Bioethanol production from agricultural residues as lignocellulosic biomass feedstock's waste valorization approach: A comprehensive review

Life cycle assessment and techno-economic analysis of wood-based biorefineries for cellulosic ethanol production

Poplar is widely used in the paper industry and accompanied by abundant branches waste, which is potential feedstock for bioethanol production. Acid-chlorite pretreatment can selectively remove lignin, thereby significantly increasing enzymatic efficiency. Moreover, lignin residues valorization via gasification-syngas fermentation can achieve higher fuel yield. Herein, environmental and economic aspects were conducted to assess technological routes, which guides further process optimization. Life cycle assessment results show that wood-based biorefineries especially coupling scenarios have significant advantages in reducing global warming potential in contrast to fossil-based automotive fuels. Normalization results indicate that acidification potential surpasses other indicators as the primary impact category. In terms of economic feasibility, coupling scenarios present better investment prospects. Bioethanol yield is the most critical factor affecting market competitiveness. Minimum ethanol selling price below ethanol international market price is promising with higher-levels technology. Further work should be focused on technological breakthrough, consumable reduction or replacement.

Multifaced application of AFEX-pretreated biomass in producing second-generation biofuels, ruminant animal feed, and value-added bioproducts

Lignocellulosic biomass holds a crucial position in the prospective bio-based economy, serving as a sustainable and renewable source for a variety of bio-based products. These products play a vital role in displacing fossil fuels and contributing to environmental well-being. However, the inherent recalcitrance of biomass poses a significant obstacle to the efficient access of sugar polymers. Consequently, the bioconversion of lignocellulosic biomass into fermentable sugars remains a prominent challenge in biorefinery processes to produce biofuels and biochemicals. In addressing these challenges, extensive efforts have been dedicated to mitigating biomass recalcitrance through diverse pretreatment methods. One noteworthy process is Ammonia Fiber Expansion (AFEX) pretreatment, characterized by its dry-to-dry nature and minimal water usage. The volatile ammonia, acting as a catalyst in the process, is recyclable. AFEX contributes to cleaning biomass ester linkages and facilitating the opening of cell wall structures, enhancing enzyme accessibility and leading to a fivefold increase in sugar conversion compared to untreated biomass. Over the last decade, AFEX has demonstrated substantial success in augmenting the efficiency of biomass conversion processes. This success has unlocked the potential for sustainable and economically viable biorefineries. This paper offers a comprehensive review of studies focusing on the utilization of AFEX-pretreated biomass in the production of second-generation biofuels, ruminant feed, and additional value-added bioproducts like enzymes, lipids, proteins, and mushrooms. It delves into the details of the AFEX pretreatment process at both laboratory and pilot scales, elucidates the mechanism of action, and underscores the role of AFEX in the biorefinery for developing biofuels and bioproducts, and nutritious ruminant animal feed production. While highlighting the strides made, the paper also addresses current challenges in the commercialization of AFEX pretreatment within biorefineries. Furthermore, it outlines critical considerations that must be addressed to overcome these challenges, ensuring the continued progress and widespread adoption of AFEX in advancing sustainable and economically viable bio-based industries.

Fast analysis of straw proximates based on partial least squares using near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) is a rapid measurement technique based on the spectroscopic absorption bands of specific functional groups within biomass. Its main advantages include simple preparation, precise analysis, and the ability to analyze multiple components simultaneously. Fast analysis of straw proximates (moisture, ash, and fixed carbon) has been investigated by means of NIRS. A total of 144 samples were collected, the spectral data were analyzed by partial least squares (PLS) regression and support vector regression (SVR) with four wavelength selection methods. PLS combined with competitive adaptive reweighted sampling (CARS) provided excellent predictive performance for moisture, ash, and fixed carbon. For moisture prediction, the values of RP2, RMSEP and RPD were 0.7202, 0.8196, and 2.11, respectively. For ash prediction, the values of RP2, RMSEP and RPD were 0.9307, 0.5901, and 3.69, respectively. For fixed carbon prediction, the values of RP2, RMSEP and RPD were 0.8504, 0.2735, and 2.76, respectively. Fast analysis of proximates of corn stover was possible using this NIRS system.

Microalgae to Bioenergy: Optimization of Aurantiochytrium sp. Saccharification

Microalgae are a promising feedstock for bioethanol production, essentially due to their high growth rates and absence of lignin. Hydrolysis-where the monosaccharides are released for further fermentation-is considered a critical step, and its optimization is advised for each raw material. The present study focuses on the thermal acid hydrolysis (with sulfuric acid) of Aurantiochytrium sp. through a response surface methodology (RSM), studying the effect of acid concentration, hydrolysis time and biomass/acid ratio on both sugar concentration of the hydrolysate and biomass conversion yield. Preliminary studies allowed to establish the range of the variables to be optimized. The obtained models predicted a maximum sugar concentration (18.05 g/L; R² = 0.990) after 90 min of hydrolysis, using 15% (w/v) biomass/acid ratio and sulfuric acid at 3.5% (v/v), whereas the maximum conversion yield (12.86 g/100 g; R² = 0.876) was obtained using 9.3% (w/v) biomass/acid ratio, maintaining the other parameters. Model outputs indicate that the biomass/acid ratio and time are the most influential parameters on the sugar concentration and yield models, respectively. The study allowed to obtain a predictive model that is very well adjusted to the experimental data to find the best saccharification conditions for the Aurantiochytrium sp. microalgae.