adaptive neuro-fuzzy inference system. Chemosphere. 2020; 263 ():128002.
Chicago/Turabian StyleMohammad Ebrahimi; Farhad Qaderi. 2020. "Determination of the most effective control methods of SO2 Pollution in Tehran based on adaptive neuro-fuzzy inference system." Chemosphere 263, no. : 128002.
The present study provided a comparison of two species of microalgae growth in dairy wastewater treatment plant effluents. In optimum conditions their operation to biomass production, lipid accumulation and fatty acids methyl ester composition so as to biodiesel production is studied. For the first time, the not sterilized effluents of dairy wastewater treatment plant was used as the culture mediums of native microalgae, Chlorella sorokiniana strain pa.91, and another one Chlorella vulgaris. They were cultured under 5 light intensity levels so as to find optimum conditions to observed high biomass and lipid production. At the optimum light intensity the composition of fatty acids methyl ester in their lipids was analyzed by GC-MS. The light intensity of 7500 Lux was obtained as the optimum for both microalgae to produce high biomass. The biomass productivity of C. sorokiniana pa.91 and C. vulgaris in preliminary treated effluent at this light intensity was obtained 0.233 and 0.214 g L−1 day−1, respectively. This parameter in secondary treated effluent was achieved 0.185 and 0.166 g L−1 day−1, respectively. Moreover, the highest lipid content of their biomass was observed at the light intensity of 2500 Lux. At this light intensity and at the preliminary effluent the maximum lipid content of C. sorokiniana pa.91 and C. vulgaris was observed 31% and 34%, respectively and at the secondary one it was obtained 35% and 36.67%, respectively. Based on the results, the fatty acids composition in the lipids of microalgae C. sorokiniana pa.91 and C. vulgaris cultured in both effluents had the high amount of cetane number which is really useful for high quality biodiesel production. Also, the other valuable properties which produce the high quality biodiesel were the obtained amounts of CFPP and CP which shown a high performance potential biodiesel even at low temperatures. This feature was obtained, on the grounds that the unsaturated fatty acid was obtained more than saturated fatty acid. The nutrients-rich media of dairy wastewater effluents were applicable to growth both microalgae and useful biomass production, lipid accumulation and fatty acids profiling. Furthermore, the compounds of fatty acids had the best conditions to biodiesel production especially in cold weather areas.
Pariya Asadi; Hassan Amini Rad; Farhad Qaderi. Lipid and biodiesel production by cultivation isolated strain Chlorella sorokiniana pa.91 and Chlorella vulgaris in dairy wastewater treatment plant effluents. Journal of Environmental Health Science and Engineering 2020, 18, 573 -585.
AMA StylePariya Asadi, Hassan Amini Rad, Farhad Qaderi. Lipid and biodiesel production by cultivation isolated strain Chlorella sorokiniana pa.91 and Chlorella vulgaris in dairy wastewater treatment plant effluents. Journal of Environmental Health Science and Engineering. 2020; 18 (2):573-585.
Chicago/Turabian StylePariya Asadi; Hassan Amini Rad; Farhad Qaderi. 2020. "Lipid and biodiesel production by cultivation isolated strain Chlorella sorokiniana pa.91 and Chlorella vulgaris in dairy wastewater treatment plant effluents." Journal of Environmental Health Science and Engineering 18, no. 2: 573-585.
Removing aromatic contaminants from the soil using ultrasonic waves is a new technology with the potential for practical use in industrial scale. In this study, the ultrasonication technology was presumed as a pre-treatment for soils contaminated with phenanthrene. Since the removal of this contaminant from the soil by ultrasonication reduces the cost of treatments such as soil washing, the optimization of independent variables has been investigated in the present study. Effect of variables such as phenanthrene primary concentration (7.5–517.5 mg/kg), ultrasonic power (0–395 W), the volume of water (0–400 mL) and the overall retention time (0–1 h) on the cost-saving of treatment for 100 g soil samples has been presented. The Response Surface Methodology has been used for modeling the results of this research. Based on the results of this research, the optimal conditions have been proposed for maximization of the cost-savings by ultrasonication and minimization of the ultrasonication operating costs. The best proposed conditions to achieve the maximum pollutant removal occurred in soil pretreatments using ultrasonication in water volume of 300 mL, the ultrasonic power of 139W, and 0.5 h process duration, which led to saving of 1.42 ¢/100 g soil for the replacement of the soil washing by the ultrasonication process.
