Programs and Communities

Objectives: We estimated neighborhood effects of population characteristics and built and natural environments on deaths due to heat exposure in Maricopa County, Arizona (2000–2008).

Methods: We used 2000 U.S. Census data and remotely sensed vegetation and land surface temperature to construct indicators of neighborhood vulnerability and a geographic information system to map vulnerability and residential addresses of persons who died from heat exposure in 2,081 census block groups. Binary logistic regression and spatial analysis were used to associate deaths with neighborhoods.

Results: Neighborhood scores on three factors—socioeconomic vulnerability, elderly/isolation, and unvegetated area—varied widely throughout the study area. The preferred model (based on fit and parsimony) for predicting the odds of one or more deaths from heat exposure within a census block group included the first two factors and surface temperature in residential neighborhoods, holding population size constant. Spatial analysis identified clusters of neighborhoods with the highest heat vulnerability scores. A large proportion of deaths occurred among people, including homeless persons, who lived in the inner cores of the largest cities and along an industrial corridor.

Conclusions: Place-based indicators of vulnerability complement analyses of person-level heat risk factors. Surface temperature might be used in Maricopa County to identify the most heat-vulnerable neighborhoods, but more attention to the socioecological complexities of climate adaptation is needed.

In this study we characterized the relationship between temperature and mortality in central Arizona desert cities that have an extremely hot climate. Relationships between daily maximum apparent temperature (ATmax) and mortality for eight condition-specific causes and all-cause deaths were modeled for all residents and separately for males and females ages <65 and ≥65 during the months May–October for years 2000–2008. The most robust relationship was between ATmax on day of death and mortality from direct exposure to high environmental heat. For this condition-specific cause of death, the heat thresholds in all gender and age groups (ATmax = 90–97 °F; 32.2‒36.1 °C) were below local median seasonal temperatures in the study period (ATmax = 99.5 °F; 37.5 °C). Heat threshold was defined as ATmax at which the mortality ratio begins an exponential upward trend. Thresholds were identified in younger and older females for cardiac disease/stroke mortality (ATmax = 106 and 108 °F; 41.1 and 42.2 °C) with a one-day lag. Thresholds were also identified for mortality from respiratory diseases in older people (ATmax = 109 °F; 42.8 °C) and for all-cause mortality in females (ATmax = 107 °F; 41.7 °C) and males <65 years (ATmax = 102 °F; 38.9 °C). Heat-related mortality in a region that has already made some adaptations to predictable periods of extremely high temperatures suggests that more extensive and targeted heat-adaptation plans for climate change are needed in cities worldwide.

In an extreme heat event, people can go to air-conditioned public facilities if residential air-conditioning is not available. Residences that heat slowly may also mitigate health effects, particularly in neighborhoods with social vulnerability. We explored the contributions of social vulnerability and these infrastructures to heat mortality in Maricopa County and whether these relationships are sensitive to temperature. Using Poisson regression modeling with heat-related mortality as the outcome, we assessed the interaction of increasing temperature with social vulnerability, access to publicly available air conditioned space, home air conditioning and the thermal properties of residences. As temperatures increase, mortality from heat-related illness increases less in census tracts with more publicly accessible cooled spaces. Mortality from all internal causes of death did not have this association. Building thermal protection was not associated with mortality. Social vulnerability was still associated with mortality after adjusting for the infrastructure variables. To reduce heat-related mortality, the use of public cooled spaces might be expanded to target the most vulnerable.

The spatial configuration of cities can affect how urban environments alter local energy balances. Previous studies have reached the paradoxical conclusions that both sprawling and high-density urban development can amplify urban heat island intensities, which has prevented consensus on how best to mitigate the urban heat island effect via urban planning. To investigate this apparent dichotomy, we estimated the urban heat island intensities of the 50 most populous cities in the United States using gridded minimum temperature data sets and quantified each city's urban morphology with spatial metrics. The results indicated that the spatial contiguity of urban development, regardless of its density or degree of sprawl,was a critical factor that influenced the magnitude of the urban heat island effect. A ten percentage point increase in urban spatial contiguity was predicted to enhance the minimum temperature annual average urban heat island intensity by between 0.3 and 0.4 °C. Therefore, city contiguity should be considered when devising strategies for urban heat island mitigation, with more discontiguous development likely to ameliorate the urban heat island effect. Unraveling how urban morphology influences urban heat island intensity is paramount given the human health consequences associated with the continued growth of urban populations in the future.

