 indices to identify heat-vulnerable populations (Vescovi et al. 2005; Reid et al. 2009; Reid et al. 2012; Chuang and Gober 2015).
Human health vulnerability to heat is most often expressed as a combination of three factors: adaptive capacity, exposure to heat, and sensitivity to heat (Smit and Wandel 2006; Füssel 2010; Inostroza et al. 2016) (see sidebar). In our analysis, heat vulnerability was calculated as a combination of a) the historical land-surface temperature and future projections of heat to describe exposure; and b) county-level socioeconomic factors to describe sensitivity and adaptive capacity (see Appendix A for details). We will refer to the climate impacts as exposure, and the socioeconomic factors as sensitivity, with sensitivity inclusive of adaptive capacity, but no health factors were directly included due to incomplete county health factor data.
Factors Considered in Determining Vulnerability to Extreme Heat
Vulnerability, in the present context, is the extent to which a person is susceptible to the impacts of climate change. As described in the text and below, many factors go into calculating a person’s vulnerability to extreme heat. Three key terms bear definition:
- adaptive capacity.—The ability of a person (or society) to cope with climate change.
- exposure.—The type and magnitude of a climate change.
- sensitivity.—How easily affected a person is by climate change.
Vulnerability (the “V” in the diagram below) is assumed to be the intersection of adaptive capacity, exposure, and sensitivity (Smit and Wandel 2006; Füssel 2010; Inostroza et al. 2016). We combine adaptive capacity and sensitivity into one group, which is based on socioeconomic factors (see Appendix A for details). We continue to use the intersection of the three areas to determine vulnerability; and assume adaptive capacity is simply implicit in the socioeconomic layers that comprise our sensitivity factor.
Heat exposure is modeled as the combination of historical land-surface temperatures and projected heat. To determine the county average land-surface temperature on days of extreme heat, we use the 95th percentile of daily average land-surface temperatures from 2000-2019 (Figure 3-3). For future projected heat, we use the heat index of each county (UCS 2019) generated from an ensemble of general circulation models. The heat index includes a combination of temperature and humidity to create a “feels-like” heat rating.
We base our calculation of sensitivity to heat on socioeconomic variables from the US Census Bureau, 2013-2017 American Community Survey 5-Year Estimates (US Census Bureau undated). Socioeconomic factors include age, the average income for people in the county, the percent of county population under the poverty line, the percent of poverty households with children, the percent of population employed in construction and production (implying predominantly outdoor workers with greatest exposure to heat), the percent of population unemployed, and type of housing (see further details in Appendix A).
Human exposure to heat has been quantified and mapped, although only a few studies have combined socioeconomic sensitivity with heat exposure data to evaluate human vulnerability to the health risks associated with extreme heat (Buscail et al. 2012; Ho et al. 2015). Most studies that examine health vulnerability to heat use aggregate data that matches the spatial units from which sensitivity information is derived by the US Census Bureau (Ho et al. 2015). For example, most socioeconomic factors are measured at the county scale so exposure measurements (i.e., land-surface temperature and change in future heat) must be averaged across a county. Despite this complication, heat vulnerability is a useful measure to relate climate to human health impacts (see further details in Appendix A). Municipalities can use heat vulnerability information to guide heat mitigation interventions, such as establishment of green or reflective roofs, urban parks, and water features (see Section 5).
By combining exposure and sensitivity data, we id