Urban heat is a growing problem that impacts public health, water and energy use, and the economy and affects population subgroups differently. Exposure and sensitivity, two key factors in determining vulnerability, have been widely researched. This dissertation focuses on the adaptive capacity component of heat vulnerability at the individual, household, and community scale. Using a mixed methods approach and metropolitan Phoenix as a test site, I explored how vulnerable communities understand and adapt to increasing extreme urban heat to uncover adaptive capacity that is not being operationalized well through current heat vulnerability frameworks. Twenty-three open-ended interviews were conducted where residents were encouraged to tell their stories about past and present extreme heat adaptive capacity behaviors. A community-based participatory research project consisting of three workshops and demonstration projects was piloted in three underserved neighborhoods to address urban heat on a local scale and collaboratively create community heat action plans. Last, a practitioner stakeholder meeting was held to discuss how the heat action plans will be integrated into other community efforts. Using data from the interviews, workshops, and stakeholder meeting, social capital was examined in the context of urban heat. Although social capital has been measured in a multitude of ways to gauge social relationships, trust, and reciprocity within a community, it is situational and reflects a position within the formal and informal aspects of any issue. Three narratives emerged from the interviews illuminating differentiated capacities to cope with urban heat: heat is an inconvenience, heat is a manageable problem, and heat is a catastrophe. For each of these narratives, generic adaptive capacity is impacted differently by specific heat adaptive capacity. The heat action plan workshops generated hyper-local heat solutions that reflected the neighborhoods’ different identities. Community-based organizations were instrumental in the success of this program. Social capital indicators were developed specific to urban heat that rely on heavily on family and personal relationships, attitudes and beliefs, perceived support, network size and community engagement. This research highlights how extreme heat vulnerability may need to be rethought to capture adaptive capacity nuances and the dynamic structure of who is vulnerable under what circumstances.
The City of Phoenix has committed to public transit improvements in the Transportation 2050 plan and has recently adopted a Complete Streets Policy. Proposed changes include mobility improvements and creating a safe and comfortable environment for non-motorized road participants. To understand what kind of improvements would benefit thermal comfort the most, it is necessary to understand heat exposure at finer spatial scales, explore whether current bus shelter designs are adequate in mitigating heat-health effects, and comprehensively assess the impact of design on physical, psychological and behavioral aspects of thermal comfort. A study conducted at bus stops in one Phoenix neighborhood examined grey and green infrastructure types preferred for cooling and found relationships between perception of pleasantness and thermal sensation votes. Walking interviews conducted in another neighborhood event examined the applicability of a framework for walking behavior under the stress of heat, and how differences between the streets affected perceptions of the walkers. The interviews revealed that many of the structural themes from the framework of walking behavior were applicable, however, participants assessed the majority of the elements in their walk from a heat mitigation perspective. Finally, guiding questions for walkability in hot and arid climates were developed based on the literature review and results from the empirical studies. This dissertation contributes to filling the gap between walkability and outdoor thermal comfort, and presents methodology and findings that can be useful to address walkability and outdoor thermal comfort in the world’s hot cities as well as those in temperate climates that may face similar climate challenges in the future as the planet warms.
Environmental hazards and disaster researchers have demonstrated strong associations between sociodemographic indicators, such as age and socio-economic status (SES), and hazard exposures and health outcomes for individuals and in certain communities. At the same time, behavioral health and risk communications research has examined how individual psychology influences adaptive strategies and behaviors in the face of hazards. However, at present, we do not understand the explanatory mechanisms that explain relationships between larger scale social structure, individual psychology, and specific behaviors that may attenuate or amplify risk. Extreme heat presents growing risks in a rapidly warming and urbanizing world. This dissertation examines the social and behavioral mechanisms that may explain inequitable health outcomes from exposure to concurrent extreme heat and electrical power failure in Phoenix, AZ and extreme heat in Detroit, MI. Exploratory analysis of 163 surveys in Phoenix, AZ showed that age, gender, and respondent’s racialized group identity did not relate to thermal discomfort and self-reported heat illness, which were only predicted by SES (StdB = -0.52, p < 0.01). Of the explanatory mechanisms tested in the study, only relative air conditioning intensity and thermal discomfort explained self-reported heat illness. Thermal discomfort was tested as both a mechanism and outcome measure. Content analysis of 40 semi-structured interviews in Phoenix, AZ revealed that social vulnerability was associated with an increase in perceived hazard severity (StdB = 0.44, p < 0.01), a decrease in perceived adaptation efficacy (StdB = -0.38, p = 0.02), and an indirect increase (through adaptive efficacy) in maladaptive intentions (StdB = 0.18, p = 0.01). Structural equation modeling of 244 surveys in Phoenix, AZ and Detroit, MI revealed that relationships between previous heat illness experience, perceived heat risk, and adaptive intentions were significantly moderated by adaptive capacity: high adaptive capacity households were more likely to undertake adaptive behaviors, and those decisions were more heavily influenced by risk perceptions and previous experiences. However, high adaptive capacity households had lower risk perceptions and fewer heat illness experiences than low adaptive capacity households. A better understanding of the mechanisms that produce social vulnerability can facilitate more salient risk messaging and more targeted public health interventions. For example, public health risk messaging that provides information on the efficacy of specific adaptations may be more likely to motivate self-protective action, and ultimately protect populations.
