Reduced Atmospheric Manganese in Montreal Following Removal of Methylcyclopentadienyl Manganese Tricarbonyl (MMT)
Bibliographic record
Abstract
ISEE-0084 Background and Objectives: Methylcyclopentadienyl Manganese Tricarbonyl (MMT) was used as an antiknock agent and as an octane booster in Canadian unleaded gasoline. Its combustion leads to Mn emissions. Considering that MMT is no longer used in the Canadian gasoline since 2003, the objective of this research was to examine the variations in atmospheric Mn in Montreal (Canada) from 2001 to 2007, covering the period prior (2001–2003) to and following (2005–2007) MMT use. Methods: Three sampling stations were selected because their proximity to roads with widely differing and well-known traffic. Filters from 2001 to 2007 were obtained. The first sample of each month was selected and Mn analysis was performed by neutron activation analysis. TSP (total suspended particulates) was calculated by weighing the filters before and after dust collection. Results: Results show a significant decrease of Mn over time at each station while TSP decreased significantly in two stations. Comparing atmospheric Mn during and after the period of use of MMT 2001–2003 vs 2005–2007 showed a significant decrease at all stations. For TSP, only one station showed borderline significant difference between these two periods. The difference between the two periods shows 41% and 17% of decrease for Mn and TSP, respectively. Conclusion: These data suggest that the combustion of MMT led to an increase of airborne Mn of approximately 24%. These results should help in decision-making processes leading to the acceptance or rejection of the use of MMT in gasoline in other countries.
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 | 0.000 | 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 | 0.001 | 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".