Speciated atmospheric mercury on haze and non-haze days in an inland city in China
Bibliographic record
Abstract
Abstract. Long-term continuous measurements of speciated atmospheric mercury were conducted from July 2013 to June 2014 in Hefei, a midlatitude inland city in eastern central China that experiences frequent haze pollution. The mean concentrations (±standard deviation) of gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) were 3.95 ± 1.93 ng m−3, 2.49 ± 2.41 and 23.3 ± 90.8 pg m−3, respectively, on non-haze days, and 4.74 ± 1.62 ng m−3, 4.32 ± 8.36 and 60.2 ± 131.4 pg m−3, respectively, on haze days. Potential source contribution function (PSCF) analysis suggested that atmospheric mercury pollution on haze days was caused primarily by local emissions, instead of via long-range transport. The poorer mixing conditions on haze days also favored the accumulation of atmospheric mercury. Compared to GEM and GOM, PBM was especially sensitive to haze pollution. The mean PBM concentration on haze days was 2.5 times that on non-haze days due to elevated concentrations of particulate matter. PBM also showed a clear seasonal trend; its concentration was the highest in fall and winter, decreased rapidly in spring and was the lowest in summer, following the same order in the frequency of haze days in different seasons. On both non-haze and haze days, GOM concentrations remained low at night, but increased rapidly just before sunrise, which could be due to diurnal variation in air exchange between the boundary layer and free troposphere. However, non-haze and haze days showed different trends in daytime GEM and GOM concentrations. On non-haze days, GEM and GOM declined synchronously through the afternoon, probably due to the retreat of the free tropospheric air as the height of the atmospheric boundary layer increases. In contrast, on haze days, GOM and GEM showed opposite trends with the highest GOM and lowest GEM observed in the afternoon, suggesting the occurrence of photochemical oxidation. This is supported by simple box-model calculations, which showed that oxidation of GEM to GOM does occur and that the transport of free tropospheric GOM alone is not large enough to account for the observed increase in daytime GOM. Our results further postulate that NO2 aggregation with the HgOH intermediate may be a potential mechanism for the enhanced production of GOM during daytime.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".