The biodegradation of Cypermethrin (20 to 125 mg/L) in effluent using batch activated sludge was studied. Degradation was found to occur to a great extent only in the presence of Pseudomonas (IES-Ps-1) culture. Under aerobic conditions using mechanical aerators, Cypermethrin (20 mg/L) was almost completely degraded in just over 48 h at ambient temperature. Further loading of organic compound in subsequent experiments demonstrated that IES-PS-1was capable to degrade 82 % Cypermethrin at 40 mg/L dose in approximately 48 h. When the concentration was increased to 80 mg/L, 50% degradation of this compound was observed. Over this time period the cells could utilize only 17 % of Cypermethrin when it was given 125 mg/L, respectively. These findings indicate that increased concentration of Cypermethrin has a marked effect on biodegradation performance of IES-Ps-1 with a modest increased in the duration of lag phase, but did not lead to complete inhibition or cell death. These results proved that IES-Ps-1 is responsible for Cypermethrin degradation. Such finding may be useful in designing a scale-up in situ or on-site hazardous waste bioremediation process for field application.      

Biodesulfurization of coal has been carried out in batch culture of single strain and mixed culture of sulfur oxidizing bacteria. The pure cultures of Thiobacillus thiooxidans and Thiobacillus ferrooxidans utilized inorganic sulfur content of Malaysian coal. The chemolithotroph bacteria were able to grow on coal and metabolize the coal's sulfur content. The batch cultures of coal with 3-5 percent sulfur were used for growing microorganisms. A few species of bacteria and fungi had potential to utilize coal complex media, which were isolated from coal rice hulls and pharmaceutical wastewater. Asperigillus niger and Thiobacillus species isolated from coal, fungi from rice hulls and Saccharomyces species from wastewater, all microorganisms capable to grow on coal. The main concern was the sulfur oxidizing bacteria were screened out from all non-sulfur reducing bacteria. In the Batch cultures, the biooxidation coal's sulfur was affected by several parameters, such as pH, nutrients, agitation rate, growth stimulants and percentage coal. The trace amount of magnesium and cobalt ions, 200 rpm agitation rate with initial pH of2.6 for mixed culture of Thiobacillus thiooxidans and Thiobacillus ferrooxidans showed maximum growth rate and optimum batch operating conditions. The highest sulfur oxidation was obtained at the optimal Thiobacillus growth rate. Morethan 75 percent of sulfur was removed from coal. The biooxidation of coal, the kinetic model followed by Monod rate equation with specific growth rate,  mmax= 4.8 d-1 and rate constant, Ks = 16.7 g/L.

Mathematical modeling and simulation of microbial Polyhydroxybutyrate (PHB) production process is beneficial for optimization, design, and control purposes. In this study a batch model developed by Mulchandani et al., [1] was used to simulate the process in MATLAB environment. It was revealed that the kinetic model parameters were estimated off the optimal or at a local optimal point. Therefore, an optimization program was written using AM TLAB codes to estimate those parameters again. It resulted in a significant improvement in the accuracy of Mulchandanis kinetic model. The batch model was evaluated using two batch experiments performed in this work and also Mulchandanis batch data when kinetic model parameter values estimated in this work were used. Visual comparisons between the model profiles and experimental data indicate that the model represents the process reasonably. A goodness of fit criterion used in this work and some similar researches proved higher accuracy of Mulchandanis model using this works kinetic parameter values compared to other models. Theoretical model verification was also performed that lead to identification of the possible limitations of the model.

Background and Objective: Considering the importance of environmental protection and necessity of using new energy sources and innovative fuels, using of renewable energies have been a great concern. Due to this necessity, in this study, mathematical modeling and simulation of a batch bioreactor to produce methane from livestock waste was investigated numerically. Method: The relationship between microorganism’ s growth rate and substrate concentration were established by Monod model. The equations of mathematical model were solved with fourth order Rung Kutta. The effect of initial microorganisms’ concentration on methane production was also investigated. Initial concentration of substrate and microorganisms are 51. 74 g/L and 1. 61 g/L, respectively. Findings: The results revealed that the mathematical model average deviation from experimental data is 8. 53%. The amount of methane produced after 70 days is equal to 10. 29 g/L. The substrate disintegration and methane production are a function of substrate retention time. Enhancement in the initial concentration of microorganisms causes methane gas production in less time. The amount of methane gas produced is independent of initial microorganisms’ concentration. Discussion and Conclusion: The model which presented in this study could be used to predict the time required to carry out the reaction, ooptimum performance of bioreactor, the relevant process equipment design, scale up of equipment such as digestive and appropriate control of operation to produce high-purity methane and higher volume of biogas in the bioreactor.

This paper deals with batch process control in presence of unmodeled dynamics. An estimator is designed to estimate unmodeled dynamics without need of output differentiation and then, a Global Linearized Control (GLC) law is developed. The overall controller-estimator shows a good behavior against various disturbances and uncertainties in the process as well as unmodeled dynamics.