Photochemical reactions and surface ozone measurements in Tehran city center
Bibliographic record
Abstract
Efforts have been made for surface ozone concentration measurements considering secondary reactions via actinometry. Pyro heliometry, pyranometry and spectrophotometry, idometry in Amir Abad station of Tehran city center in parallel. In actinometry method consideration were made to show solar radiation in all different filters of green, yellow, red and dark red by means of 525 nm, 630 nm, 695 nm and 721 nm in parallel by the same time during 1991–1992. Resulted as solar radiation reduction in all filters and concluded for secondary reactions at Amirabad station for the first time in Iran. Measurements were made daily and seasonally at midday in Amirabad station. Where in idometry and spectrophotometry method consideration were made in certain wavelengths of 276.5 nm and 301 nm, for surface ozone measurements during autumn winter considering, October, November, December 1991–1992 and 1999–2001, using rain samples. Which has shown a concentration range of 30–60 (ppb) and 80–115 (ppb), respectively. The concentration measurements of surface ozone were made as a function of photochemical reactions of NO2. NO and photon rays in agreement with the results of spectrometry method by the same time due to F.M. Shahrtash for the first time in Iran. This study was in agreements with the works in Montreal, Ca (1992). Other consideration was made for surface ozone data collection analysis of (MOI) from Mehrabad station of Tehran city center via Dobson method during summer–autumn 2015. Which has shown a range of concentration of 80–92 (ppb), in comparison with the measurements of Amirabad station. Besides consideration was made for recent research work in China, which has detected the surface ozone concentration of 70–100 ppb during 2013–2018, mainly in North China and Yangtze river plain” by means of “photochemical reactions and surface ozone” in agreement with this study as a whole.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".