Model-Based Experimental Design to Estimate Kinetic Parameters of the Enzymatic Hydrolysis of Lignocellulose

A Novel Kinetic Modeling of Enzymatic Hydrolysis of Sugarcane Bagasse Pretreated by Hydrothermal and Organosolv Processes

Lignocellulosic biomasses have a complex and compact structure, requiring physical and/or chemical pretreatments to produce glucose before hydrolysis. Mathematical modeling of enzymatic hydrolysis highlights the interactions between cellulases and cellulose, evaluating the factors contributing to reactor scale-up and conversion rates. Furthermore, this study evaluated the influence of two pretreatments (hydrothermal and organosolv) on the kinetics of enzymatic hydrolysis of sugarcane bagasse. The kinetic parameters of the model were estimated using the Pikaia genetic algorithm with data from the experimental profiles of cellulose, cellobiose, glucose, and xylose. The model considered the phenomenon of non-productive adsorption of cellulase on lignin and inhibition of cellulase by xylose. Moreover, it included the behavior of cellulase adsorption on the substrate throughout hydrolysis and kinetic equations for obtaining xylose from xylanase-catalyzed hydrolysis of xylan. The model for both pretreatments was experimentally validated with bagasse concentration at 10% w/v. The Plackett-Burman design identified 17 kinetic parameters as significant in the behavior of process variables. In this way, the modeling and parameter estimation methodology obtained a good fit from the experimental data and a more comprehensive model.

Bio-ionic liquid pretreatment and ultrasound-promoted enzymatic hydrolysis of black soybean okara

The effective processing method to produce fermentable sugars and modify the microstructure of black soybean okara using bio-ionic liquid (bio-IL) pretreatment and ultrasound-promoted enzymatic hydrolysis was investigated. The morphology and structural characteristics of okara before and after bio-IL pretreatment and enzymatic hydrolysis under different ultrasonic frequencies were analyzed by field emission scanning electron microscope (FE-SEM), X-ray energy dispersive spectrometer (EDS), and Fourier transform infrared spectroscopy (FTIR). Without pretreatment, the production of total reducing sugar (TRS) under ultrasound (40 kHz/300 W) was 3.4 times of that without ultrasound. Using the bio-IL choline acetate ([Ch][OAc]) in water for the pretreatment of black soybean okara, the TRS production of enzymatic hydrolysis was further increased to 5.2 times of that without ultrasound in 4 h of reaction. The analysis by FTIR and EDS showed that the highly structured matrix of okara was unfolded and broken by the action of combining ultrasound and choline acetate pretreatment, due to which the surface structures with large pores were presented to facilitate the reduction of unfavorable hindrance for enzymatic hydrolysis. The simplified kinetic model was proposed to describe the transport and reaction phenomena of enzymes in a solid-liquid system by using two kinetic parameters to show the impeded behavior of enzyme within the matrix of okara. The combination of bio-IL pretreatment and ultrasound-promoted enzymatic hydrolysis was able to make the efficient structural changes of black soybean okara to enhance the digestion of enzymes, and the okara could be valorized for use in foods.

Emissions of fine particulate nitrated phenols from the burning of five common types of biomass

Nitrated phenols are among the major constituents of brown carbon and affect both climates and ecosystems. However, emissions from biomass burning, which comprise one of the most important primary sources of atmospheric nitrated phenols, are not well understood. In this study, the concentrations and proportions of 10 nitrated phenols, including nitrophenols, nitrocatechols, nitrosalicylic acids, and dinitrophenol, in fine particles from biomass smoke were determined under three different burning conditions (flaming, weakly flaming, and smoldering) with five common types of biomass (leaves, branches, corncob, corn stalk, and wheat straw). The total abundances of fine nitrated phenols produced by biomass burning ranged from 2.0 to 99.5 μg m^-3. The compositions of nitrated phenols varied with biomass types and burning conditions. 4-nitrocatechol and methyl nitrocatechols were generally most abundant, accounting for up to 88-95% of total nitrated phenols in flaming burning condition. The emission ratios of nitrated phenols to PM_2.5 increased with the completeness of combustion and ranged from 7 to 45 ppmm and from 239 to 1081 ppmm for smoldering and flaming burning, respectively. The ratios of fine nitrated phenols to organic matter in biomass burning aerosols were comparable to or lower than those in ambient aerosols affected by biomass burning, indicating that secondary formation contributed to ambient levels of fine nitrated phenols. The emission factors of fine nitrated phenols from flaming biomass burning were estimated based on the measured mass fractions and the PM_2.5 emission factors from literature and were approximately 0.75-11.1 mg kg^-1. According to calculations based on corn and wheat production in 31 Chinese provinces in 2013, the total estimated emission of fine nitrated phenols from the burning of corncobs, corn stalks, and wheat straw was 670 t. This work highlights the apparent emission of methyl nitrocatechols from biomass burning and provides basic data for modeling studies.

A discretized model for enzymatic hydrolysis of cellulose in a fed-batch process

In the enzymatic hydrolysis of cellulose, several phenomena have been proposed to cause a decrease in the reaction rate with increasing conversion. The importance of each phenomenon is difficult to distinguish from batch hydrolysis data. Thus, kinetic models for the enzymatic hydrolysis of cellulose often suffer from poor parameter identifiability. This work presents a model that is applicable to fed-batch hydrolysis by discretizing the substrate based on the feeding time. Different scenarios are tested to explain the observed decrease in reaction rate with increasing conversion, and comprehensive assessment of the parameter sensitivities is carried out. The proposed model performed well in the broad range of experimental conditions used in this study and when compared to literature data. Furthermore, the use of data from fed-batch experiments and discretization of the model substrate to populations was found to be very informative when assessing the importance of the rate-decreasing phenomena in the model.