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Enregistrement W2046315956 · doi:10.1115/1.4023176

Review of World Urban Heat Islands: Many Linked to Increased Mortality

2013· article· en· W2046315956 sur OpenAlex

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no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
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Notice bibliographique

RevueJournal of Energy Resources Technology · 2013
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueClimate Change and Health Impacts
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOverheating (electricity)DemographyHeat waveExtreme heatUrban heat islandPopulationGeographyMeteorologyClimate changeEngineeringGeologyOceanography

Résumé

récupéré en direct d'OpenAlex

Medical and health researchers have shown that fatalities during heat waves are most commonly due to respiratory and cardiovascular diseases, primarily from heat's negative effect on the cardiovascular system. In an attempt to control one's internal temperature, the body’s natural instinct is to circulate large quantities of blood to the skin. However, to perform this protective measure against overheating actually harms the body by inducing extra strain on the heart. This excess strain has the potential to trigger a cardiac event in those with chronic health problems, such as the elderly, Cui et al. Frumkin showed that the relationship of mortality and temperature creates a J-shaped function, showing a steeper slope at higher temperatures. Records show that more casualties have resulted from heat waves than hurricanes, floods, and tornadoes together. This statistic’s significance is that extreme heat events (EHEs) are becoming more frequent, as shown by Stone et al. Their analysis shows a growth trend of EHEs by 0.20 days/year in U.S. cities between 1956 and 2005, with a 95% confidence interval and uncertainty of ±0.6. This means that there were 10 more days of extreme heat conditions in 2005 than in 1956. Studies held from 1989 to 2000 in 50 U.S. cities recorded a rise of 5.7% in mortality during heat waves. The research of Schifano et al. revealed that Rome’s elderly population endures a higher mortality rate during heat waves, at 8% excess for the 65–74 age group and 15% for above 74. Even more staggering is findings of Dousset et al. on French cities during the 2003 heat wave. Small towns saw an average excess mortality rate of 40%, while Paris witnessed an increase of 141%. During this period, a 0.5 °C increase above the average minimum nighttime temperature doubled the risk of death in the elderly. Heat-related illnesses and mortality rates have slightly decreased since 1980, regardless of the increase in temperatures. Statistics from the U.S. Census state that the U.S. population without air conditioning saw a drop of 32% from 1978 to 2005, resting at 15%. Despite the increase in air conditioning use, a study done by Kalkstein through 2007 proved that the shielding effects of air conditioning reached their terminal effect in the mid-1990s. Kan et al. hypothesize in their study of Shanghai that the significant difference in fatalities from the 1998 and 2003 heat waves was due to the increase in use of air conditioning. Protective factors have mitigated the danger of heat on those vulnerable to it, however projecting forward the heat increment related to sprawl may exceed physiologic adaptation thresholds. It has been studied and reported that urban heat islands (UHI) exist in the following world cities and their countries and/or states: Tel-Aviv, Israel, Newark, NJ, Madrid, Spain, London, UK, Athens, Greece, Taipei, Taiwan, San Juan, Puerto Rico, Osaka, Japan, Hong Kong, China, Beijing, China, Pyongyang, North Korea, Bangkok, Thailand, Manila, Philippines, Ho Chi Minh City, Vietnam, Seoul, South Korea, Muscat, Oman, Singapore, Houston, USA, Shanghai, China, Wroclaw, Poland, Mexico City, Mexico, Arkansas, Atlanta, USA, Buenos Aires, Argentina, Kenya, Brisbane, Australia, Moscow, Russia, Los Angeles, USA, Washington, DC, USA, San Diego, USA, New York, USA, Chicago, USA, Budapest, Hungary, Miami, USA, Istanbul, Turkey, Mumbai, India, Shenzen, China, Thessaloniki, Greece, Rotterdam, Netherlands, Akure, Nigeria, Bucharest, Romania, Birmingham, UK, Bangladesh, and Delhi, India. The strongest being Shanghai, Bangkok, Beijing, Tel-Aviv, and Tokyo with UHI intensities (UHII) of 3.5–7.0, 3.0–8.0, 5.5–10, 10, and 12 °C, respectively. Of the above world cities, Hong Kong, Bangkok, Delhi, Bangladesh, London, Kyoto, Osaka, and Berlin have been linked to increased mortality rates due to the heightened temperatures of nonheat wave periods. Chan et al. studied excess mortalities in cities such as Hong Kong, Bangkok, and Delhi, which currently observe mortality increases ranging from 4.1% to 5.8% per 1 °C over a temperature threshold of approximately 29 °C. Goggins et al. found similar data for the urban area of Bangladesh, which showed an increase of 7.5% in mortality for every 1 °C the mean temperature was above a similar threshold. In the same study, while observing microregions of Montreal portraying heat island characteristics, mortality was found to be 28% higher in heat island zones on days with a mean temperature of 26 °C opposed to 20 °C compared to a 13% increase in colder areas.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,330
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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.

Tête enseignante Opus0,025
Tête enseignante GPT0,288
Écart entre enseignants0,263 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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