The impact of wildfires on the abundance of polycyclic aromatic hydrocarbons (PAH) in soils of Northwestern Canada
Bibliographic record
Abstract
The intensifying wildfire regimes under climate change, as expressed, for example, in the recent fire seasons in the boreal zones, call for an improved understanding of the impacts of forest fires on air, water and soil quality. One group of compounds released during wildfires are the polycyclic aromatic hydrocarbons (PAHs), of which many are considered toxic for organisms, including human health.This study investigated 13 sites along a transect across five boreal forest and tundra biomes for the abundance and composition of 16 USEPA listed PAHs in soil organic and mineral horizons. Accelerated solvent extraction in a combination with organic solvents (MeOH:DCM and n-hexane:DCM) was used for PAHs extraction and subsequently analyzing them using an Agilent 7890A gas chromatograph coupled to an Agilent 5975C mass spectrometer. We tested how far distance to the nearest fire event (15 years), total PAH concentrations declined significantly (range: 0.7 to 1806.7 ng/g) in comparison to recent fire sites, likely due to degradation and wash-out processes. Litter horizons generally exhibited higher PAH levels than organic and mineral horizons, with high molecular weight (HMW) PAHs dominating (~30% LMW vs. ~70% high molecular weight). Apparently, the distance to the fire source had no significant effect on PAHs abundance. However, fire intensity, as indicated by fire radiative power (FRP) and dNBR, correlated with PAHs levels in the litter horizon, suggesting that temperature and combustion conditions are critical determinants of PAHs formation and persistence. Diagnostic PAHs ratios also confirmed the predominance of pyrogenic sources. These initial findings highlight the post-fire loss of PAHs via degradation and wash-out, reducing soil toxicity over time. More research might focus on a high-resolution soil and water monitoring shortly after wildfires to better understand how far degradation and wash-out dominates PAHs loss that could shift burning residues from soil to water biomes.
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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 | 0.002 | 0.001 |
| 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".