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Record W2996582524 · doi:10.1029/2019gl085498

Anthropogenic Control Over Wintertime Oxidation of Atmospheric Pollutants

2019· article· en· W2996582524 on OpenAlexaff
Jessica D. Haskins, Felipe D. Lopez‐Hilfiker, Ben H. Lee, Viral Shah, Glenn M. Wolfe, Joshua P. DiGangi, D. L. Fibiger, Erin E. McDuffie, Patrick R. Veres, Jason C. Schroder, Pedro Campuzano‐Jost, Douglas A. Day, J. L. Jiménez, A. J. Weinheimer, Tamara L. Sparks, R. C. Cohen, T. Campos, Amy P. Sullivan, Hongyu Guo, Rodney J. Weber, Jack E. Dibb, J. Green, Marc N. Fiddler, Solomon Bililign, Lyatt Jaeglé, Steven S. Brown, Joel A. Thornton

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsDalhousie University
FundersNational Science Foundation of Sri LankaGoddard Space Flight CenterNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsParticulatesOxidizing agentEnvironmental scienceOzoneEnvironmental chemistryAerosolPollutantPollutionAtmosphere (unit)Middle latitudesAtmospheric sciencesAir pollutionNitrogen oxideNOxChemistryMeteorologyCombustionGeology

Abstract

fetched live from OpenAlex

Abstract During winter in the midlatitudes, photochemical oxidation is significantly slower than in summer and the main radical oxidants driving formation of secondary pollutants, such as fine particulate matter and ozone, remain uncertain, owing to a lack of observations in this season. Using airborne observations, we quantify the contribution of various oxidants on a regional basis during winter, enabling improved chemical descriptions of wintertime air pollution transformations. We show that 25–60% of NOx is converted to N2O5 via multiphase reactions between gas‐phase nitrogen oxide reservoirs and aerosol particles, with ~93% reacting in the marine boundary layer to form >2.5 ppbv ClNO2. This results in >70% of the oxidizing capacity of polluted air during winter being controlled by multiphase reactions and emissions of volatile organic compounds, such as HCHO, rather than reaction with OH. These findings highlight the control local anthropogenic emissions have on the oxidizing capacity of the polluted wintertime atmosphere.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.268
Teacher spread0.253 · 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

Citations42
Published2019
Admission routes1
Has abstractyes

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