Current situation and health risk assessment of neonicotinoids insecticides in urban indoor dust from Ha Noi, Viet Nam
Bibliographic record
Abstract
In the several decades, although neonicotinoids insecticides (typically imidacloprid and thiamethoxam) are widely used and account for 24 % of the total global pesticide production, they still have negative impacts on natural enemies such as kinds of bees as well as adversely affect human health. However, there are only a few studies evaluating the levels of imidacloprid and thiamethoxam in airborne environments including indoor dust. Therefore, the aim of this study was to investigate the distribution, concentration and health risk to human of imidacloprid and thiamethoxam in indoor dust samples collected from 6 inner districts of Hanoi. Imidacloprid was found in indoor dust samples at all samples with an average concentration of 0.079 µg/g (ranging from 0.028 to 0.216 µg/g, the detection frequency of 100 %). Meanwhile, the mean concentration of thiamethoxam was revealed lower than imidacloprid at 0.013 µg/g (ranging from 0.01 to 0.027 µg/g, the detection frequency of 60 %). In high-end exposure, based on the measured concentrations, daily intake doses (IDs) of imidacloprid and thiamethoxam were calculated to be 9.96 × 10-1 and 1.10 × 10-2 ng/kg-bw/day for adults, and 1.78 and 1.98 × 10-1 ng/kg-bw/day for children, respectively. The estimated values of hazard quotient (HQ) of imidacloprid and thiamethoxam were 1.75 × 10-6 and 9.20 × 10-7 ng/kg-bw/day for adults, and 3.13 × 10-5 and 1.65 × 10-5 ng/kg-bw/day for children, respectively. All HQ and HI values of the insecticides were less than 1 for both of adults and children, indicating the potential adverse effects to human health are negligible.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".