Is There a Formaldehyde Deficit in Emissions Inventories for Southeast Michigan?
Bibliographic record
Abstract
Formaldehyde is a key Volatile Organic Compound (VOC) and ozone precursor that plays a vital role in the urban atmospheric radical budget on par with water vapor, ozone, and nitrous acid. In addition to modulating radical and ozone production, ambient formaldehyde has both carcinogenic and non-carcinogenic inhalation health effects. This study concludes that ambient formaldehyde in the Southeast Michigan (SEMI) ozone nonattainment area may be underestimated up to a factor of two or more by regional air quality models. The addition of plausible amounts of primary formaldehyde to the U.S. National Emissions Inventory based on estimated formaldehyde-to-CO emission ratios partially alleviates this modeling deficit and indicates the presence of formaldehyde concentrations above 5 ppb at a previously unsuspected location northeast of Detroit. Standard 24-h formaldehyde samples obtained during the Michigan-Ontario Ozone Source Experiment (MOOSE) verified the presence of high ambient formaldehyde concentrations at this location. Moreover, the addition of plausible amounts of primary formaldehyde to VOC emissions inventories may add more than 1 ppb of ozone to ambient air in the SEMI nonattainment area, where ozone design values exceeded the U.S. National Ambient Air Quality Standard (NAAQS) by 1–2 ppb for the 2018–2020 design value period.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".