Volatile organic compounds in the marine troposphere and surface oceans: methods, measurements and biogeochemical implications
Bibliographic record
Abstract
Volatile organic compounds (VOCs), among them non-methane hydrocarbons (NMHCs) and low molecular weight carbonyl compounds (aldehydes and ketones), affect the oxidative capacity of the atmosphere and thus pollutant lifetimes and global climate. VOCs in the surface oceans may be transported into, or derived from, the atmosphere. This thesis describes the development and optimization of chromatographic and preconcentration methods to determine volatile organic compounds (VOCs) in surface seawater and marine air, and their use to explore VOC distribution and fluxes at the sea-air interface. It includes the first measurements of many carbonyl compounds in temperate and subarctic marine waters and the first estimates of fluxes of several aldehydes from the ocean surface into the marine atmosphere. Sea surface air, size-fractionated marine aerosols, and surface ocean water dissolved organic matter were simultaneously sampled in the Nordic seas. Nineteen C2-C7 NMHCs were quantified in the air samples. Site-to-site variability in NMHC concentrations was high, suggesting variable, local sources. The aerosols consisted mainly of inorganic marine material, but a culturable bacterium identified as Micrococcus luteus was also isolated from the 9.9 18 micrometre fraction, suggesting organic matter may be transferred from the surface oceans to the atmosphere by marine aerosols. Lastly, a number of VOCs, including acetone, were detected in the seawater samples using solid-phase microextraction (SPME), leading to the subsequent development of an SPME application for carbonyl compounds in seawater. A mobile, economical and solventless method for the detection and quantification of carbonyl compounds in seawater, a matrix of global importance, was developed. The compounds were derivatized using O-(2,3,4,5,6-pentafluorobenzyl)-hydroxylamine (PFBHA)and then pre-concentrated by SPME for gas chromatography with mass spectrometric (GC/MS) or flame ionization (GC-FID) detectio
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".