Field intercomparison of continuous ambient FRM and FEM NO<sub>2</sub> instruments in the Athabasca Oil Sands Region, Alberta, Canada and the potential impact on ambient regulatory compliance
Bibliographic record
Abstract
The Canadian Federal Government promulgated new and lower NO2 Ambient Air Quality Standards (CAAQS) that went into effect in 2020 with additional decreases scheduled for 2025. The new hourly and annual NO2 CAAQS are 60 and 17 ppb, respectively, and the 2025 hourly and annual CAAQS are 42 and 12 ppb, respectively. The province of Alberta has also promulgated Ambient Air Quality Objectives (AAAQO) for NO2 currently set to 159 and 24 ppb on an hourly and annual basis, respectively. The Wood Buffalo Environmental Association (WBEA) in northeastern Alberta, Canada monitors NO2 at 21 community and industrial sites throughout the Athabasca Oil Sands Region (AOSR), for regulatory compliance using Thermo-Environmental (TEI) Model 42i Federal Reference Method (FRM) designated NO-NO2-NOx analyzers. The 42i measures NO directly via NO-O3 chemiluminescence, and NOx following the reduction of oxidized nitrogen to NO by a heated internal molybdenum converter. The difference between the NOx and NO channels is reported as NO2. This study presents the results of a three-year (2018–2021) WBEA comparison of four continuous NO2 analyzers: TEI 42i FRM; the API Model T500U cavity attenuated phase shift (CAPS) Federal Equivalent Method (FEM); a total reactive odd nitrogen analyzer (TEI Model 42i-Y); and a TEI 42i equipped with an external photolytic converter. The study showed that NO2 data from all analyzers were highly correlated and in general agreement, with r2 values (vs. the CAPS) ranging from 0.990–0.997 and slopes ranging from 0.933–0.992. Mean NO2 concentrations over the study period ranged from 7.2–7.5 ppb. Differences between the TEI 42i, TEI 42i-Y, and PhoNO, relative to the CAPS were all positive and highly significant (p < 0.0001), based upon nonparametric tests. The potential impact from the selection of different FRM/FEM measurement methods on current and future Canadian 2025 regulatory compliance in the region is evaluated. Implications: The study objective was to compare/evaluate different regulatory NO2 measurement techniques from a regional monitoring authority in a routine network operational context. Relatively small NO2 differences resulted in significant differences with respect to regulatory compliance triggers, particularly hourly standards based on daily extreme value statistics (e.g., 99th percentiles). For example, mean hourly NO2 △ differences ranged from 0.02–0.26 ppb over the study period but resulted in 2–3 ppb differences in the 3-year hourly CAAQS metrics. These differences could affect regulatory CAAQS and LARP compliance (management level) at monitoring sites observed during 2019 annual and 2020 hourly LARP trigger exceedances.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".