Underestimation of sulfate concentration in PM2.5 using a semi-continuous particle instrument based on ion chromatography
Bibliographic record
Abstract
Recently, a variety of ion-chromatography-based semi-continuous particle instruments such as the Dionex gas particle ion chromatograph (GP-IC), wet-annular denuder/steam-jet aerosol collector (WAD/SJAC), particle-into-liquid sampler with ion chromatograph (PILS-IC), gas and aerosol monitoring system (GAMS) have been introduced for measuring particle chemical components in the atmosphere. It has been reported that sulfate concentrations in PM2.5 measured by these semi-continuous particle instruments correlate well with those measured by other semi-continuous instruments such as the Aerodyne aerosol mass spectrometer (AMS), R&P 8400S and R&P 8400N analyzers, and Thermo model 5020 sulfate particle analyzer and at times exhibit a unity slope. However, the sulfate concentration measured by some of these semi-continuous instruments has been reported to be underestimated by 20-50%, as compared to that in PM2.5 filter samples. In this study, numerous potential causes for underestimation of the sulfate concentrations by the GP-IC were investigated. We found a 30-40% negative artifact arising from an improper calibration procedure inherent within the instrument design. An improved calibration procedure was developed and it substantially reduced the sulfate concentration difference between the GP-IC measurements and PM2.5 filter samples from 36% to 5%.
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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 | 0.000 |
| 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) | 0.000 | 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".