Diurnal cycle of fossil and nonfossil carbon using radiocarbon analyses during CalNex
Bibliographic record
Abstract
Abstract Radiocarbon (14C) analysis is a unique tool to distinguish fossil/nonfossil sources of carbonaceous aerosols. We present 14C measurements of organic carbon (OC) and total carbon (TC) on highly time resolved filters (3–4 h, typically 12 h or longer have been reported) from 7 days collected during California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 in Pasadena. Average nonfossil contributions of 58% ± 15% and 51% ± 15% were found for OC and TC, respectively. Results indicate that nonfossil carbon is a major constituent of the background aerosol, evidenced by its nearly constant concentration (2–3 μgC m−3). Cooking is estimated to contribute at least 25% to nonfossil OC, underlining the importance of urban nonfossil OC sources. In contrast, fossil OC concentrations have prominent and consistent diurnal profiles, with significant afternoon enhancements (~3 μgC m−3), following the arrival of the western Los Angeles (LA) basin plume with the sea breeze. A corresponding increase in semivolatile oxygenated OC and organic vehicular emission markers and their photochemical reaction products occurs. This suggests that the increasing OC is mostly from fresh anthropogenic secondary OC (SOC) from mainly fossil precursors formed in the western LA basin plume. We note that in several European cities where the diesel passenger car fraction is higher, SOC is 20% less fossil, despite 2–3 times higher elemental carbon concentrations, suggesting that SOC formation from gasoline emissions most likely dominates over diesel in the LA basin. This would have significant implications for our understanding of the on‐road vehicle contribution to ambient aerosols and merits further study.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".