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Record W2754086704 · doi:10.5194/acp-18-6887-2018

Intercontinental transport of biomass burning pollutants over the Mediterranean Basin during the summer 2014 ChArMEx-GLAM airborne campaign

2018· article· en· W2754086704 on OpenAlexaboutno aff
Vanessa Brocchi, Gisèle Krysztofiak, Valéry Catoire, Jonathan Guth, Virginie Marécal, R. Zbinden, L. El Amraoui, François Dulac, Philippe Ricaud

Bibliographic record

VenueAtmospheric chemistry and physics · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersInstitut national des sciences de l'UniversCentre National de la Recherche ScientifiqueAgence de l'Environnement et de la Maîtrise de l'EnergieCentre National d’Etudes SpatialesAgence Nationale de la RechercheNational Aeronautics and Space Administration
KeywordsAerosolLongitudeEnvironmental scienceTroposphereAtmospheric sciencesMediterranean BasinAltitude (triangle)Trace gasBiomass burningMediterranean climateTransectAtmosphere (unit)PlumeLatitudeMeteorologyClimatologyOceanographyGeographyGeology

Abstract

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The Gradient in Longitude of Atmospheric constituents above the Mediterranean basin (GLAM) campaign was set up in August 2014, as part of the Chemistry and Aerosol Mediterranean Experiment (ChArMEx) project. This campaign aimed to study the chemical variability of gaseous pollutants and aerosols in the troposphere along a west–east transect above the Mediterranean Basin (MB). In the present work, we focus on two biomass burning events detected at 5.4 and 9.7 km altitude above sea level (a.s.l.) over Sardinia (from 39 ∘ 12 ′ N–9 ∘ 15 ′ E to 35 ∘ 35 ′ N–12 ∘ 35 ′ E and at 39 ∘ 30 ′ N–8 ∘ 25 ′ E, respectively). Concentration variations in trace gas carbon monoxide (CO), ozone (O 3 ) and aerosols were measured thanks to the standard instruments on board the Falcon 20 aircraft operated by the Service des Avions Français Instrumentés pour la Recherche en Environnement (SAFIRE) and the Spectromètre InfraRouge In situ Toute Altitude (SPIRIT) developed by LPC2E. Twenty-day backward trajectories with Lagrangian particle dispersion model FLEXPART (FLEXible PARTicle) help to understand the transport processes and the origin of the emissions that contributed to this pollution detected above Sardinia. Biomass burning emissions came (i) on 10 August from the North American continent with air masses transported during 5 days before arriving over the MB, and (ii) on 6 August from Siberia, with air masses travelling during 12 days and enriched in fire emission products above Canada 5 days before arriving over the MB. In combination with the Global Fire Assimilation System (GFAS) inventory and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite fire locations, FLEXPART reproduces well the contribution of those fires to CO and aerosols enhancements under adjustments of the injection height to 10 km in both cases and application of an amplification factor of 2 on CO GFAS emissions for the 10 August event. The chemistry transport model (CTM) MOCAGE is used as a complementary tool for the case of 6 August to confirm the origin of the emissions by tracing the CO global atmospheric composition reaching the MB. For this event, both models agree on the origin of air masses with CO concentrations simulated with MOCAGE lower than the observed ones, likely caused by the coarse model horizontal resolution that yields the dilution of the emissions and diffusion during transport. In combination with wind fields, the analysis of the transport of the air mass documented on 6 August suggests the subsidence of CO pollution from Siberia towards North America and then a transport to the MB via fast jet winds located at around 5.5 km in altitude. Finally, using the ratio ΔO 3 ∕ ΔCO, the plume age can be estimated and the production of O 3 during the transport of the air mass is studied using the MOCAGE model.

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 score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations27
Published2018
Admission routes1
Has abstractyes

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