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Record W2116840300 · doi:10.4209/aaqr.2011.11.0224

Aircraft Measurements of Ionic and Elemental Components in PM2.5 over Eastern Coastal Area of China

2012· article· en· W2116840300 on OpenAlexaff
Lihong Ren, Renjian Zhang, Zhipeng Bai, Jianhua Chen, Hongjie Liu, Meigen Zhang, Xiaoyang Yang, Leiming Zhang

Bibliographic record

VenueAerosol and Air Quality Research · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsEnvironmental chemistrySulfateIonic bondingAmmoniumNitrateAerosolChemistryMass concentration (chemistry)Environmental scienceSea saltIon

Abstract

fetched live from OpenAlex

To understand the ionic and elemental components in PM2.5 over eastern coastal areas in China, aircraft measurements were carried out from 25 December, 2002 to 6 January, 2003. PM2.5 filter samples were collected and analyzed for mass concentrations, nine ionic components and 15 trace elements. The highest concentrations of PM2.5 were observed at the lowest altitudes, indicating the influence of ground-level sources. Sulfate, nitrate and ammonium were the main water-soluble components, and the sum of their concentrations accounted for 60–70% of the total ionic mass. Cl− depletion was observed to an extent of 3–26%. Anthropogenic ally derived particles contributed about 60% of the total measured ionic components, and natural sources such as sea salts and soil dusts contributed another 40%. Different to many earlier studies, Ca2+ was found to mainly originate from anthropogenic sources. PM2.5 showed an acidic nature, with a neutralization potential/acidic potential ratio of less than 1.0. NH4+ was the major neutralizer of aerosol acidity. A good correlation was observed between the concentrations of NO3− and nssCa2+, suggesting that photochemically produced HNO3 was partly absorbed by mineral particles. S had the highest concentrations among the 15 elements. The enrichment factor values of the observed elements were all over 1, indicating that all of them were influenced by anthropogenic sources. The enrichment factors of Pb, S, As, Cu and Zn were over 100, and suggesting that they were greatly enriched.

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)0.002
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 score0.014
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.161
GPT teacher head0.348
Teacher spread0.187 · 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

Citations11
Published2012
Admission routes1
Has abstractyes

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