Discussion
We used a fine resolution geostatistical prediction model to understand potential disparities in warm season ambient air temperature exposures for ethnoracially minoritized groups using measures of residential segregation in 2003–2019. We found that non-Hispanic Black and Latino people were consistently exposed to hotter warm seasons than would be expected if simply using the county average. Asian people also tended to experience higher average temperatures, but with a notable exception in Delaware where they experienced cooler summers. Finally, white people consistently tended to experience cooler warm seasons compared to the county averages. Spatial segregation analyses suggested that higher levels of minoritized groups are associated with hotter warm seasons and, relatedly, higher concentrations of white people are associated with cooler warm seasons. These results have potential ramifications for climate, health, and energy research and policy.
Many temperature-related studies have used coarse exposure assessments, often averaged to the county level or some other large administrative scale. However, we found systematically different exposure profiles for populations within counties in this region. This represents potential differential exposure misclassification, which could be a concern for temperature exposure and epidemiology studies if not properly addressed. With regard to policy, energy poverty alleviation programs like LIHEAP use statewide CDDs among measures of energy demand, implicitly assuming that all subgroups in the state are exposed to the same magnitude of season. Yet we found that throughout the study region, minoritized groups were exposed to higher warm season temperatures. Therefore, energy demand is likely underestimated for these populations. This is bolstered by other evidence that Black people are most likely to experience energy insecurity nationwide year-round (11), but Latino people experience the highest rates of warm season energy insecurity (12). Given that we found some of the most prominent warm season temperatures for Latino people, this may be one possible pathway explaining this energy insecurity disparity. Finally, other studies have found that historical redlining is associated with present-day land cover characteristics associated with the urban heat island effect (16, 17). Those studies were limited to cities with documented redlining, but our study covers entire states in our region using present-day measures of segregation and air temperature. Given that we found statewide temperature disparities beyond just formerly redlined cities, this suggests that the historical processes associated with land use and land cover disparities were not restricted to redlined cities. This is an area for future investigation but speaks to the potential importance of targeted greening initiatives in urban areas nationwide.
Our study has many strengths. We leveraged fine-resolution air temperature predictions to understand temperature disparities, while many other studies have used either coarser models or land surface temperatures, which we believe more accurately reconstruct neighborhood-level exposures. We also used metrics and methods to enhance interpretability and policy relevance—our use of weighted effect coding provides an intuitive comparison of the ethnoracial average compared to the county average, and our use of CDDs is relevant to U.S. energy policy. Our study also covered a large region of more than 72 million people and more than 17 years. Finally, our data and programmatic code are freely available to enhance reproducibility of our findings.
Nonetheless, our study also has limitations. First, we examined temperature exposures as assigned by residential location, but there may be exposure disparities due to occupational exposures. Second, all confidence intervals for Washington D.C. crossed zero, and thus we concluded there were no apparent disparities. However, it is possible that our spatial inference methods were overly conservative for a small spatial area. Third, we examined two measures of residential segregation based on concentration, but residential segregation is a multidimensional construct (22). Relatedly, we examined segregation measures concurrent to temperature exposures. While these and other research suggest that residential segregation is a pathway towards temperature exposure disparities, we need to examine the sequence of segregation and later land development and temperature to make those conclusions. Further, while we adjusted for year, we did not assess time trends in these results across the study period. Finally, our temperature prediction model covered the northeast and mid-Atlantic regions of the U.S., but future studies should examine other regions or the entire U.S.
Overall, our findings suggest that ethnoracially minoritized groups experienced hotter average summers across the 13 states in the Northeastern U.S. in 2003–2019. This study highlights the importance of energy poverty alleviation programs, specifically for these subgroups. These findings are critical to target interventions that enhance the adaptive capacity of systematically marginalized groups in a warming climate.