MétaCan
Menu
Back to cohort
Record W3117831061 · doi:10.4209/aaqr.200528

Ground-level Particulate Sulphate and Gaseous Sulphur Dioxide Downwind of an Aluminium Smelter

2020· article· en· W3117831061 on OpenAlexafffund
Dane Blanchard, Julian Aherne

Bibliographic record

VenueAerosol and Air Quality Research · 2020
Typearticle
Languageen
FieldEngineering
TopicIndustrial Gas Emission Control
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity College DublinTrent University
KeywordsSmeltingAluminium smeltingParticulatesAluminiumEnvironmental scienceEnvironmental chemistrySulfur dioxideMetallurgyChemistryMaterials scienceInorganic chemistry

Abstract

fetched live from OpenAlex

Particulate sulphate (pSO42–) is an atmospheric pollutant known to affect human/environmental health and global radiative-forcing. The Rio Tinto (RT) aluminium smelting facility in Kitimat, British Columbia, is the primary source of sulphur dioxide (SO2) emissions to the surrounding Kitimat Valley, a relatively isolated and unpolluted region. A network of active two-stage filter-packs and passive-diffusive samplers was established between June 2017 to October 2018 with the objective to evaluate the spatiotemporal variation and relative contribution of pSO42– to total anthropogenic atmospheric oxidized sulphur (SOx = SO2 + pSO42–). Average pSO42– across all sites (n = 9) was 0.41 µg m–3 (24–48 hour exposures) and ranged from 0.03 to 2.03 µg m–3. In contrast, average filter-pack SO2 ranged from 0.11 to 8.9 µg m–3 (during the same exposure periods). The filter-pack pSO42–/SOx concentration ratio (Fs) increased downwind of the smelter, indicating that the relative concentration of pSO42– increased with distance from the smelter. Furthermore, the increasing pSO42–/vanadium (V) ratio (used as a tracer of smelter emissions) relative to distance confirmed particulate formation was occurring within the emission plume during the sampling period. Irrespective of in-plume aerosol formation, pSO42– contributed a relatively minor fraction of total atmospheric SOx within the emission plume (field campaign averages Fs < 20%; pSO42– < 0.1 µg S m–3; SO2 > 1.0 µg S m–3).

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.207
GPT teacher head0.371
Teacher spread0.164 · 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
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueAerosol and Air Quality ResearchSame topicIndustrial Gas Emission ControlFrench-language works237,207