Size Distribution of Airborne Particle-Bound Polybrominated Diphenyl Ethers and Its Implications for Dry and Wet Deposition
Bibliographic record
Abstract
Size distribution of particles in part dictates the environmental behavior of particle-bound organic pollutants in the atmosphere. The present study was conducted to examine the potential mechanisms responsible for the distribution of organic pollutants in size fractionated particles and their environmental implications, using an e-waste recycling zone in South China as a case study. Size-fractionated atmospheric particles were collected at the heights of 1.5, 5, and 20 m near two residential apartments and analyzed for polybrominated diphenyl ethers (PBDEs). The concentrations of particle-bound ΣPBDE (sum of 18 PBDE congeners) were significantly greater at 5 and 20 m than those at 1.5 m. The size-fractionated distributions of airborne ΣPBDE displayed trimodal peaks in 0.10–0.18, 1.8–3.2, and 10–18 μm at 1.5 m but only an unimodal peak in 1.0–1.8 μm at 20 m height. Emission sources, resuspension of dust and soil, and volatility of PBDEs were important factors influencing the size distribution of particle-bound PBDEs. The dry deposition fluxes of particle-bound PBDE estimated from the measured data in the present study were approximately twice the estimated wet deposition fluxes, with a total deposition flux of 3000 ng m(–2) d(–1). The relative contributions of particles to dry and wet deposition fluxes were also size-dependent, e.g., coarse (aerodynamic diameters (Dp) > 1.8 μm) and fine (Dp < 1.8 μm) particles dominated the dry and wet deposition fluxes of PBDEs, respectively.
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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 | 0.001 | 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".