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Record W7132936050

Quantifying Sources of Nitrogen Oxides in Remote Environments: From Biosphere-Atmosphere Exchange to Renoxification

2021· dissertation· W7132936050 on OpenAlexaffabout
Qianwen Shi

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
FundersNational Oceanic and Atmospheric Administration
KeywordsNOxParticulatesNitrateOzoneFlux (metallurgy)Peroxyacetyl nitrateNitrogen oxideNitrogenAtmosphere (unit)Nitrogen dioxide
DOInot available

Abstract

fetched live from OpenAlex

Nitrogen oxides (NOx = NO + NO2) are an important constituent to the global atmosphere due to their strong connection to ozone (O3) and hydroxyl radical (OH). Anthropogenic NOx emissions have been regulated worldwide, leading to a decreasing trend over the past 15 years in North America and Europe, which makes biogenic sources and recycling pathways more important, especially in remote regions that are less influenced by human activities.A two-channel chemiluminescence instrument with high precision and time resolution was used to quantify NOx in the field and the laboratory. In the field, direct measurements of biosphere-atmosphere exchange of NOx were made above a temperate broadleaf forest using the eddy covariance flux method. Near-zero NOx fluxes suggest that the soil NO emissions barely escape the canopy, and an air mass back trajectory analysis indicates that the morning NOx maximum is mainly associated with long-range transport of pollution. Flux divergence observed at this site is a consequence of fast chemical processes and different light intensity above and below the canopy. In the laboratory, NOx and other products from the photolysis of suspended inorganic particulate nitrate were measured in chamber experiments as a function of wavelength, relative humidity, and presence of photosensitizers. The photolysis rate constants of particulate nitrate measured are within an order of magnitude of that of gas-phase HNO3. This finding is in contrast with several studies showing a larger enhancement factor (EF) of renoxification of particle nitrate relative to HNO3. Different values of EF were applied to monitoring data from Environment and Climate Change Canada, to estimate NOx production from the photolysis of particulate nitrate and HNO3. Results were then compared with soil NOx emissions from a global model, showing that renoxification could potentially compete with biogenic NOx in remote environments and needs further investigation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.031
GPT teacher head0.279
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes2
Has abstractyes

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