Estimation of NO <sub> <i>x</i> </sub> and SO <sub>2</sub> emissions from Sarnia, Ontario, using a mobile MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) and a NO <sub> <i>x</i> </sub> analyzer
Bibliographic record
Abstract
Sarnia, Ontario, experiences pollutant emissions disproportionate to its relatively small size. The small size of the city limits traditional top-down emission estimate techniques (e.g., satellite) but a low-cost solution for emission monitoring is the mobile MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy). Measurements were made using this technique from 21 March 2017 to 23 March 2017 along various driving routes to retrieve vertical column densities (VCDs) of NO 2 and SO 2 and to estimate emissions of NO x and SO 2 from the Sarnia region. A novel aspect of the current study was the installation of a NO x analyzer in the vehicle to allow real time measurement and characterization of near-surface NO x ∕NO 2 ratios across the urban plumes, allowing improved accuracy of NO x emission estimates. Confidence in the use of near-surface-measured NO x ∕NO 2 ratios for estimation of NO x emissions was increased by relatively well-mixed boundary layer conditions. These conditions were indicated by similar temporal trends in NO 2 VCDs and mixing ratios when measurements were sufficiently distant from the sources. Leighton ratios within transported plumes indicated peroxy radicals were likely disturbing the NO–NO 2 –O 3 photostationary state through VOC (volatile organic compound) oxidation. The average lower-limit emission estimate of NO x from Sarnia was 1.60±0.34 t h −1 using local 10 m elevation wind-speed measurements. Our estimates were larger than the downscaled annual 2017 NPRI-reported (National Pollution Release Inventory) industrial emissions of 0.9 t NO x h −1 . Our lower-limit estimate of SO 2 emissions from Sarnia was 1.81±0.83 t SO 2 h −1 , equal within uncertainty to the 2017 NPRI downscaled value of 1.85 t SO 2 h −1 . Satellite-derived NO 2 VCDs over Sarnia from the ozone monitoring instrument (OMI) were lower than mobile MAX-DOAS VCDs, likely due to the large pixel size relative to the city's size. The results of this study support the utility of the mobile MAX-DOAS method for estimating NO x and SO 2 emissions in relatively small, highly industrialized regions, especially when supplemented with mobile NO x measurements.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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 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".