A comparison of methods for the measurement of CO<sub>2</sub> and CH<sub>4</sub> emissions from surface water reservoirs: Results from an international workshop held at Three Gorges Dam, June 2012
Bibliographic record
Abstract
Abstract Fluxes of carbon dioxide (CO2) and methane (CH4) from hydroelectric and water supply reservoirs are receiving increasing attention around the world with a number of research groups having undertaken measurements of these emissions across a range of lakes and reservoirs located in different climates and landscapes. The use of floating chambers (aka flux chambers) is the most common technique for direct measurement of these fluxes. However, the relative performance of different measurement systems, especially different chamber designs, is not well documented. We report the results of an international workshop held in June 2012 at Three Gorges Dam, China, to compare measurements performed by four groups with extensive chamber monitoring experience: the Chinese Academy of Science (China), CSIRO (Australia), SINTEF (Norway), Hydro‐Québec/Environnement Illimité (Canada). A fifth group, Eawag (Switzerland), performed hydroacoustic surveys to detect ebullition in the water column. We recommend CH4 as a more suitable trace gas for comparing methodologies due to its relative stability in the surface layer of the water column, for example, it is not subject to significant diurnal changes due to photosynthesis and respiration. Measured fluxes agreed to within 20% between the four teams suggesting that the shape and dimensions of the floating chambers and the chamber gas flow rates (i.e., chamber residence time) did not have an appreciable systematic effect on the measured fluxes for the relatively low wind speeds prevalent at the reservoir. The CO2 and CH4 fluxes measured during the workshop agree well with previous measurements in Three Gorges Reservoir.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".