Secondary organic aerosols from OH oxidation of cyclic volatile methyl siloxanes as an important Si source in the atmosphere
Bibliographic record
Abstract
Cyclic volatile methyl siloxanes (cVMSs), which can volatilize into the atmosphere, are active ingredients in widely used consumer products, thus attracting much attention due to their potential environmental risks. While in the atmosphere the cVMSs undergo oxidation, yielding both gaseous and particulate products. The aerosol yields and compositions from the OH oxidation of four cVMSs (D3–D6) were determined under low- and high-NO x conditions in an oxidation flow reactor. The aerosol yields increased progressively from D3 to D6, consistent with the volatilities and molecule weights of these cVMSs. NO x can restrict the formation of secondary organic aerosols (SOAs), leading to lower SOA yields under high-NO x conditions than under low-NO x conditions, with a yield decrease between 0.05–0.30 depending on the cVMSs. Ammonium sulfate seeds exhibited minor impacts on SOA yields under low-NO x conditions but significantly increased the SOA yields in the oxidation of D3–D5 at short photochemical ages under high-NO x conditions. The mass spectra of the SOAs showed a dependence of its chemical compositions on OH exposure. At high exposures equivalent to photochemical ages of > 4 d in the atmosphere, D4–D6 SOAs mainly consisted of C x H y and C x H y O z Si n under low-NO x conditions, whereas they primarily contained N m O z , C x H y , C x H y O 1 , C x H y O >1 and C x H y O z Si n under high-NO x conditions. The potential contributions of cVMSs to SOA formation in the atmosphere were evaluated using the reported cVMSs annual production and the yield obtained in the present study. A global cVMS-derived (D4–D6) SOA source strength is estimated to be 0.01 Tg yr −1 , distributed over major urban centers.
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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".