Journal of Applied Research in Water and Wastewater
Volume:2 Issue: 2, Summer and Autumn 2015

Environmental pollution caused by industrial effluents is an important issue. Biosorption of crystal violet (CV) from aqueous solution using pearl millet powder (PMP) was investigated in a batch mode. The use of pearl millet powder was as an additional substitution of activated carbon for the adsorption of CV from its aqueous solution. The adsorbent pearl millet powder was productively used for the biosorption of dye from its aqueous solution. The effect of initial concentration for CV, sorption time, dose of adsorbent, pH and temperature on dye removal were studied. The equilibrium sorption isotherms have been analyzed by the Freundlich, Langmuir and Temkin models. Sorption kinetic is quick and the data agree well with pseudo-first order kinetic model. But the kinetics studies were provided with Pseudo second order. The adsorption capacity (Qo) of PMP was found to be 48.535 mg/g. Thermodynamic parameters such as the free energy change (∆Go), enthalpy change (∆Ho) and entropy change (∆So) were determined from Van’t Hoff plot. The data reported shows the adsorption process is endothermic in nature.

In current study, sulfonic acid-functionalized ordered nanoporous Na+-Montmorillonite (SANM) has been utilized as the adsorbent for the removal of a cationic dye, methylene blue (MB), from aqueous solution using the batch adsorption technique under different conditions such as temperature, adsorbent dosage, initial dye concentration, contact time, and pH solution. The optimum sorption conditions were found as following: contact time 10 min, initial dye concentration 800 mg/L, adsorbent dose 0.3 g and temperature 25 °C. The results indicate that the process is pH independent. The sorption capacity was 500 mg/g for this dye. Different thermodynamic parameters i.e., changes in standard free energy, enthalpy, and entropy have also been evaluated. The ΔHads and ΔSads values are thus found to be +38240 (J/mol) and ΔSads138.43 J/K, respectively, while the ΔGads values is -3012.14 J in 298 K and it has been found that the reaction was spontaneous and endothermic in nature. On the other hand, Kinetic parameters have been investigated with pseudo first and second order. The result of experimental data indicates that pseudo second order equation fit better than the other.

In this study, ozone combination with a sequencing batch reactor was tested in laboratory scale for treating a soft drink wastewater characterized by high concentrations of chemical oxygen demand (COD). A bench scale aerobic sequencing batch reactor (SBR) is carried out by two stages. The system was operated under three different mixed liquid suspended solids (MLSS) concentrations (3000, 4500, 6000 mg/l). The results show that the integrated ozonation with biological process was able to achieve high removal efficiencies for chemical oxygen demand (COD), with residual concentrations much lower than the current discharge limits. Also, the process was characterized by a very low MLSS concentration. Hence, the ratio between ozone dose and the COD removal was 0.72, indicating that the removed COD was higher than the dosed ozone. Artificial neural networks (ANN) was also employed to model the COD data obtained. A network consisting of two layers of five neurons in the hidden layer was considered. Regression coefficient between experimental data and data predicted by neural networks and root mean square error (R2, RMSE) obtained 0.991, 80.36, respectively. Very low error in the network estimation confirmed validity of the obtained networks for further analysis and optimization.

Nitrogen in treatment plants effluent causing problems such as oxygen depletion, toxic impacts on aquatic organisms, eutrophication, and negative impacts on public health. The aim of present study was to determine the performance of integrated system activated sludge/nitrifying trickling filter to improve nitrification in the wastewater treatment plant of Isfahan. In this applied experimental study, an integrated activated sludge (AS) process (in full scale) was used with a trickling filter (TF) (in semi-industrial scale). The diameter and height of TF were 1.8 m and 3 m of steel, respectively. The volume of polypropylene media was 8 m3 and surface area of 240 m2/m3. The hydraulic loading rate during the startup period was 2.4 m3/h which was raised to 7.2 m3/h in the operation period. Flow rate, BOD5, COD, pH, TKN, N-NH3, N-NO2-, N-NO3-, alkalinity and temperature were measured weekly according to standard methods during the operation period. The effect of filter depth on nitrification was studied in 3.6, 4.2, 5.4 and 6 m and HRT of 3.6 m/h. The samples were analyzed by SPSS. The results showed that the best hydraulic and ammonia loading rate achieved here were 3.6-4.2 m/h and 2-2.5 g N/m2d, respectively. The AS/TF system efficiency were 86 % COD removal, 94 % BOD5 removal, 70 % turbidity removal, 94.4 % TSS removal, 55.5-75.5 % TKN removal and 85 % nitrification, respectively. The highest efficiency to reduce of wastewater pollution and nitrification was occurred in depth 4.5 m. Integration of the activated sludge and trickling filter processes, especially in old wastewater treatment plants is a good way to reduce the amounts of nitrogen in treatment plants effluent.

