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Record W4385242719 · doi:10.11159/rtese23.151

COBMA Impact on CO2 Concentrations in the Mitigation of Air Pollution-Anthropogenic Climate Change from Mobile Sources Emissions

2023· article· en· W4385242719 on OpenAlexaff
Raúl Guerrero Torres, Mehrab Mehrvar

Bibliographic record

VenueProceedings of the International Conference of Recent Trends in Environmental Science and Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEnvironmental scienceClimate changePollutionAir pollutionOceanographyGeology

Abstract

fetched live from OpenAlex

The purpose of this paper is to present implementation of COBMA as a crucial action to effectively abating Air Pollution, controlling CO2 emissions, from mobile sources.It is supported on new analyses from new and past emissions tests results and recent announcements from authoritative sources.From WHO, April 4/2022, billions of people still breathe unhealthy air; NOAA´s monitoring climate and IPCC reports, among others, are increasingly alarming to the extent that keeping the current levels of CO2 emissions concentrations will warm the Earth to 1.5°C above pre-industrial temperatures in just nine years; Announcements are pointing out the global ineffectiveness on cutting emissions, missing the right path to a sustainable future and thoughtlessly moving away increasingly fast from it, towards a close unstable-equilibrium. Implementation of COBMA and other proven actions constitute an urgent path we must follow right now to keep the planet temperature from rising above 2°C, averting a climate catastrophe.We only will achieve this goal working together as stated in COPs 26 and 27 but, globally integrated around a more comprehensive view of the Earth-Atmosphere system balance; seeing the Earth as a planet that behaves as if it were alive, at least to the extent of regulating its climate and chemistry, as James Lovelock and other independent scientists have stated for long.Consequently, in this paper, we detailly analyze the recent alarming reports, highlighting the scientific heritage on diagnosing Climate-Change evolution;The main roots of global ineffectiveness to guarantee a sustainable future are Characterized; The importance of a balanced combustion and its connection with the Earth-Atmosphere balance is emphasized and, finally, from analysis of periodic tests results in 2 cars and 2 motorcycles, is concluded that COBMA, with and without pre-treatment, reduces efficiently CO and HC emissions concentrations controlling CO2 emissions concentrations, keeping them steady after several weeks.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.023
GPT teacher head0.260
Teacher spread0.237 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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