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Record W4415431424 · doi:10.5194/amt-19-2379-2026

Modification and validation of a commercial dynamic chamber for reactive nitrogen and greenhouse gas flux measurements

2025· preprint· en· W4415431424 on OpenAlexafffund
Mehraj D. Shah, Kifle Aregahegn, Danial Nodeh-Farahani, Leigh R. Crilley, Tasnia Hasan, Yashar Ebrahimi-Iranpour, Fahim Sarker, Nick Nickerson, Chance Creelman, Sarah Ellis, Alexander Moravek, Trevor C. VandenBoer

Bibliographic record

VenueAtmospheric measurement techniques · 2025
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsMEG-3 (Canada)Nova Scotia HospitalYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTrace gasNitrogenGreenhouse gasReactive nitrogenSpectrum analyzerNitrogen dioxideFlux (metallurgy)Gas analyzerAtmosphere (unit)

Abstract

fetched live from OpenAlex

Abstract. Reactive nitrogen compounds (NO, NO2, HONO, NH3 and others; Nr) play important roles in atmospheric processes, and their cascading impacts throughout the Earth system have adverse effects on both the environment and human health. The fluxes of these gases at the surface-atmosphere interface have been studied in isolation or in smaller subsets by micrometeorological techniques or chambers, but simultaneous observations of all Nr species alongside standard greenhouse gases (GHGs) as a function of time have not been reported. Here, a dual-dynamic chamber system was developed for Nr by modifying a commercially available system for GHG fluxes for use with destructive analyzers and to account for chemical changes. The resulting platform makes the measurement of Nr and, by extension other reactive gases, more widely accessible to the scientific community, as custom chambers do not need to be fabricated. System modifications to passivate surfaces were implemented, so that Nr gases like NO2 could be effectively transferred to standard gas analyzers, with an initial 36 % loss due to transformations ultimately minimized below analyzer detection limits (~10 %) under relevant atmospheric conditions. The modified 72 L chamber did not see a change in the baseline response times for GHGs or NO at a flow rate of 2 L min-1. They retained the same values as an ideal non-reactive trace gas (τ = 37–39 min versus 36 min. The modifications improved the transfer time constants of NO2, HONO, and NH3 by up to 2 min, but substantial surface interactions for NH3 remain. In all cases, a surface interaction term needs to be characterized for these gases to obtain accurate fluxes. Losses of NO2 and O3 by known gas phase reactions, or from deposition and reaction on pristine and aged chamber surfaces, were characterized across a range of environmentally relevant relative humidities (RH) and mixing ratios. The final dual-chamber system configuration includes a measurement and reference chamber, which are necessary to implement the corrections for surface effects and chemical transformations when accurately quantifying dynamic fluxes via a mass balance framework. Proof-of-concept measurements of Nr fluxes from agricultural soil samples under controlled lab conditions as a function of soil water content were able to quantify emissions of NO, NO2, HONO, NH3, and N2O simultaneously, when subject to fertilization experiments using urea, ammonium carbonate and bicarbonate, and ammonium nitrate. Unfertilized replicate agricultural soil samples showed variability in NO2 and HONO emissions when prepared with minimal disturbance to the soil structure, with values consistent with those reported by in-situ field measurements. These oppose maximum potential fluxes characterized in prior lab soil manipulations, particularly for HONO relative to NO. Last, fluxes were quantified with destructive gas analyzers in the field with the dual-chamber system on an in-use agricultural soil and included a urea-based fertilizer perturbation to stimulate microbial and chemical transformation and transfer Nr to the atmosphere. The resulting fluxes observed show good agreement with prior reports based on other flux techniques. The mass balance terms within the dual-chamber approach are fully inspected from the pilot deployment in the field, along with an error analysis, to aid in the uptake of this approach by the community.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.274
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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