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Record W4211068769 · doi:10.33140/eesrr/01/01/00002

The Fight to Overcoming Greenhouse Effect for Anti Global Climate Change and Current Situation

2018· article· en· W4211068769 on OpenAlexaboutno aff

Bibliographic record

VenueEarth & Environmental Science Research & Reviews · 2018
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouse gasEnvironmental scienceGlobal warmingCarbon dioxideReuseFossil fuelGreenhouse gas removalWaste managementGreenhouseGreenhouse effectClimate changeEnvironmental engineeringClimate change mitigationEngineeringChemistryOceanography

Abstract

fetched live from OpenAlex

The greenhouse effect is caused by CO2 released from various industrial and agricultural sources. Now assumed that, If we treat about 50% of the global greenhouse emission gases, global warming is considered to be remedied, while half of the total greenhouse gas emissions are nearly equal to the total emissions of greenhouse gases. From all thermal power plants. So if we treat all the exhaust gases from all thermal plants, global warming is considered to be remedied. So far, the greenhouse effects have not been treated yet. In our opinion, There are four reasons for this situation, that is: 1- We do not have a new generation of suitable industrial equipment and no suitable technologies 2- .We cannot remove the dust thoroughly before CO2 separation from the exhaust gases. 3- We have used ethanolamine to CO2 separation from industrial emissions, 4-We do not have the suitable solution to bury CO2 on the ocean floor. The authors of this project have overcome all the disadvantages mentioned above by proposing new generation of suitable new equipment as well as proposing new no-waste technologies suitable for treatment and reusing industrial exhaust gas as well as CO2 separation out of it, proposed using a cheap solvent called soda instead of ethanolamine to remove carbon dioxide from industrial emissions, suggests two inexpensive solutions to bury carbon dioxide in the ocean floor. The author has designed some major industrial equipment with a sufficiently large scale to handle industrial emissions of 3.4 million m3 per hour from a fossil fuel-fired 1,000MW plant. Industrial processes from very costly processes have many unreasonable steps have turned into less expensive industrial processes, even profitable. Content of the project is represented by 27 exclusive patents VN, 23 of these inventions were participated in the international invention innovation competition in Toronto Canada in 2017, and all 23 proposals are awarded with 15 gold medals and 8 silver medals. The project concludes with the following conclusions: 1. Conclusion on the generation of the suitable new equipment. 2. Conclusion on the suitable new technologies. 3. Conclusion on the two stages for the treatment of industrial exhaust gases. 4. Conclusion on the CO2 separation from the industrial emissions and CO2 transportation storage. 5. Conclusion on the CO2 storing on the deep ocean. 6. Conclusion on the economic efficiency. 7. General conclusion.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.003

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 head0.066
GPT teacher head0.356
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2018
Admission routes1
Has abstractyes

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