Bibliographic record
Abstract
The study of organic acids recorded in snow and ice provides a unique way to obtain information on a variety of the species in response topast climate change,past environment and past ecosystem, and represents one of the main fields in glaciochemistry. It also provides insight into biogeochemical cycles of carbon, hydrogen and oxygen and other major biological elements. In August 1987, a special session on organic acids and related compounds in the atmosphere was held at the Sixth International Symposium of the Commission on Atmospheric Chemistry and Global Pollution in Peterborough, Canada, which symbolized that studies of organic acids had drawn attention of researchers around the world. The organic acids detected in snow and ice are formic, acetic, propionic, pyruvic, oxalic and glycolic. The former two represent the most abundant ones. In some places, their concentrations are even higher than inorganic acids such as sulfate, nitrate and chloride. For the past decade, the study of the organic acids mainly focused on Greenland and Antarctica. Recent two years, however, the study turns to alpine glaciers in the middle and low latitude areas because organic acids recorded in alpine glaciers are much closer to the sources than those in polar areas. Studies show that formic and acetic in Greenland ice cores reached up to 10ng·g -1 in their average concentrations with the former higher than the latter, while the oxalic and glycolic are below 1 ng·g -1 . They mainly came from biomass burning, which accounts for about 20 %, and vegetation emissions in the north hemisphere that contribute to the background of the organic acids. In even lower concentrations, the formic acids recorded in Antarctic ice cores are below 2 ng·g -1 , whereas the acetic below 0.15ng·g -1 . They are considered as from the atmospheric oxidation of numerous hydrocarbons such as methane and alkenes. MSA in Greenland ice cores is below 5ng·g -1 on an average, whereas that in Antarctica up 7ng·g -1 . They all came from the oceanic emission of DMS. In sharp contrast, formic and acetic acids in the Glacier No.1 at the headwaters of the rumqi River, a middle latitude alpine glacier in the Tianshan Mountains, West China, are several ten-fold higher than those in Greenland, and a few thousands times more than those in Antarctica. Moreover, resolution of organic acid records in middle latitude alpine glaciers is also higher than those in polar areas. This demonstrates that the organic records in alpine glaciers are more conducive to understanding the biogeochemical cycles of the organic acids. Climate changes affect the terrestrial vegetation, the source for the carboxylic acids, and the oceanic production of DMS, the precursor of MSA, thus the secular trends of the organic acid records in ice cores. It is interested to note that MSA connects the climate change in different ways for the two hemispheres. Greenland ice cores demonstrate the MSA correlates positively with climate change, while it does somewhat negatively in Antarctica. ENSO affects the production of DMS in the southern hemisphere and it probably causes the disparity. The change of the formic/acetic ratio in the Greenland ice core from 1945 suggests the anthropogenic impact from the northern hemisphere, which caused an increase of acetic acid while a decrease of formic.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".