A method for the simultaneous quantification of 23 C1–C9 trace aldehydes and ketones in seawater
Bibliographic record
Abstract
Environmental context Low-molecular weight aldehydes and ketones formed in the oceans may be transferred to the atmosphere, affecting its oxidant chemistry and capacity. This in turn affects the lifetimes of other trace gases, as well as leading to secondary organic aerosol formation, both of which have climatic implications. We describe a facile, economical and readily available technique to measure low-molecular weight aldehydes and ketones in seawater. Abstract Low molecular weight aldehydes and ketones in the surface oceans are produced by dissolved organic matter photochemistry or by biology, and can be transferred to the atmosphere, affecting its oxidative capacity. They therefore link the organic carbon biogeochemistry of the atmosphere and the oceans. We have developed and optimised a mobile, economical and facile method which allows for the simultaneous quantification of 23 C1–C9 low molecular weight aldehydes and ketones in seawater. The compounds are derivatised using O-(2,3,4,5,6-pentafluorobenzyl)-hydroxylamine (PFBHA), pre-concentrated by solid-phase microextraction and analysed by gas chromatography with mass spectrometric or flame ionisation detection. Detection limits range from 0.01 to 23.5 nM, depending on the compound, with sub-nanomolar detection limits achieved for most compounds. High process blanks were observed for C1–C3 carbonyl compounds; sparging with ultrahigh purity argon, and solid phase extraction of the dissolved PFBHA to remove pre-existing carbonyl oximes, were the most effective blank reduction methods. The method was applied to surface waters from the lower St Lawrence Estuary (Quebec, Canada), revealing C2–C6 carbonyl compounds at concentrations of up to 7.5 nM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".