Identifying Changes in Source Regions Impacting Speciated Atmospheric Mercury at a Rural Site in the Eastern United States
Bibliographic record
Abstract
Abstract To investigate the effectiveness of emission reductions on the concentrations of gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particulate-bound mercury (PBM) at a rural site in Maryland (MD08), long-term (2005–14) measurements of speciated atmospheric mercury were analyzed using concentration-weighted trajectory (CWT) analysis. CWT results suggested that the number of major source regions contributing to GEM, GOM, and reactive mercury (RM = GOM + PBM) over the eastern United States and southeastern Canada declined over time. Across much of these regions, source contributions in 2011–14 decreased by up to 20% for GEM, by greater than 60% for GOM, and by 20%–60% for PBM compared to 2006–08, largely because of the decreases in power-plant mercury emissions since 2009. Changes in the spatial distribution of the source regions were also observed over time. Increases in source contributions of GEM after 2011 over the northeastern United States and southeastern Canada were predominantly from emission increases in metal and steel production and forest fires. Source contribution increases in PBM were more widespread, which can be attributed potentially to mercury transformation processes in the air or wood combustion rather than industrial sources.
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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 | 0.001 |
| 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".