Source Identification of Gaseous Mercury Measured in New York State Using Hybrid Receptor Modeling
Bibliographic record
Abstract
Ambient gas phase mercury concentrations including elemental mercury () were measured at the Potsdam, Stockton, and Sterling sites in NY from 2000 to 2003. Also, concentrations of ambient reactive gaseous mercury (RGM; ) were measured at the Potsdam site during one year. The contribution of RGM() was about of the total gas phase mercury concentration measured (TGM: in Potsdam. Stockton, and Sterling, respectively) at the receptor sites. Potential Source Contribution Function (PSCF), a hybrid receptor modeling incorporating backward trajectories was performed to identify source areas of TGM. Using PSCF, southern New York, North Carolina, and eastern Massachusetts were identified as important source areas in the United States, while the copper smelters and waste incinerators located in eastern Quebec and Ontario were determined to be significant sources in Canada. The Atlantic Ocean was suggested to be a possible mercury source. PSCF incorporating back-dispersion and deposition was applied for RGM , as well as PSCF based on 2-days back-trajectories. Two different approaches yielded considerably different results, primarily due to the consideration of dispersion rather than deposition. Using back-trajectory based PSCF, eastern Ohio, southern New York, and southern Pennsylvania where large coal -fired power plants area located were identified as the large sources in US. Metallurgical industry located in eastern Quebec was resolved as well. From the result of back-dispersion and deposition based PSCF, Pennsylvania, mining facilities around Lake Superior, Toronto, Boston, MA, Quebec, and coal power plants in NY were identified to be the significant source areas for Potsdam site.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".