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Record W2744071782 · doi:10.5194/acp-18-3269-2018

Organic functional groups in the submicron aerosol at 82.5° N, 62.5° W from 2012 to 2014

2018· article· en· W2744071782 on OpenAlexafffundabout
W. R. Leaitch, Lynn M. Russell, Jun Liu, Felicia Kolonjari, Desiree Toom, Lin Huang, Sangeeta Sharma, Alina Chivulescu, Dan Veber, Wendy Zhang

Bibliographic record

VenueAtmospheric chemistry and physics · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersMinistère de la Défense NationaleEnvironment and Climate Change Canada
KeywordsAerosolSulfateTotal organic carbonSnowChemistrySea saltArcticEnvironmental chemistryMeteorologyGeographyOrganic chemistryGeologyOceanography

Abstract

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Abstract. The first multi-year contributions from organic functional groups to the Arctic submicron aerosol are documented using 126 weekly-integrated samples collected from April 2012 to October 2014 at the Alert Observatory (82.45° N, 62.51° W). Results from the particle transport model FLEXPART, linear regressions among the organic and inorganic components and positive matrix factorization (PMF) enable associations of organic aerosol components with source types and regions. Lower organic mass (OM) concentrations but higher ratios of OM to non-sea-salt sulfate mass concentrations (nss-SO4=) accompany smaller particles during the summer (JJA). Conversely, higher OM but lower OM ∕ nss-SO4= accompany larger particles during winter–spring. OM ranges from 7 to 460 ng m−3, and the study average is 129 ng m−3. The monthly maximum in OM occurs during May, 1 month after the peak in nss-SO4= and 2 months after that of elemental carbon (EC). Winter (DJF), spring (MAM), summer and fall (SON) values of OM ∕ nss-SO4= are 26, 28, 107 and 39 %, respectively, and overall about 40 % of the weekly variability in the OM is associated with nss-SO4=. Respective study-averaged concentrations of alkane, alcohol, acid, amine and carbonyl groups are 57, 24, 23, 15 and 11 ng m−3, representing 42, 22, 18, 14 and 5 % of the OM, respectively. Carbonyl groups, detected mostly during spring, may have a connection with snow chemistry. The seasonally highest O ∕ C occurs during winter (0.85) and the lowest O ∕ C is during spring (0.51); increases in O ∕ C are largely due to increases in alcohol groups. During winter, more than 50 % of the alcohol groups are associated with primary marine emissions, consistent with Shaw et al. (2010) and Frossard et al. (2011). A secondary marine connection, rather than a primary source, is suggested for the highest and most persistent O ∕ C observed during the coolest and cleanest summer (2013), when alcohol and acid groups made up 63 % of the OM. A secondary marine source may be a general feature of the summer OM, but higher contributions from alkane groups to OM during the warmer summers of 2012 (53 %) and 2014 (50 %) were likely due to increased contributions from combustion sources. Evidence for significant contributions from biomass burning (BB) was present in 4 % of the weeks. During the dark months (NDJF), 29, 28 and 14 % of the nss-SO4=, EC and OM were associated with transport times over the gas flaring region of northern Russia and other parts of Eurasia. During spring, those percentages dropped to 11 % for each of nss-SO4= and EC values, respectively, and there is no association of OM. Large percentages of the Arctic haze characterized at Alert likely have origins farther than 10 days of transport time and may be from outside of the Eurasian region. Possible sources of unusually high nss-SO4= and OM during September–October 2014 are volcanic emissions or the Smoking Hills' area of the Northwest Territories, Canada.

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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 score0.103
Threshold uncertainty score0.204

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 studies0.0000.000
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 head0.186
Teacher spread0.178 · 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

Citations70
Published2018
Admission routes3
Has abstractyes

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