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The ever-increasing number and production capacity of petroleum refineries in recent years have intensified the need for developing an effective and practical method for treating their wastewaters. In this study, the application of Fenton process with scrap iron powder was investigated for the treatment of a bio-refractory petroleum refinery effluent. Response surface methodology was employed with a cubic IV optimal design to optimize the process using chemical oxygen demand (COD) removal as the target response. H 2 O 2 /COD, and H 2 O 2 /Fe mass ratios as well as pH were considered as the relevant parameters. A COD removal of more than 83 % was achieved under optimal conditions (H 2 O 2 /COD 10.03, H 2 O 2 /Fe 2.66 and pH 3.0) within 90 min. Kinetics studies were conducted to investigate the effect of reaction time on COD removal. In addition, the role of post-coagulation on COD removal under optimal conditions was investigated and it was found that 37 % of COD removal occurred due to coagulation, indicating its high potential in the Fenton process.

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To evaluate the performance of Adaptive Neural-Based Fuzzy Inference System (ANFIS) model in estimating the efficiency of Pb (II) ions removal from aqueous solution by ostrich bone ash, a batch experiment was conducted. Five operational parameters including adsorbent dosage (C(s)), initial concentration of Pb (II) ions (C(o)), initial pH, temperature (T) and contact time (t) were taken as the input data and the adsorption efficiency (AE) of bone ash as the output. Based on the 31 different structures, 5 ANFIS models were tested against the measured adsorption efficiency to assess the accuracy of each model. The results showed that ANFIS5, which used all input parameters, was the most accurate (RMSE = 2.65 and R(2) = 0.95) and ANFIS1, which used only the contact time input, was the worst (RMSE = 14.56 and R(2) = 0.46). In ranking the models, ANFIS4, ANFIS3 and ANFIS2 ranked second, third and fourth, respectively. The sensitivity analysis revealed that the estimated AE is more sensitive to the contact time, followed by pH, initial concentration of Pb (II) ions, adsorbent dosage, and temperature. The results showed that all ANFIS models overestimated the AE. In general, this study confirmed the capabilities of ANFIS model as an effective tool for estimation of AE.

The presented paper describes an experimental study to reduce electrical conductivity (EC) of composting leachate-polluted water by using electrodialysis (ED) process. High efficiency, simple operation, low waste generation and selectivity are considered as major advantageous of applying ED process. Along with evaluation of ED method for desalination, the possibility of the process for COD (chemical oxygen demand) removal was also studied. The impact of- applied voltage, feed concentration and process time on ED performances were investigated. Increasing of the applied voltage and decrease of feed concentration enhanced the reduction of EC and improved the COD removal from the sample. At optimal condition (Voltage=10 Volt, feed solution=Cf/4 and time operation=120 min), the reduction of EC and COD removal were 92.7%, and 83.8%, respectively. Applying higher voltage and using more feed solution concentrations resulted in more energy consumption. The obtained results showed that ED method can be considered as an acceptable method to reduce salt and organic content.