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Record W2076220644 · doi:10.5194/acpd-15-2085-2015

Separating refractory and non-refractory particulate chloride and estimating chloride depletion by aerosol mass spectrometry in a marine environment

2015· article· en· W2076220644 on OpenAlexaff
I. Nuaaman, Shao‐Meng Li, Katherine Hayden, T. B. Onasch, P. Massoli, D. Sueper, Douglas R. Worsnop, T. S. Bates, Patricia K. Quinn, R. McLaren

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsYork UniversityEnvironment and Climate Change Canada
Fundersnot available
KeywordsAerosolChlorideSea saltChemistryMass spectrometrySalt (chemistry)Environmental chemistrySea salt aerosolIonAnalytical Chemistry (journal)Chromatography

Abstract

fetched live from OpenAlex

Abstract. Aerosol composition and concentration measurements along the coast of California were obtained using an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) onboard the research vessel Atlantis during the CalNex study in 2010. This paper focuses on the measurement of aerosol chloride using the HR-AMS that can be ambiguous in regions with significant quantities of sea salt aerosols. This ambiguity arises due to large differences in the sensitivity of the HR-AMS to refractory chloride species (i.e., NaCl) and non refractory chloride species (i.e., NH4Cl, HCl, etc.). Using the HR-AMS, the aerosol chloride signal is typically quantified using ion signals for 35Cl+, H35Cl+, 37Cl+ and H37Cl+ (HxCl+). During this study, the highest aerosol chloride signal was observed during sea sweep experiments when the source of the aerosol chloride was NaCl present in artificially generated sea salt aerosols even though the HR-AMS has significantly lower sensitivity to such refractory species. Other prominent ion signals that arise from NaCl salt were also observed at m/z 22.99 for Na+ and m/z 57.96 for Na35Cl+ during both sea sweep experiments and during periods of ambient measurements. Thus, refractory NaCl contributes significantly to the HxCl+ signal, interfering with attempts to quantify non sea salt chloride (nssCl). It was found that during ambient aerosol measurements, the interference in the HxCl+ signal from sea salt chloride (ssCl) was as high as 89%, but with a study wide average of 10%. The Na35Cl+ ion signal was found to be a good tracer for NaCl. We outline a method to establish nssCl in the ambient aerosols by subtracting the sea salt chloride (ssCl) signal from the HxCl+ signal. The ssCl signal is derived from the Na35Cl+ ion tracer signal and the HxCl+ to Na35Cl+ ratio established from the sea sweep experiments. Ambient submicron concentrations of ssCl were also established using the Na35Cl+ ion tracer signal and a scaling factor determined through simultaneous measurements of submicron aerosol chloride on filters. This scaling factor accounts for the low vaporization response of the AMS heater to ssCl, although regular calibration of this response is recommended in future applications. It follows that true total particulate chloride (pCl) is the sum of nssCl and ssCl. In this study, the median levels observed for the concentrations of pCl, nssCl and ssCl were 0.052, 0.017 and 0.024 μg m−3 respectively. The average contributions of nssCl and ssCl to pCl were 48 and 52% respectively, with nssCl dominating in periods of continental outflow and ssCl dominating during other periods. Finally, we propose a method to measure percentage chloride depletion of NaCl in ambient submicron sea salt aerosols, strictly using the AMS measurements of Na+ and Na35Cl+ ion signals. The median chloride depletion in submicron aerosols in this study was found to be 78%.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.012
GPT teacher head0.212
Teacher spread0.200 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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