1998/99 national survey of pesticides in grdundwater using GCMS and ELISA
Bibliographic record
Abstract
Abstract A total of 95 wells throughout New Zealand were sampled during summer 1998/99 and analysed for a range of pesticides using gas chroma‐tography‐mass spectroscopy (GCMS). Thirty‐three wells (35%) had pesticides including triazine metabolites detected, with 18 wells (19%) having two or more pesticides detected. Only one well (K38/ 0172) had pesticides detected at levels greater than the maximum acceptable value (MAV) for drinking water. There were 20 different pesticides detected, usually at very low concentrations, as well as two triazine metabolites. Fifty‐seven out of the 75 pesticide detections (76%) belonged to the triazine group, with only five of these (9%) being >1 mg m −3 and 74% of these being <0.1 mg m‐ 3 . Three of the 18 non‐triazine pesticide detections (17%) were > 1 mg m −3 with all three detections being in Well K38/ 0172. About half (44%) of the non‐triazine pesticides were <0.1 mg M −3 . Apart from Well K38/0172, the highest levels of pesticides with respect to the MAV were seen for simazine and terbuthylazine, which were 16 and 44% of the MAV, respectively, with the remaining pesticides all below 4% of their MAV. This indicates that, although there were very low levels of pesticides present in 35% of the wells, there would be no significant health risk based on the pesticides analysed from drinking the groundwater investigated with the exception of Well K38/0172. There was a significant decrease in the detection limits for many pesticides for the 1998/99 survey compared to the two earlier surveys. When the detection limits for the earlier surveys were applied to the present survey there would have been a total of 10 wells out of the 95 sampled (11%) with pesticides detected. This compared with 7% of the 82 wells in 1990 and 13.6% of the 116 wells in 1994 with detectable pesticides, indicating that a similar percentage of wells have had detectable pesticides in each survey once correction for variable detection limits has been made. There was a significant difference between wells with and without pesticide detections for the following factors: wells with pesticide detections had shallower well screens, were screened nearer the water table, had lower pH values and higher nitrate levels. Samples for analysis using two enzyme‐linked immunosorbent assay (ELISA) atrazine test kits were collected at the same time as the other pesticide samples. The “normal” atrazine ELISA test kit only showed four positive detections, mainly because of a relatively high detection limit. The high sensitivity (HS) atrazine test kits detected pesticides in 20 of the 28 samples that were tested. Nineteen of the 20 detections had pesticide detections using GCMS, with the other eight samples having no pesticides detected using GCMS. The HS atrazine ELISA test kit appears to be a useful indicator of pesticide contamination for New Zealand groundwater systems at a relatively low level of detection. All the positive GCMS results that were tested gave positive test kit results and there was only one potential false positive result. This is probably because the majority of pesticides detected in groundwater in New Zealand are triazines, and the HS atrazine kit has cross reactivity with most triazines and related pesticides.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".