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Record W3087541731

A Backward Modeling Study of Intercontinental Pollution Transport Using Aircraft Measurements

2002· article· en· W3087541731 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venueelib (German Aerospace Center) · 2002
Typearticle
Languageen
FieldEngineering
TopicAir Traffic Management and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceMeteorologyPollutionAeronauticsComputer scienceGeographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

In this paper we present simulations with a Lagrangian particle dispersion model to study the intercontinental transport of pollution from North America during an aircraft measurement campaign over Europe. The model was used for both the flight planning and a detailed source analysis after the campaign, which is described here with examples from two episodes. Forward calculations of emission tracers from North America, Europe, and Asia were made in order to understand the transport processes. Both episodes were preceded by stagnant conditions over North America, leading to the accumulation of pollutants in the North American boundary layer. Both anthropogenic sources and, to a lesser extent, forest fire emissions contributed to this pollution, which was then exported by warm conveyor belts to the middle and upper troposphere, where it was transported rapidly to Europe. Concentrations of many trace gases (CO, NO<sub>y</sub>, CO<sub>2</sub>, acetone, and several volatile organic compounds; O<sub>3</sub> in one case) and of ambient atmospheric ions measured aboard the research aircraft were clearly enhanced in the pollution plumes compared to the conditions outside the plumes. Backward simulations with the particle model were introduced as an indispensable tool for a more detailed analysis of the plume's source region. They make trajectory analyses (which, to date, were mainly used to interpret aircraft measurement data) obsolete. Using an emission inventory, we could decompose the tracer mixing ratios at the receptors (i.e., along the flight tracks) into contributions from every grid cell of the inventory. For both plumes we found that emission sources contributing to the tracer concentrations over Europe were distributed over large areas in North America. In one case, sources in California, Texas, and Florida contributed almost equally, and smaller contributions were also made by other sources located between the Yucatan Peninsula and Canada. In the other case, sources in eastern North America, including moderate contributions from forest fires, were most important. The plume's maximum was mainly caused by anthropogenic emissions from the New York area. To our knowledge, this is the first case reported where a pollution plume from a megacity was reliably detected over another continent.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.236
Teacher spread0.193 · 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