INFLUENCE OF BENZO(A)PYRENE ON ENVIRONMENTAL QUALITY AND POPULATION HEALTH (BY EXAMPLE OF IVANOVO)
Bibliographic record
Abstract
The paper presents the results of measurements of the content of benzo(a)pyrene (BaP) in the snow cover in the territory of the Ivanovo city. It was revealed that the concentration of BaP at the controlled points is 2.7 times higher than the background level on average. The degree of pollution of the snow cover in Ivanovo is much less than in Moscow (the level of excess varies in the range 2.3 - 89 times). The intake levels (from 0.02 μg/m2 to 3.76 μg/m2) and deposition density (0.02 - 1.88 ng/m2 · day-1) of BaP are estimated that are commensurate with the values typical for such areas, as urban areas of Germany and Canada. Interpolation the BaP concentrations in snow is allowed to reveal anomalies in the city with BaP content of 35 ng/l, which is 7 times higher than the average value for the whole city. The obtained data made it possible to estimate the BaP concentration in atmospheric air, which on the average is 0.7· 10-6 mg/m3, which is 0.7 fraction of the maximum permissible concentration. The values of individual carcinogenic risk for public health were calculated, which amounted to 0.6·10-6 and 1.6·10-6, which corresponds to negligible individual risk (for the adult population) or corresponds to the maximum allowable level (for children), respectively. The obtained results allowed to evaluate the environmental risk from pollution of the snow cover with BaP, the level of which corresponds to a moderate one, however, indicates a potential public health hazard related to the ability of the BаP to accumulate in environmental objects. It is established that the most likely source of BaP is automobile transport. The contribution of the fuel and energy complex should be much less.
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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 | 0.000 | 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) | 0.001 | 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".