Non-volatile marine and non-refractory continental sources of particle-phase amine during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES)
Bibliographic record
Abstract
Amines were measured by aerosol mass spectrometry (AMS) and Fourier transform infrared (FTIR) spectroscopy during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) cruises. Both AMS non-refractory (NR) amine ion fragments comprising the AMS C x H y N z family and FTIR non-volatile (NV) primary (C–NH 2 ) amine groups typically had greater concentrations in continental air masses than in marine air masses. Secondary continental sources of AMS NR amine fragments were identified by consistent correlations with AMS NR nitrate, AMS NR f 44 (the contribution of AMS ion signal at m/z 44 (CO2+) to the total AMS NR organic mass (OM) signal), ion chromatography (IC) non-sea-salt potassium (nssK + ), and radon for most air masses. FTIR NV amine group mass concentrations for particles with diameters <1µm showed large contributions from a primary marine source that was identified by significant correlations with measurements of wind speed, chlorophyll a (chl a ), seawater dimethylsulfide (DMS), AMS NR chloride, and IC sea salt as well as FTIR NV alcohol groups in both marine and continental air masses. FTIR NV amine group mass concentrations in <0.18 and <0.5 µm particle samples in marine air masses likely have a biogenic secondary source associated with strong correlations with FTIR NV acid groups, which are not present for <1 µm particle samples. The average seasonal contribution of AMS NR amine fragments and FTIR NV amine groups ranged from 27±57 % amine from primary marine sources and 73±152 % secondary continental amine during early spring to 53±76 % amine from primary marine sources and 47±68 % secondary continental amine during winter. These results demonstrate that AMS NR and FTIR NV amine measurements are complementary and can be used together to investigate the variety and sources of amines in the marine environment.
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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 | 0.001 |
| 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 | 0.001 |
| 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".