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Record W2032190598 · doi:10.3390/atmos2040633

Emission Ratios for Ammonia and Formic Acid and Observations of Peroxy Acetyl Nitrate (PAN) and Ethylene in Biomass Burning Smoke as Seen by the Tropospheric Emission Spectrometer (TES)

2011· article· en· W2032190598 on OpenAlexaboutno aff
M. J. Alvarado, Karen Cady‐Pereira, Yaping Xiao, Dylan B. Millet, Vivienne H. Payne

Bibliographic record

VenueAtmosphere · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersUniversity of MinnesotaNational Aeronautics and Space Administration
KeywordsTroposphereFormic acidMixing ratioEnvironmental scienceTrace gasSmokeAtmospheric sciencesEnvironmental chemistryChemistryGeology

Abstract

fetched live from OpenAlex

We use the Tropospheric Emission Spectrometer (TES) aboard the NASA Aura satellite to determine the concentrations of the trace gases ammonia (NH3) and formic acid (HCOOH) within boreal biomass burning plumes, and present the first detection of peroxy acetyl nitrate (PAN) and ethylene (C2H4) by TES. We focus on two fresh Canadian plumes observed by TES in the summer of 2008 as part of the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS-B) campaign. We use TES retrievals of NH3 and HCOOH within the smoke plumes to calculate their emission ratios (1.0% ± 0.5% and 0.31% ± 0.21%, respectively) relative to CO for these Canadian fires. The TES derived emission ratios for these gases agree well with previous aircraft and satellite estimates, and can complement ground-based studies that have greater surface sensitivity. We find that TES observes PAN mixing ratios of ~2 ppb within these mid-tropospheric boreal biomass burning plumes when the average cloud optical depth is low ( < 0.1) and that TES can detect C2H4 mixing ratios of ~2 ppb in fresh biomass burning smoke plumes.

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 score0.206
Threshold uncertainty score0.410

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 head0.025
GPT teacher head0.221
Teacher spread0.196 · 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

Citations53
Published2011
Admission routes1
Has abstractyes

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