Global climate change and contaminants—an overview of opportunities and priorities for modelling the potential implications for long-term human exposure to organic compounds in the Arctic
Bibliographic record
Abstract
This overview seeks to provide context and insight into the relative importance of different aspects related to global climate change for the exposure of Northern residents to organic contaminants. A key objective is to identify, from the perspective of researchers engaged in contaminant fate, transport and bioaccumulation modelling, the most useful research questions with respect to projecting the long-term trends in human exposure. Monitoring studies, modelling results, the magnitude of projected changes and simplified quantitative approaches are used to inform the discussion. Besides the influence of temperature on contaminant amplification and distribution, accumulation of organic contaminants in the Arctic is expected to be particularly sensitive to the reduction/elimination of sea-ice cover and also changes to the frequency and intensity of precipitation events (most notably for substances that are highly susceptible to precipitation scavenging). Changes to key food-web interactions, in particular the introduction of additional trophic levels, have the potential to exert a relatively high influence on contaminant exposure but the likelihood of such changes is difficult to assess. Similarly, changes in primary productivity and dynamics of organic matter in aquatic systems could be influential for very hydrophobic contaminants, but the magnitude of change that may occur is uncertain. Shifts in the amount and location of chemical use and emissions are key considerations, in particular if substances with relatively low long range transport potential are used in closer proximity to, or even within, the Arctic in the future. Temperature-dependent increases in emissions via (re)volatilization from primary and secondary sources outside the Arctic are also important in this regard. An increased frequency of boreal forest fires has relevance for compounds emitted via biomass burning and revolatilization from soil during/after burns but compound-specific analyses are limited by the availability of reliable emission factors. However, potentially more influential for human exposure than changes to the physical environment are changes in human behaviour. This includes the gradual displacement of traditional food items by imported foods from other regions, driven by prey availability and/or consumer preference, but also the possibility of increased exposure to chemicals used in packaging materials and other consumer products, driven by dietary and lifestyle choices.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".