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Record W2152662303 · doi:10.5194/acp-10-3759-2010

Hydroxyl radicals in the tropical troposphere over the Suriname rainforest: airborne measurements

2010· article· en· W2152662303 on OpenAlexaff
Mònica Martínez, Hartwig Harder, Dagmar Kubistin, M. Rudolf, Heiko Bozem, G. Eerdekens, Hubertus Fischer, T. Klüpfel, C. Gurk, R. Königstedt, Uwe Parchatka, C. L. Schiller, Alexander Stickler, Jonathan Williams, Jos Lelieveld

Bibliographic record

VenueAtmospheric chemistry and physics · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsYork University
FundersMax-Planck-Gesellschaft
KeywordsIsopreneTroposphereRainforestAtmospheric sciencesTrace gasEnvironmental scienceTropical rainforestPlanetary boundary layerBoundary layerMixing ratioEnvironmental chemistryChemistryEcologyGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract. Direct measurements of OH and HO2 over a tropical rainforest were made for the first time during the GABRIEL campaign in October 2005, deploying the custom-built HORUS instrument (HydrOxyl Radical measurement Unit based on fluorescence Spectroscopy), adapted to fly in a Learjet wingpod. Biogenic hydrocarbon emissions were expected to strongly reduce the OH and HO2 mixing ratios as the air is transported from the ocean over the forest. However, surprisingly high mixing ratios of both OH and HO2 were encountered in the boundary layer over the rainforest. The HORUS instrumentation and calibration methods are described in detail and the measurement results obtained are discussed. The extensive dataset collected during GABRIEL, including measurements of many other trace gases and photolysis frequencies, has been used to quantify the main sources and sinks of OH. Comparison of these measurement-derived formation and loss rates of OH indicates strong previously overlooked recycling of OH in the boundary layer over the tropical rainforest, occurring in chorus with isoprene emission.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.996

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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.

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

Citations153
Published2010
Admission routes1
Has abstractyes

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