Updated ozone absorption cross section will reduce air quality compliance
Bibliographic record
Abstract
Abstract. Photometric ozone measurements rely upon an accurate value of the ozone absorption cross section at 253.65 nm. This has recently been re-evaluated by Viallon et al. (2015) as 1.8 % smaller than the accepted value (Hearn, 1961) used for the preceding 50 years. Thus, ozone measurements that applied the older cross section systematically underestimate the amount of ozone in air. We correct the reported historical surface data from North America and Europe and find that this modest change in cross section has a significant impact on the number of locations that are out of compliance with air quality regulations if the air quality standards remain the same. We find 18, 23, and 20 % increases in the number of sites that are out of compliance with current US, Canadian, and European ozone air quality health standards for the year 2012. Should the new cross-section value be applied, it would impact attainment of air quality standards and compliance with relevant clean air acts, unless the air quality target values themselves were also changed proportionately. We draw attention to how a small change in gas metrology has a global impact on attainment and compliance with legal air quality standards. We suggest that further laboratory work to evaluate the new cross section is needed and suggest three possible technical and policy responses should the new cross section be adopted.
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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".