Promising Pathways to Lower Atmospheric Carbon Without Sacrificing the Petroleum Advantage
Bibliographic record
Abstract
Abstract The traditional advantage of petroleum-based transport fuels of unmatched energy-density and affordability is diluted with the requirement to lower atmospheric carbon. However, despite a significant R&D effort and investment over the last three decades, humanity is still looking for carbon neutral alternatives to petroleum that can be commercially viable. This paper presents meaningful novel approaches to deal with carbon abatement utilizing petroleum that have a better chance to succeed in fulfilling the underlying techno-economic desirables. While the multi-directional work performed in the past on the subject has informed us on a variety of related topics, going forward the society can benefit from a systematic approach to solving atmospheric CO2 problem building on the petroleum advantage. A framework formulating the challenge in terms of techno-economic and environmental requirements is presented that narrows down further work to only meaningful and promising leads. With this framework in mind a few specific pathways are proposed that naturally hold the desired traits if certain conditions are met. These conditions in turn define specific objectives of the subsequent developmental work. While it is premature to suggest any of these will develop into a commercially viable pragmatic method, due to the underlying criteria they hold a better chance to be successful. The presented pathways using advances in electro-chemistry, nanoscience, rational design, and other areas range from (a) mimicking natural fixation of CO2 as in plants to produce tailored polysaccharides or food, to (b) converting CO2 to substances such as carboxylic acids for easy and cost effective sequestration, to (c) changing the way petroleum fuel is used in internal combustion engines to alter the exit state of oxidation of carbon so that the waste product is easily and economically captured compared to the conventional waste product - CO2. One outcome from the framework results in collapse of the economic models and associated technical approaches that aim to convert CO2 to sellable products, owing mainly to the volume of the global GHG challenge. On the other hand, a common element in the proposed promising leads is to deal with the problem of carbon abatement as an added step with an associated cost. The lower this cost, the less diluted the petroleum-advantage. In this context the framework also points to a range of relative costs that the carbon abatement approaches have to work within to retain the petroleum advantage. The outlined technical approaches of carbon abatement are not previously discussed in the literature and hold the promise to help combat the global GHG challenge in a more practical and significant way.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".