Abstract Lignocellulosic biorefining has traditionally focused on either converting biomass into sugars for fuels or isolating solid cellulose for bioproducts. However, cost-effective strategies to maximize sugar yields while preserving crystalline cellulose remain underexplored. This study addresses that gap by optimizing cellulase enzymes to the co-production of fermentable sugars and crystalline cellulose. Laboratory-scale results also informed a techno-economic analysis (TEA) to evaluate the feasibility of industrial-scale implementation. To this end, a selective hydrolysis process was developed to target hemicelluloses and amorphous cellulose, while retaining crystalline regions, using an optimized enzyme cocktail tested on three feedstocks: unbleached hardwood pulp, wild-type poplar, and clustered regularly interspaced short palindromic repeats (CRISPR)-edited poplar. Optimization across varying pH and temperature conditions enabled effective selective hydrolysis. Low-lignin unbleached pulp and CRISPR-edited poplar, each containing less than 15% lignin on a dry weight basis, exhibited improved enzymatic accessibility and eliminated the need for pretreatment, resulting in higher sugar yields (74 g/L and 33 g/L, respectively) and more efficient downstream processing. An engineered yeast strain co-fermented C5 and C6 sugars into ethanol, leaving behind high-crystallinity cellulose. CRISPR-edited poplar outperformed wild type, with 18% more sugar and 25% more ethanol yield, while enhancing cellulose crystallinity. TEA estimated crystalline cellulose production costs at $4,438 per metric tonne from unbleached pulp and $1,474 from CRISPR-edited biomass, highlighting the economic advantage of engineered feedstocks. This work presents a novel lignocellulosic biorefining approach that, for the first time, prioritizes the co-production of fermentable sugars and crystalline cellulose from low-lignin biomass.

Abstract Physicochemical and operational parameters affect microbial communities, impacting anaerobic digestion (AD) systems. Microbial dynamics in response to these parameters were temporally investigated by DNA and cDNA of the 16 S rrna gene in a pilot-scale hybrid anaerobic reactor (HAnR) fed with sugarcane vinasse. Key microbes for biogas production, including Bacteroidetes -vadinHA17, Paludibacteraceae -H1, Prolixibacteraceae , Desulfovibrio , Syntrophobacter and Methanospirillum , were favored by the maintenance of volatile fatty acids (VFA) < 3700 mg.L − 1 , pH ≥ 5.6, temperature ≥ 29.8 °C, chemical oxygen demand (COD) < 31.4 g.L − 1 and organic loading rate (OLR) < 9.7 kg.COD.m − 3 .d − 1 . Temperature and pH also favored the redundancy of fermentation and H 2 -mediated methanogenesis and the evenness and diversity indexes, all related to biogas quality. Concentrations up to 2,050 mg.SO 4 2− .L − 1 , 3,270 mg.K.L − 1 , 367 mg.Mg.L − 1 , 0.4 mg.Cu.L − 1 and 1.1 mg.Zn.L − 1 led to adverse effects over microbial abundance, functional redundancy and ecology, but tolerant microorganisms, like Paludibacteraceae , Anaerolineaceae and Methanosaeta , kept fermentation and methanogenesis ongoing, although less efficiently. Microbial interactions were also affected by evaluated parameters beyond metabolic dependence. This study highlights the importance of parameter monitoring in scaled-up AD reactors to promote the adequate establishment of microbial communities and therefore contribute to system stability.

Abstract Annually, over 92 million metric tonnes (Mt) of textile waste are produced globally, with 17 Mt discarded in the US alone. Textile waste is typically comprised of approximately 50% biomass-derived cellulosic fiber and 50% fossil carbon-derived synthetic fiber, with the biogenic portion representing a global CO 2 removal capacity estimated at 75 Mt CO 2 (14 Mt CO 2 in the US alone). Bioenergy with carbon capture and storage (BECCS) offers a promising solution for permanently removing atmospheric CO 2 by converting biomass into energy while capturing and storing the resulting carbon emissions. Despite its potential, textile waste remains an underutilized feedstock in BECCS research and deployment. This study evaluates the techno-economic feasibility and environmental performance of small-scale modular BECCS systems that process textile waste to produce electricity and achieve net-negative emissions. Four waste-to-energy scenarios were modeled using 100% cotton or a 50/50 cotton–polyethylene terephthalate (PET) blend, with and without carbon capture. In 2018, the US EPA reported that 66% of discarded textiles were landfilled. As a result, a fifth landfilling end-of-life scenario was introduced to compare valorization scenarios to a baseline scenario. Life cycle assessment (LCA) and techno-economic analysis (TEA) are applied to quantify levelized cost of electricity (LCOE) and CO 2 removal. For 100% cotton waste, the removal cost was 329 USD per metric ton (t) CO 2 e, significantly lower than 777 USD per t-CO 2 e for 50/50 cotton-PET. The carbon removal efficiencies of 100% cotton and 50/50 cotton-PET textile waste materials were 91% and 59%, respectively. The lowest LCOE was observed for a 50/50 cotton-PET mixture with CCS at 0.17 USD/kWh, due to the relatively high energy density of the feedstock. In contrast, 100% cotton with CCS had the highest LCOE at 0.29 USD/kWh due to the lower feedstock energy density, higher capital expenditure (CAPEX), and reduced CO 2 sales, due to the lower carbon content in cotton compared to PET. In addition, the LCOE for the 50/50 cotton-PET without CCS was 0.18 USD/kWh and the LCOE for the 100% cotton without CCS was 0.24 USD/kWh. The LCA with CCS showed that direct and indirect emissions lead to high acidification potential due to ammonia release via monoethanolamine (MEA) degradation, compared to electricity production without CCS. Additionally, the production of MEA itself exhibited high ecotoxicity potential compared to other process inputs such as NaOH and activated carbon. Overall, this study demonstrated textile waste’s potential as a viable alternative for producing bioenergy and waste-derived energy. In terms of overall environmental impact, all four valorization scenarios significantly outperformed landfilling.