Meteorological parameters as an important factor on the energy recovery of landfill gas in landfills

The effect of meteorological factors on the composition and the energy recovery of the landfill gas (LFG) were evaluated in this study. Landfill gas data consisting of methane, carbon dioxide, and oxygen content as well as LFG temperature were collected from April 2009 to March 2010 along with meteorological data. The data set were, first, used to visualize the similarity by using self-organizing maps and to calculate correlation factors. Then, the data was used with ANN to further analyze the impacts of meteorological factors. In both analysis, it is seen that the most important meteorological parameter effective on LFG energy content is soil temperatures. Furthermore, ANN was found to be successful in explaining variations of methane content and temperature of LFG with correlation coefficients of 0.706 and 0.984, respectively. ANN was proved itself to be a useful tool for estimating energy recovery of the landfill gas. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4769202

Neural network prediction of thermophilic (65 degrees C) sulfidogenic fluidized-red reactor performance for the treatment of metal-containing wastewater

The performance of a fluidized-bed reactor (FBR) based sulfate reducing bioprocess was predicted using artificial neural network (ANN). The FBR was operated at high (65 degrees C) temperature and it was fed with iron (40-90 mg/ L) and sulfate (1,000-1,500 mg/L) containing acidic (pH = 3.5-6) synthetic wastewater. Ethanol was supplemented as carbon and electron source for sulfate reducing bacteria (SRB). The wastewater pH of 4.3-4.4 was neutralized by the alkalinity produced in acetate oxidation and the average effluent pH was 7.8 +/- 0.8. The oxidation of acetate is the rate-limiting step in the sulfidogenic ethanol oxidation by thermophilic SRB, which resulted in acetate accumulation. Sulfate reduction and acetate oxidation rates showed variation depending on the operational conditions with the maximum rates of 1 g/L/d (0.2 g/g volatile solids (VS)/d) and 0.3 g/L/d (0:06 g/g VS/d), respectively. This study presents an ANN model predicting the performance of the reactor and determining the optimal architecture of this model; such as best back-propagation (BP) algorithm and neuron numbers. The Levenberg-Marquardt algorithm was selected as the best of 12 BP algorithms and optimal neuron number was determined as 20. The developed ANN model predicted acetate (R=0.91), sulfate (R=0.95), sulfide (R=0.97), and alkalinity (R=0.94) in the FBR effluent. Hence, the ANN based model can be used to predict the FBR performance, to control the operational conditions for improved process performance

Biological treatability processes of textile wastewaters using electrocoagulation and ozonation

496-500This study presents biotreatment of textile wastewaters using electrocoagulation and ozone processes. Ozonation process gave better results than electrocoagulation process. For electrocoagulation, optimum working conditions were found as follows: pH, 6.5; electrode type, iron electrode; current density, 20 mA/cm2; and reaction time, 15 min. Under these circumstances, values determined for electrocoagulation and ozonation processes, respectively, were as follows: COD removal, 73, 46%; color removal, 85, 93%; BOD/COD ratio, 0.60, 0.69; and cost per unit of wastewater treatment, 1.7, 1.3 $

Post-treatment of anaerobically-treated compost leachate by membrane systems: emphasis on molecular weight distribution

Compost leachate contains high concentrations of organic matter, sulphate and ammonia which requires combined treatment systems. In case of the use of membrane containing combined systems, the effect of pretreatment on molecular weight distribution (MWD) is important in terms of appropriate membrane selection. In this study the leachate from Istanbul full-scale composting plant was firstly treated in an anaerobic fluidized bed reactor (AFBR). Performance of the reactor was low due to the inhibiton by high ammonia content while treatment efficiencies of COD and SO42- were around 41% with 50% ammonia removal. During the anaerobic treatment high molecular weight materials were mostly converted to low molecular fractions. However, changes in the distribution of molecular fractions differed in each pollutant parameters. Subsequent membrane treatment scheme was determined according to the molecular weight distribution analyses. Particular and collodial materials from AFBR effluent was effectively treated by MF and UF membranes. Post-treatment studies were performed using four different NF and RO membranes and performance comparison was made based on removal efficiency and flux changes. BW30 membrane provided the lowest treatment efficiency while other TXN45, NF90 and XLE membranes had similar effluent quality. Effluent from all membrane systems met discharge limits and optimum treatment scheme has been suggested as AFBR+MF+UF+TXN45 based on operational flux values