MétaCan
Menu
Back to cohort
Record W2086132822 · doi:10.5194/acp-15-2227-2015

Identifying fire plumes in the Arctic with tropospheric FTIR measurements and transport models

2015· article· en· W2086132822 on OpenAlexafffundabout
Camille Viatte, Kimberly Strong, James W. Hannigan, E. Nussbaumer, L. K. Emmons, Stéphanie Conway, Clare Paton‐Walsh, John W. Hartley, Joshua Benmergui, John C. Lin

Bibliographic record

VenueAtmospheric chemistry and physics · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of WaterlooUniversity of Toronto
FundersEurostarsNatural Sciences and Engineering Research Council of CanadaOffice of Polar ProgramsFonds Québécois de la Recherche sur la Nature et les TechnologiesCanadian Foundation for Climate and Atmospheric SciencesNational Science FoundationGovernment of CanadaNational Oceanic and Atmospheric AdministrationNova Scotia Research Innovation TrustNational Aeronautics and Space AdministrationNational Center for Atmospheric Research
KeywordsHYSPLITAtmospheric sciencesEnvironmental sciencePlumeSCIAMACHYBiomass burningTroposphereChemistryMeteorologyAerosolGeology

Abstract

fetched live from OpenAlex

Abstract. We investigate Arctic tropospheric composition using ground-based Fourier transform infrared (FTIR) solar absorption spectra, recorded at the Polar Environment Atmospheric Research Laboratory (PEARL, Eureka, Nunavut, Canada, 80°05' N, 86°42' W) and at Thule (Greenland, 76°53' N, −68°74' W) from 2008 to 2012. The target species, carbon monoxide (CO), hydrogen cyanide (HCN), ethane (C2H6), acetylene (C2H2), formic acid (HCOOH), and formaldehyde (H2CO) are emitted by biomass burning and can be transported from mid-latitudes to the Arctic. By detecting simultaneous enhancements of three biomass burning tracers (HCN, CO, and C2H6), ten and eight fire events are identified at Eureka and Thule, respectively, within the 5-year FTIR time series. Analyses of Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model back-trajectories coupled with Moderate Resolution Imaging Spectroradiometer (MODIS) fire hotspot data, Stochastic Time-Inverted Lagrangian Transport (STILT) model footprints, and Ozone Monitoring Instrument (OMI) UV aerosol index maps, are used to attribute burning source regions and travel time durations of the plumes. By taking into account the effect of aging of the smoke plumes, measured FTIR enhancement ratios were corrected to obtain emission ratios and equivalent emission factors. The means of emission factors for extratropical forest estimated with the two FTIR data sets are 0.40 ± 0.21 g kg−1 for HCN, 1.24 ± 0.71 g kg−1 for C2H6, 0.34 ± 0.21 g kg−1 for C2H2, and 2.92 ± 1.30 g kg−1 for HCOOH. The emission factor for CH3OH estimated at Eureka is 3.44 ± 1.68 g kg−1. To improve our knowledge concerning the dynamical and chemical processes associated with Arctic pollution from fires, the two sets of FTIR measurements were compared to the Model for OZone And Related chemical Tracers, version 4 (MOZART-4). Seasonal cycles and day-to-day variabilities were compared to assess the ability of the model to reproduce emissions from fires and their transport. Good agreement in winter confirms that transport is well implemented in the model. For C2H6, however, the lower wintertime concentration estimated by the model as compared to the FTIR observations highlights an underestimation of its emission. Results show that modeled and measured total columns are correlated (linear correlation coefficient r > 0.6 for all gases except for H2CO at Eureka and HCOOH at Thule), but suggest a general underestimation of the concentrations in the model for all seven tropospheric species in the high Arctic.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score0.657

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 head0.020
GPT teacher head0.205
Teacher spread0.184 · 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 designSimulation or modeling
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

Citations52
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueAtmospheric chemistry and physicsSame topicAtmospheric and Environmental Gas DynamicsFrench-language works237,207