Sugarcane bagasse valorization to xylitol: Techno‐economic and life cycle assessment
Bibliographic record
Abstract
Abstract A detailed techno‐economic analysis and life cycle assessment (LCA) of a novel bio‐refinery that produces xylitol from sugarcane bagasse are provided. The proposed process includes dilute acid pretreatment in pressurized conditions followed by fermentation (upstream section). The fermentation broth is then sent for separation and purification to the downstream section. Calculations are performed for a plant with 4 t/h of dry bagasse throughput. With a fermentation yield of 0.54 g xylitol per g of xylose, the plant produced 437.4 kg/h of xylitol. Upstream data are adapted from experimental studies, while ASPEN PLUS ® flowsheet simulation is used to obtain data for the downstream section. The xylitol production facility is assumed to be annexed to an existing sugar mill in India. The total utility requirement in the process is reduced using heat integration strategies. Cradle‐to‐gate scope is considered for the LCA and 1 kg of xylitol is taken as the functional unit. The product cost of xylitol is calculated to be 230 INR/kg (US$3.17/kg). For a 4 year payback period, the selling price of xylitol must be 450 INR/kg (US$6.2/kg). The fermentation and pretreatment sections are the major components of the product cost. The LCA results show that the life cycle greenhouse gas emissions are 2.759 kg CO 2 eq. per kg xylitol. The electricity requirement within the plant is identified as the major source of greenhouse gas emissions, and reduction of fermentation duration is identified as a key factor. The results identify opportunities to improve the process from an economic as well as an environmental standpoint. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".