Closure between particulate matter concentrations measured ex situ by thermal–optical analysis and in situ by the CPMA–electrometer reference mass system
Bibliographic record
Abstract
The thermal-optical analysis (TOA) of black carbon in particulate matter (PM) collected on filters has been recommended and used for the calibration of mass-concentration instruments. However, filter-based TOA calibrations have substantial practical limitations, requiring high sample flow rates (>10 litres per minute), long sampling times (up to 3 h), and subsequently manual filter processing with long analysis times (>15 min per filter). These limitations are avoided by in situ calibration techniques such as the centrifugal particle mass analyzer (CPMA)–electrometer reference mass system (CERMS). The CERMS is capable of producing and monitoring in situ reference mass concentrations below 1 µg m−3 and in real-time (∼1 Hz). Additional advantages of the CERMS are its improved repeatability (1.1%) over TOA (9–11%), and its measurement of a well-defined quantity: total post-CPMA suspended PM mass. In the present work, we demonstrate closure between these two techniques in terms of PM mass concentration for three different soot generators (viz., the Argonaut miniature inverted soot generator, Jing miniCAST, and National Research Council inverted-flame burner) under carefully controlled conditions. We also demonstrate the sensitivity of the CERMS by characterizing the limits of detection of a commercial laser-induced incandescence instrument and a photoacoustic instrument. Our data support the use of the CERMS with well-characterized PM sources to provide reference mass concentrations for the calibration of instruments measuring PM or black-carbon mass concentration.
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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".