Organochlorine Pesticides in Surface Water of Jiuxi Valley, China: Distribution, Source Analysis, and Risk Evaluation
Why this work is in the frame
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Bibliographic record
Abstract
Residual levels of 11 organochlorine pesticides (OCPs) in surface water of Jiuxi Valley were determined during spring and autumn at nine sampling points to assess their contamination and potential risks. The water samples were extracted by solid-phase extraction (SPE), and OCPs were analyzed by gas chromatograph equipped with a 63 Ni-ECD detector. The investigation results indicated that the concentration of total OCPs varied from 4.07 to 13.5 ng·L −1 with an average value of 7.15 ng·L −1 in spring, and from 12.5 to 30.1 ng·L −1 with an average value of 19.9 ng·L −1 in autumn. Jiuxi Valley was slightly contaminated by OCPs, and the concentrations of ΣHCHs and ΣDDTs in the river were at relatively low levels. HCHs were the main pollutant in spring, and also in autumn, and α -HCH was the main component of the HCH isomers at most sampling points. Source analysis indicated that local use of lindane or input of fresh γ -HCH contributed to the presence of HCHs. New inputs were the major sources of DDTs, aldrin, heptachlor, and endrin. The OCP levels of this investigation were within the standard limits set by a majority of the water quality standards and guidelines of China, WHO, European Union, and Canada. However, although the γ -HCH concentrations at all sampling sites, endrin concentrations at all sampling sites, and β -HCH concentrations at most sampling sites were below the human health water quality standard, and the levels of other tested OCPs ( α -HCH, p,p′-DDD, p,p′-DDE, p,p′-DDT, aldrin, and heptachlor) exceeded the value of EPA-recommended water quality criteria for human health, which indicated potential risks to human health around the region.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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