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Related Concept Videos

Quantifying Heat02:46

Quantifying Heat

Thermal Energy Microscopically, thermal energy is the kinetic energy associated with the random motion of atoms and molecules. Temperature is a quantitative measure of “hot” or “cold”, which depends on the amount of thermal energy. When the atoms and molecules in an object are moving or vibrating quickly, they have a higher average kinetic energy (KE) (or higher thermal energy), and the object is perceived as “hot”, or it is described as being at a higher temperature. When the atoms and...
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Assessing Body Temperature - Axilla01:14

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Updated: Jun 13, 2026

Fa&#231;ade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers
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Assessing Intraurban Variation in Heat-Attributable Health Burden to Inform Local Interventions.

K Burley Farr1,2, E M McInroe3, W L Tsai4

  • 1Department of Public Policy University of North Carolina at Chapel Hill Chapel Hill NC USA.

Geohealth
|June 12, 2026
PubMed
Summary
This summary is machine-generated.

Extreme heat significantly increases cardiovascular hospitalizations in older adults. This study developed a framework to pinpoint high-risk neighborhoods, enabling targeted public health interventions for heat-related illnesses.

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Last Updated: Jun 13, 2026

Fa&#231;ade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers
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Published on: December 23, 2022

Area of Science:

  • Environmental Health
  • Epidemiology
  • Spatial Analysis

Background:

  • Extreme heat poses significant cardiovascular risks, particularly for older adults.
  • Geographic misalignment between health data and heat exposure hinders effective local interventions.
  • Existing methods struggle to provide granular estimates of heat-related health burdens.

Purpose of the Study:

  • To develop an adaptable framework for estimating heat-attributable cardiovascular disease burden at fine geographic scales (census block groups).
  • To integrate small area analysis (SAA) with epidemiologic models for localized health risk assessment.
  • To inform targeted public health interventions by identifying high-risk neighborhoods.

Main Methods:

  • Estimated exposure-response functions using individual-level cardiovascular disease (CVD) hospitalizations for adults aged 65+.
  • Downscaled ZCTA-level CVD hospitalization rates to census block groups (CBGs) using SAA, adjusting for demographic factors.
  • Linked exposure-response functions with downscaled incidence rates to quantify heat-attributable burden at the CBG scale.

Main Results:

  • Estimated 1.8 to 22.0 excess hospitalizations per 10,000 people across CBGs during summer 2018 in a southeastern US metropolitan area.
  • Classified neighborhoods into four risk groups (Low, Health-driven, Heat-driven, Dual-channel) to guide interventions.
  • Demonstrated that coarse-resolution temperature data significantly underestimated heat-attributable burden and altered geographic distribution.

Conclusions:

  • The developed 3-step framework effectively estimates localized heat-attributable health burdens.
  • Fine-scale exposure data and SAA are crucial for accurate assessment and effective heat intervention strategies.
  • This approach supports targeted interventions addressing both heat exposure and underlying health vulnerabilities.