Comprehensive Assessment of Dioxin Contamination in Da Nang Airbase and Its Vicinities: Environmental Levels, Human Exposure and Options for Mitigating Impacts
Bibliographic record
Abstract
Abstract—This study investigated contamination of dioxin in environment, food chains and human blood of communities living in ad around Da Nang military airbase. Significant quantities of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), a contaminant in Agent Orange, were detected in over 80 % of analyzed soil samples collected in December 2006. The maximum soil TEQ concentration recorded in this study was 365,000 ppt, from samples collected from the former Mixing and Loading Area; this is 365 times the globally acceptable maximum standard of 1,000 ppt. The maximum TCDD level recorded in fish fat in this study was 3,000 ppt (wet weight basis), which is 100 times the acceptable fish consumption level established by Health Canada. Blood dioxin levels recorded in this study (n = 55 patients sampled) for Da Nang residents directly associated with the Airbase were the highest reported for Viet Nam to date, and exceed all international standards for these chemicals. Those individuals who work on the Da Nang Airbase in Sen Lake (harvesting fish and lotus) and in the Airbase gardens (which are often flooded) were found to have dioxin concentrations in their blood more than 100 times globally acceptable levels. The maximum concentration was recorded in a 42-year old male, who had a TCDD level of 1,150 ppt lipid (1,220 ppt TEQ; 94 % TCDD). A number of other contaminants, including PCBs, were also recorded in blood samples analyzed, and contributed significantly to the Total TEQ. In 2007, five construction/measures have been implemented in order to prevent continuous spread of dioxin-contaminated soil and sediment to wider environment and thus may cause impacts to larger population.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".