Detection and quantification of reactive atmospheric nitrogen species in remote ecosystems
Bibliographic record
Abstract
Anthropogenic inputs of nitrogen to the environment have increased by over 150 % \nin the last 150 years causing concern for vital biophysical processes on Earth. Thus being \nable to measure these increased inputs in terrestrial, aquatic and atmospheric \nenvironments is essential to understanding how the global nitrogen cycle has been \nimpacted since the industrial revolution. With respect to the atmosphere, emissions of \nreduced and oxidized forms of nitrogen have increased largely due to the anthropogenic \nactivities of agriculture and combustion, respectively. Emissions of these nitrogenous \nspecies not only impact regions adjacent to their point sources, but also have the ability to \ninfluence ecosystems hundreds of kilometers away due to the long-range transport of \nsome of these compounds. This can impact sensitive remote ecosystems positively or \nnegatively by either stimulating growth or causing acidification, eutrophication and \nbiodiversity shifts. Therefore developing analytical techniques that are capable of \nmeasuring oxidized and reduced atmospheric inputs to remote ecosystems is of great \nimportance. \nIn part I of this work a method employing custom-built physisorption-based passive \nsamplers coupled with ion chromatography analysis was developed to sample \natmospheric nitric acid (HNO₃(g)) in remote ecosystems. The developed HNO₃(g) sampling \nmethod was able to detect HNO₃(g) mixing ratios as low as 2 parts per trillion by volume \n(pptv) over a monthly sampling period, following a rigorous quality assurance and quality \ncontrol procedure. The passive samplers were installed across the Newfoundland and \nLabrador – Boreal Ecosystem Latitudinal Transect (NL-BELT) in the summer of 2015, and average mixing ratios of HNO₃(g) at the NL-BELT field sites from 2015-16 were \ndetermined to be in the tens of parts per trillion by volume (pptv) range. The dry \ndeposition flux of HNO₃(g) as nitrogen (N) to the field sites ranged from 3 – 16 mg N yr-1. \nThrough an air mass back trajectory analysis, coupled with a steady-state chemical box \nmodel approximation, it was determined that the HNO₃(g) quantities observed at a single \nNL-BELT site likely originated from local production and regional transport from central \nand eastern Newfoundland, with an additional contribution from the down welling of \nperoxyacetyl nitrates from the upper troposphere, possibly occurring during the spring \nand early summer. \nIn part II of this work, an ion chromatography method was developed to speciate \nand quantify alkylamines (NR₃(g)). NR₃(g) have been shown to influence Earth’s climate \nand may be an important source of new nitrogen to remote ecosystems. The developed \nmethod was shown to be sensitive, accurate, and robust in separating and quantifying 11 \natmospheric alkylamines, including 3 sets of alkylamine isomers, from 5 common \natmospheric inorganic cations. The method was able to detect NR₃(g) at a picogram per \ninjection level, and the method performed robustly in the presence of a complex biomassburning \nmatrix containing amounts of inorganic cations up to 3 orders of magnitude \nlarger than the NR₃(g) quantified in the samples. Thus the ion chromatography method can \nbe applied to the remote atmosphere where alkylamine concentrations are often detected \nin quantities 1000 times less than other atmospheric cations. In the biomass-burning \nparticle samples tested using the ion chromatography method unprecedented quantities of \ndimethylamine and diethylamine were observed, with the summed molar quantity \nexceeding that of ammonium in the 100 – 560 nm particle diameter fraction. \nThe applicability of these atmospheric measurement techniques to measure and \nquantify HNO₃(g) and NR₃(g) has been demonstrated for remote ecosystems and will \nhopefully allow for a greater understanding of these two species roles’ in remote \nenvironments.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".