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Record W2563386950

Carbon Capture and Storage

2007· book· en· W2563386950 on OpenAlexaboutno aff
S. Julio Friedmann

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2007
Typebook
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon sequestrationGreenhouse gasEnvironmental scienceCarbon dioxideCarbon capture and storage (timeline)Greenhouse gas removalBiomass (ecology)Carbon fibersCarbonateNegative carbon dioxide emissionCarbon dioxide in Earth's atmosphereTotal inorganic carbonAtmospheric carbon cycleEarth scienceClimate changeChemistryGeologyOceanographyMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Carbon capture and sequestration (CCS) is the long-term isolation of carbon dioxide from the atmosphere through physical, chemical, biological, or engineered processes. This includes a range of approaches including soil carbon sequestration (e.g., through no-till farming), terrestrial biomass sequestration (e.g., through planting forests), direct ocean injection of CO{sub 2} either onto the deep seafloor or into the intermediate depths, injection into deep geological formations, or even direct conversion of CO{sub 2} to carbonate minerals. Some of these approaches are considered geoengineering (see the appropriate chapter herein). All are considered in the 2005 special report by the Intergovernmental Panel on Climate Change (IPCC 2005). Of the range of options available, geological carbon sequestration (GCS) appears to be the most actionable and economic option for major greenhouse gas reduction in the next 10-30 years. The basis for this interest includes several factors: (1) The potential capacities are large based on initial estimates. Formal estimates for global storage potential vary substantially, but are likely to be between 800 and 3300 Gt of C (3000 and 10,000 Gt of CO{sub 2}), with significant capacity located reasonably near large point sources of the CO{sub 2}. (2) GCS can begin operations with demonstrated technology. Carbon dioxide has been separated from large point sources for nearly 100 years, and has been injected underground for over 30 years (below). (3) Testing of GCS at intermediate scale is feasible. In the US, Canada, and many industrial countries, large CO{sub 2} sources like power plants and refineries lie near prospective storage sites. These plants could be retrofit today and injection begun (while bearing in mind scientific uncertainties and unknowns). Indeed, some have, and three projects described here provide a great deal of information on the operational needs and field implementation of CCS. Part of this interest comes from several key documents written in the last three years that provide information on the status, economics, technology, and impact of CCS. These are cited throughout this text and identified as key references at the end of this manuscript. When coupled with improvements in energy efficiency, renewable energy supplies, and nuclear power, CCS help dramatically reduce current and future emissions (US CCTP 2005, MIT 2007). If CCS is not available as a carbon management option, it will be much more difficult and much more expensive to stabilize atmospheric CO{sub 2} emissions. Recent estimates put the cost of carbon abatement without CCS to be 30-80% higher that if CCS were to be available (Edmonds et al. 2004).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.008
GPT teacher head0.163
Teacher spread0.155 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2007
Admission routes1
Has abstractyes

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