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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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

Results are available here

The environmental life cycle assessment of electric rail public transit modes requires an assessment of electricity generation mixes. The provision of electricity to a region does not usually adhere to geopolitical boundaries. Electricity is governed based on lowest cost marginal dispatch and reliability principles. Additionally, there

Results are available here

The environmental life cycle assessment of electric rail public transit modes requires an assessment of electricity generation mixes. The provision of electricity to a region does not usually adhere to geopolitical boundaries. Electricity is governed based on lowest cost marginal dispatch and reliability principles. Additionally, there are times when a public transit agency may purchase wholesale electricity from a particular service provider. Such is the case with electric rail modes in the San Francisco Bay Area.

An environmental life cycle assessment of San Francisco Bay Area public transit systems was developed by Chester and Horvath (2009) and includes vehicle manufacturing/maintenance, infrastructure construction/operation/maintenance, energy production, and supply chains, in addition to vehicle propulsion. For electric rail modes, vehicle propulsion was based on an average electricity mix for the region. Since 2009, new electricity contract information and renewable electricity goals have been established. As such, updated life cycle results should be produced.

Using recent wholesale electricity mix and renewable electricity goal data from the transit agencies, updated electricity precombustion, generation, transmission, and distribution environmental impacts of vehicle propulsion are estimated. In summary, SFMTA Muni light rail is currently purchasing 100% hydro electricity from the Hetch Hetchy region of California and the Bay Area Rapid Transit (BART) system is purchasing 22% natural gas, 9% coal, 2% nuclear, 66% hydro, and 1% other renewables from the Pacific Northwest . Furthermore, the BART system has set a goal of 20% renewables by 2016. Using the GREET1 2012 electricity pathway, a life cycle assessment of wholesale and renewable electricity generation for these systems is calculated.

Chester and Horvath (2009)