Comparison of chitosan based nano-adsorbents for dairy industry wastewater treatment through response surface methodology and artificial neural network models.

The present investigation was focused to compare chitosan based nano-adsorbents (CZnO and CTiO2) for efficient treatment of dairy industry wastewater using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) models. The nano-adsorbents were synthesized using chemical precipitation method and characterized by using scanning electron microscope with elemental detection sensor (SEM-EDS) and atomic force microscope (AFM). Maximum %RBOD (96.71 and 87.56%) and %RCOD (90.48 and 82.10%) for CZnO and CTiO2 nano-adsorbents were obtained at adsorbent dosage of 1.25 mg/L, initial biological oxygen demand (BOD) and chemical oxygen demand (COD) concentration of 100 and 200 mg/L, pH of 7.0 and 2.00, contact time of 100 and 60 min, respectively. The results obtained for both the nano-adsorbents were subject to RSM and ANN models for determination of goodness of fit in terms of sum of square errors (SSE), root mean square error (RMSE), R2 and Adj. R2, respectively. The well trained ANN model was found superior over RSM in prediction of the treatment effect. Hence, the developed CZnO and CTiO2 nano-adsorbents could be effectively used for dairy industry wastewater treatment.

Do emissions from thermal power plants affect crop productivity? A study from the vicinity of Bellary Thermal Power Station, Karnataka, India.

In the present study, ambient air quality was monitored during July to November 2013 in the vicinity of Bellary Thermal Power Station (BTPS), Karnataka to assess the impact of pollutants emitted from power plant on the productivity of maize (Zea mays L.). Atmospheric pollutant load were measured in five different villages at varying distances and directions from thermal power plant, with the village farthest away from BTPS (Yelubenchi) as control. Maize yield was also estimated in these locations and correlated to the pollutant concentrations. It was found that, both particulate matter and SO2 which are indicators of emissions from coal-fueled power plants were highest in Thimmalapur village located in the predominant down wind direction. A significant reduction in maize yield was noticed (8197 to 6509 kg ha-1 for seed and 14041 to 9933 kg ha-1 for stover) across the gradient in distance and direction from BTPS which might be influenced by the pollutants emitted. The implications of these observations are further discussed in the paper.