Amin Tamadoni; Farhad Qaderi. Environmental-economical assessment of the use of ultrasonication for pre-treatment of the soils contaminated by phenanthrene. Journal of Environmental Management 2020, 259, 109991 .
AMA StyleAmin Tamadoni, Farhad Qaderi. Environmental-economical assessment of the use of ultrasonication for pre-treatment of the soils contaminated by phenanthrene. Journal of Environmental Management. 2020; 259 ():109991.
Chicago/Turabian StyleAmin Tamadoni; Farhad Qaderi. 2020. "Environmental-economical assessment of the use of ultrasonication for pre-treatment of the soils contaminated by phenanthrene." Journal of Environmental Management 259, no. : 109991.
Wastewater containing phenol is one of the problems that environmental engineering tries to solving it. Cascade reactors are used in water treatment to increase the dissolved oxygen. In this study, this reactor is used for increasing the removal efficiency of phenol treatment in the photocatalytic process. The parameters studied in this research are the initial phenol concentration, UV source power, retention time and flow rate. For the first time, the individual, simultaneous and interactive effects of these four parameters were examined in cascade photocatalytic reactor using the response surface methodology. In this research, a predictive model was presented based on response surface methodology, and the phenol treatment conditions were optimized by this method. According to the results, the optimum removal efficiency occurred at 4.93619 h, with the flow rate of 5.19626 L/min, the initial phenol concentration of 34.7437 mg/L and the UV source power of 40 W. Analysis of variance was done on the experimental data, and its result showed that the UV source power had the most significant effect and that the flow rate had the least significant effect on the removal efficiency. So that by increasing the UV source power from 35 to 55 W, the removal efficiency increased from 54% to approximately 78%. But by increasing the flow rate from 5 to 8 L/min, the removal efficiency increased from about 63% to approximately less than 70%. Prediction of removal efficiency has an uncertainty because of simultaneous and interactive effects of the independent variables on the process; therefore, in this research, Monte Carlo calculations were used to determine the uncertainty of the efficiency prediction. Based on Mont Carlo result, the efficiency will be at the range of 37.542–91.898% at the confidence level of 5–95%. According to the results, this reactor can be used for the treatment of phenolic wastewater.
F. Azizpour; F. Qaderi. Optimization, modeling and uncertainty investigation of phenolic wastewater treatment by photocatalytic process in cascade reactor. Environment, Development and Sustainability 2019, 22, 6315 -6342.
AMA StyleF. Azizpour, F. Qaderi. Optimization, modeling and uncertainty investigation of phenolic wastewater treatment by photocatalytic process in cascade reactor. Environment, Development and Sustainability. 2019; 22 (7):6315-6342.
Chicago/Turabian StyleF. Azizpour; F. Qaderi. 2019. "Optimization, modeling and uncertainty investigation of phenolic wastewater treatment by photocatalytic process in cascade reactor." Environment, Development and Sustainability 22, no. 7: 6315-6342.
Nanophotocatalytic process among various methods is used more for BTEX removal as an aromatic hydrocarbon in produced water. For this purpose, γ-Fe2O3 nanoparticle, which has significant efficiency to remove and degraded the contaminants. γ-Fe2O3 photocatalysis nanoparticle was synthesized by co-precipitation process, and the nanoparticle characteristics were determined by XRD, SEM and DRS. The main factors impact were studied including: pH (2–8), photocatalyst concentration (0–300 mg/l) and visible light irradiation intensity (0–270 W). The experiments were applied by a CCD and analyzed by using RSM. From the results analysis the polynomial formula has been derived for the model. For the first time, the effects of interactions of the main factors were investigated and the interactive diagrams were presented. The results show that the maximum BTEX removal efficiency (90.94%) was observed in 3.64 of pH, 167 mg/l of the nanoparticle concentration, and 180 W of the light intensity.
Z. Sheikholeslami; Daryoush Yousefi Kebria; F. Qaderi. Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light. Journal of Molecular Liquids 2019, 299, 112118 .
AMA StyleZ. Sheikholeslami, Daryoush Yousefi Kebria, F. Qaderi. Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light. Journal of Molecular Liquids. 2019; 299 ():112118.
