Multiscale observations of NH3 around Toronto, Canada
Bibliographic record
Abstract
Ammonia (NH3) is a major source of nitrates in the atmosphere, and a major source of fine particulate matter. As such, there have been increasing efforts to monitor NH3. This study examines long-term measurements of NH3 around Toronto, Canada, derived from three multiscale datasets: 16 years of total column measurements using ground-based Fourier transform infrared (FTIR) spectroscopy, three years of surface in-situ measurements, and ten years of total columns from the Infrared Atmospheric Sounding Interferometer (IASI) sensor onboard the Metop satellites. These datasets were used to quantify NH3 temporal variabilities (trends, inter-annual, seasonal) over Toronto to assess the observational footprint of the FTIR measurements, and two case studies of pollution events due to transport of biomass burning plumes. All three timeseries showed increasing trends in NH3 over Toronto: 3.34 ± 0.44 %/year from 2002 to 2018 in the FTIR columns, 8.88 ± 2.49 %/year from 2013 to 2017 in the surface in-situ data, and 8.78 ± 0.84 %/year from 2008 to 2018 in the IASI columns. To assess the observational footprint of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was found for coincidence criterion of ≤ 50 km and ≤ 20 minutes, with r = 0.66 and a slope of 0.988 ± 0.058. The FTIR column and in-situ measurements were standardized and correlated, with 24-day averages and monthly averages yielding correlation coefficients of r = 0.72 and r = 0.75, respectively. FTIR and IASI were also compared against the GEOS-Chem model, run at 2° by 2.5° resolution, to assess model performance and investigate correlation of the model output with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (domain spanning from 35°N to 53°N, and 93.75°W to 63.75°W) resulted in r = 0.62, and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2 = 0.38, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2 = 0.26, indicating that a finer spatial resolution is needed to adequately model the variability of NH3. This study also examines two case studies of NH3 enhancements due to biomass burning plumes, in August 2014 and May 2016. In these events, enhancements in both the total columns and surface NH3, were observed.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".