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Record W2971237053 · doi:10.5194/amt-12-4543-2019

Inter-comparison of elemental and organic carbon mass measurements from three North American national long-term monitoring networks at a co-located site

2019· article· en· W2971237053 on OpenAlexafffundabout
Tak Wai Chan, Lin Huang, Kulbir Banwait, Wendy Zhang, D. Ernst, Xiaoliang Wang, John G. Watson, Judith C. Chow, Mark Green, C. I. Czimczik, Guaciara M. Santos, Sangeeta Sharma, Keith Jones

Bibliographic record

VenueAtmospheric measurement techniques · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersNatural Resources CanadaClean Air Regulatory AgendaEnvironment and Climate Change CanadaDesert Research InstituteNational Park ServiceU.S. Environmental Protection Agency
KeywordsAerosolEnvironmental scienceTotal organic carbonEnvironmental chemistryCarbon fibersCharringChemistryAnalytical Chemistry (journal)Materials science

Abstract

fetched live from OpenAlex

Abstract. Carbonaceous aerosol is a major contributor to the total aerosol load and being monitored by diverse measurement approaches. Here, 10 years (2005–2015) of continuous carbonaceous aerosol measurements collected at the Centre of Atmospheric Research Experiments (CARE) in Egbert, Ontario, Canada, on quartz-fiber filters by three independent networks (Interagency Monitoring of Protected Visual Environments, IMPROVE; Canadian Air and Precipitation Monitoring Network, CAPMoN; and Canadian Aerosol Baseline Measurement, CABM) were compared. Specifically, the study evaluated how differences in sample collection and analysis affected the concentrations of total carbon (TC), organic carbon (OC), and elemental carbon (EC). Results show that different carbonaceous fractions measured by various networks were consistent and comparable in general among the three networks over the 10-year period, even with different sampling systems/frequencies, analytical protocols, and artifact corrections. The CAPMoN TC, OC, and EC obtained from the DRI model 2001 thermal–optical carbon analyzer following the IMPROVE-TOR protocol (denoted as DRI-TOR) method were lower than those determined from the IMPROVE_A TOR method by 17 %, 14 %, and 18 %, respectively. When using transmittance for charring correction, the corresponding carbonaceous fractions obtained from the Sunset-TOT were lower by as much as 30 %, 15 %, and 75 %, respectively. In comparison, the CABM TC, OC, and EC obtained from a thermal method, EnCan-Total-900 (ECT9), were higher than the corresponding fractions from IMPROVE_A TOR by 20 %–30 %, 0 %–15 %, and 60 %–80 %, respectively. Ambient OC and EC concentrations were found to increase when ambient temperature exceeded 10 ∘C. These increased ambient concentrations of OC during summer were possibly attributed to secondary organic aerosol (SOA) formation and forest fire emissions, while elevated EC concentrations were potentially influenced by forest fire emissions and increased vehicle emissions. Results also show that the pyrolyzed organic carbon (POC) obtained from the ECT9 protocol could provide additional information on SOA although more research is still needed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.031
GPT teacher head0.251
Teacher spread0.221 · 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.

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

Citations19
Published2019
Admission routes3
Has abstractyes

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