Chicago/Turabian StyleZ. Sheikholeslami; Daryoush Yousefi Kebria; F. Qaderi. 2019. "Application of γ-Fe2O3 nanoparticles for pollution removal from water with visible light." Journal of Molecular Liquids 299, no. : 112118.
Treatment of wastewater by using of microalgae is a cost-effective system. Chlorella sorokiniana pa.91 and Chlorella vulgaris were studied in this research. Chlorella sorokiniana pa.91 was isolated from the dairy wastewater. In this study, treated wastewaters in preliminary and secondary treatment units of dairy wastewater treatment plant were used as medium. Maximum growth of two species of microalgae was examined in these two mediums, and also, nutrient removal was studied. The performance of two species of microalgae was studied on laboratory scale at different temperatures and light intensities. The best observed temperatures for Chlorella vulgaris and Chlorella sorokiniana pa.91 were 25 and 28 °C, respectively, and the best observed performance for them was obtained at 7500 lx. The values of specific growth rate and biomass productivity in effluent of preliminary treatment unit for Chlorella vulgaris were 0.331 day−1 and 0.214 g L−l day−1, respectively, and for Chlorella sorokiniana pa.91 were 0.375 day−1 and 0.233 g L−l day−1, respectively. Also, these parameters for Chlorella vulgaris in effluent of secondary treatment unit were determined 0.359 day−1 and 0.166 g L-l day−1, respectively, and for Chlorella sorokiniana pa.91 were obtained 0.422 day−1 and 0.185 g L−l day−1, respectively. The removal efficiency of nitrate, ammonia, phosphate, and chemical oxygen demand for Chlorella sorokiniana pa.91 and Chlorella vulgaris in both of effluents was more than 80%. Based on the results, effluent of treatment plants can be a suitable microalgae growth medium, and the microalgae can be used as effective post treatment system.
Pariya Asadi; Hassan Amini Rad; Farhad Qaderi. Comparison of Chlorella vulgaris and Chlorella sorokiniana pa.91 in post treatment of dairy wastewater treatment plant effluents. Environmental Science and Pollution Research 2019, 26, 29473 -29489.
AMA StylePariya Asadi, Hassan Amini Rad, Farhad Qaderi. Comparison of Chlorella vulgaris and Chlorella sorokiniana pa.91 in post treatment of dairy wastewater treatment plant effluents. Environmental Science and Pollution Research. 2019; 26 (28):29473-29489.
Chicago/Turabian StylePariya Asadi; Hassan Amini Rad; Farhad Qaderi. 2019. "Comparison of Chlorella vulgaris and Chlorella sorokiniana pa.91 in post treatment of dairy wastewater treatment plant effluents." Environmental Science and Pollution Research 26, no. 28: 29473-29489.
Soil remediation is one of the most important issues in environmental engineering. In this study, the effect of phenanthrene, anthracene, and benz(a)anthracene chemical structures on their removal from different soil slurries were investigated. Also, the effects of initial pollution concentration, injected ozone, water content and processing time on soil remediation were examined by response surface methodology. In the optimized condition for the soil of industrial site, anthracene, phenanthrene, and benz(a)anthracene have 67.87%, 85.2%, and 45.9% removal efficiencies, respectively. Based on these results, better water solubility, and less fine-grained soil particles are contributors to more efficient soil remediation system by ozonation. Abbreviations: ANOVA: analysis of variance; RSM: response surface methodology; CCD: central composite design; PAHs: polycyclic aromatic hydrocarbons; ANT: anthracene; PHE: phenanthrene; BaA: benz(a)anthracene; Vw: water volume; InjO3: injected ozone; T: time; CANT: initial anthracene concentration; CPHE: initial phenanthrene concentration; Wt: Weight percentage; PGSEZ: persian gulf special economic zone
Amin Tamadoni; F. Qaderi. Optimization of Soil Remediation by Ozonation for PAHs Contaminated Soils. Ozone: Science & Engineering 2019, 41, 454 -472.
AMA StyleAmin Tamadoni, F. Qaderi. Optimization of Soil Remediation by Ozonation for PAHs Contaminated Soils. Ozone: Science & Engineering. 2019; 41 (5):454-472.
