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Record W2253377212 · doi:10.5194/acp-16-7587-2016

Wildfires in northern Eurasia affect the budget of black carbon in the Arctic – a 12-year retrospective synopsis (2002–2013)

2016· article· en· W2253377212 on OpenAlexaff
Nikolaos Evangeliou, Yves Balkanski, W. M. Hao, A. Petkov, R. P. Silverstein, R. Corley, B. L. Nordgren, S. P. Urbanski, Sabine Eckhardt, A. Stohl, P. Tunved, S. Crepinsek, A. Jefferson, S. Sharma, J. K. Nøjgaard, Henrik Skov

Bibliographic record

VenueAtmospheric chemistry and physics · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsEnvironment and Climate Change Canada
FundersRocky Mountain Research StationU.S. Forest ServiceGrand Équipement National De Calcul Intensif
KeywordsArcticAffect (linguistics)The arcticEnvironmental scienceCarbon blackClimatologyPhysical geographyGeographyGeologyOceanographyChemistryPsychology

Abstract

fetched live from OpenAlex

Abstract. In recent decades much attention has been given to the Arctic environment, where climate change is happening rapidly. Black carbon (BC) has been shown to be a major component of Arctic pollution that also affects the radiative balance. In the present study, we focused on how vegetation fires that occurred in northern Eurasia during the period of 2002–2013 influenced the budget of BC in the Arctic. For simulating the transport of fire emissions from northern Eurasia to the Arctic, we adopted BC fire emission estimates developed independently by GFED3 (Global Fire Emissions Database) and FEI-NE (Fire Emission Inventory – northern Eurasia). Both datasets were based on fire locations and burned areas detected by MODIS (Moderate resolution Imaging Spectroradiometer) instruments on NASA's (National Aeronautics and Space Administration) Terra and Aqua satellites. Anthropogenic sources of BC were adopted from the MACCity (Monitoring Atmospheric Composition and Climate and megacity Zoom for the Environment) emission inventory.During the 12-year period, an average area of 250 000 km2 yr−1 was burned in northern Eurasia (FEI-NE) and the global emissions of BC ranged between 8.0 and 9.5 Tg yr−1 (FEI-NE+MACCity). For the BC emitted in the Northern Hemisphere (based on FEI-NE+MACCity), about 70 % originated from anthropogenic sources and the rest from biomass burning (BB). Using the FEI-NE+MACCity inventory, we found that 102 ± 29 kt yr−1 BC was deposited in the Arctic (defined here as the area north of 67° N) during the 12 years simulated, which was twice as much as when using the MACCity inventory (56 ± 8 kt yr−1). The annual mass of BC deposited in the Arctic from all sources (FEI-NE in northern Eurasia, MACCity elsewhere) is significantly higher by about 37 % in 2009 (78 vs. 57 kt yr−1) to 181 % in 2012 (153 vs. 54 kt yr−1), compared to the BC deposited using just the MACCity emission inventory. Deposition of BC in the Arctic from BB sources in the Northern Hemisphere thus represents 68 % of the BC deposited from all BC sources (the remaining being due to anthropogenic sources). Northern Eurasian vegetation fires (FEI-NE) contributed 85 % (79–91 %) to the BC deposited over the Arctic from all BB sources in the Northern Hemisphere.We estimate that about 46 % of the BC deposited over the Arctic from vegetation fires in northern Eurasia originated from Siberia, 6 % from Kazakhstan, 5 % from Europe, and about 1 % from Mongolia. The remaining 42 % originated from other areas in northern Eurasia. About 42 % of the BC released from northern Eurasian vegetation fires was deposited over the Arctic (annual average: 17 %) during spring and summer.

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 score0.011
Threshold uncertainty score0.444

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 studies0.0000.001
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 head0.003
GPT teacher head0.178
Teacher spread0.175 · 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

Citations84
Published2016
Admission routes1
Has abstractyes

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