Tropospheric NO2 Monitoring Using the Multi-Axis Differential Optical Absorption Spectroscopy in Urban Area
Bibliographic record
Abstract
Spectroscopic methods have played an important role in the study of chemical and physical processes related to the composition of the atmosphere and the differential optical absorption spectroscopy (DOAS) has been one of the most powerful methods to measure a wide range of trace gases. The pollutants are identified by their respective ranges of wavelengths that must be previously known. A Passive Differential Optical Absorption Spectroscopy system that uses the ultraviolet region from 400 to 480 nm of the solar radiation is presented. In this research diurnal variation of NO2 was remotely measured by means of MAX-DOAS system which uses multiple viewing angles to monitor pollutant concentrations in urban area at the city of Rio de Janeiro. The instrument was placed on the roof of a building oriented to the center of the city. Tropospheric NO2 amounts are retrieved from the measured spectra using the DOAS technique. In this paper we give a general description of the procedure and present the results from measurements during four days in winter 2017 associated with the prevailing meteorological aspects. These days were characterized by mostly sunny and dry conditions, no convection, periods of medium clouds and clear sky. The tropospheric NO2 slant column densities values are presented and the results are consistent for all three used elevation angles (5º, 10º, and 15º). The results demonstrate the capability and the potential of the MAX-DOAS technique to derive information on spatial distribution of NO2 in an urban environment.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 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".