Bibliographic record
Abstract
Organic nitrogen compounds are present in our atmosphere from biogenic and anthropogenic sources and have impacts on air quality and climate. Due to recent advances in instrumentation, these compounds are being detected in the gas and particle phases, raising questions as to their source, processing and sinks in the environment. With their recently identified role as contributors to aerosol formation and growth, their novel large scale use as solvents in carbon capture and storage (CCS) technology and their emissions from cigarette smoke, it is now important to address the gaps in our understanding of the fate of organic nitrogen. Experimentally and theoretically, I studied the chemical atmospheric fate of specific organic nitrogen compounds in the amine, amide and isocyanate families, yielding information that can be used in chemical transport models to assess the fate of this emerging class of atmospheric molecules. \nI performed kinetic laboratory studies in a smog chamber to measure the room temperature rate coefficient for reaction with the hydroxyl radical of monoethanolamine, nicotine, and five different amides. I employed online-mass spectrometry techniques to quantify the oxidation products. I found that amines react quickly with OH radicals with lifetimes of a few hours under sunlit conditions, producing amides as oxidation products. My studies on amides revealed that they have much longer lifetimes in the atmosphere, ranging from a few hours to a week. Photo-oxidation of amides produces isocyanates and I investigated these mechanisms in detail using ab initio calculations. Furthermore, I experimentally measured isocyanic acid’s Henry’s Law constant as well as its hydrolysis rate constants to better understand its sinks in the atmosphere. Finally, I re-examined the structure-activity relationship (SAR) of organic nitrogen molecules for improved model parameterizations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 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 teacher head, 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".