Impacts of large-scale circulation on urban ambient concentrations of gaseous elemental mercury in New York, USA
Bibliographic record
Abstract
Abstract. The impact of large-scale circulation on urban gaseous elemental mercury (GEM) was investigated through analysis of 2008–2015 measurement data from an urban site in New York City (NYC), New York, USA. Distinct annual cycles were observed in 2009–2010 with mixing ratios in warm seasons (i.e., spring–summer) 10–20 ppqv ( ∼ 10–25 %) higher than in cool seasons (i.e., fall–winter). This annual cycle was disrupted in 2011 by an anomalously strong influence of the US East Coast trough in that warm season and was reproduced in 2014 associated with a particularly strong Bermuda High. The US East Coast trough axis index (TAI) and intensity index (TII) were used to characterize the effect of the US East Coast trough on NYC GEM, especially in winter and summer. The intensity and position of the Bermuda High appeared to have a significant impact on GEM in warm seasons. Regional influence on NYC GEM was supported by the GEM–carbon monoxide (CO) correlation with r of 0.17–0.69 (p ∼ 0) in most seasons. Simulated regional and local anthropogenic contributions to wintertime NYC anthropogenically induced GEM concentrations were averaged at ∼ 75 % and 25 %, with interannual variation ranging over 67 %–83 % and 17 %–33 %, respectively. Results from this study suggest the possibility that the increasingly strong Bermuda High over the past decades could dominate over anthropogenic mercury emission control in affecting ambient concentrations of mercury via regional buildup and possibly enhancing natural and legacy emissions.
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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 | 0.001 | 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".