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Record W4247237468 · doi:10.5194/acp-2017-236

Source attribution of Arctic black carbon constrained by aircraft and surfacemeasurements

2017· preprint· en· W4247237468 on OpenAlexafffund
Jun‐Wei Xu, Randall V. Martin, Andrew Morrow, Sangeeta Sharma, W. Richard Leaitch, Julia Burkart, Hannes Schulz, Marco Zanatta, Megan D. Willis, Daven K. Henze, Colin J. Lee, Andreas Herber, Jonathan P. D. Abbatt

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of TorontoEnvironment and Climate Change CanadaDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsArcticEnvironmental scienceAtmospheric sciencesBiomass burningTroposphereClimatologyMeteorologyOceanographyGeographyGeologyAerosol

Abstract

fetched live from OpenAlex

Abstract. Black carbon (BC) contributes to both degraded air quality and Arctic warming, however sources of Arctic BC and their geographic contributions remain uncertain. We interpret a series of recent airborne and ground-based measurements with the GEOS-Chem global chemical transport model and its adjoint to attribute the sources of Arctic BC. The springtime airborne measurements performed by the NETCARE campaign in 2015 and the PAMARCMiP campaigns in 2009 and 2011 offer BC vertical profiles extending to > 6 km across the Arctic and include profiles above Arctic ground monitoring stations. Long-term ground-based measurements are examined from multiple methods (thermal, laser incandescence and light absorption) at Alert (2011–2013), Barrow (2009–2015) and Ny-Ålesund (2009–2014) stations. Our simulations with the addition of gas flaring emissions are consistent with ground-based measurements of BC concentrations at Alert and Barrow in winter and spring (rRMSE < 13 %), and with airborne measurements of BC vertical profile across the Arctic (rRMSE = 17 %). Sensitivity simulations suggest that anthropogenic emissions in eastern and southern Asia are the largest source of the Arctic BC column both in spring (56 %) and annually (37 %), with larger contributions aloft than near the surface (e.g. a contribution of 66 % between 400–700 hPa and of 46 % below 900 hPa in spring). Anthropogenic emissions from northern Asia contribute considerable BC to the lower troposphere (a contribution of 27 % in spring and of 43 % annually below 900 hPa). Biomass burning has a substantial contribution to Arctic BC below 400 hPa of 25 % annually, despite minor influence in spring ( 50 %) in winter and those from eastern and southern Asia are the largest in spring (~ 40 %). At Ny-Ålesund, anthropogenic emissions from Europe (~ 30 %) and northern Asia (~ 30 %) are major sources in winter and early spring. Biomass burning from North America is the most important contributor to surface BC at all stations in summer, especially at Barrow where North American biomass burning contributes more than 90 % of BC in July and August. Our adjoint simulations indicate pronounced spatial and seasonal heterogeneity in the contribution of emissions to the Arctic BC column concentrations with noteworthy contributions from emissions in eastern China (15 %) and western Siberia (6.5 %). Although uncertain, gas flaring emissions from oilfields in western Siberia could have a striking impact (13 %) on Arctic BC loadings in January, comparable to the total influence of continental Europe and North America (6.5 % each in January).

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.226
Teacher spread0.202 · 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

Citations7
Published2017
Admission routes2
Has abstractyes

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