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Record W2104948191 · doi:10.5194/acp-15-5161-2015

Origin of springtime ozone enhancements in the lower troposphere over Beijing: in situ measurements and model analysis

2015· article· en· W2104948191 on OpenAlexaff
Jiayue Huang, Hongyu Liu, J. H. Crawford, Chung Yee Zenobia Chan, David B. Considine, Y. Zhang, Xiaohui Zheng, Chunsheng Zhao, V. Thouret, S. J. Oltmans, S. C. Liu, Dylan B. A. Jones, S. D. Steenrod, Megan Damon

Bibliographic record

VenueAtmospheric chemistry and physics · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
FundersGoddard Space Flight CenterCentre National de la Recherche ScientifiqueCentre National d’Etudes SpatialesEuropean CommissionStrongNational Aeronautics and Space AdministrationNational Natural Science Foundation of ChinaHarvard UniversityNational Science Foundation
KeywordsTroposphereBeijingTropospheric ozoneAtmospheric sciencesEnvironmental scienceOzoneClimatologyChemical transport modelWater vaporAltitude (triangle)PollutionMeteorologyGeographyChinaGeology

Abstract

fetched live from OpenAlex

Abstract. Ozone (O3) concentrations in the lower troposphere (LT) over Beijing have significantly increased over the past 2 decades as a result of rapid industrialization in China, with important implications for regional air quality and the photochemistry of the background troposphere. We characterize the vertical distribution of lower-tropospheric (0–6 km) O3 over Beijing using observations from 16 ozonesonde soundings during a field campaign in April–May 2005 and MOZAIC (Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft) over 13 days in the same period. We focus on the origin of LT O3 enhancements observed over Beijing, particularly in May. We use a global 3-D chemistry and transport model (GEOS-Chem CTM; GEOS – Goddard Earth Observing System) driven by assimilated meteorological fields to examine the transport pathways for O3 pollution and to quantify the sources contributing to O3 and its enhancements in the springtime LT over Beijing. Output from the Global Modeling Initiative (GMI) CTM is also used. High O3 concentrations (up to 94.7 ppbv) were frequently observed at the altitude of ~ 1.5–2 km. The CTMs captured the timing of the occurrences but significantly underestimated their magnitude. GEOS-Chem simulations and a case study showed that O3 produced in the Asian troposphere (especially from Asian anthropogenic pollution) made major contributions to the observed O3 enhancements. Contributions from anthropogenic pollution in the European and North American troposphere were reduced during these events, in contrast with days without O3 enhancements when contributions from Europe and North America were substantial. The O3 enhancements typically occurred under southerly wind and warmer conditions. It is suggested that an earlier onset of the Asian summer monsoon would cause more O3 enhancement events in the LT over the North China Plain in late spring and early summer.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.025
GPT teacher head0.238
Teacher spread0.213 · 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

Citations36
Published2015
Admission routes1
Has abstractyes

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