Volume 20 - 2018

In this study, a new model for biomass higher heating value (HHV) prediction based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) approach was proposed. Proximate analysis (volatile matter, fixed carbon and ash content) data for a wide range of various biomass types from the literature were used as input in model studies. Optimization of ANFIS parameters and formation of the model structure were performed by genetic algorithm (GA) and particle swarm optimization (PSO) algorithm in order to achieve optimum prediction capability. The best-fitting model was selected using statistical analysis tools. According to the analysis, PSO-ANFIS model showed a superior prediction capability over ANFIS and GA optimized ANFIS model. The Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Bias Error (MBE) and coefficient of determination (R2) for PSO-ANFIS were determined as 0.3138, 0.2545, -0.00129 and 0.9791 in the training phase and 0.3287, 0.2748, 0.00120 and 0.9759 in the testing phase, respectively. As a result, it can be concluded that the proposed PSO-ANFIS model is an efficient technique and has potential to calculate biomass HHV prediction with high accuracy.

The extensive use of pesticides for controlling insects has been widely used in agricultural activities. However, the indiscriminate use of the pesticides has inflicted serious harmful problems to humans in the ecosystem. Our study aims to evaluating the capacity of Armillaria tabescens to remove the chemical oxygen demand (COD) and biochemical oxygen demand (BOD5) at different concentration of malathion insecticide (50, 100 and 150 ppm) under agitated (130 rpm) submerged culture conditions at 27 0C after 8 and 15 days. According to our results, A. tabescens has achieved COD reduction as 52.39, 27.24, and 38.30% at concentration of 50, 100 and 150 ppm respectively on 15 days. The BOD5 reduction rates were found as 78.2, 74.76 and 81.26% at 50, 100 and 150 ppm concentration respectively at the end of the 15th days. At the end of this time period, the dried biomass of A. tabescens was weighted and we have suggested that malathion in medium reduced the biomass production compared the control group (Sabouraud dextrose broth + A. tabescens). Our experiments have focused that; A. tabescens could be an alternative and useful fungus for bioremediation of wastewater containing malathion insecticide.

Removal of Co(II) ions from aqueous solutions using chitosan-vanillin (polymer I) and chitosan-ortho-vanillin (polymer II) adsorbents has been investigated under different experimental conditions. The effect of pH, contact time, adsorbent mass, temperature, and initial concentration of studied ion on the sorption process has been studied using batch experiments. The quantity of residual ion has been estimated via atomic absorption spectrometry. The highest removal of Co(II) ions has been achieved at pH 4 with a maximum removal of 93.2% of ions after two hours of agitation. Langmuir isotherm model represents the best fit for the experimental data; whereas the highest chelation capacity was 5.899 mg g-1 and 7.651 mg g-1 for polymers I and II, respectively. Results from this study imply that chemisorption is the rate-determining step and thermodynamic parameters indicate that the uptake process is spontaneous and endothermic in nature.

The ecological structure and function of the water reservoirs deteriorate dramatically because of streams fed by the excess nitrogen-containing wastewater. To protect the water reservoirs from polluted streams, structures such as natural wastewater treatment (NWT) systems to be created inside or outside streams may be a most suitable and economical solution method to overcoming the problem. In this study, a hybrid NWT system was installed to remove nitrogenous pollutants in Karasu creek (Nigde city, Turkey) in 2014. The system built near the creek consisted of feeding basin (FB), settlement basin (SB), free water surface-constructed wetland (FWS-CW), and overland flow (OF) system respectively. Despite quite high nitrogen loading rates, the system managed to reduce NH4+-N from average 29 mg/L to 12 mg/L and TN from 44 mg/L to 19 mg/L with an average removal efficiency of 57 %. Results revealed that hydraulic and nitrogen loading rate, temperature and seasonal variation, BOD/TKN ratio, hydraulic residence time (HRT), and the use of the filter material were effective on nitrogen removal. The results suggest that the hybrid NWT systems can be used as a low-cost wastewater treatment alternative to improve water quality in streams contaminated by nitrogenous pollutants in the similar areas.