Influence of Precipitation on the Spatial Distribution of 210Pb, 7Be, 40K and 137Cs in Moss
Why this work is in the frame
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Bibliographic record
Abstract
Mosses have been widely used as biomonitors of a variety of atmospheric pollutants, including radionuclides. Here we determine the radionuclide activity concentration of 210Pb, 137Cs, 7Be, and 40K in moss tissue (Hylocomium splendens) collected from 24 sites across Ireland and assess the influence of precipitation on radionuclide spatial distribution. Lead-210 was the most abundant radionuclide (range: 226–968 Bq kg–1), followed by 7Be (range: <DL—604 Bq kg–1), 40K (range: <DL—155 Bq kg–1), and 137Cs (range: <DL—41 Bq kg–1). Albeit nearly thirty years since the Chernobyl disaster, 137Cs activity concentration was detected at 67% of the study sites; however, the spatial distribution was not fully consistent with the 1986 Chernobyl deposition pattern. Rather, 137Cs was weakly correlated with rainfall, with higher concentrations along the west coast, suggesting that the 2011 Fukushima Dai-ichi nuclear accident was also a potential source. Average annual rainfall was a significant predictor of 210Pb activity (linear regression, R2 = 0.63, p < 0.001). As such, the highest radionuclide activity was observed for 210Pb (average: 541 Bq kg–1), owing to the high levels of precipitation across the study sites (average: 1585 mm). In contrast, 7Be or 40K were not correlated with precipitation; rather, 40K and 7Be were significantly correlated to each other (rs = 0.7), suggesting that both radionuclides were transferred from the substrate or through soil re-suspension. Precipitation is widely reported as an important factor in the spatial distribution of radionuclides; however, only 210Pb activity concentrations in moss were strongly influenced by precipitation in the current study.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it