Urban climate conditions are the physical manifestation of formal and informal social forces of design, policy, and urban management. The urban design community (e.g. planners, architects, urban designers, landscape architects, engineers) impacts urban development through influential built projects and design discourse. Their decisions create urban landscapes that impact physiological and mental health for people that live in and around them. Therefore, to understand possible opportunities for decision-making to support healthier urban environments and communities, this dissertation examines the role of neighborhood design on the thermal environment and the effect the thermal environment has on mental health. In situ data collection and numerical modeling are used to assess current and proposed urban design configurations in the Edison Eastlake public housing community in central Phoenix for their efficacy in cooling the thermal environment. A distributed lagged non-linear model is used to investigate the relative risk of hospitalization for schizophrenia in Maricopa County based on atmospheric conditions. The dissertation incorporates both an assessment of design strategies for the cooling of the thermal environment and an analysis of the existing thermal environment’s relationship with mental health. By reframing the urban design of neighborhoods through the lens of urban climate, this research reinforces the importance of incorporating the community into the planning process and highlights some unintended outcomes of prioritizing the thermal environment in urban design.
To address the dearth of knowledge about person-based and trip-level exposure, we developed the Icarus model. Icarus uses mesoscale traffic model—activity-based model—to analyze the heat exposure of regions of interest at an individual level. The goal with Icarus was to design accurate, granular models of population and temperature behavior for a target region, which could be transformed into a heat exposure model by means of simulation and spatial-temporal joining. By combining and implementing the most robust software and data available, Icarus was able to capture person-based exposure with unparalleled detail. Here we describe the model methodology. We use the metropolitan region of Phoenix, Arizona, USA to carry out a case study using Icarus.
Background: Most excess deaths that occur during extreme hot weather events do not have natural heat recorded as an underlying or contributing cause. This study aims to identify the specific individuals who died because of hot weather using only secondary data. A novel approach was developed in which the expected number of deaths was repeatedly sampled from all deaths that occurred during a hot weather event, and compared with deaths during a control period. The deaths were compared with respect to five factors known to be associated with hot weather mortality. Individuals were ranked by their presence in significant models over 100 trials of 10,000 repetitions. Those with the highest rankings were identified as probable excess deaths. Sensitivity analyses were performed on a range of model combinations. These methods were applied to a 2009 hot weather event in greater Vancouver, Canada.
Results: The excess deaths identified were sensitive to differences in model combinations, particularly between univariate and multivariate approaches. One multivariate and one univariate combination were chosen as the best models for further analyses. The individuals identified by multiple combinations suggest that marginalized populations in greater Vancouver are at higher risk of death during hot weather.
Conclusions: This study proposes novel methods for classifying specific deaths as expected or excess during a hot weather event. Further work is needed to evaluate performance of the methods in simulation studies and against clinically identified cases. If confirmed, these methods could be applied to a wide range of populations and events of interest.
The Arctic, even more so than other parts of the world, has warmed substantially over the past few decades. Temperature and humidity influence the rate of development, survival and reproduction of pathogens and thus the incidence and prevalence of many infectious diseases. Higher temperatures may also allow infected host species to survive winters in larger numbers, increase the population size and expand their habitat range. The impact of these changes on human disease in the Arctic has not been fully evaluated. There is concern that climate change may shift the geographic and temporal distribution of a range of infectious diseases. Many infectious diseases are climate sensitive, where their emergence in a region is dependent on climate-related ecological changes. Most are zoonotic diseases, and can be spread between humans and animals by arthropod vectors, water, soil, wild or domestic animals. Potentially climate-sensitive zoonotic pathogens of circumpolar concern include Brucella spp., Toxoplasma gondii, Trichinella spp., Clostridium botulinum, Francisella tularensis, Borrelia burgdorferi, Bacillus anthracis, Echinococcus spp., Leptospira spp., Giardia spp., Cryptosporida spp., Coxiella burnetti, rabies virus, West Nile virus, Hantaviruses, and tick-borne encephalitis viruses.
Background: Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat–mortality relationships.
Objectives: We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method.
Methods: Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series.
Results: In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature–mortality relationships were associated with maximum temperature, although mean temperature results were comparable.
Conclusions: There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature–mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum temperatures in most cities we examined, particularly those typically prone to heat-related mortality.
Background: Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.
Objectives: This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season.
Methods: Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature–health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different “trigger points” at which heat-health intervention measures might be activated.
Results: We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22°C) across multiple health events and diagnoses.
Conclusion: Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.
Background: Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to “adaptation uncertainty” (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios.
Objectives: This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments.
Methods: We estimated impacts for 2070–2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty.
Results: The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty.
Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope.