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Record W2163882954 · doi:10.5194/acp-12-779-2012

Atmospheric aerosol compositions in China: spatial/temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols

2012· article· en· W2163882954 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAtmospheric chemistry and physics · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsAerosolHazeSulfateEnvironmental scienceEnvironmental chemistryTotal organic carbonNitrateAtmospheric sciencesAmmoniumAmmonium sulfateChemistryMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract. From 2006 to 2007, the daily concentrations of major inorganic water-soluble constituents, mineral aerosol, organic carbon (OC) and elemental carbon (EC) in ambient PM10 samples were investigated from 16 urban, rural and remote sites in various regions of China, and were compared with global aerosol measurements. A large difference between urban and rural chemical species was found, normally with 1.5 to 2.5 factors higher in urban than in rural sites. Optically-scattering aerosols, such as sulfate (~16%), OC (~15%), nitrate (~7%), ammonium (~5%) and mineral aerosol (~35%) in most circumstance, are majorities of the total aerosols, indicating a dominant scattering feature of aerosols in China. Of the total OC, ~55%–60% can be attributed to the formation of the secondary organic carbon (SOC). The absorbing aerosol EC only accounts for ~3.5% of the total PM10. Seasonally, maximum concentrations of most aerosol species were found in winter while mineral aerosol peaks in spring. In addition to the regular seasonal maximum, secondary peaks were found for sulfate and ammonium in summer and for OC and EC in May and June. This can be considered as a typical seasonal pattern in various aerosol components in China. Aerosol acidity was normally neutral in most of urban areas, but becomes some acidic in rural areas. Based on the surface visibility observations from 681 meteorological stations in China between 1957 and 2005, four major haze areas are identified with similar visibility changes, namely, (1) Hua Bei Plain in N. China, and the Guanzhong Plain; (2) E. China with the main body in the Yangtze River Delta area; (3) S. China with most areas of Guangdong and the Pearl River Delta area; (4) The Si Chuan Basin in S.W. China. The degradation of visibility in these areas is linked with the emission changes and high PM concentrations. Such quantitative chemical characterization of aerosols is essential in assessing their role in atmospheric chemistry and weather-climate effects, and in validating atmospheric models.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score1.000

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 studies0.0000.001
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 head0.008
GPT teacher head0.209
Teacher spread0.201 · 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