Center researcher Maren Hale recently attended AGU Fall Meeting, where she shared her masters’ program capstone work on green space as a heat wave adaptation strategy in an eLightning talk. Maren’s work was advised by CCCIA partner Tarik Benmarhnia, and co-advised by director Mark Merrifield, with additional collaboration from Lara Schwarz, Anais Teyton, Kristen Hansen, and David Rojas-Rueda. In this blog post, she shares a bit about that research.
If you know just one thing about climate change, it’s probably that the world is projected to get much hotter – it’s even in the name: global warming. But perhaps what you didn’t know is just how large of a threat the increased frequency, intensity, and duration of extreme heat events will place on human health – and not just from heat stroke, but also by worsening underlying conditions such as heart disease (1).
Already, extreme heat is the leading cause of weather-related deaths in the United States (2), and as the climate warms, this toll will likely grow. Extreme heat is a particularly important problem here in Southern California, where temperatures will likely warm by around 2.5°C over the next few decades (3), exacerbating the heat-health impacts that have already been established in the region by researchers like SIO’s Kristen Guirguis. Large urban centers like San Diego and Los Angeles will face even more risk of deadly extreme heat events due to the added influence of the urban heat island effect.
But it’s not all doom and gloom. In addition to growing understanding about the impacts of extreme heat, new research is also assessing how adaptation strategies can mitigate these heat impacts. This type of research is what I presented at the AGU Fall Meeting this past December. Expanding on prior research that established a link between changes to the built environment (such as reducing impervious surface cover or planting trees) and reductions in both temperature and hospitalizations, my colleagues and I attempted to assess with finer detail exactly how much a given change in “green space” (i.e. trees, public parks, etc.) could affect the number of hospital admissions caused by extreme heat in San Diego County. The results are striking.
In more than 30 hypothetical simulated greening scenarios – which ranged in size and scope, from increasing tree canopy all throughout the county to only planting more trees in areas where the city is most heavily urbanized, or where the most vulnerable populations live – we found that almost all greening scenarios caused strong reductions in heat-related hospitalizations (Figure 1). Some of these hypothetical scenarios even led to county-wide reductions in hospitalizations of over 400 avoided admissions per every 100 heat wave days.
What sets our work apart from others is our fine-scale approach, which determines heat-health relationships specific to every zip code in the county, allowing our estimates of avoided hospital admissions for each greening scenario to be highly specific and tailored to the local context of San Diego. In future work, we hope to assess how people interact with extreme heat and the built environment at an even finer scale by conducting studies using citizen scientists and wearable temperature sensors. It is our sincere hope that this and future work might be useful to policymakers (in San Diego and beyond) when considering adaptation strategies in response to the ever-growing threat of extreme heat.
- Mora, C., Counsell, C. W. W., Bielecki, C. R., & Louis, L. V. (2017). Twenty-Seven Ways a Heat Wave Can Kill You: Circulation: Cardiovascular Quality and Outcomes, 10(11), e004233. https://doi.org/10.1161/CIRCOUTCOMES.117.004233
- US Department of Commerce, N. (n.d.). Weather Related Fatality and Injury Statistics. NOAA’s National Weather Service. Retrieved July 18, 2020, from https://www.weather.gov/hazstat/
- Pierce, D. W., Das, T., Cayan, D. R., Maurer, E. P., Miller, N. L., Bao, Y., Kanamitsu, M., Yoshimura, K., Snyder, M. A., Sloan, L. C., Franco, G., & Tyree, M. (2013). Probabilistic estimates of future changes in California temperature and precipitation using statistical and dynamical downscaling. Climate Dynamics, 40(3), 839–856. https://doi.org/10.1007/s00382-012-1337-9