Chicago/Turabian StyleAmin Tamadoni; F. Qaderi. 2019. "Optimization of Soil Remediation by Ozonation for PAHs Contaminated Soils." Ozone: Science & Engineering 41, no. 5: 454-472.
Treatment of dye wastewaters by nanoparticles is an attractive research in environmental engineering. In this research, for the treatment of wastewater containing methylene blue, a novel process was introduced in which a hybrid of ultrasound and photocatalysis was used. ZnO nanoparticle was employed as the catalyst. A synthesis technique for ZnO nanoparticles was used, and the resulted nanoparticle was capable of conducting photocatalytic activity in the visible light spectrum. Since the efficiency of a photocatalytic process in strongly dependent on the characteristics of the nanoparticle, in this study, the synthesis temperature parameter along with other parameters (that affect the ultrasonic/photocatalytic hybrid process such as pH, nanoparticle concentration, ultrasonic power, light source power, dye concentration, and time) were investigated as independent variables. Since treatment cost plays an important role in the selection for a proper treatment process, the cost of energy consumed in the hybrid process was chosen as the dependent variable. Examining the simultaneous effect of independent variables on the cost was one of the innovations of this research. Another novel aspect of this research is the determination of the synergetic or antagonistic effects of independent variables on each other. Furthermore, the optimal conditions to reach the optimum energy consumption level were also determined. Based on the SEM test results, the morphology of optimal nanoparticle (synthesized at 300 °C) was achieved, and the nanoparticle produced at this temperature was then analyzed via FTIR, XRD, EDS and BET techniques. The most appropriate conditions of the independent variables to reach the minimum energy consumption in treatment were observed at the pH of 8.76, nanoparticle concentration of 1.401 g/l, ultrasonic power of 119 W, light source power of 21.909 W, dye concentration of 45.905 ppm, and the process time of 13.695 min. According to the results, the optimum cost of the energy was about 0.001 ¢ for removing each milligram of dye and it obtained for optimum reaction conditions.
Reyhane Khalegh; Farhad Qaderi. Optimization of the effect of nanoparticle morphologies on the cost of dye wastewater treatment via ultrasonic/photocatalytic hybrid process. Applied Nanoscience 2019, 9, 1869 -1889.
AMA StyleReyhane Khalegh, Farhad Qaderi. Optimization of the effect of nanoparticle morphologies on the cost of dye wastewater treatment via ultrasonic/photocatalytic hybrid process. Applied Nanoscience. 2019; 9 (8):1869-1889.
Chicago/Turabian StyleReyhane Khalegh; Farhad Qaderi. 2019. "Optimization of the effect of nanoparticle morphologies on the cost of dye wastewater treatment via ultrasonic/photocatalytic hybrid process." Applied Nanoscience 9, no. 8: 1869-1889.
Given the vastness of the environment, modern methods for its monitoring its behavior and changes are of great importance. The Neka power plant uses the Caspian Sea to cool its machines, and then the return water is discharged directly from the power plant into the sea. So far, no precise, economical method has been provided for detecting thermal pollution in marine resources in the previous studies. Therefore, this paper proposes a method for detection of thermal pollution through remote sensing and satellite imagery. Landsat 8 can calculate the water temperature with the OLI and TIRS sensors. In this study, the water temperature around the Neka power plant was calculated at the eastern channel (the water inlet channel from the sea to the power plant) and the western channel (the water outlet channel from the power plant to the sea) in two different images using the separate window algorithm in MATLAB. The results indicated an increase in the temperature in the western channel. For the western channel, the mean and highest temperatures on May 26, 2015, were 292.7 K and 294.3 K and were 300.5 K and 303.4 K on April 10, 2016. Based on the results, this can have environmental impacts due to water thermal pollution.
S. M. Yavari; F. Qaderi. Determination of thermal pollution of water resources caused by Neka power plant through processing satellite imagery. Environment, Development and Sustainability 2018, 22, 1953 -1975.
AMA StyleS. M. Yavari, F. Qaderi. Determination of thermal pollution of water resources caused by Neka power plant through processing satellite imagery. Environment, Development and Sustainability. 2018; 22 (3):1953-1975.
Chicago/Turabian StyleS. M. Yavari; F. Qaderi. 2018. "Determination of thermal pollution of water resources caused by Neka power plant through processing satellite imagery." Environment, Development and Sustainability 22, no. 3: 1953-1975.
