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Record W2922252987 · doi:10.5194/acp-19-9309-2019

The sensitivity of PM <sub>2.5</sub> acidity to meteorological parameters and chemical composition changes: 10-year records from six Canadian monitoring sites

2019· article· en· W2922252987 on OpenAlexaffabout
Ye Tao, J. G. Murphy

Bibliographic record

VenueAtmospheric chemistry and physics · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsAerosolChemical compositionSulfateChemistryEnvironmental chemistrySulfate aerosolEnvironmental scienceAtmospheric sciences

Abstract

fetched live from OpenAlex

Aerosol pH is difficult to measure directly but can be calculated if the chemical composition is known with sufficient accuracy and precision to calculate the aerosol water content and the H + concentration through the equilibrium among acids and their conjugate bases. In practical terms, simultaneous measurements of at least one semi-volatile constituent, e.g. NH 3 or HNO 3 , are required to provide a constraint on the calculation of pH. Long-term records of aerosol pH are scarce due to the limited monitoring of NH 3 in conjunction with PM 2.5 . In this study, 10-year (2007–2016) records of pH of PM 2.5 at six eastern Canadian sites were calculated using the E-AIM II model with the input of gaseous NH 3 , gaseous HNO 3 and major water-soluble inorganic ions in PM 2.5 provided by Canada's National Air Pollution Surveillance (NAPS) Program. Clear seasonal cycles of aerosol pH were found with lower pH (∼2) in summer and higher pH (∼3) in winter consistently across all six sites, while the day-to-day variations of aerosol pH were higher in winter compared to summer. Tests of the sensitivity of aerosol pH to meteorological parameters demonstrate that the changes in ambient temperature largely drive the seasonal cycle of aerosol pH. The sensitivity of pH to chemical composition shows that pH has different responses to the changes in chemical composition in different seasons. During summertime, aerosol pH was mainly determined by temperature with limited impact from changes in NH x or sulfate concentrations. However, in wintertime, both meteorological parameters and chemical composition contribute to the variations in aerosol pH, resulting in the larger variation during wintertime. This study reveals that the sensitivity of aerosol pH to chemical composition is distinctly different under different meteorological conditions and needs to be carefully examined for any particular region.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.011
GPT teacher head0.194
Teacher spread0.182 · 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

Citations83
Published2019
Admission routes2
Has abstractyes

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