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Record W1999029641 · doi:10.1029/2007jg000637

CO<sub>2</sub> emissions from saline lakes: A global estimate of a surprisingly large flux

2008· article· en· W1999029641 on OpenAlexaff
Carlos M. Duarte, Yves T. Prairie, Carlos Montes, Jonathan J. Cole, Robert G. Striegl, John M. Mélack, John Downing

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsAtmosphere (unit)Flux (metallurgy)Environmental scienceAtmospheric sciencesEnvironmental chemistrySalineSaline waterSalinityHydrology (agriculture)ChemistryOceanographyMeteorologyGeologyPhysicsBiology

Abstract

fetched live from OpenAlex

The role of saline lakes in CO 2 exchange with the atmosphere was evaluated on the basis of calculated partial pressure ( p CO 2 ) and CO 2 exchange rates with the atmosphere derived from a compilation of published data for 196 saline lakes around the world. The average surface water p CO 2 exceeded atmospheric p CO 2 by a factor of 5–8 times, indicative of a tendency for saline lakes to emit CO 2 to the atmosphere. Chemically enhanced emission, calculated from solute chemistry, pH, and wind speed, increased gas exchange an average of 2.3 times over that of freshwater lakes having equivalent p CO 2 . The globally distributed lakes emitted CO 2 at rates in excess of 80 mmol m −2 d −1 . The Caspian Sea was calculated to support alone a total CO 2 emission of 0.02 to 0.04 Gt C a −1 , with the total CO 2 emissions to the atmosphere from saline lakes calculated to be 0.11–0.15 Gt C a −1 . Consideration of CO 2 emissions from saline lakes raises the total CO 2 emissions to the atmosphere from all lakes to 0.28–0.32 Gt CO 2 . These results point to a significant role of saline lakes in global C cycling.

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)0.001
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 score0.115
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.300
Teacher spread0.272 · 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

Citations203
Published2008
Admission routes1
Has abstractyes

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