Novel electrospun polyacrylonitrile (PAN) nanofiber mats and PAN fabric were chemically modified by dissolved anhydrous stannous chloride diethyl ether saturated with hydrogen chloride to contain aldehyde groups on their surfaces, which are suitable for ammonium adsorption due to their high adsorption affinity for NH4+ ion. Scanning electron microscopy (SEM), and Fourier-transform infrared spectra (FT-IR) were employed to characterize the prepared adsorbents. FT-IR spectra of these adsorbents confirmed that aldehyde groups are successfully formed on the surface of these chemically modified adsorbents. The aldehydic electrospun PAN nanofiber mats and aldehydic PAN fabric were assessed for their chelating property with NH4+ ion from aqueous solution. The effects of contact time on the amounts of ammonium adsorbed into the prepared adsorbents were also studied. Results revealed that ammonium removal increased by increasing contact time which finally reached equilibrium at about 3.5 h and 4 h for aldehydic electrospun PAN nanofiber mats and aldehydic PAN fabric, respectively. The adsorption performance of these prepared adsorbents for ammonium adsorption with initial ammonium concentration of 300 ppm via isotherm studies was investigated. The maximum ammonium removal efficiency (% R) was 48.33 and 70 for aldehydic electrospun PAN nanofiber mats and PAN fabric, respectively. Results indicated that the adsorption of ammonium by both prepared adsorbents followed Langmuir isotherm.

The main objective of this study was to synthesize an environmentally friendly nano-structural adsorbent. These nano magnetic particles can be applied to remove heavy metal ions from industrial wastewater because the surface of the particles is covered with SiO2, and the SiO2 is inactive and can adsorb heavy metal ions. Tests were then conducted to study the adsorption of Cu(II) ions onto Fe3O4@SiO2 from an aqueous solution for the effect of contact time, adsorbent dose, solution pH and concentration of metal ions in batch systems. The equilibrium data were analyzed using the Langmuir and Freundlich isotherm by nonlinear regression analysis and found that the adsorption isotherm data will better fit by Langmuir model. The maximum adsorption capacities of Cu (II) were 47 mg/g. Fe3O4@SiO2 was regenerated and found to be suitable for reuse in successive adsorption-desorption cycles 5 times without significant loss of adsorption capacity.

Urmia Lake’s water surface area is among the most important parameters needed for water balance analysis. Periodical measurement of this parameter directly by conventional topography almost seems impossible since it is costly and time – consuming. Such limitations highlight the needs for new approaches to be taken, namely remote sensing technique which could provide a good approximation of lake’s surface area in terms of some other parameters available or at least easily measured. This paper considers development of a new model for lake’s surface area measurement according to available water levels and its comparison with other methods in this field as well as the calculations regarding salt-land formation and coastline changes. High resolution images provided by NASA satellites, Aqua and Terra were collected and passed an image processing stage through MATLAB software for surface area calculations. Finally, the water level and surface area values resulted from the home made code, were put together to reach relationship. The comparison between the results of proposed method and provided data by Eastern Azerbaijan Water Organization and also a similar study indicated that the proposed image processing technique has good performance to estimate the surface area of Urmia Lake. The maximum error between the results of proposed model and a similar study which was used combination method of Cellular Automata and Markov Chain was 5.96 % which indicates the good performance of image processing technique in estimation of surface area of Urmia Lake.