Quantifying the impact of the transition to LED lighting on night sky brightness and colour using ground-based measurements and satellite imagery
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Notice bibliographique
Résumé
• The impact of the transition from HPS to LED on light pollution is unknown. • We quantified changes in night time brightness and color using remote sensing. • We compared three sensors: TESS-4C and LANcube (ground), SDGSAT-1 (satellite). • We applied machine learning to separate between cloudy and clear nights. • We found that the transition to LED resulted with brighter and whiter lights. Nighttime light pollution is gaining significant interest in the scientific community and the public due to its harmful effects on human health, ecosystems, and leisure activities. Recently, many countries worldwide have been retrofitting their streetlights with light emitting diodes (LEDs) to enable smart street lighting while reducing energy use for street lights. However, little is known about the rate of change in brightness and even less about the new composition of the nighttime light spectrum. In this study, we investigated the changes of brightness and colour of light pollution at night in a major road interchange, conducting measurements before and after the transition from high pressure sodium (HPS) yellow street lights to white LED lights. We used two ground-based photometers, one fixed (TESS-4C) and one mobile (LANcube), which provided long-term record of the artificial light at night at this location. We also quantified changes in nighttime lights as observed by the multispectral nighttime lights satellite SDGSAT-1. To ensure non-biased conditions, we used a random forest model to discriminate between clear and cloudy nights for our analysis of the TESS-4C measurements. These instruments offer a comprehensive analysis by measuring night-time brightness in various units and capturing distinct response spectra across different colour bands. We found an increase in nighttime brightness after the interchange was equipped with LED lamps compared to the previous HPS lamps. However, this increase was only identified by the ground sensors and not by the satellite. All sensors identified a shift in the emitted spectrum towards shorter wavelengths, with an increase in the red/green ratio being the most consistent across the sensors in quantifying the spectral change. We discuss the advantages of each instrument used and explore the expected changes in artificial nighttime light for areas that are retrofitting their streetlights with similar LED lamps.
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Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 découle