Venting of Heat and Carbon Dioxide from Urban Canyons at Night
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Turbulent fluxes of carbon dioxide and sensible heat were observed in the surface layer of the weakly convective nocturnal boundary layer over the center of the city of Marseille, France, during the Expérience sur Sites pour Contraindre les Modèles de Pollution Atmosphérique et de Transport d’Emission (ESCOMPTE) field experiment in the summer of 2001. The data reveal intermittent events or bursts in the time series of carbon dioxide (CO2) concentration and air temperature that are superimposed upon the background values. These features relate to intermittent structures in the fluxes of CO2 and sensible heat. In Marseille, CO2 is primarily emitted into the atmosphere at street level from vehicle exhausts. In a similar way, nocturnal sensible heat fluxes are most likely to originate in the deep street canyons that are warmer than adjacent roof surfaces. Wavelet analysis is used to examine the hypothesis that CO2 concentrations can be used as a tracer to identify characteristics of the venting of pollutants and heat from street canyons into the above-roof nocturnal urban boundary layer. Wavelet analysis is shown to be effective in the identification and analysis of significant events and coherent structures within the turbulent time series. Late in the evening, there is a strong correlation between the burst structures observed in the air temperature and CO2 time series. Evidence suggests that the localized increases of temperature and CO2 observed above roof level in the urban boundary layer (UBL) are related to intermittent venting of sensible heat from the warmer urban canopy layer (UCL). However, later in the night, local advection of CO2 in the UBL, combined with reduced traffic emissions in the UCL, limit the value of CO2 as a tracer of convective plumes in the UBL.
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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 | 0.000 |
| 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 it