There are several physical, chemical and biological methods to treat petroleum pollutants. Moving bed biofilm reactor is a biological process for treatment of these pollutants. In this research, moving bed biofilm reactor has been selected owing to its eco-friendly features and because of its high efficiency in removing these pollutants. In this study, for the first time, serial moving bed biofilm reactor was introduced and used to remove petroleum pollutants from wastewater. In this biological system, two moving bed biofilm reactors were connected. Feed forward and feed backward systems were used for this connection. Also, in this research, the response surface methodology was used to model the removal efficiency of petroleum pollutants in serial moving bed biofilm reactor. The optimal operation conditions were obtained by examining three effective independent parameters: retention time (11.23-34.77h), influent total petroleum hydrocarbon concentration (164.78-585.22 mg/L), and media filling ratio (28.18-61.82%). The results of the study showed that decreasing influent total petroleum hydrocarbon concentration and increasing retention time and media filling ratio led to a decline in the food to microorganism ratio, and thereby improved removal efficiency of pollutants. The experiments showed that retention time of 23 h, influent total petroleum hydrocarbon of 164.78 mg/L, and media filling ratio of 45% yielded the highest efficiency of 97% in removing petroleum pollutants. This high efficiency under optimal conditions makes it possible to use serial moving bed biofilm reactors for petroleum wastewater treatment.
F. Qaderi; A.H. Sayahzadeh; M. Azizi. Efficiency optimization of petroleum wastewater treatment by using of serial moving bed biofilm reactors. Journal of Cleaner Production 2018, 192, 665 -677.
AMA StyleF. Qaderi, A.H. Sayahzadeh, M. Azizi. Efficiency optimization of petroleum wastewater treatment by using of serial moving bed biofilm reactors. Journal of Cleaner Production. 2018; 192 ():665-677.
Chicago/Turabian StyleF. Qaderi; A.H. Sayahzadeh; M. Azizi. 2018. "Efficiency optimization of petroleum wastewater treatment by using of serial moving bed biofilm reactors." Journal of Cleaner Production 192, no. : 665-677.
In this study, for the first time, the combination of Air Q+ software and wavelet neural network was used to predict the mortality rate caused by the increase in NO2 concentration in Tehran. In the combination of these two softwares, the wavelet neural network software was used to predict daily NO2 concentration based on 12 effective parameters, and then the annual concentration of NO2 was calculated using the daily concentration of wavelet neural network output. Then, annual concentration of NO2 was used as the input of Air Q+ software. The mortality rate was calculated by Air Q+ software. In this research, the most appropriate predictive algorithm for neural network was studied and layer recurrent algorithm was the most appropriate algorithm. Then, capability of this network was enhanced to predict future NO2 concentration by wavelet transformation, and wavelet neural network was designed. Also, NO2 concentration is predicted for future 47 months by using of the time series of the previous data and the wavelet neural network. Analyzing the sensitivity of mortality resulted from NO2 concentration was done by using of wavelet neural network and Air Q+ software, and it was concluded that the increase or decrease in the parameters affecting NO2 concentration will affect the mortality rate. This research has identified petrol consumption as the most influential parameter. The conclusion is that by lowering the 10% of petrol consumption, the mortality based on NO2 concentration in ambient air will decrease about 50%.
M. Ebrahimi Ghadi; F. Qaderi; E. Babanezhad. Prediction of mortality resulted from NO2 concentration in Tehran by Air Q+ software and artificial neural network. International Journal of Environmental Science and Technology 2018, 16, 1351 -1368.
AMA StyleM. Ebrahimi Ghadi, F. Qaderi, E. Babanezhad. Prediction of mortality resulted from NO2 concentration in Tehran by Air Q+ software and artificial neural network. International Journal of Environmental Science and Technology. 2018; 16 (3):1351-1368.
Chicago/Turabian StyleM. Ebrahimi Ghadi; F. Qaderi; E. Babanezhad. 2018. "Prediction of mortality resulted from NO2 concentration in Tehran by Air Q+ software and artificial neural network." International Journal of Environmental Science and Technology 16, no. 3: 1351-1368.
