Improved Measurement of Seasonal and Diurnal Differences in the Carbonaceous Components of Urban Particulate Matter Using a Denuder-Based Air Sampler
Bibliographic record
Abstract
A denuder-based integrated organic gas and particle sampler (IOGAPS), designed to minimize artifacts often encountered during conventional filter pack (FP) sampling, was used in this study to examine seasonal and diurnal variations of particle-bound organic carbon (OC) and elemental carbon (EC) in Toronto, Canada. Daytime and nighttime PM 2.5 samples were collected using both the IOGAPS and FP in Toronto from 16–21 July 2001 and 17–24 March 2003. The average OC determined by the IOGAPS (IOGAPS-OC) was 6.7 μ g C/mbm3 in July 2001 and 5.3 μ g C/mbm3 in March 2003. The average EC determined by the IOGAPS (IOGAPS-EC) was 0.9 μ g C/mbm3 and 0.4 μ g C/mbm3, respectively, during these periods. The IOGAPS-OC concentrations were often higher during the night. This could be explained by the partitioning of the gas phase semivolatile organic carbon (SVOC) onto the existing aerosols due to decreased ambient temperatures. The average of the SVOC measured by the IOGAPS was 0.5 μ g C/mbm3 and 4.5 μ g C/mbm3 during the day and night in July 2001, respectively. In March 2003 the daytime average SVOC was 1.9 μ g C/mbm3 and the nighttime average SVOC was 2.5 μ g C/mbm3. The formation of secondary organic aerosols (SOA) contributed significantly to the summertime OC in July 2001, which was confirmed by a poor correlation between the IOGAPS-OC and IOGAPS-EC (Rbm2 = 0.01). In contrast, a relatively strong correlation between IOGAPS-OC and IOGAPS-EC (Rbm2 = 0.87) during the winter in March 2003 suggests that the main sources of the carbonaceous aerosols were primary.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".