Identification of potential regional sources of atmospheric total gaseous mercury in Windsor, Ontario, Canada using hybrid receptor modeling
Bibliographic record
Abstract
Abstract. Windsor (Ontario, Canada) experiences trans-boundary air pollution as it is located on the border immediately downwind of industrialized regions of the United States of America. A study was conducted in 2007 to identify the potential regional sources of total gaseous mercury (TGM) and investigate the effects of regional sources and other factors on seasonal variability of TGM concentrations in Windsor. TGM concentration was measured at the University of Windsor campus using a Tekran® 2537A Hg vapour analyzer. An annual mean of 2.02±1.63 ng/m3 was observed in 2007. The average TGM concentration was high in the summer (2.48±2.68 ng/m3) and winter (2.17±2.01 ng/m3), compared to spring (1.88±0.78 ng/m3) and fall (1.76±0.58 ng/m3). Hybrid receptor modeling potential source contribution function (PSCF) was used by incorporating 72-h backward trajectories and measurements of TGM in Windsor. The results of PSCF were analyzed in conjunction with the Hg emissions inventory of North America (by state/province) to identify regions affecting Windsor. In addition to annual modeling, seasonal PSCF modeling was also conducted. The potential source region was identified between 24–61° N and 51–143° W. Annual PSCF modeling identified major sources southwest of Windsor, stretching from Ohio to Texas. The emissions inventory also supported the findings, as Hg emissions were high in those regions. Results of seasonal PSCF modeling were analyzed to find the combined effects of regional sources, meteorological conditions, and surface re-emissions, on seasonal variability of Hg concentrations. It was found that the summer and winter highs of atmospheric Hg can be attributed to areas where large numbers of coal fired power plants are located in the USA. Weak atmospheric dispersion due to low winds and high re-emission from surfaces due to higher temperatures also contributed to high concentrations in the summer. In the winter, the atmospheric removal of Hg was slow, but strong winds led to more dispersion, resulting in lower concentrations than the summer. Future studies could use smaller grid sizes and refined emission inventories, for more accurate analysis of source-receptor relationship of atmospheric Hg.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".