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Record W3181700346 · doi:10.1029/2021gl092816

Chinese Regulations Are Working—Why Is Surface Ozone Over Industrialized Areas Still High? Applying Lessons From Northeast US Air Quality Evolution

2021· article· en· W3181700346 on OpenAlexaff
Xiaokang Chen, Zhe Jiang, Yanan Shen, Rui Li, Yunfei Fu, Jane Liu, Han Han, Hong Liao, Xugeng Cheng, Dylan B. A. Jones, H. M. Worden, Gonzalo González Abad

Bibliographic record

VenueGeophysical Research Letters · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of ChinaU.S. Environmental Protection Agency
KeywordsChinaDeltaYangtze riverEnvironmental scienceOzoneAir quality indexClimatologyAtmospheric sciencesMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract Observational data indicate increasing trends of surface ozone (O 3 ) in China, despite emission controls that have resulted in reductions of precursor emissions. Here, we explore the cause of this contradiction, through analysis of surface observations (2014–2019) in China and historical observation record in the United States (US, 1990–2019). Our observation‐based analysis indicates that the reductions of nitrogen oxides (NO x ) emissions led to increase of surface O 3 in North China Plain (NCP) and Yangtze River Delta (YRD) of around 8 ppb. However, NO x controls resulted in shift of O 3 chemical regimes over NCP and YRD, with turning points between NO x ‐ and volatile organic compound (VOC)‐limited regimes around 2019, while model simulations suggest transitional or NO x ‐limited regimes over the rest of China. The impacts of high fine particles (PM 2.5 ) on O 3 formation has declined because of the reduction of PM 2.5 concentrations. Stricter NO x controls can mitigate O 3 pollutions over industrialized areas in China.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.061
GPT teacher head0.325
Teacher spread0.264 · 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 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

Citations124
Published2021
Admission routes1
Has abstractyes

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