Increasing Equitable Heat Resilience in Baltimore City by Improving Access and Adaptive Capacity for Disproportionately Impacted Populations

Urban centers are particularly susceptible to extreme heat and its consequences, especially due to their infrastructure and population density. Limited green space, greater impervious surfaces, and building density contribute to the urban heat island effect, causing cities to be several degrees hotter than the surrounding areas. Extreme heat exacerbates this effect, leading to worse air quality, heat-related illness, worsening of other chronic conditions, and death. This is particularly concerning for populations experiencing disproportionate health effects, such as young children, the elderly, those with pre-existing health conditions, and socioeconomic groups that do not have access to air conditioning at home or at their place of employment. Like many cities, Baltimore City uses cooling centers to provide the public with relief from extreme heat. However, not all individuals and populations have an equal capacity to prepare for, respond to, and recover from the impacts of extreme heat. With such a diverse population, it is critical to identify the factors that inhibit people from accessing cooling centers meant to serve everyone in the community, and identify what populations are at risk of reduced access to these resources. Geospatial intelligence, including analyses and visualizations, can provide data-driven insights to inform effective and equitable policies and practices to mitigate the impact of extreme heat exposure on people and their health. There are two major gaps that must be addressed to effectively build equitable resilience in large urban centers facing increased frequency and duration of extreme heat events: 1) existing analytical frameworks do not adequately represent the geospatial dynamics of communities and the individuals and populations within these communities, and 2) metrics used to identify effective adaptation options at the community level need improved data-driven validation to ensure that the metrics used to inform policy and practice are appropriate and applicable at the right scale. This study aims to lay the foundation to address these gaps. Using Baltimore City as a case study, a standardized set of measures was selected to assess community resilience at actionable spatial and temporal scales. Geospatial analysis was conducted to evaluate potential relationships between measures of risk and resilience for this community. The result of this analysis was a proof-of-concept tool capable of visualizing relevant metrics, analytical outputs, and population characteristics. This enables community decision-makers to explore “what-if” scenarios in their planning and intervention for extreme heat events, evaluate the community’s ability to adapt during extreme heat events, identify vulnerable or high-risk areas, and assess the potential effectiveness of their intervention plans. These capabilities empower community leaders to make data-driven decisions and well-informed infrastructure and climate resilience investments that do not perpetuate inequities across population groups.