Phenol is one of the dangerous organic pollutants in industrial effluents, and it has high toxicity and numerous environmental problems. Thus, there is a growing need for more studies on its removal. The goal of this research is to provide a statistical modeling, analysis, and optimization of the simultaneous impact of temperature and phenol concentration on the efficiency of stabilization ponds in treatment of wastewater containing phenol. The experiments were performed using two stabilization ponds at laboratory scales. The experiments were designed by using response surface methodology and Design-Expert software. According to the presented model, optimum removal rate of phenol is achieve when temperature and phenol concentration are 14.20° C and 109.58 mg/l, respectively. The results showed that the removal rate dropped with decreased temperature and increased concentrations of phenol. At 20 °C, by increasing the concentration of phenol from 40 to 130 mg/l, the removal rate dropped from 73 to 45%. Based on this research results, it can be concluded that the stabilization pond had a proper performance in removing phenol, and stabilization ponds can be an alternative for complex and expensive systems.
F. Qaderi; A. H. Sayahzadeh; F. Azizpour; P. Vosughi. Efficiency modeling of serial stabilization ponds in treatment of phenolic wastewater by response surface methodology. International Journal of Environmental Science and Technology 2018, 16, 4193 -4202.
AMA StyleF. Qaderi, A. H. Sayahzadeh, F. Azizpour, P. Vosughi. Efficiency modeling of serial stabilization ponds in treatment of phenolic wastewater by response surface methodology. International Journal of Environmental Science and Technology. 2018; 16 (8):4193-4202.
Chicago/Turabian StyleF. Qaderi; A. H. Sayahzadeh; F. Azizpour; P. Vosughi. 2018. "Efficiency modeling of serial stabilization ponds in treatment of phenolic wastewater by response surface methodology." International Journal of Environmental Science and Technology 16, no. 8: 4193-4202.
Regulating the water supply for a specified district needs comprehensive quality information about the nearest aquifer. There are many methods to investigate the water quality, but in most cases, they involve time series study and do not consider space dimension. The application of advanced qualitative assessments such as geographical information systems (GIS) could be a reasonable choice. In addition, the classic Schoeller diagram (CSD) is one of the diverse drinking water assessments in which aquifer quality is distinguished according to major ions concentrations. However, the results of this diagram are limited to one point, and there is no possibility of qualitative classification of the surrounding area. Because of this, in this investigation, a new procedure, called the Schoeller-GIS (S-GIS) approach, is presented in order to apply CSD onto a district through GIS tools. For this project, the quality information of 105 wells in the study area (near Khorramabad, Iran) has been collected, and a quality assessment of the aquifer has been conducted based on both classic and novel approaches. Results indicated that, according to the CSD method, all qualitative parameters of the aquifer except Ca and Mg were located within the Good range, whereas the results of S-GIS approach categorized the study area into Good (55%), Permissible (36%), and Moderately suitable (8%). This indicates that the latest method may be more accurate by about 30% which could lead to more efficient management of water resources.
E. Babanezhad; F. Qaderi; Moslem Salehiziri. Spatial modeling of groundwater quality based on using Schoeller diagram in GIS base: a case study of Khorramabad, Iran. Environmental Earth Sciences 2018, 77, 339 .
AMA StyleE. Babanezhad, F. Qaderi, Moslem Salehiziri. Spatial modeling of groundwater quality based on using Schoeller diagram in GIS base: a case study of Khorramabad, Iran. Environmental Earth Sciences. 2018; 77 (9):339.
Chicago/Turabian StyleE. Babanezhad; F. Qaderi; Moslem Salehiziri. 2018. "Spatial modeling of groundwater quality based on using Schoeller diagram in GIS base: a case study of Khorramabad, Iran." Environmental Earth Sciences 77, no. 9: 339.
F. Qaderi; E. Babanezhad. Prediction of the groundwater remediation costs for drinking use based on quality of water resource, using artificial neural network. Journal of Cleaner Production 2017, 161, 840 -849.
AMA StyleF. Qaderi, E. Babanezhad. Prediction of the groundwater remediation costs for drinking use based on quality of water resource, using artificial neural network. Journal of Cleaner Production. 2017; 161 ():840-849.
Chicago/Turabian StyleF. Qaderi; E. Babanezhad. 2017. "Prediction of the groundwater remediation costs for drinking use based on quality of water resource, using artificial neural network." Journal of Cleaner Production 161, no. : 840-849.