Evaluation and Application of Max-DOAS Methods for Monitoring Aerosols, NO2, and SO2 in Urban and Industrial Environments
Bibliographic record
Abstract
The ideal measurement technique to effectively address an air quality problem depends on the chemical and physical properties of the species and its environment. Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) techniques allow a diversity of applications for studying atmospheric species, including the determination of emissions, vertical profiles, and the tropospheric column loading of trace gases. Deployment of the MAX-DOAS instrument during the comprehensive air quality campaign in the Athabasca Oil Sands Region in 2013 provided a rare opportunity to evaluate the performance of multiple aspects of the MAX-DOAS retrievals. Retrievals of aerosol extinction, NO2, and SO2 were compared to data from lidar, sun photometer, Active-DOAS, and airborne in-situ measurements of trace gases. The MAX-DOAS retrievals performed well except under conditions of rapidly changing vertical profiles of pollution. Important elements required to achieve useful inter-comparisons of MAX-DOAS with other instruments (e.g., the lidar S-ratio) and advantages of the MAX-DOAS technique were identified. MAX-DOAS measurements of SO2 gas calibration cells were conducted to determine the optimal settings for fitting SO2 differential slant column densitities (dSCDs), currently absent in the literature. Fitting dSCDs of SO2 from solar measurements is challenging due to the effects of stray light, potential interference by O3 absorption, and low solar intensity in wavelength regions where SO2 absorption features are strong. Based on the experiments, the use of a short-pass filter and a fitting window of 307.5 < <319 nm are recommended. MAX-DOAS measurements in Toronto, Ontario, during 2015 quantified the impact of lake-breeze circulations on the tropospheric loading of NO2 and aerosol extinction. These first measurements of the total tropospheric loading of pollutants behind a lake breeze front on multiple days using MAX-DOAS confirms previously theorized 3-D structures of lake breezes. Finally, the mobile-MAX-DOAS technique of estimating NOx and SO2 emissions was improved by conducting simultaneous Mobile-MAX-DOAS and in-situ NO-NO2-NOx measurements and deploying a modular meteorological station while observing urban plumes in the industrial city of Sarnia, Ontario. These studies demonstrated the utility of MAX-DOAS techniques for monitoring tropospheric air quality in industrial and urban settings when in-situ and other remote sensing techniques are limited.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".