Combination effect of pH and acetate on enzymatic cellulose hydrolysis

The productivity and efficiency of cellulase are significant in cellulose hydrolysis. With the accumulation of volatile fatty acids (VFAs), the pH value in anaerobic digestion system is reduced. Therefore, this study will find out how the pH and the amount of acetate influence the enzymatic hydrolysis of cellulose. The effects of pH and acetate on cellulase produced from Bacillus coagulans were studied at various pH 5-8, and acetate concentrations (0-60 mmol/L). A batch kinetic model for enzymatic cellulose hydrolysis was constructed from experimental data and performed. The base hypothesis was as follows: the rates of enzymatic cellulose hydrolysis rely on pH and acetate concentration. The results showed that the suitable pH range for cellulase production and cellulose hydrolysis (represents efficiency of cellulase) was 2.6-7.5, and 5.3-8.3, respectively. Moreover, acetate in the culture medium had an effect on cellulase production (K1= 49.50 mmol/L, n=1.7) less than cellulose hydrolysis (K1=37.85 mmol/L, n=2.0). The results indicated that both the pH of suspension and acidogenic products influence the enzymatic hydrolysis of cellulose in an anaerobic environment. To enhance the cellulose hydrolysis rate, the accumulated acetate concentration should be lower than 25 mmol/L, and pH should be maintained at 7.     

Combination e ect of pH and acetate on enzymatic cellulose hydrolysis

The productivity and e ciency of cellulase are significant in cellulose hydrolysis. With the accumulation of volatile fatty acids (VFAs), the pH value in anaerobic digestion system is reduced. Therefore, this study will find out how the pH and the amount of acetate influence the enzymatic hydrolysis of cellulose. The e ects of pH and acetate on cellulase produced from Bacillus coagulans were studied at various pH 5–8, and acetate concentrations (0–60 mmol/L). A batch kinetic model for enzymatic cellulose hydrolysis was constructed from experimental data and performed. The base hypothesis was as follows: the rates of enzymatic cellulose hydrolysis rely on pH and acetate concentration. The results showed that the suitable pH range for cellulase production and cellulose hydrolysis (represents e ciency of cellulase) was 2.6–7.5, and 5.3–8.3, respectively. Moreover, acetate in the culture medium had an e ect on cellulase production (KI = 49.50 mmol/L, n = 1.7) less than cellulose hydrolysis (KI = 37.85 mmol/L, n = 2.0). The results indicated that both the pH of suspension and acidogenic products influence the enzymatic hydrolysis of cellulose in an anaerobic environment. To enhance the cellulose hydrolysis rate, the accumulated acetate concentration should be lower than 25 mmol/L, and pH should be maintained at 7.     

Neural-fuzzy control system application for monitoring process response and control of anaerobic hybrid reactor in wastewater treatment and biogas production

Based on the developed neural-fuzzy control system for anaerobic hybrid reactor (AHR) in wastewater treatment and biogas production, the neural network with backpropagation algorithm for prediction of the variables pH, alkalinity (Alk) and total volatile acids (TVA) at present day time t was used as input data for the fuzzy logic to calculate the influent feed flow rate that was applied to control and monitor the process response at di erent operations in the initial, overload influent feeding and the recovery phases. In all three phases, this neural-fuzzy control system showed great potential to control AHR in high stability and performance and quick response. Although in the overloading operation phase II with two fold calculating influent flow rate together with a two fold organic loading rate (OLR), this control system had rapid response and was sensitive to the intended overload. When the influent feeding rate was followed by the calculation of control system in the initial operation phase I and the recovery operation phase III, it was found that the neural-fuzzy control system application was capable of controlling the AHR in a good manner with the pH close to 7, TVA/Alk < 0.4 and COD removal > 80% with biogas and methane yields at 0.45 and 0.30 m3/kg COD removed.     

Application of the IPCC Waste Model to solid waste disposal sites in tropical countries: case study of Thailand

Measurements of landfill methane emission were performed at nine solid waste disposal sites in Thailand, including five managed sanitary landfills (four deep and one shallow landfills) and four unmanaged landfills (three deep and one shallow dumpsites). It was found that methane emissions during the rainy season were about five to six times higher than those during the winter and summer seasons in the case of managed landfills and two to five times higher in the case of unmanaged landfills. Methane emission estimate using the Intergovernmental Panel on Climate Change (IPCC) Waste Model was compared with the actual field measurement from the studied disposal sites with methane correction factors and methane oxidation factors that were obtained by error function analysis with default values of half-life parameters. The methane emissions from the first-order decay model from the IPCC Waste Model yielded fair results compared to field measurements. The best fitting values of methane correction factor were 0.65, 0.20, 0.15, and 0.1 for deep landfills, shallow landfills, deep dumpsites, and shallow dumpsites, respectively. Using these key parameters in the case of Thailand, it was estimated that 89.22 Gg of methane were released from solid waste disposal sites into the atmosphere in 2006.     

Kinetics and dynamic modelling of batch anaerobic digestion of municipal solid waste in a stirred reactor

A series of batch, slurry anaerobic digestion experiments were performed where the soluble and insoluble fractions, and unwashed MSW were separately digested in a 200l stirred stainless steel vessel at a pH of 7.2 and a temperature of 38 degrees C. It was found that 7% of the total MSW COD was readily soluble, of which 80% was converted to biogas; 50% of the insoluble fraction was solubilised, of this only 80% was converted to biogas. The rate of digesting the insoluble fraction was about four times slower than the rate of digesting the soluble fraction; 48% of the total COD was converted to biogas and 40% of the total nitrogen was converted to ammonia. Soluble and insoluble fractions were broken down simultaneously. The minimum time to convert 95% of the degradable fraction to biogas was 20 days. The lag phase for the degradation of insoluble fraction of MSW can be overcome by acclimatising the culture with the soluble fraction. The rate of digestion and the methane yield was not affected by particle size (within the range of 2-50mm). A dynamic model was developed to describe batch digestion of MSW. The parameters of the model were estimated using data from the separate digestion of soluble and insoluble fractions and validated against data from the digestion of unwashed MSW. Trends in the specific aceticlastic and formate-utilising methanogenic activity were used to estimate initial methanogenic biomass concentration and bacterial death rate coefficient. The kinetics of hydrolysis of insoluble fraction could be adequately described by a Contois equation and the kinetics of acidogenesis, and aceticlastic and hydrogen utilising methanogenesis by Monod equations.