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Record W2655620776 · doi:10.1002/2017gl073859

Long‐term (2005–2014) trends in formaldehyde (HCHO) columns across North America as seen by the OMI satellite instrument: Evidence of changing emissions of volatile organic compounds

2017· article· en· W2655620776 on OpenAlexaboutno aff
Lei Zhu, Loretta J. Mickley, Daniel J. Jacob, Eloïse A. Marais, Jian‐Xiong Sheng, Lu Hu, Gonzalo González Abad, K. Chance

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersEarth Sciences DivisionGoddard Space Flight CenterNational Aeronautics and Space Administration
KeywordsIsopreneEnvironmental scienceVolatile organic compoundFormaldehydeOzone Monitoring InstrumentAtmospheric sciencesOzoneSatelliteAtmosphere (unit)Environmental chemistryLatitudeTroposphereMeteorologyChemistryGeographyGeology

Abstract

fetched live from OpenAlex

Abstract Satellite observations of formaldehyde (HCHO) columns provide top‐down information on emissions of highly reactive volatile organic compounds (VOCs). We examine the long‐term trends in HCHO columns observed by the Ozone Monitoring Instrument from 2005 to 2014 across North America. Biogenic isoprene is the dominant source of HCHO, and its emission has a large temperature dependence. After correcting for this dependence, we find a general pattern of increases in much of North America but decreases in the southeastern U.S. Over the Houston‐Galveston‐Brazoria industrial area, HCHO columns decreased by 2.2% a −1 from 2005 to 2014, consistent with trends in emissions of anthropogenic VOCs. Over the Cold Lake Oil Sands in the southern Alberta in Canada, HCHO columns increased by 3.8% a −1 , consistent with the increase in crude oil production there. HCHO variability in the northwestern U.S. and Midwest could be related to afforestation and corn silage production. Although NO x levels can affect the HCHO yield from isoprene oxidation, we find that decreases in anthropogenic NO x emissions made only a small contribution to the observed HCHO trends.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.865

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 studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.024
GPT teacher head0.311
Teacher spread0.287 · 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.

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

Citations138
Published2017
Admission routes1
Has abstractyes

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