A collection of scholarly work published by and supporting the Center for Earth Systems Engineering and Management (CESEM) at Arizona State University.

CESEM focuses on "earth systems engineering and management," providing a basis for understanding, designing, and managing the complex integrated built/human/natural systems that increasingly characterize our planet.

Works in this collection are particularly important in linking engineering, technology, and sustainability, and are increasingly intertwined with the work of ASU's Global Institute of Sustainability (GIOS).

Collaborating Institutions:
School of Sustainable Engineering and the Built Environment (SSEBE), Center for Earth Systems Engineering and Management
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Description

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

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.

Description

Essay scoring is a difficult and contentious business. The problem is exacerbated when there are no “right” answers for the essay prompts. This research developed a simple toolset for essay analysis by integrating a freely available Latent Dirichlet Allocation (LDA) implementation into a homegrown assessment assistant. The complexity of the

Essay scoring is a difficult and contentious business. The problem is exacerbated when there are no “right” answers for the essay prompts. This research developed a simple toolset for essay analysis by integrating a freely available Latent Dirichlet Allocation (LDA) implementation into a homegrown assessment assistant. The complexity of the essay assessment problem is demonstrated and illustrated with a representative collection of open-ended essays. This research also explores the use of “expert vectors” or “keyword essays” for maximizing the utility of LDA with small corpora. While, by itself, LDA appears insufficient for adequately scoring essays, it is quite capable of classifying responses to open-ended essay prompts and providing insight into the responses. This research also reports some trends that might be useful in scoring essays once more data is available. Some observations are made about these insights and a discussion of the use of LDA in qualitative assessment results in proposals that may assist other researchers in developing more complete essay assessment software.

Description

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

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

Created2014-06-12