On-Road Remote Sensing of Automobile Emissions in the La Brea Area: Year 3, October 2003
Notice bibliographique
Résumé
The University of Denver conducted a five-day remote sensing study in the La Brea, California area in October of 2003. The remote sensor used in this study measures the ratios of CO, HC, and NO to CO2 in motor vehicle exhaust. From these ratios, we calculate the percent concentrations of CO, CO2, HC and NO in the exhaust that would be observed by a tailpipe probe, corrected for water and any excess oxygen not involved in combustion. Mass emissions per mass or volume of fuel can also be determined. The system used in this study was configured to determine the speed and acceleration of the vehicle, and was accompanied by a video system to record the license plate of the vehicle.\nFive days of fieldwork, October 27-31, 2003, were conducted as vehicles entered I-10 eastbound frontage road from La Brea Blvd. in west Lost Angles basin. A database was compiled containing 25,847 records. Of these records, the State of California provided make and model year information on 20,191 which contained valid measurements for at least CO and CO2, and most contained valid measurements for HC and NO as well. The database, as well as others compiled by the University of Denver, can be found at www.feat.biochem.du.edu.\nThe mean percent CO, HC, and NO were determined to be 0.34%, 0.012%, and 0.032%, respectively. The emissions measurements in this study exhibit a gamma distribution, with the dirtiest 10% of the measurements responsible for 72.2%, 60.3%, and 59.3% of the CO, HC, and NO emissions, respectively. The HC readings contain a 35 ppm offset, which has been used to reduce all of the measured HC values for comparisons.\nVehicle emissions as a function of vehicle specific power revealed that NO emissions show a flat dependence on specific power when speed and acceleration are measured after emissions. This is quite possibly a result of increased CO emissions in the same VSP range. HC emissions show a negative dependence on specific power – the expected trend. CO emissions show a positive dependence on specific power in the range from 5 to 30 kW/tonne.\nUsing vehicle specific power, the emissions from the vehicle fleet measured in 2003 were adjusted to match the vehicle driving patterns of the fleet measured in 1999. After doing so, it was seen that the emissions measured in the current year are lower than those measured during 1999. Model year adjustments gave equivocal results.\nA new analysis looked at vehicle emission levels as a function of the type of transmission the vehicle uses. It suggests that when comparing emissions between E-23 sites one may need to consider transmission type in addition to age and vsp. Since, even after age adjustments are made, manual transmission equipped vehicles at La Brea had more than twice the average CO, 40% higher HC and 20% higher NO emissions.\nAn analysis of high emitting vehicles showed that there is considerable overlap of CO and HC high emitters, for instance 3.7% of the measurements contribute 36% of the total CO and 35% of the total HC. The noise levels in the CO, HC and NO measurement channels were determined to be within acceptable limits that were minimal when compared to the standard error of the mean of the measurements.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».