Contributions of natural and anthropogenic sources to ambient ammonia in the Athabasca Oil Sands and north-western Canada
Bibliographic record
Abstract
Abstract. Atmospheric ammonia (NH3) is a short-lived pollutant that plays an important role in aerosol chemistry and nitrogen deposition. Dominant NH3 emissions are from agriculture and forest fires, both of which are increasing globally. The Alberta Oil Sands region has relatively low ambient NH3 concentrations because of its remote location in northern Canada; however, a previous attempt to model NH3 in the region showed a substantial negative bias compared to satellite column and aircraft observations. Known missing sources of NH3 in the model were re-emission of NH3 from plants and soils (bidirectional flux), and forest fire emissions, but the relative impact of these sources on NH3 concentrations and column totals was unknown. Here we have used a research version of the high-resolution air quality forecasting model, GEM-MACH, to quantify the relative impacts of natural (bidirectional flux of NH3 and forest fire emissions) and anthropogenic (Oil Sands operations, combustion of fossil fuels, and agriculture) sources on ammonia concentrations, both at the surface and aloft, with a focus on the Athabasca Oil Sands region, during a measurement-intensive campaign in the summer of 2013. The addition of fires and bidirectional flux has improved the model bias, slope and correlation coefficients relative to ground, aircraft, and satellite measurements significantly. By running the GEM-MACH model in three configurations and calculating their differences, we find that averaged over Alberta and Saskatchewan during this time period; an average of 23.1 % of surface NH3 came from direct anthropogenic sources, 56.6 % (or 1.24 ppbv) from bidirectional flux (reemission from plants and soils), and 20.3 % (or 0.42 ppbv) from forest fires. In the NH3 total column, an average of 19.5 % came from direct anthropogenic sources, 50.0 % from bidirectional flux, and 30.5 % from forest fires. The addition of bidirectional flux and fire emissions caused the overall average net flux of NH3 across the domain to be positive (upward). It also increased the NH+4 wet deposition by nearly a factor of three during the period simulated. Note that forest fires are very episodic and their contributions will vary significantly for different time periods and regions.
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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 | 0.001 | 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".