Characterization of two aerosol carbon analyzers based on temperature programmed oxidation: TCA08 and FATCAT
Bibliographic record
Abstract
Combustion and air-pollution aerosol particles often contain a substantial mass fraction of carbon. In biomass or residual-fuel smoke, this carbon may span a continuum of molecular sizes and physical properties, from macromolecular black carbon (BC) and tarballs to smaller molecules of organic particulate matter (OM). The quantification of these materials presents a metrological challenge which rapid temperature programmed oxidation instruments (RTPOs) may address. RTPOs collect particles on filters, which are then rapidly heated (> 700 K/min) in ambient or synthetic air while CO2 in the emitted gases is quantified either with (e.g. the “FATCAT” instrument) or without (e.g., “TCA08”) first passing gases over an oxidation catalyst. Both RTPOs monitor CO2 concentrations in real time to provide thermograms; both report total carbon mass by reference to baseline-subtracted CO2 thermograms. In this study, we investigated the response of these instruments to a variety of laboratory samples. Integrated carbon mass from the FATCAT and TCA08 agreed with one another, and with reference measurements, for both mature, fully graphitized soot (OC/TC < 0.1) and young, partially formed soot (OC/TC = 0.6 after denuding at 350 °C). However, due to its lack of an oxidation catalyst, the TCA08 CO2 measurements were Equation1(1) Fi=TCTCA08TCTOA(1) 0-fold lower than reference measurements for two model OM compounds (dioctyl sebacate and sucrose). Since a previous atmospheric study has observed consistency between a TCA08 and a reference instrument, our data imply a large difference in the evaporation kinetics of these surrogates and atmospheric OM, as expected for highly-viscous (glassy) atmospheric OM. Finally, we discuss the thermograms of nebulized BC surrogates (C60, graphene, graphite), which showed two peaks at lower and higher temperatures, even after denuding at 350 °C.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".