This repository houses peer-reviewed literature, data sets, reports, and other materials generated by researchers, practitioners, and other regional stakeholders that may be informative for local and regional efforts mitigating the adverse impacts of heat. The collection is intended to serve as a resource for anyone looking for information on top research findings, reports, or initiatives related to heat and air quality. This includes community, local, state, and regional partners and other interested parties contributing to heat and air quality planning, preparedness, and response activities.

More Information: The Phoenix Regional Heat and Air Quality Knowledge Repository is product of the Healthy Urban Environments (HUE) initiative in partnership with the Urban Climate Research Center. 

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Description

Context:
With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems.

Objectives:
We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat

Context:
With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems.

Objectives:
We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat illnesses in the subtropical desert city of Phoenix, AZ USA.

Methods:
We conducted an airborne imaging campaign that acquired high resolution urban land surface temperature data (7 m/pixel) during the day and night. We performed a geographic overlay of these data with high resolution land cover maps, parcel boundaries, neighborhood boundaries, and a household survey.

Results:
Land cover composition, including percentages of vegetated, building, and road areas, and values for NDVI, and albedo, was correlated with residential parcel surface temperatures and the effects differed between day and night. Vegetation was more effective at cooling hotter neighborhoods. We found consistencies between heat risk factors in neighborhood environments and residents’ perceptions of these factors. Symptoms of heat-related illness were correlated with parcel scale surface temperature patterns during the daytime but no corresponding relationship was observed with nighttime surface temperatures.

Conclusions:
Residents’ experiences of heat vulnerability were related to the daytime land surface thermal environment, which is influenced by micro-scale variation in land cover composition. These results provide a first look at parcel-scale causes and consequences of urban surface temperature variation and provide a critically needed perspective on heat vulnerability assessment studies conducted at much coarser scales.

ContributorsJenerette, Darrel G. (Author) / Harlan, Sharon L. (Author) / Buyantuev, Alexander (Author) / Stefanov, William L. (Author) / Declet-Barreto, Juan (Author) / Ruddel, Benjamin L. (Author) / Myint, Soe Win (Author) / Kaplan, Shari (Author) / Li, XiaiXiao (Author)
Created2015-10-19
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Description

This study examines the impact of spatial landscape configuration (e.g., clustered, dispersed) on land-surface temperatures (LST) over Phoenix, Arizona, and Las Vegas, Nevada, USA. We classified detailed land-cover types via object-based image analysis (OBIA) using Geoeye-1 at 3-m resolution (Las Vegas) and QuickBird at 2.4-m resolution (Phoenix). Spatial autocorrelation (local

This study examines the impact of spatial landscape configuration (e.g., clustered, dispersed) on land-surface temperatures (LST) over Phoenix, Arizona, and Las Vegas, Nevada, USA. We classified detailed land-cover types via object-based image analysis (OBIA) using Geoeye-1 at 3-m resolution (Las Vegas) and QuickBird at 2.4-m resolution (Phoenix). Spatial autocorrelation (local Moran’s I ) was then used to test for spatial dependence and to determine how clustered or dispersed points were arranged. Next, we used Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired over Phoenix (daytime on 10 June and nighttime on 17 October 2011) and Las Vegas (daytime on 6 July and nighttime on 27 August 2005) to examine day- and nighttime LST with regard to the spatial arrangement of anthropogenic and vegetation features. Local Moran’s I values of each land-cover type were spatially correlated to surface temperature. The spatial configuration of grass and trees shows strong negative correlations with LST, implying that clustered vegetation lowers surface temperatures more effectively. In contrast, clustered spatial arrangements of anthropogenic land-cover types, especially impervious surfaces and open soil, elevate LST. These findings suggest that city planners and managers should, where possible, incorporate clustered grass and trees to disperse unmanaged soil and paved surfaces, and fill open unmanaged soil with vegetation. Our findings are in line with national efforts to augment and strengthen green infrastructure, complete streets, parking management, and transit-oriented development practices, and reduce sprawling, unwalkable housing development.

ContributorsMyint, Soe Win (Author) / Zheng, Baojuan (Author) / Talen, Emily (Author) / Fan, Chao (Author) / Kaplan, Shari (Author) / Middel, Ariane (Author) / Smith, Martin (Author) / Huang, Huei-Ping (Author) / Brazel, Anthony J. (Author)
Created2015-06-29
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Description

Rapid urbanization of the planet is occurring at an unprecedented pace, primarily in arid and semi-arid hot climates [Golden, J.S., 2004. The built environment induced urban heat island effect in rapidly urbanizing arid regions – a sustainable urban engineering complexity. Environ. Sci. J. Integr. Environ. Res. 1 (4), 321–349]. This

Rapid urbanization of the planet is occurring at an unprecedented pace, primarily in arid and semi-arid hot climates [Golden, J.S., 2004. The built environment induced urban heat island effect in rapidly urbanizing arid regions – a sustainable urban engineering complexity. Environ. Sci. J. Integr. Environ. Res. 1 (4), 321–349]. This growth has manifested itself as a cause of various impacts including elevated urban temperatures in comparison to rural sites known as the Urban Heat Island (UHI) effect [Oke, T.R., 1982. The energetic basis of the urban heat island. Q. J. R. Meteor. Soc. 108, 1–24]. Related are the increased demands for electric power as a result of population growth and increased need for mechanical cooling due to the UHI. In the United States, the Environmental Protection Agency has developed a three-prong approach of (1) cool pavements, (2) urban forestry and (3) cool roofs to mitigate the UHI. Researchers undertook an examination of micro scale benefits of the utilization of photovoltaic panels to reduce the thermal impacts to surface temperatures of pavements in comparison to urban forestry. The results of the research indicate that photovoltaic panels provide a greater thermal reduction benefit during the diurnal cycle in comparison to urban forestry while also providing the additional benefits of supporting peak energy demand, conserving water resources and utilizing a renewable energy source.

ContributorsGolden, Jay S. (Author) / Carlson, Joby (Author) / Kaloush, Kamil (Author) / Phelan, Patrick (Author)
Created2006-12-26
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Description

This established model is applied here to show the relative effects of four common mitigation strategies: increasing the overall (1) emissivity, (2) percentage of vegetated area, (3) thermal conductivity, and (4) albedo of the urban environment in a series of percentage increases by 5, 10, 15, and 20% from baseline

This established model is applied here to show the relative effects of four common mitigation strategies: increasing the overall (1) emissivity, (2) percentage of vegetated area, (3) thermal conductivity, and (4) albedo of the urban environment in a series of percentage increases by 5, 10, 15, and 20% from baseline values.

ContributorsHumberto, Silva R. (Author) / Phelan, Patrick E. (Author) / Golden, Jay S. (Author)
Created2009-07-26