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Record W4322010891 · doi:10.5194/egusphere-egu23-13487

NH3 emissions derived from CRIS observations over Europe

2023· preprint· en· W4322010891 on OpenAlexaff
Jieying Ding, Ronald van der A, Henk Eskes, Enrico Dammers, Mark S. Shephard

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsNOxEnvironmental scienceHuman healthEmission inventorySatelliteClimate changeAtmospheric sciencesPopulationMeteorologyClimatologyAir quality indexGeographyEcologyEngineering

Abstract

fetched live from OpenAlex

Over the past century ammonia (NH3) emissions have increased with human population growth and fertilizer usage. The abundant NH3 emissions lead to climate change, reduction in biodiversity and affect the human health. Up-to-date information of NH3emissions are essential to better understand the impact of NH3. In this study we adapted the existing DECSO (Daily Emissions Constrained by Satellite Observations) algorithm for use of NH3 observations from the Cross-track Infrared Sounder (CrIS) to estimate NH3 emissions. By considering the interaction between NH3 and NOx, we implemented DECSO to estimate NOx and NH3 emissions simultaneously on 20 km resolution over European domain. NH3 and NOx emissions over Europe are derived for 2020 on a daily basis from CrIS and TROPOMI (on Sentinel 5p). Due to the sparseness of daily satellite observations of NH3, monthly emissions of NH3 are constructed and analysed. The comparison of these emissions with other existing emission inventories will be presented.

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)0.001
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.038
GPT teacher head0.241
Teacher spread0.202 · 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
Published2023
Admission routes1
Has abstractyes

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