MétaCan
Menu
Back to cohort
Record W2133081455 · doi:10.5194/acp-15-3077-2015

Properties and evolution of biomass burning organic aerosol from Canadian boreal forest fires

2015· article· en· W2133081455 on OpenAlexaboutno aff
Matthew D. Jolleys, Hugh Coe, G. McFiggans, Jonathan Taylor, Sebastian O’Shea, Michael Le Breton, Stéphane Bauguitte, Sarah Möller, Piero Di Carlo, Eleonora Aruffo, Paul I. Palmer, James Lee, Carl J. Percival, M. W. Gallagher

Bibliographic record

VenueAtmospheric chemistry and physics · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersMet OfficeNatural Environment Research CouncilSight Research UKLeverhulme Trust
KeywordsTaigaAerosolPlumeAtmospheric sciencesBiomass burningEnvironmental scienceBorealTroposphereAir mass (solar energy)CombustionBiomass (ecology)Mass spectrometryEnvironmental chemistryMeteorologyChemistryForestryGeologyGeographyOceanography

Abstract

fetched live from OpenAlex

Abstract. Airborne measurements of biomass burning organic aerosol (BBOA) from boreal forest fires reveal highly contrasting properties for plumes of different ages. These measurements, performed using an Aerodyne Research Inc. compact time-of-flight aerosol mass spectrometer (C-ToF-AMS) during the BORTAS (quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites) experiment in the summer of 2011, have been used to derive normalised excess organic aerosol (OA) mass concentrations (ΔOA / ΔCO), with higher average ratios observed closer to source (0.190±0.010) than in the far-field (0.097±0.002). The difference in ΔOA / ΔCO between fresh and aged plumes is influenced by a change in dominant combustion conditions throughout the campaign. Measurements at source comprised 3 plume interceptions during a single research flight and sampled largely smouldering fires. Twenty-three interceptions were made across four flights in the far-field, with plumes originating from fires occurring earlier in the campaign when fire activity had been more intense, creating an underlying contrast in emissions prior to any transformations associated with aging. Changing combustion conditions also affect the vertical distribution of biomass burning emissions, as aged plumes from more flaming-dominated fires are injected to higher altitudes of up to 6000 m. Proportional contributions of the mass-to-charge ratio (m/z) 60 and 44 peaks in the AMS mass spectra to the total OA mass (denoted f60 and f44) are used as tracers for primary and oxidised BBOA, respectively. f44 is lower on average in near-field plumes than those sampled in the far-field, in accordance with longer aging times as plumes are transported a greater distance from source. However, high levels of ΔO3 / ΔCO and −log(NOx / NOy) close to source indicate that emissions can be subject to very rapid oxidation over short timescales. Conversely, the lofting of plumes into the upper troposphere can lead to the retention of source profiles after transportation over extensive temporal and spatial scales, with f60 also higher on average in aged plumes. Evolution of OA composition with aging is comparable to observations of BB tracers in previous studies, revealing a consistent progression from f60 to f44. The elevated levels of oxygenation in aged plumes, and their association with lower average ΔOA / ΔCO, are consistent with OA loss through evaporation during aging due to a combination of dilution and chemical processing, while differences in combustion conditions throughout the campaign also have a significant influence on BBOA production and composition.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.265

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.176
Teacher spread0.163 · 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

Citations90
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueAtmospheric chemistry and physicsSame topicAtmospheric chemistry and aerosolsFrench-language works237,207