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Acidity of Size-Resolved Sea-Salt Aerosol in a Coastal Urban Area: Comparison of Existing and New Approaches

2022· article· en· W4224321636 on OpenAlexafffundabout
Ye Tao, Alexander Moravek, Teles C. Furlani, Cameron E. Power, Trevor C. VandenBoer, Rachel Chang, Aldona Wiacek, Cora J. Young

Bibliographic record

VenueACS Earth and Space Chemistry · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsMemorial University of NewfoundlandDalhousie UniversitySaint Mary's UniversityYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundEnvironment and Climate Change Canada
KeywordsAerosolSea saltSea salt aerosolSalt (chemistry)Inorganic ionsChemistryEnvironmental chemistrySeawaterEnvironmental scienceIonGeologyOceanography

Abstract

fetched live from OpenAlex

Aging of sea-salt aerosol and the corresponding phase partitioning behavior of HCl/Cl– were monitored and studied in the Halifax Fog and Air Quality Study (HaliFAQS) field campaign in Canada in the early summer of 2019. Ionic chemical composition of ambient aerosol from total suspended particles (TSPs) to 10 nm was sampled and measured into 14 size ranges, which showed that aerosol at the sampling location was mainly composed of sea-salt constituents with little influence from anthropogenic emissions of secondary inorganic precursors. The size-resolved pH of aged sea-salt aerosol was calculated by Extended Aerosol Inorganic Model (E-AIM) IV and a newly derived method based on the measurement of NH3/NH4+ and HNO3/NO3– or HCl/Cl– coupled phase partitioning behavior. The latter pH calculation method does not require information about the aerosol liquid water content or complete water-soluble ion measurement, compensating for the role of oxidized organics to influence the proton activity. In comparison, E-AIM calculation requires the input of all major hygroscopic species. The size-resolved pH calculated by E-AIM IV generally agrees with the one calculated by NH3–HCl coupled phase partitioning. The sensitivities of HCl and HNO3 phase partitioning to aerosol pH are studied with both observational data and conceptual modeling, which gives evidence that the phase partitioning of HCl is more sensitive and therefore more reflective of aerosol pH changes than HNO3 in sea-salt dominated atmospheres where particles typically have pH > 3. The higher concentration and more reliable measurement also make HCl a more suitable choice to track pH changes in this study.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score0.632

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 studies0.0000.000
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 head0.059
GPT teacher head0.236
Teacher spread0.177 · 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

Citations19
Published2022
Admission routes3
Has abstractyes

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