Elemental analysis of oxygenated organic coating on black carbon particles using a soot-particle aerosol mass spectrometer
Bibliographic record
Abstract
Abstract. Chemical characterization of organic coatings is important to advance our understanding of the physio-chemical properties and environmental fate of black carbon (BC) particles. The soot-particle aerosol mass spectrometer (SP-AMS) has been utilized for this purpose in recent field studies. The laser vaporization (LV) scheme of the SP-AMS can heat BC cores gradually until they are completely vaporized, during which organic coatings can be vaporized at temperatures lower than that of the thermal vaporizer (TV) used in a standard high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) that employs flash vaporization. This work investigates the effects of vaporization schemes on fragmentation and elemental analysis of known oxygenated organic species using three SP-AMS instruments. We show that LV can reduce fragmentation of organic molecules. Substantial enhancement of C2H3O+/CO2+ and C2H4O2+ signals was observed for most of the tested species when the LV scheme was used, suggesting that the observational frameworks based on the use of HR-ToF-AMS field data may not be directly applicable for evaluating the chemical evolution of oxygenated organic aerosol (OOA) components coated on ambient BC particles. The uncertainties of H:C and O:C determined using the improved-ambient (I-A) method for both LV and TV approaches were similar, and scaling factors of 1.10 for H:C and 0.89 for O:C were determined to facilitate more direct comparisons between observations from the two vaporization schemes. Furthermore, the I-A method was updated based on the multilinear regression model for the LV scheme measurements. The updated parameters can reduce the relative errors of O:C from −26.3 % to 5.8 %, whereas the relative errors of H:C remain roughly the same. Applying the scaling factors and the updated parameters for the I-A method to ambient data, we found that even though the time series of OOA components determined using the LV and TV schemes are strongly correlated at the same location, OOA coatings were likely less oxygenated compared to those externally mixed with BC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".