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Record W2046315956 · doi:10.1115/1.4023176

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

2013· article· en· W2046315956 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Energy Resources Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsOverheating (electricity)DemographyHeat waveExtreme heatUrban heat islandPopulationGeographyMeteorologyClimate changeEngineeringGeologyOceanography

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.025
GPT teacher head0.288
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it