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Record W4388890347 · doi:10.5194/acp-23-14393-2023

Radical chemistry and ozone production at a UK coastal receptor site

2023· article· en· W4388890347 on OpenAlexaff
Robert Woodward-Massey, Roberto Sommariva, Lisa K. Whalley, Danny R. Cryer, Trevor Ingham, William J. Bloss, S. M. Ball, Sam Cox, James Lee, Chris P. Reed, Leigh R. Crilley, Louisa J. Kramer, Brian Bandy, Grant L. Forster, Claire E. Reeves, P. S. Monks, Dwayne E. Heard

Bibliographic record

VenueAtmospheric chemistry and physics · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsYork University
FundersPeking UniversityNatural Environment Research CouncilUniversity of LeedsUniversity of LeicesterSight Research UK
KeywordsOzoneNOxBox modelHydroxyl radicalChemistryAtmospheric chemistryAtmosphere (unit)Atmospheric sciencesEnvironmental chemistryReactivity (psychology)MeteorologyRadicalOrganic chemistryGeologyCombustionPhysics

Abstract

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Abstract. OH, HO2, total and partially speciated RO2, and OH reactivity (kOH′) were measured during the July 2015 ICOZA (Integrated Chemistry of OZone in the Atmosphere) project that took place at a coastal site in north Norfolk, UK. Maximum measured daily OH, HO2 and total RO2 radical concentrations were in the range 2.6–17 × 106, 0.75–4.2 × 108 and 2.3–8.0 × 108 molec. cm−3, respectively. kOH′ ranged from 1.7 to 17.6 s−1, with a median value of 4.7 s−1. ICOZA data were split by wind direction to assess differences in the radical chemistry between air that had passed over the North Sea (NW–SE sectors) and that over major urban conurbations such as London (SW sector). A box model using the Master Chemical Mechanism (MCMv3.3.1) was in reasonable agreement with the OH measurements, but it overpredicted HO2 observations in NW–SE air in the afternoon by a factor of ∼ 2–3, although slightly better agreement was found for HO2 in SW air (factor of ∼ 1.4–2.0 underprediction). The box model severely underpredicted total RO2 observations in both NW–SE and SW air by factors of ∼ 8–9 on average. Measured radical and kOH′ levels and measurement–model ratios displayed strong dependences on NO mixing ratios, with the results suggesting that peroxy radical chemistry is not well understood under high-NOx conditions. The simultaneous measurement of OH, HO2, total RO2 and kOH′ was used to derive experimental (i.e. observationally determined) budgets for all radical species as well as total ROx (i.e. OH + HO2 + RO2). In NW–SE air, the ROx budget could be closed during the daytime within experimental uncertainty, but the rate of OH destruction exceeded the rate of OH production, and the rate of HO2 production greatly exceeded the rate of HO2 destruction, while the opposite was true for RO2. In SW air, the ROx budget analysis indicated missing daytime ROx sources, but the OH budget was balanced, and the same imbalances were found with the HO2 and RO2 budgets as in NW–SE air. For HO2 and RO2, the budget imbalances were most severe at high-NO mixing ratios, and the best agreement between HO2 and RO2 rates of production and destruction rates was found when the RO2 + NO rate coefficient was reduced by a factor of 5. A photostationary-steady-state (PSS) calculation underpredicted daytime OH in NW–SE air by ∼ 35 %, whereas agreement (∼ 15 %) was found within instrumental uncertainty (∼ 26 % at 2σ) in SW air. The rate of in situ ozone production (P(Ox)) was calculated from observations of ROx, NO and NO2 and compared to that calculated from MCM-modelled radical concentrations. The MCM-calculated P(Ox) significantly underpredicted the measurement-calculated P(Ox) in the morning, and the degree of underprediction was found to scale with NO.

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 score0.374
Threshold uncertainty score0.744

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.193
Teacher spread0.185 · 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

Citations19
Published2023
Admission routes1
Has abstractyes

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