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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Meaningful sustainable consumption patterns require informed consumers who understand the actual impact of their actions on a quantitative and tangible basis. Life cycle assessment (LCA) is a tool well suited to achieving this goal, but has only been superficially applied to the analysis of plant-based diets. This analysis looks at

Meaningful sustainable consumption patterns require informed consumers who understand the actual impact of their actions on a quantitative and tangible basis. Life cycle assessment (LCA) is a tool well suited to achieving this goal, but has only been superficially applied to the analysis of plant-based diets. This analysis looks at a common component of plant-based meat alternatives: a wheat-based protein known as seitan, which is a common substitute for beef. A comparative consequential analysis shows the overall change in environmental impact when 1000 servings of seitan displace 1000 servings of beef. The functional unit for comparison is one serving of seitan or one serving of beef and the system boundaries include production but not distribution, consumption or disposal. Life cycles are created for seitan and beef in the LCA modeling software SimaPro and an analysis is run using the Eco-indicator 99 methodology. The beef life cycle is created using complete existing LCA data, while the seitan life cycle is created using LCA data for constituent materials and processes.

Findings indicate that beef is much more environmentally impactful than seitan, but the largest difference is found in land use change. Significant data quality and uncertainty issues exist due to the data being incomplete or not representative for US processes and the use of proxy processes to estimate industrial processing. This analysis is still useful as a screening tool to show rough differences in impact. It is noted that despite seitan having a lower environmental impact than beef, increasing seitan production will probably have the effect of increasing overall environmental impacts, as beef production is not likely to decrease as a result. Massive changes in consumer purchase patterns are required before reductions in impact can be expected. Recommendations for future work include expanding system boundaries and obtaining industry specific data for seitan production.

Created2012-05
Description

In the spring of 2016, the City of Apache Junction partnered with the School of Geographical Sciences and Urban Planning at Arizona State University on three forward-thinking plans for development in Apache Junction. Graduate students in the Urban and Environmental Planning program worked alongside City staff, elected officials and the

In the spring of 2016, the City of Apache Junction partnered with the School of Geographical Sciences and Urban Planning at Arizona State University on three forward-thinking plans for development in Apache Junction. Graduate students in the Urban and Environmental Planning program worked alongside City staff, elected officials and the public to identify opportunities and visions for:
       1. Multi-modal access and connectivity improvements for City streets and open space.
       2. Downtown development.
       3. A master-planned community on state land south of the U.S. 60.

The following sections of the report present Apache Junction’s unique characteristics, current resident demographics, development needs and implementation strategies for each project:
       1. Community Profile
       2. Trail Connectivity Master Plan
       3. Downtown Visioning
       4. State Land Visioning

The Trail Connectivity Master Plan optimizes existing trails and wide road shoulders to improve multi-modal connections across the city. The proposed connections emphasize access to important recreation, education and other community facilities for pedestrians, equestrians and bicycles. Trail and lane designs recommend vegetated buffers, wherever possible, to improve traveler safety and comfort. The proposals also increase residents’ interaction with open space along urban-rural trails and park linkages to preserve opportunities to engage with nature. The objectives of the report are accomplished through three goals: connectivity, safety improvements and open space preservation.

Downtown Visioning builds on a large body of conceptual design work for Apache Junction’s downtown area along Idaho Road and Apache Trail. This report identifies three goals: to establish a town center, to reestablish the grid systems while maintaining a view of the Superstition Mountains, and to create an identity and sense of place for the downtown.

State Land Visioning addresses a tract of land, approximately 25 square miles in area, south of the U.S. 60. The main objective is to facilitate growth and proper development in accordance with existing goals in Apache Junction’s General Plan. This is accomplished through three goals:
       1. Develop a foundation for the creation of an economic corridor along US-60 through
           preliminary market research and land use planning.
       2. Create multi-modal connections between existing development north of US-60 and
           future recreational space northeast of US-60.
       3. Maintain a large ratio of open space to developed area that encompasses existing
           washes and floodplains using a master planned community framework to provide an
           example for future land use planning.