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Record W4407209998 · doi:10.1029/2024jd042960

Oxidized Nitrogen‐Containing Organic Compounds Formation Enhanced the Light Absorption of PM<sub>2.5</sub> Brown Carbon

2025· article· en· W4407209998 on OpenAlexaff
Diwei Wang, Zhenxing Shen, Gezi Bai, Leiming Zhang, Shasha Huang, Honghao Zheng, Cailan Li, Jian Sun, Hongmei Xu, Junji Cao

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersNational Natural Science Foundation of China
KeywordsNitrogenCarbon fibersAbsorption (acoustics)ChemistryEnvironmental chemistryTotal organic carbonPhotochemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Brown carbon (BrC) is known to have a great impact on atmospheric radiative forcing, but its absorption characteristics at the molecular level is not well understood. This study investigated the seasonal variations of light absorption characteristics and molecular composition of BrC in Xi'an, China. Results showed that BrC exhibited higher light absorption capacity in cold (autumn and winter) than warm seasons (spring and summer). Nitrogen‐containing organic compounds were identified as important BrC chromophores. Oxidized‐N compounds originated from biomass burning emissions and NOx/NO3− mediated oxidation reactions were predominant in cold seasons, whereas reduced‐N compounds mainly formed from NH3/NH4+ mediated reactions were abundant in warm seasons. These results contribute to a better understanding of formation mechanisms and light absorption characteristics of nitrogen‐containing BrC chromophores in PM2.5.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.017
GPT teacher head0.264
Teacher spread0.247 · 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 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

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Geophysical Research Atmospheres→Same topicAtmospheric chemistry and aerosols→French-language works237,207→