Development and comparative eco-techno-economic analysis of two carbon capture and utilization pathways for polyethylene production
Bibliographic record
Abstract
The aim of this work is the design and eco-techno-economic analysis of novel technologies for low- and high-density polyethylene production, based on CO 2 capture and utilization in the methanol-to-olefins process. Two primary routes for methanol production are investigated and compared to the conventional method: direct hydrogenation of CO 2 to methanol and tri-reforming of methane and CO 2 . The former involves the conversion of CO 2 into methanol, while the second, natural gas and CO 2 are reformed to produce methanol. Methanol is converted into ethylene which is then polymerized into polyethylene. Utilizing simulation and lifecycle assessment results, we conducted comprehensive eco-techno-economic assessments for both polymers to assess the potential contribution of these pathways to a more circular economy. The results showed that a minimum selling price of at least 5,934 USD/tonne of polymer is needed to make the processes financially attractive. Since these prices are significantly higher than market prices, they are unable to compete in the market. Consequently, the impact of CO 2 utilization credit, as a financial incentive to encourage the adoption of technologies that reduce CO 2 emissions, is also studied. The analysis revealed that a minimum credit of 668 USD/tonne of CO 2 is needed to make the process economically viable. Moreover, our e-TEA results showed that the TRM-based route is more financially viable than the CO 2 hydrogenation alternative, provided that the CO 2 mitigation credit is lower than 468 USD/tonne of CO 2 . The sensitivity analysis of various parameters is also conducted to determine the profitability of each technology at various market conditions. • CCU is used for the production of LDPE and HDPE via the intermediate methanol • TRM is used as a comparative pathway for polyethylene production • e-TEA is conducted to compare the selling price of polyethylene to market price • Electricity and equipment costs have the largest contribution to selling price • A CO 2 credit of at least 668 USD/tonne CO 2 is needed to reduce the price gap
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".