Programs and Communities

Climatic changes have the potential to impact electricity generation in the U.S. Southwest and methods are needed for estimating how cities will be impacted. This study builds an electricity vulnerability risk index for two Southwest cities (Phoenix and Los Angeles) based on climate-related changes in electricity generation capacity. Planning reserve margins (PRM) are used to estimate the potential for blackouts and brownouts under future climate scenarios. Reductions in PRM occur in both cities in 2016 with the most significant reductions occurring in regions relying more heavily on hydropower.

Disease burden is higher in the United States than in comparable countries. The Patient Self Determination Act of 1990 requires healthcare facilities to provide Advance Care Planning (ACP) information to all Medicare patients. The healthcare staffs’ (n=7) commitment to 3-days of ACP training increase ACP rates in the primary care setting. The Medicare Incentive Program is the platform for this initiative. This quantitative project used a valid and reliable pre and posttest design that consisted of 27 items on a Likert-scale. A 3.5-month chart audit (n=91) was conducted to assess the completion rate. Descriptive statistics was used to describe the demographic data.

The results of the two-tailed Wilcoxon signed rank test were significant based on an alpha value of 0.05, V = 0.00, z = -2.37, p = .018. There was a significant increase in the post-readiness to change average scores. A Mann Whitney test was used to analyze the statistically significant difference between the averages in two ACP types and electronic health record documentation (EHR). Staff did not always code (Mdn = 0.00) but they documented in the EHR (Mdn =1.00; 512.00, p = 0.003). ACP discussion was performed 63% of the time during Annual Wellness Visits (AWV), and there was a 49% increase in the EHR documentation. Trained staff are key stakeholders in guiding ACP conversations. They understand the barriers, impact, and consequences related to the lack of advance directives.

Phoenix is the sixth most populated city in the United States and the 12th largest metropolitan area by population, with about 4.4 million people. As the region continues to grow, the demand for housing and jobs within the metropolitan area is projected to rise under uncertain climate conditions.

Undergraduate and graduate students from Engineering, Sustainability, and Urban Planning in ASU’s Urban Infrastructure Anatomy and Sustainable Development course evaluated the water, energy, and infrastructure changes that result from smart growth in Phoenix, Arizona. The Maricopa Association of Government's Sustainable Transportation and Land Use Integration Study identified a market for 485,000 residential dwelling units in the urban core. Household water and energy use changes, changes in infrastructure needs, and financial and economic savings are assessed along with associated energy use and greenhouse gas emissions.

The course project has produced data on sustainable development in Phoenix and the findings will be made available through ASU’s Urban Sustainability Lab.

Already the leading cause of weather-related deaths in the United States, extreme heat events (EHEs) are expected to occur with greater frequency, duration and intensity over the next century. However, not all populations are affected equally. Risk factors for heat mortality—including age, race, income level, and infrastructure characteristics—often vary by geospatial location. While traditional epidemiological studies sometimes account for social risk factors, they rarely account for intra-urban variability in meteorological characteristics, or for the interaction between social and meteorological risks.

This study aims to develop estimates of EHEs at an intra-urban scale for two major metropolitan areas in the Southwest: Maricopa County (Arizona) and Los Angeles County (California). EHEs are identified at a 1/8-degree (12 km) spatial resolution using an algorithm that detects prolonged periods of abnormally high temperatures. Downscaled temperature projections from three general circulation models (GCMs) are analyzed under three relative concentration pathway (RCP) scenarios. Over the next century, EHEs are found to increase by 340-1800% in Maricopa County, and by 150-840% in Los Angeles County. Frequency of future EHEs is primarily driven by greenhouse gas concentrations, with the greatest number of EHEs occurring under the RCP 8.5 scenario. Intra-urban variation in EHEs is also found to be significant. Within Maricopa County, “high risk” regions exhibit 4.5 times the number of EHE days compared to “low risk” regions; within Los Angeles County, this ratio is 15 to 1.

The project website can be accessed here. 

Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and usage can introduce complexity that emerges from the composition itself.

To improve assurance of model correctness, sub-systems using disparate modeling formalisms must be integrated above and beyond just the data and control level; their composition must have model specification and simulation execution aspects as well. Poly-formalism composition is one approach to composing models in this manner.

This dissertation describes a poly-formalism composition between a Discrete EVent System specification (DEVS) model and a Cellular Automata (CA) model types. These model specifications have been chosen for their broad applicability in important and emerging domains. An agent-environment domain exemplifies the composition approach. The inherent spatial relations within a CA make it well-suited for environmental representations. Similarly, the component-based nature of agents fits well within the hierarchical component structure of DEVS.

This composition employs the use of a third model, called an interaction model, that includes methods for integrating the two model types at a formalism level, at a systems architecture level, and at a model execution level. A prototype framework using DEVS for the agent model and GRASS for the environment has been developed and is described. Furthermore, this dissertation explains how the concepts of this composition approach are being applied to a real-world research project.

This dissertation expands the tool set modelers in computer science and other disciplines have in order to build hybrid system models, and provides an interaction model for an on-going research project. The concepts and models presented in this dissertation demonstrate the feasibility of composition between discrete-event agents and discrete-time cellular automata. Furthermore, it provides concepts and models that may be applied directly, or used by a modeler to devise compositions for other research efforts.