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Record W2605414336 · doi:10.5194/acp-18-865-2018

Seasonal characteristics, formation mechanisms and source origins of PM <sub>2.5</sub> in two megacities in Sichuan Basin, China

2018· article· en· W2605414336 on OpenAlexaff
Huanbo Wang, Mi Tian, Yang Chen, Guangming Shi, Yuan Liu, Fumo Yang, Leiming Zhang, Liqun Deng, Jiayan Yu, Chao Peng, Xuyao Cao

Bibliographic record

VenueAtmospheric chemistry and physics · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersChinese Academy of SciencesChongqing Science and Technology CommissionNational Natural Science Foundation of China
KeywordsMegacityStructural basinPollutionEnvironmental scienceHomogeneousSeasonalityAerosolEnvironmental chemistryAir quality indexChinaAtmospheric sciencesHydrology (agriculture)ChemistryGeographyMeteorologyEcologyBiologyGeology

Abstract

fetched live from OpenAlex

Abstract. To investigate the characteristics of PM2.5 and its major chemical components, formation mechanisms, and geographical origins in the two megacities, Chengdu (CD) and Chongqing (CQ), in Sichuan Basin of southwest China, daily PM2.5 samples were collected simultaneously at one urban site in each city for four consecutive seasons from autumn 2014 to summer 2015. Annual mean concentrations of PM2.5 were 67.0 ± 43.4 and 70.9 ± 41.4 µg m−3 at CD and CQ, respectively. Secondary inorganic aerosol (SNA) and organic matter (OM) accounted for 41.1 and 26.1 % of PM2.5 mass at CD, and 37.4 and 29.6 % at CQ, respectively. Seasonal variations of PM2.5 and major chemical components were significant, usually with the highest mass concentration in winter and the lowest in summer. Daily PM2.5 concentration exceeded the national air quality standard on 30 % of the sampling days at both sites, and most of the pollution events were at the regional scale within the basin formed under stagnant meteorological conditions. The concentrations of carbonaceous components were higher at CQ than CD, likely partially caused by emissions from the large number of motorcycles and the spraying processes used during automobile production in CQ. Heterogeneous reactions probably played an important role in the formation of SO42−, while both homogeneous and heterogeneous reactions contributed to the formation of NO3−. Geographical origins of emissions sources contributing to high PM2.5 masses at both sites were identified to be mainly distributed within the basin based on potential source contribution function (PSCF) analysis.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.841

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 head0.006
GPT teacher head0.195
Teacher spread0.189 · 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 designBench or experimental
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

Citations213
Published2018
Admission routes1
Has abstractyes

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