USC Center for Sustainability Solutions Undergraduate Student Grand Challenge (USGC) Fellows, AY 23-24

The USC Center for Sustainability Solutions (CSS) is pleased to announce the Undergraduate Student Grand Challenge Fellows for 2023-2024. The Undergraduate Student Grand Challenge Fellowship (USGCF) supports, through a competitive process, multidisciplinary research projects focused on sustainability. Funded by the CSS, and open to undergraduate students in all USC majors, the USGCF contributes to extending to the larger USC community the values espoused by the Viterbi School of Engineering, the Price School of Public Policy, and the National Academy of Engineering Grand Challenges Scholars Program.

The selected projects include:

Carbon-Smart Jerky: A Research Initiative on Sustainable Protein

Matias Mansilla (Marshall School of Business) and Simon Callaghan (Marshall School of Business) – both are returning Fellows

The Carbon-Smart Jerky project, born out of the Undergraduate Sustainability Grand Challenge Fellowship, seeks to translate two years of research into a sustainable business. Building on experience in Australia and Argentina, where regenerative practices were implemented to reduce carbon footprints, the project aims to introduce a low-carbon beef jerky product, incorporating organs to enhance nutritional value and reduce costs. By addressing the carbon-intensive nature of beef production and improving supply chain transparency, the project aims to make a significant impact on reducing the carbon footprint of American households’ food choices. Through interdisciplinary partnerships, entrepreneurial innovation, cultural understanding of farming practices, and a focus on societal impact, the project aims to offer an affordable and sustainable protein option, encouraging responsible production practices.

Evaluating the Implementation of Flow Batteries as Parts of Grid Infrastructure 

Ellie Mastrobattista (Viterbi School of Engineering) and Nico Peji (Roski School of Art and Design)

This project focuses on the critical need for sustainable battery technologies to support large-scale grid storage of renewable electricity, especially in the context of transitioning to electric transport to combat climate change. The team aims to compare flow batteries, known for scalable capacity and fast charge/discharge cycles, with traditional energy storage systems such as lithium-ion batteries and pumped hydro. Through Life Cycle Assessments (LCAs), the project seeks to provide insights into the environmental impact and advantages of flow batteries. Additionally, the project aims to address the novelty of flow battery technology by creating visual material to communicate its integration into the grid and people’s lives. The technical approach involves a comprehensive comparison of environmental impacts across different energy storage systems using the ReCiPe2016 Life Cycle Assessment method. The previous iteration of the project highlighted the importance of material selection, efficiency improvements, and a shift away from narrow supply chains for raw materials like vanadium.

Reversing and Renovating Market Cycle: Product Design and Consumer Psychology in Zero-Waste and Sustainability Efforts

Peizhuo Ji (Dornsife College of Letters, Arts and Sciences/Price School of Public Policy) and Yixiao Li (Viterbi School of Engineering/Dornsife College of Letters, Arts and Sciences)

This project addresses sustainability challenges, highlighting issues like California’s low recycling rates and significant plastic waste in the United States. Despite global and local initiatives, such as the Paris Agreement and USC’s sustainability efforts, a UN climate change report underscores the urgency for more impactful actions. The project aims to tackle the toxic relationship between producers and consumers, exploring ways to encourage sustainable practices. It outlines objectives, including advocating for sustainable approaches, evaluating communication strategies, studying consumer psychology, determining price sensitivity, establishing a comprehensive rating system, and aligning behaviors with sustainability attitudes. The technical approach involves data collection through AI-generated surveys, statistical testing, economic modeling, and machine learning methods to analyze consumer preferences and behaviors. The project’s significance lies in bridging the informational gap between consumers and producers, aiming to transform the market cycle into a virtuous one. By exploring sustainable materials, improving business communication, and influencing consumer behaviors, the project seeks to construct a mutually beneficial and sustainable business mode.

Sustainability Education Picture Book Publication

Chaeyeon Park (Dornsife College of Letters, Arts and Sciences/Roski School of Art and Design) – returning Fellow

This project aims to enhance sustainability and environmental education for children aged 4-10 through the creation of a children’s picture book and an accessible website. The threefold objectives involve introducing a sustainability-focused storybook, promoting arts-based education in bookmaking to slow down consumption, and exploring alternative methods of conceptualizing books, including an online format. The completed manuscript, titled “The Myoja,” addresses the environmental issue of light pollution, encouraging children to ponder sustainable solutions. The project also delves into sustainable publishing by experimenting with an e-book platform and researching paper recycling, paper making, and book binding. Despite challenges in introducing a salt water-based paper production system, the project emphasizes the importance of promoting sustainable practices in the publishing industry. The technical approach involves data collection through AI-generated surveys, focusing on consumer preferences and behaviors. Statistical testing, economic modeling, and machine learning methods will analyze the collected data, providing insights into efficient business communication and sustainable practices. The project’s significance lies in bridging the informational gap between consumers and producers, aiming to transform the market cycle into a virtuous one, benefitting both parties and contributing to zero-waste efforts. By exploring sustainable materials, improving business communication, and influencing consumer behaviors, the project aims to construct a mutually beneficial and sustainable business model.

Aloha AIr: Applying Machine Learning for Precise Air Quality Predictions in the Wake of Hawaiian Volcanic Activity

Jaron Kawamura (Viterbi School of Engineering) and Pratyush Jaishanker (Viterbi School of Engineering)

This project responds to the urgent need for advanced air quality prediction in Hawaii, emphasizing the impact of volcanic eruptions. Recent wildfires in Lahaina highlighted the vulnerability of Hawaiian communities to hazardous air conditions, necessitating the development of early warning systems. With climate change intensifying, there is growing concern about increased natural disasters, necessitating predictive models to provide insights into the contents and spread of dangerous air pollutants. The project aims to develop a machine learning model using atmospheric and meteorological data post-volcanic eruption on the Big Island, focusing on predicting air quality impacts across multiple islands. Target pollutants include sulfur dioxide (SO2) and particulate matter (PM 2.5). The goal is a mean absolute error of less than 10%. Leveraging machine learning, particularly tree-based models, the approach involves analyzing datasets combining air quality data from Hawaii’s Department of Health with meteorological data from NOAA. The long-term objective is embedding the model into a user-friendly mobile app for real-time, personalized air quality alerts, particularly beneficial for individuals with respiratory conditions. This interdisciplinary collaboration in biomedical engineering, computer science, and earth sciences addresses the unique challenges of Hawaii’s environmental health, atmospheric monitoring, and computational modeling.

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