Size-Dependent Dry Deposition of Airborne Polybrominated Diphenyl Ethers in Urban Guangzhou, China
Bibliographic record
Abstract
Gaseous and size-segregated particulate PBDEs (specifically BDE-47, -99, -183, -207, and -209) in the air were measured in urban Guangzhou at 100 and 150 m above the ground in daytime and at night in August and December 2010, to assess dry deposition of these contaminants accurately with regards to influences of meteorological factors but without confounding surface effects. Particulate PBDEs were more abundant at night than in daytime, and slightly higher in winter than in summer, likely from varying meteorological conditions and atmospheric boundary layers. More than 60% of particulate-phase PBDEs was contained in particles with an aerodynamic diameter (D(p)) below 1.8 μm, indicating long-range transport potential. The average daily particle dry deposition fluxes of PBDEs in August ranged from 2.6 (BDE-47) to 88.6 (BDE-209) ng m(-2) d(-1), while those in winter ranged from 2.0 (BDE-47) to 122 (BDE-209) ng m(-2) d(-1). Deposition fluxes of all PBDE congeners were significantly higher in daytime than at night for both months, due to the effect of diurnal variability of meteorological factors. In addition, mean overall particle deposition velocities of individual BDE congeners ranged from 0.11 to 0.28 cm s(-1). These values were within a factor of 2 of assumed values previously used in southern China and the Laurentian Great Lakes, suggesting that such assumptions were reasonable for sites with similar particulate size distributions and PBDE sources. Dry deposition velocities of PBDEs were lower at night than those in the daytime, probably reflecting higher mechanical and thermal turbulence during daytime. Dry deposition of particulate-bound PBDEs is influenced by short-term temporal variability from meteorological factors, and also by particulate size fractions.
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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 | 0.000 |
| 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 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".