Experimental study of benzene, toluene, ethylbenzene, and xylene (BTEX) contributions in the air pollution of Tehran, Iran
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Bibliographic record
Abstract
Abstract Urbanization and development are associated with air pollution, including emissions of volatile organic compounds (VOCs) such as benzene, toluene, ethylbenzene, and xylene (BTEX). For this study, we measured and investigated the outdoor concentrations of BTEX in Tehran, Iran. National Institute for Occupational Safety and Health (NIOSH, 1996) methods were applied to measure the concentrations of BTEX in winter and spring of 2015 at 46 air monitoring stations. BETX concentrations were also measured at 19 monitoring stations in June and July of 2003. In 2003, BTEX compound pollutants were observed at greater concentration in the eastern, central, and southern zones of Tehran than in other zones. The average concentrations of the BTEX compounds were 238 parts per billion (ppb), 130 ppb, 69 ppb, and 118 ppb, respectively, for benzene, toluene, ethylbenzene, and xylene. The benzene to toluene (B/T) ratios ranged from 0.8 to 3.2, which indicated that the gasoline used in the city was of poor quality at that time. In 2015, the BTEX concentrations in District 19 (south of Tehran) were higher than in the eastern and central regions, which included restricted “traffic zones” and the extensive development of public transportation systems. In the restricted traffic zones, only public vehicles, such as buses, taxis, ambulances, etc., and other authorized vehicles are allowed to operate. By ameliorating the quality of gasoline, encouraging the use of late model private cars, and development of subway and public transportation during the years between 2003 and 2015, the BTEX concentrations have fallen to levels that comply with Iran's air quality standards. The 2015 measurements revealed that the average concentrations of the BTEX compounds were 5.3, 9.2, 1.5, and 2.6 ppb, respectively. The B/T ratio fluctuated from 0.39 to 0.76, demonstrating the remarkable role that vehicle traffic plays in BTEX pollution.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it