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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

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.

ContributorsNahlik, Matthew (Author) / Chester, Mikhail Vin (Author) / Andrade, Luis (Author) / Archer, Melissa (Author) / Barnes, Elizabeth (Author) / Beguelin, Maria (Author) / Bonilla, Luis (Author) / Bubenheim, Stephanie (Author) / Burillo, Daniel (Author) / Cano, Alex (Author) / Guiley, Keith (Author) / Hamad, Moayyad (Author) / Heck, John (Author) / Helble, Parker (Author) / Hsu, Will (Author) / Jensen, Tate (Author) / Kannappan, Babu (Author) / Kirtley, Kelley (Author) / LaGrou, Nick (Author) / Loeber, Jessica (Author) / Mann, Chelsea (Author) / Monk, Shawn (Author) / Paniagua, Jaime (Author) / Prasad, Saransh (Author) / Stafford, Nicholas (Author) / Unger, Scott (Author) / Volo, Tom (Author) / Watson, Mathew (Author) / Woodruff, Abbie (Author) / Arizona State University. School of Sustainable Engineering and the Built Environment (Contributor) / Arizona State University. Center for Earth Systems Engineering and Management (Contributor)
Description
The Arizona State University (ASU) Masters of Sustainability Solutions (MSUS) program connects student teams with real-world clients to solve real-world sustainability problems as a part of the students’ Culminating Experience in the program. This report details the project assigned to our group, the Emissions Data Detectives (EDD), in partnership with

The Arizona State University (ASU) Masters of Sustainability Solutions (MSUS) program connects student teams with real-world clients to solve real-world sustainability problems as a part of the students’ Culminating Experience in the program. This report details the project assigned to our group, the Emissions Data Detectives (EDD), in partnership with our client, Gannett Fleming. This project focuses on calculating greenhouse gas (GHG) emissions from the client’s leased office spaces across the United States and Canada. In excess, GHGs trap heat in the atmosphere, negatively affecting global air quality and human health. In addition, top companies similar to our client are already disclosing their emissions, new legislation is aiming to require such reporting, and stakeholders are trending to gravitate towards firms measuring and reducing their environmental impact. During the first semester of this project, we noticed that Gannett Fleming lacked data on specific utility usage in their leased office spaces, as not all data is shared, standardized, or robust enough for accurate emissions calculations. After conducting a landscape analysis where group members interviewed companies facing a similar problem, the team identified best practices for addressing this issue. Such practices included using mixed methods for calculations based on data availability, leveraging organizational connections for efficient communication with landlords, creating custom communication plans, and using concise language with landlords. The team also conducted an sTOWS analysis to understand better how our research could best be applied to Gannett Fleming’s problem. From there, we developed a project plan that included an Invitation to Participate and Data Request to collect the necessary data. Next, the team outlined strategies for emissions calculations, including applying calculations from the GHG Protocol and compiling all calculations in a navigable spreadsheet. Greenhouse gas calculations were made using a mix of asset-specific data from the Data Request forms and average data from the EPA estimates using equations from Scope 3, Category 8, or Leased Upstream Assets per the Greenhouse Gas Protocol. Emissions were categorized under Scope 3 since the client has no control over the leased offices, and the control approach was used. Final results showed that the emissions calculated for the 8 offices where asset-specific data was used combined with the 31 offices where average data was used totaled 2,390 metric tonnes of CO2e for FY2022. In order to ensure that this project can be helpful to Gannet Fleming long-term, we came up with three main deliverables including a GHG spreadsheet including all calculations and findings, a GHG roadmap with simplified step-by-step instructions of our methodology, and a Sustainable Leasing Policy information to ensure the client’s emissions reduction goals are communicated and considered in the decision-making process for future lease agreements. This version contains results that have been edited to ensure client confidentiality. Offices have been anonymized, and numbers used are not representative of actual emissions findings.
ContributorsGutierrez, Lukas (Author) / Carlson, Chloe (Author) / Davitt, Akilah (Author) / Cobb, James (Author)
Created2023-04-24
Description

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

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.

ContributorsMayer, Gary R. (Author)
Created2009