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Record W4285159157 · doi:10.18174/570194

Emissies naar lucht uit de landbouw berekend met NEMA voor 1990-2020

2022· report· nl· W4285159157 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typereport
Languagenl
FieldEnergy
TopicEnergy, Environment, Agriculture Analysis
Canadian institutionsImpact
Fundersnot available
KeywordsLimeEnvironmental scienceManureLivestockParticulatesNitrous oxideManure managementGreenhouse gasCarbon dioxideEnvironmental chemistryAnimal scienceEnvironmental engineeringChemistryAgronomyForestryGeographyEcology

Abstract

fetched live from OpenAlex

In the Netherlands, agricultural activities are a major source of gaseous emissions of ammonia (NH3 ), nitrogenoxide (NO), nitrous oxide (N2O), methane (CH4 ), non-methane volatile organic compounds (NMVOC), carbon dioxide(CO 2 ) from lime fertilisers and urea fertiliser, and particulate matter (PM10 and PM2.5 ). These emissions were calculated using the National Emission Model for Agriculture (NEMA). In 2020, NH3 emissions from livestock manure, fertiliser and other sources on farms and hobby farms, from private use and from manure application in terrestrial ecosystems amounted to 113.4 million kg NH3 . This is 0.6 million kg higher than in 2019. Nitrogen excretion from livestock in 2020 was almost the same as in 2019. Emissions of N2 O in 2020 were 19.1 million kg, equal to the level in 2019. Emissions of NO increased by 0.2 million kg in 2020 to 22.3 million kg. Emissions of CH4 decreased slightly from 479 to 477 million kg. Emissions of NMVOC also decreased slightly, from 87.8 to87.6 million kg. Emissions of particulate matter PM10 decreased from 5.5 in 2019 to 5.4 million kg in 2020 and PM 2.5 emissions remained at 0.5 million kg. Emissions of CO2 from lime fertilisers and urea decreased from 85.2 to78.2 million kg. Based on new data for several factors described in this report, emission figures were updated for a number of years in the time series. Emissions of NH3 from livestock manure have decreased by two-thirds since1990, mainly as a result of lower nitrogen excretion rates and the introduction of low-emission manure application. Emissions of N2O and NO also decreased over the same period, but less markedly than the NH3 reduction, by 41% and 33% respectively. Manure injection led to an increase in these emissions compared with surface spreading of manure, while the shift from grazing to housing led to a reduction in these emissions. Emissions of CH4 decreasedby 19% between 1990 and 2020 due to a decrease in livestock numbers and increased feed use efficiency of dairy cattle. Emissions of PM10 increased by 12% in the same period due to laying poultry farms switching from housing systems with slurry manure to systems with solid manure.

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.

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.213
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2150.002

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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

Quick stats

Citations18
Published2022
Admission routes1
Has abstractyes

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