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Record W2395319182

Chapter 5: Anthropogenic methane sources, emissions and future projections

2015· article· en· W2395319182 on OpenAlex
Hoglund-Isaksson Lena, Thomson Allison, Kupiainen Kaarle, Shilpa Rao, Janssens-Maenhout Greet

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJoint Research Centre (European Commission) · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsMethane emissionsEnvironmental scienceMethaneGreenhouse gasGeologyOceanographyChemistry
DOInot available

Abstract

fetched live from OpenAlex

This chapter reviews recent global assessments of anthropogenic methane emissions, their expected future development and estimated reduction potentials. Because methane is a gas which mixes rapidly in the global atmosphere, it is of interest to review emissions at the global scale as well as for the area covered by the eight Arctic nations. The following key findings have been identified: • Bottom-up emission inventories agree fairly well in terms of the overall magnitude of global anthropogenic methane emissions in recent years, that is, about 300 Tg CH4 in 2000 and between 320 and 346 Tg CH4 in 2005. However, the relative contributions from the different source sectors differ markedly between inventories, which can be taken as an indication of high uncertainty within existing emission inventories despite the relatively close agreement between them in terms of total emissions. • Without further implementation of control policies addressing methane than currently adopted, global anthropogenic methane emissions are estimated to increase to between 400 and 500 Tg CH4 in 2030 and between 430 and 680 Tg CH4 in 2050. Primary drivers for the expected emission increase are increased coal production in China and extended shale gas extraction in the USA and Canada, activities which are known to release fugitive methane emissions. • With maximum technically feasible implementation of existing control technology, the estimated reduction potential for global anthropogenic methane emissions amounts to about 200 Tg CH4 in 2030, which is almost 50% below baseline emissions. The control technologies assessed to have the greatest reduction potentials are extended recovery of associated gas from oil production, control of fugitive leakages from gas production, transmission and distribution, extended separation, recycling and treatment of biodegradable waste instead of landfill disposal, extended pre-mining degasification of coal mines, and the implementation of ventilation air oxidizers on shafts from underground coal mines. • External factors, in particular the development of the future price of gas, could have significant effects on the future cost of reducing methane emissions and on the need for further policies to stimulate such reductions. The reason is that many measures to reduce methane emissions involve gas recovery or reduced gas leakage, which means potential opportunities to utilize the recovered gas as a source of energy. • With current policies addressing methane emissions, the eight Arctic nations are estimated to contribute about a fifth of global anthropogenic methane emissions. • As a single world region, the eight Arctic nations emit more anthropogenic methane and have a larger technical abatement potential than any other major world region (e.g. Latin America, Middle East, Africa or China). • The maximum technically feasible reduction of anthropogenic methane in Arctic nations in 2030 is estimated at 63% below baseline emissions or about a quarter of the entire global reduction potential. Within this reduction potential, measures related to fugitive methane emissions from shale gas extraction in the USA and Canada, reduced venting of associated gas from oil production in Russia, and reduced leakage from gas pipelines and distribution networks in all three countries, have the greatest potential to contribute to reduced methane emissions in Arctic nations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.053
GPT teacher head0.292
Teacher spread0.239 · 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