Second‐generation bio‐based plastics are becoming a reality – Non‐renewable energy and greenhouse gas (GHG) balance of succinic acid‐based plastic end products made from lignocellulosic biomass
Bibliographic record
Abstract
Abstract Bio‐based and bio‐degradable plastics such as polybutylene succinate (PBS) have the potential to become sustainable alternatives to petrochemical‐based plastics. Polybutylene succinate can be produced from bio‐based succinic acid and 1,4‐butanediol using first‐generation (1G) or second‐generation (2G) sugars. A cradle‐to‐grave environmental assessment was performed for PBS products in Europe to investigate the non‐renewable energy use (NREU) and greenhouse gas (GHG) impacts. The products investigated are single‐use trays and agricultural film, with incineration, industrial composting and degradation on agricultural land as end‐of‐life scenarios. Both end products manufactured from fully bio‐based PBS and from partly bio‐based PBS (made from bio‐based succinic acid and fossil fuel‐based 1,4 butanediol) were analysed. We examine corn (1G) as well as corn stover, wheat straw, miscanthus and hardwood as 2G feedstocks. For the cradle‐to‐grave system, 1G fully bio‐based PBS plastic products were found to have environmental impacts comparable with their petrochemical incumbents, while 2G fully bio‐based PBS plastic products allow to reduce NREU and GHG by around one third under the condition of avoidance of concentration of sugars and energy integration of the pretreatment process with monomer production. Without energy integration and with concentration of sugars (i.e., separate production), the impacts of 2G fully bio‐based PBS products are approximately 15–20% lower than those of 1G fully bio‐based PBS products. The environmental analysis of PBS products supports the value proposition related to PBS products while also pointing out areas requiring further research and development. © 2018 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".