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Record W4327716482 · doi:10.3390/atmos14030569

Distribution and Long-Term Trends of Tropospheric Ozone Concentrations in Ireland

2023· article· en· W4327716482 on OpenAlexaff
Keelan McHugh, Thomas Cummins, Julian Aherne

Bibliographic record

VenueAtmosphere · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsTrent University
FundersEnvironmental Protection Agency
KeywordsEnvironmental scienceOzoneTropospheric ozoneTroposphereLatitudeAtmospheric sciencesClimatologySeasonalityRange (aeronautics)GeographyMeteorologyEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Tropospheric ozone (O3) is highly variable over space and time reflecting local production and destruction as well as addition and loss through regional and long-range transport. In this study, O3 concentrations at 11 stations in Ireland and their long-term trends (7–9 sites) were evaluated; O3 concentrations (2015–2019) varied spatially, with the highest annual mean concentrations along the Atlantic west coast (69–75 µg/m3), and the lowest in urban centres (39–43 µg/m3). Ozone followed a seasonal pattern of spring and winter maximum and summer–autumn minimum. Significant long-term (2005–2019) increases were observed in annual O3 concentration at two rural stations, while increases were larger and more frequent during winter with increases at four out of seven stations. During the decade 2010–2019, significant annual increases were observed at four out of nine stations. Observed site- and season-specific increasing trends in O3 concentrations likely reflected changes in regional precursor gas emissions sources. Despite reported decreases in background concentrations in the marine boundary layer in northern mid-latitudes in recent decades, O3 concentrations at some sites in Ireland have increased significantly primarily driven by changes in winter concentrations. There were no significant decreasing trends at any site or in any season.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.223
Teacher spread0.212 · 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
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

Citations8
Published2023
Admission routes1
Has abstractyes

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