How important is biomass burning in Canada to mercury contamination?
Bibliographic record
Abstract
Abstract. Wildfire frequency has increased in past four decades in Canada and is expected to increase in future as a result of climate change (Wotton et al., 2010). Mercury (Hg) emissions from biomass burning are known to be significant; however, the impact of biomass burning on air concentration and deposition fluxes in Canada has not been previously quantified. We use estimates of burned biomass from FINN (Fire INventory from NCAR) and vegetation-specific emission factors (EFs) of mercury to investigate the spatiotemporal variability of Hg emissions in Canada. We use Environment and Climate Change Canada's GEM-MACH-Hg (Global Environmental Multi-scale, Modelling Air quality and Chemistry model, mercury version) to quantify the impact of biomass burning in Canada on spatiotemporal variability of air concentrations and deposition fluxes of mercury in Canada. We use North American gaseous elemental mercury (GEM) observations (2010–2015), GEM-MACH-Hg, and an inversion technique to optimize the EFs for GEM for five vegetation types represented in North American fires to constrain the biomass burning impacts of mercury. The inversion results suggest that EFs representing more vegetation types – specifically peatland – are required. This is currently limited by the sparseness of measurements of Hg from biomass burning plumes. More measurements of Hg concentration in the air, specifically downwind of fires, would improve the inversions. We use three biomass burning Hg emissions scenarios in Canada to conduct three sets of model simulations for 2010–2015: two scenarios where Hg is emitted only as GEM using literature or optimized EFs and a third scenario where Hg is emitted as GEM using literature EFs and particle bound mercury (PBM) emitted using the average GEM∕PBM ratio from lab measurements. The three biomass burning emission scenarios represent a range of possible values for the impacts of Hg emissions from biomass burning in Canada on Hg concentration and deposition.We find total biomass burning Hg emissions to be highly variable from year to year and estimate average 2010–2015 total atmospheric biomass burning emissions of Hg in Canada to be between 6 and 14 t during the biomass burning season (i.e. from May to September), which is 3–7 times the mercury emission from anthropogenic sources in Canada for this period. On average, 65 % of the emissions occur in the provinces west of Ontario. We find that while emissions from biomass burning have a small impact on surface air concentrations of GEM averaged over individual provinces/territories, the impact at individual sites can be as high as 95 % during burning events. We estimate average annual mercury deposition from biomass burning in Canada to be between 0.3 and 2.8 t, compared to 0.14 t of mercury deposition from anthropogenic sources during the biomass burning season in Canada. Compared to the biomass burning emissions, the relative impact of fires on mercury deposition is shifted eastward, with on average 54 % percent of the deposition occurring in provinces west of Ontario. While the relative contribution of Canadian biomass burning to the total mercury deposition over each province/territory is no more than 9 % between 2010 and 2015, the local contribution in some locations (including areas downwind of biomass burning) can be as high as 80 % (e.g. northwest of Great Slave Lake in 2014) from May to September. We find that northern Alberta and Saskatchewan, central British Columbia, and the area around Great Slave Lake in the Northwest Territories are at greater risk of mercury contamination from biomass burning. GEM is considered to be the dominant mercury species emitted from biomass burning; however, there remains an uncertainty in the speciation of mercury released from biomass burning. We find that the impact of biomass burning emissions on mercury deposition is significantly affected by the uncertainty in speciation of emitted mercury because PBM is more readily deposited closer to the emission sources than GEM; an addition of ∼ 18 % percent of mercury emission from biomass burning in the form of PBM in the model increases the 6-year average deposition by ∼ 4 times.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".