Developing a model for effects of climate change on human health and health-environment interactions: Heat stress in Austin, Texas

Background/Question/Methods

In December, 2010, a consortium of EPA, Centers for Disease Control, and state and local health officials convened in Austin, Texas for a “participatory modeling workshop” on climate change effects on human health and health-environment interactions.  This was the kickoff to a project focused on developing a tool for decision-makers (EPA clients) to evaluate and explore potential public health impacts while planning adaptation and mitigation responses to global climate change.  A conceptual scoping model was laid out using Simile to represent consensus components and relations between variables.  Subsequent development stages are directed toward a research model with detailed process descriptions and data acquisition for calibration, and a management model for exploration of mitigation scenarios and management options.  Model development was geographically focused on Travis County, TX (Austin and surrounds) and a health endpoint of heat stress mortality, but with the intent to build a model that was readily transportable to other sites and expandable to other health endpoints.

Results/Conclusions

Following published work in Phoenix, Arizona, we modeled effects of vegetative cooling on study area temperatures.  These calculations were based on National Land Cover Database (NLCD) land-cover classes, typical normalized difference vegetation index (NDVI) temporal profiles per land-cover class, and changes in sensible and latent heat fluxes keyed to NDVI and temperature and humidity variables.  Water requirements for vegetative cooling were also calculated.  This resulted in a spatial pattern of temperatures reflecting an urban heat-island effect.  These variations in temperature were used to modify area weather station data to depict spatial variation in high temperature exposure based on daily temperatures, as well as frequency, duration, intensity, and timing of multi-day heat waves.  To explore spatial effects on heat stress, these patterns were overlaid with published synthetic indices of relative population vulnerability and published relations between high temperature exposure and heat stress mortality.  Outcomes vary among temperature exposure indices and vulnerability or mortality indices, but generally the greater effects are in the urban core and in populations with higher risk factors such as low income, older ages, and pre-existing medical conditions.  We are assembling scenarios of climate change and mitigation practices such as urban tree planting for further model analyses.