Bibliographic record
Abstract
Abstract Business as usual with consumption of fossil energy will see rapidly rising atmospheric CO2 concentration in the coming decades, unless radical measures are taken for capture and sequestration of carbon. Of the various approaches known to accomplish this, a closer examination of the two prominent methods of sequestration, namely, geo-sequestration and biosequestration and their large scale implementation will be necessary. As previously shown, preservation of the produced biomass (via conversion to charcoal) is a critical step in making the biosequestration work. The benefits of a two step charcoal approach, unparalleled by other methods, include permanence of sequestration, ready verification, the global applicability of the method, and creation of an energy bank for the future generations. However, two apparent issues with this approach are the associated length of time and land requirements. In this paper a couple of ways to solve the land requirement issue are discussed. It is shown that by tapping into the natural cycle of biomass production-decomposition to procure biomass for charcoal sequestration (an approach named as DUCS) eliminates any significant land requirement. According to this method, selective and intelligent use of the annual terrestrial litter fall will not only help accelerate the process of sequestration and obviate the land requirement but also have the overarching benefit of reducing overall sequestration costs. This approach is compared with biofuels use (also aimed at GHG reduction) both in terms of effectiveness and potential cost. Furthermore a practical way forward to initiate implementation of DUCS is discussed. Introduction Excess CO2 emitted into the atmosphere on account of continued consumption of fossil fuels can be offset by capturing it at industrial sources and pumping it into deep geological formations1 or by growth of biomass2 employing naturally occurring photosynthesis. Biomass in this context refers to non-fossil organic materials such as wood, straw, vegetable oils, and biodegradable wastes from plants or animals and agricultural residues that could be used for energy generation. It also includes aquatic living, or recently dead organic material such as phytoplankton or algae. While the technology for CO2 capture and sequestration in eological formations (geo-sequestration) exists, the main drawback of this approach is the associated high cost3 and the fact that it is practical only in the vicinity of concentrated sources of CO2, such as large industrial complexes and power generation plants. Additionally, this method requires raising CO2 to higher pressures which, being an energy intensive process, generates even more CO2. Natural production of biomass on earth employs sun and absorbs CO2 from atmosphere and sequesters it in the form of polysaccharides (bio-sequestration). So in principal by growing more and more plant life, progressively greater amount of carbon can be sequestered. The issue with this approach is that the sequestered biomass eventually decomposes and its decay releases back to atmosphere the sequestered CO24, 5, 6, 7. Thus the carbon is sequestered in the biomass only for the duration between its creation and decay, termed as bio-storage period in [4].
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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 | 0.001 | 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".