This paper explores how urbanization, through its role in the evolution of Urban Heat Island (UHI), affects residential water consumption. Using longitudinal data and drawing on a mesoscale atmospheric model, we examine how variations in surface temperature at the census tract level have affected water use in single family residences in Phoenix, Arizona. Results show that each Fahrenheit rise in nighttime temperature increases water consumption by 1.4%. This temperature effect is found to vary significantly with lot size and pool size. The study provides insights into the links between urban form and water use, through the dynamics of UHI.

Mortality from environmental heat is a significant public health problem in Maricopa County, especially because it is largely preventable. Maricopa County has conducted heat surveillance since 2006. Each year, the enhanced heat surveillance season usually begins in May and ends in October. The main goals of heat surveillance are to identify the demographic characteristics of heat-associated deaths (e.g., age and gender) and the risk factors for mortality (e.g., homelessness). Sharing this information helps community stakeholders to design interventions in an effort to prevent heat-associated deaths among vulnerable populations.

The two main sources of data for heat surveillance are: preliminary reports of death (PRODs) from the Office of the Medical Examiner (OME) and death certificates from the MCDPH Office of Vital Registration.

Heat-associated deaths are classified as heat-caused or heat related. Heat-caused deaths are those in which environmental heat was directly involved in the sequence of conditions causing deaths. Heat-related deaths are those in which environmental heat contributed to the deaths but was not in the sequence of conditions causing these deaths. For more information on how heat-associated deaths are classified, see the definitions in Appendix. For more information on MCDPH’s surveillance system, see Background and Methodology.

The relationship between the characteristics of the urban land system and land surface temperature (LST) has received increasing attention in urban heat island and sustainability research, especially for desert cities. This research generally employs medium or coarser spatial resolution data and primarily focuses on the effects of a few classes of land-cover composition and pattern at the neighborhood or larger level using regression models. This study explores the effects of land system architecture—composition and configuration, both pattern and shape, of fine-grain land-cover classes—on LST of single family residential parcels in the Phoenix, Arizona (southwestern USA) metropolitan area. A 1 m resolution land-cover map is used to calculate land architecture metrics at the parcel level, and 6.8 m resolution MODIS/ASTER data are employed to retrieve LST. Linear mixed-effects models quantify the impacts of land configuration on LST at the parcel scale, controlling for the effects of land composition and neighborhood characteristics. Results indicate that parcel-level land-cover composition has the strongest association with daytime and nighttime LST, but the configuration of this cover, foremost compactness and concentration, also affects LST, with different associations between land architecture and LST at nighttime and daytime. Given information on land system architecture at the parcel level, additional information based on geographic and socioeconomic variables does not improve the generalization capability of the statistical models. The results point the way towards parcel-level land-cover design that helps to mitigate the urban heat island effect for warm desert cities, although tradeoffs with other sustainability indicators must be considered.

This study seeks to determine the role of land architecture—the composition and configuration of land cover—as well as cadastral/demographic/economic factors on land surface temperature (LST) and the surface urban heat island effect of Phoenix, Arizona. It employs 1 m National Agricultural Imagery Program data of land-cover with 120mLandsat-derived land surface temperature, decomposed to 30 m, a new measure of configuration, the normalized moment of inertia, and U.S. Census data to address the question for two randomly selected samples comprising 523 and 545 residential neighborhoods (census blocks) in the city. The results indicate that, contrary to most other studies, land configuration has a stronger influence on LST than land composition. In addition, both land configuration and architecture combined with cadastral, demographic, and economic variables, capture a significant amount of explained variance in LST. The results indicate that attention to land architecture in the development of or reshaping of neighborhoods may ameliorate the summer extremes in LST.