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Record W2190210261

Air pollution impacts and sources under a changing climate:A case study for Scunthorpe, UK

2008· article· en· W2190210261 on OpenAlexfundno aff
Andrew Malby, Roger Timmis, Duncan Whyatt

Bibliographic record

VenueLancaster EPrints (Lancaster University) · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
FundersCanada Excellence Research Chairs, Government of CanadaMet Office
KeywordsEnvironmental scienceFugitive emissionsClimate changeAir quality indexAir pollutionParticulatesEnvironmental engineeringPollutionPollutantGreenhouse gasMeteorologyGeography
DOInot available

Abstract

fetched live from OpenAlex

Abstract: Climate change may affect local air quality by altering the emission, dispersion, chemical transformation and deposition of air pollutants. This study evaluates the effects of climate change in a real-life mixed land-use situation where there are adjacent urban and industrial activities and also fugitive emissions from stockpiles and unpaved roads. For this example we show how wind-speed and time-of-day dependent ‘bi-polar plots ’ created from ambient monitoring data can be used to learn more about the nature of sources responsible for exceedances of particulate matter air quality standards, and hence to assess how sensitive their impacts are to climate change. Unpaved roads and wind-blown fugitive sources such as stockpiles and coal handling beds in the industrial area appear to contribute substantially to raised air-quality impacts. The effect of climate change on impacts from these sources may differ from its effect on impacts from conventional combustion sources. Key words: particulate matter; fugitive source; climate change; industrial regulation. 1.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.939

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.271
Teacher spread0.220 · 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.

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
Published2008
Admission routes1
Has abstractyes

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