Programs and Communities

The impacts of land-cover composition on urban temperatures, including temperature extremes, are well documented. Much less attention has been devoted to the consequences of land-cover configuration, most of which addresses land surface temperatures. This study explores the role of both composition and configuration—or land system architecture—of residential neighborhoods in the Phoenix metropolitan area, on near-surface air temperature. It addresses two-dimensional, spatial attributes of buildings, impervious surfaces, bare soil/rock, vegetation and the “urbanscape” at large, from 50 m to 550 m at 100 m increments, for a representative 30-day high sun period. Linear mixed-effects models evaluate the significance of land system architecture metrics at different spatial aggregation levels. The results indicate that, controlling for land-cover composition and geographical variables, land-cover configuration, specifically the fractal dimension of buildings, is significantly associated with near-surface temperatures. In addition, statistically significant predictors related to composition and configuration appear to depend on the adopted level of spatial aggregation.

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 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.

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.

We investigated the spatial and temporal variation in June mean minimum temperatures for weather stations in and around metropolitan Phoenix, USA, for the period 1990 to 2004. Temperature was related to synoptic conditions, location in urban development zones (DZs), and the pace of housing construction in a 1 km buffer around fixed-point temperature stations. June is typically clear and calm, and dominated by a dry, tropical air mass with little change in minimum temperature from day to day. However, a dry, moderate weather type accounted for a large portion of the inter-annual variability in mean monthly minimum temperature. Significant temperature variation was explained by surface effects captured by the type of urban DZ, which ranged from urban core and infill sites, to desert and agricultural fringe locations, to exurban. An overall spatial urban effect, derived from the June monthly mean minimum temperature, is in the order of 2 to 4 K. The cumulative housing build-up around weather sites in the region was significant and resulted in average increases of 1.4 K per 1000 home completions, with a standard error of 0.4 K. Overall, minimum temperatures were spatially and temporally accounted for by variations in weather type, type of urban DZ (higher in core and infill), and the number of home completions over the period. Results compare favorably with the magnitude of heating by residential development cited by researchers using differing methodologies in other urban areas.

Abstract
Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs)
towards opioid overdose management and to assess the effect of online training on opioid
overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and
respond to opioid overdose situations.

Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid
Overdose Attitude Scale (OOAS) surveys were administered electronically to five BHTs in
2020. Data obtained were de-identified. Comparisons between responses to pre-and post-surveys questions were carried out using the standardized Wilcoxon signed-rank statistical test(z). This study was conducted in a residential treatment center (RTC) with the institutional review board's approval from Arizona State University. BHTs aged 18 years and above, working at this RTC were included in the study.

Interventions: An online training was provided on opioid overdose response (OOR) and
naloxone administration and on when to refer patients with opioid use disorder (OUD) for
medication-assisted treatment.

Results: Compared to the pre-intervention surveys, the BHTs showed significant improvements
in attitudes on the overall score on the OOAS (mean= 26.4 ± 13.1; 95% CI = 10.1 - 42.7; z =
2.02; p = 0.043) and significant improvement in knowledge on the OOKS (mean= 10.6 ± 6.5;
95% CI = 2.5 – 18.7; z =2.02, p = 0.043).

Conclusions and Relevance: Training BHTs working in an RTC on opioid overdose response is
effective in increasing attitudes and knowledge related to opioid overdose management. opioid
overdose reversal in RTCs.

Keywords: Naloxone, opioid overdose, overdose education, overdose response program

Childhood traumatic experiences are a prevalent public health issue. Children exposed to trauma often exhibit behaviors that make educating them challenging. Preschool teachers at a southwestern United States preschool receive no training related to childhood trauma and resilience. The purpose of this project was to educate preschool teachers on trauma and resilience to improve attitude related to educating children with trauma.

Following Arizona State University Internal Review Board approval, preschool teachers were recruited from a non-profit metropolitan preschool. Project included two pre-training questionnaires (Adult Resilience Measure-Revised [ARM-R] and Attitudes Related to Trauma Informed Care scale [ARTIC]), one two-hour training via Zoom on childhood trauma and resilience, and post-training ARTIC questionnaire at two and six weeks.

Seven teachers (n=7) participated in pre-training questionnaires, and three of these teachers (n=3) participated in both post-training questionnaires. All participating teachers were female and Caucasian. Average age of participants was 49.43 years (SD=8.40, range 36-60), and experience average was 17.17 years (SD=10.15, range 3-30). AMR-R average score was 72.29 (SD=8.28, range 61-83). Pre-training ARTIC score average was 3.87 (SD=0.16). Post-training ARTIC scores at two weeks and six weeks post-training were 3.65 (SD=0.22) and 3.86 (SD=0.25).

Clinical significance included improved teacher awareness of childhood trauma and improved ability to interact with children exposed to trauma. Teachers exhibited high resilience scores. Additional research needed related to further address educating preschool teachers related to trauma informed care, related to building resilience in children, and related to the impact of teacher resilience on trauma informed care.

Keywords: teacher training, adverse childhood experiences, ACEs, childhood trauma, resilience

This study investigates the impact of urban form and landscaping type on the mid-afternoon microclimate in semi-arid Phoenix, Arizona. The goal is to find effective urban form and design strategies to ameliorate temperatures during the summer months. We simulated near-ground air temperatures for typical residential neighborhoods in Phoenix using the three-dimensional microclimate model ENVI-met. The model was validated using weather observations from the North Desert Village (NDV) landscape experiment, located on the Arizona State University's Polytechnic campus. The NDV is an ideal site to determine the model's input parameters, since it is a controlled environment recreating three prevailing residential landscape types in the Phoenix metropolitan area (mesic, oasis, and xeric).

After validation, we designed five neighborhoods with different urban forms that represent a realistic cross-section of typical residential neighborhoods in Phoenix. The scenarios follow the Local Climate Zone (LCZ) classification scheme after Stewart and Oke. We then combined the neighborhoods with three landscape designs and, using ENVI-met, simulated microclimate conditions for these neighborhoods for a typical summer day. Results were analyzed in terms of mid-afternoon air temperature distribution and variation, ventilation, surface temperatures, and shading. Findings show that advection is important for the distribution of within-design temperatures and that spatial differences in cooling are strongly related to solar radiation and local shading patterns. In mid-afternoon, dense urban forms can create local cool islands. Our approach suggests that the LCZ concept is useful for planning and design purposes.

Human exposure to excessively warm weather, especially in cities, is an increasingly important public health problem. This study examined heat-related health inequalities within one city in order to understand the relationships between the microclimates of urban neighborhoods, population characteristics, thermal environments that regulate microclimates, and the resources people possess to cope with climatic conditions. A simulation model was used to estimate an outdoor human thermal comfort index (HTCI) as a function of local climate variables collected in 8 diverse city neighborhoods during the summer of 2003 in Phoenix, USA. HTCI is an indicator of heat stress, a condition that can cause illness and death. There were statistically significant differences in temperatures and HTCI between the neighborhoods during the entire summer, which increased during a heat wave period. Lower socioeconomic and ethnic minority groups were more likely to live in warmer neighborhoods with greater exposure to heat stress. High settlement density, sparse vegetation, and having no open space in the neighborhood were significantly correlated with higher temperatures and HTCI. People in warmer neighborhoods were more vulnerable to heat exposure because they had fewer social and material resources to cope with extreme heat. Urban heat island reduction policies should specifically target vulnerable residential areas and take into account equitable distribution and preservation of environmental resources.