[Effect of the Food to Mass Ratio and Hydraulic Retention Time on Hydrogen Production from Fruit and Vegetable Waste].

Semi-continuous biogas production from fruit and vegetable waste by medium temperature anaerobic fermentation was conducted. Hydrogen production under different food-microorganism ratios (F/M 0.5, 0.75, 1.0, 1.5) and hydraulic retention times (HRT) (2, 3, 4 d) were investigated. The results show that in the case of a smaller F/M values (0.5 and 0.75), not all HRT stages were conducive to the continuous production of hydrogen, however, they were conducive to producing methane, especially when HRT was 3 or 4 d. Continuous hydrogen production was viable when the F/M ration was relatively higher (1.0 and 1.5), however, this was not conducive to the production of methane, with almost no methane production detected in this process. A F/M of 1.0 and a HRT of 3 d provided the best conditions for continuous hydrogen production from fruit and vegetable waste. Meanwhile, the highest and average daily volume of hydrogen production were 451.2 mL·(L·d)-1 and (186±29) mL·(L·d)-1 respectively, whereas the highest and average hydrogen production rate of volatile solids were 133 mL·g-1 and (27±5) mL·g-1 respectively. The hydrogen content was 20%-30%.

Effects of simulated flue gas on components of Scenedesmus raciborskii WZKMT.

Scenedesmus raciborskii WZKMT cultured with simulated flue gas was investigated. Cellular components, including total sugar, starch, chlorophyll, protein and lipid, were compared between simulated flue gas and 7% (v/v) CO2. Dissolution of SO2 and NO in simulated flue gas led to pH decrease and toxicity to microalgae cells. Furthermore, the death or aging of microalgae cells reduced the buffer capacity and caused decrease of simulated flue gas absorption. With 7% CO2, the highest total sugar and starch content could attain to 66.76% and 53.16%, respectively, which indicated S. raciborskii WZKMT is a desired feedstock candidate for bioethanol production. Microalgae growth and starch accumulation was inhibited, while cells produced more chlorophyll, protein and lipid when simulated flue gas was the carbon source. Fatty acids composition analysis indicated that there was no significant distinction on fatty acids relative content (fatty acid/TFA) between cells aerated using simulated flue gas and 7% CO2.

Factors affecting the performance of a single-chamber microbial fuel cell-type biological oxygen demand sensor.

Microbial fuel cells (MFCs) are devices that exploit microorganisms as biocatalysts to degrade organic matter or sludge present in wastewater (WW), and thereby generate electricity. We developed a simple, low-cost single-chamber microbial fuel cell (SCMFC)-type biochemical oxygen demand (BOD) sensor using carbon felt (anode) and activated sludge, and demonstrated its feasibility in the construction of a real-time BOD measurement system. Further, the effects of anodic pH and organic concentration on SCMFC performance were examined, and the correlation between BOD concentration and its response time was analyzed. Our results demonstrated that the SCMFC exhibited a stable voltage after 132 min following the addition of synthetic WW (BOD concentration: 200 mg/L). Notably, the response signal increased with an increase in BOD concentration (range: 5-200 mg/L) and was found to be directly proportional to the substrate concentration. However, at higher BOD concentrations (>120 mg/L) the response signal remained unaltered. Furthermore, we optimized the SCMFC using synthetic WW, and tested it with real WW. Upon feeding real WW, the BOD values exhibited a standard deviation from 2.08 to 8.3% when compared to the standard BOD5 method, thus demonstrating the practical applicability of the developed system to real treatment effluents.

Artificial intelligence techniques to optimize the EDC/NHS-mediated immobilization of cellulase on Eudragit L-100.

Two artificial intelligence techniques, namely artificial neural network (ANN) and genetic algorithm (GA) were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) concentration, N-hydroxysuccinimide (NHS) concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R(2) = 0.99). Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful.

A fractal-like kinetic equation to investigate temperature effect on cellulose hydrolysis by free and immobilized cellulase.

According to fractal-like theory in the heterogeneous system, a cellulase-catalyzed kinetic equation that contained two parameters (rate constant k and fractal dimension h) was deduced. The equation described directly the mathematical relationship between reducing sugar concentration and hydrolytic time, and accurately fitted the experimental data of free/immobilized cellulase at 37, 40, 44, 47, and 50 °C (R(2)>0.99). The fitted h value is estimated as a constant (0.6148) in these tested temperatures. The fitted k value increased with temperature increase, and the relationship agreed with Arrhenius equation (R(2)>0.98). The fractal-like equation could predict accurately the experimental data at low temperature 34 °C for free/immobilized cellulase and high temperature 53 °C for immobilized cellulase, but the prediction at 53 °C for free cellulase was not accurate enough due to its lower stability than immobilized cellulase. The application of fractal-like theory in cellulase kinetics is successful.

Cellulase deactivation based kinetic modeling of enzymatic hydrolysis of steam-exploded wheat straw.

Applying mass action law and quasi-steady-state theory, two cellulase kinetic models namely Eqs. (5) and (8) were developed on the basis of the first and second order reactions of enzyme deactivation, respectively. The two models are compared according to analysis of experimental data from enzymatic hydrolysis steam-exploded wheat straw. Both simulation and prediction results show Eq. (8) has much higher accuracy than Eq. (5). Analysis of initial hydrolysis rate is also in accordance with Eq. (8) and against Eq. (5). Fitted values of k(2) (the rate constant of product formation), k(de2) (the rate constant of enzyme deactivation) and K(e) (the equilibrium constant) determined from Eq. (8) are 0.4732 h(-1), 0.4011 L/(hg), and 16.8597 g/L, respectively. The higher the enzyme concentration is, the larger the deactivation rate.