Research Topics and Projects
The rapid adoption and acceleration of the use of digital technologies is transforming the way we access and process information, impacting the global economy and our social dynamics. These dramatic technological and social changes also have important environmental and energy implications.
In recent decades, the digital economy* has generated tremendous growth in traditional and emerging sectors—Craigslist displaced traditional newspaper classified ads, ride-hailing apps like Uber and Lyft cut into traditional taxi services, and Amazon overshadowed catalog retailing. These trends are set to continue into the future. The COVID-19 pandemic has significantly accelerated digital economy developments in critical sectors, including e-commerce, remote work, and digital media. Given the extent and pace of digitalization, it is not surprising that the estimated energy and environmental (E&E) implications of digital economy developments are significant as well.
A growing body of research seeks to understand and quantify the direct E&E impacts of digitalization, both negative and positive, including the increase or reduction of energy use and emissions arising from the use of devices (and/or their supporting infrastructure) themselves. The environmental effects of human-technology interactions–our digital lives–remain understudied. Research indicates that the direct life-cycle impacts of digital devices are typically 100-1,000 kg CO2e per product life for mobile devices, but we lack adequate estimates for the indirect impacts—that is, the environmental impacts of the activities enabled by these devices such as shopping and transportation.
This initiative seeks to leverage academic research across various disciplines in order to provide guidance on a number of high-priority issue areas at the intersection of energy environment and digital platforms. We have provided seed funding to 10 research teams that will explore ideas from understanding Uber and Lyft driver perceptions around electric vehicle adoption to looking at the environmental impacts resulting from the use of AI in the chemical manufacturing industry.
*We define the digital economy as the parts of the economy that capitalize on the technological change that is transforming markets and consumer patterns and is based significantly if not entirely on digital technologies. It includes a broad range of activities, with the common denominator being reliance upon digital operations, infrastructure, and/or knowledge (adapted from OECD).
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Artificial Intelligence (AI)
Computation systems with the ability to learn and improve their performance over time are becoming more common. As the scope, complexity, and applications of these self-teaching machine systems expand, they will increasingly influence how we manage energy and the environment.
Blockchain
While the subject of much recent attention, there is little clarity surrounding blockchain’s energy consumption and its potential applications in support of sustainability.
Internet of Things
The objects used for daily activities are increasingly interconnected and internet-capable, enabling the objects to share information with each other and with users, from smart home devices that reduce energy and water consumption, to interconnected agricultural devices equipped with soil quality sensors.
Sharing
Digital sharing platforms such as Lyft, Uber and AirBnB have transformed the economy in numerous ways. Despite their prevalence and scope, we have yet to fully understand how use of these platforms impact a range of important environmental issues.
Projects
Autonomous Ridesharing Vehicles and the Environmental Rebound Effect
Principal investigator Assoc. Prof. Andrea Hicks will explore the rebound environmental impacts of autonomous vehicles and autonomous ride-sharing vehicles. A survey will be conducted to investigate how people think their transportation habits would change with the advent of autonomous vehicles as well as how their behavior has already changed due to other shared mobility options and the global pandemic. Environmental impacts will be quantified using the GREET model and rebound effects based on changes in vehicle miles traveled will be assessed.
Project lead(s):
Dr. Andrea Hicks, University of Wisconsin-Madison
Best Practices for Analyzing the Direct Energy Use of Blockchain Technology Systems
This project will lay a foundation for more analytically-sound and transparent estimates of blockchain energy use moving forward. For more details and project results, see the full paper and accompanying presentation.
The team also published an article in the September 2021 issue of Energy Policy.
Project leads:
Dr. Eric Masanet, Northwestern University
Dr. Jonathan Koomey, Rocky Mountain Institute
Blockchain Technology and the Sustainable Supply Chain: Theoretically Exploring Adoption Barriers
While the changes that would result from implementing blockchain solutions are worth studying, we also need to gain a deeper understanding of how these blockchain solutions are to be operated and by whom. For more details and project results, see the full paper and accompanying presentation.
Project leads:
Dr. Sara Saberi, Worcester Polytechnic Institute
Dr. Joseph Sarkis, Worcester Polytechnic Institute
Electric Vehicles in Ridehailing Applications: Insights From a Fall 2019 Survey of Lyft and Uber Drivers in Los Angeles
This project seeks to better understand why ridesourcing drivers are not choosing to purchase EVs. For more details and project results, see the full paper and accompanying presentation.
Project leads:
Dr. Deepak Rajagopal, University of California, Los Angeles
Dr. Nicole Sintov, Ohio State University
Energy Use and Carbon Emissions from E-Commerce: Implications for a Decarbonized Future
Principal investigator Prof. Miguel Jaller will quantify energy use and carbon emissions in retail distribution arising from recent changes to e-commerce during the pandemic. The research will use a retail sector energy and emissions calculator model, based on life cycle assessment, that incorporates factors such as warehousing, upstream freight, retailing store facilities, packaging, last mile distribution, customer transport, and data centers/computers/networks. Prof. Jaller and his research team will explore changes with respect to distribution structures, and innovations in vehicles, fuels, energy, and distribution technologies, and proposed corporate initiatives and commitments.
Project lead(s):
Dr. Miguel Jaller, University of California, Davis.
Ms. Sarah Dennis, Doctoral Student, University of California, Davis.
Mr. Anmol Pahwa, Doctoral Student, University of California, Davis.
Evaluating the Potential of Cooperative Ridesourcing: A Case Study of Arcade City in Austin, Texas
Our project team believes that an evaluation of AC Austin will fill knowledge gaps and provide important and novel insights into the benefits and drawbacks of decentralized cooperative sharing platforms as compared to more prevalent centralized commercial approaches. For more details and project results, see the accompanying presentation.
Project leads:
Sara Stephens, Sustainable Economies Law Center
Adam Stocker, Sustainable Economies Law Center
Investigating the Energy and Environmental Implications of Artificial Intelligence Applications in the Chemical Manufacturing Industry
This project aims to address the data and analysis gaps by developing a metric-based framework to quantify energy and environmental implications of AI applications in the production of some of the most common energy-intensive chemicals. For more details and project results, see the accompanying presentation.
Project lead:
Dr. Yuan Yao, Yale School of the Environment
Open Science Behind Closed Doors: Empowering Citizens to Use Their Private Data for Decision-making
This study is designed to provide consumers with a credible way to connect environmental footprint information on their individual consumption to make better-informed decisions.
Project lead:
Dr. Brandon Kuczenski, UC Santa Barbara
Research on the Environmental Impacts of Artificial Intelligence — Gaps and Opportunities
Principal investigator Dr. Alan Porter will use statistical (bibliometric) analysis of publications, citations, and keywords to identify trends and gaps in research on the environmental impact of artificial intelligence. The analysis will identify the leading research players, prominent research topics, in what countries the research is
concentrated, and plot overall trends. Based on those findings, the analysis will also explore the interconnections of research through network analyses and mapping.
Project lead(s):
Alan Porter, Search Technology, Inc.
Social and Environmental Analysis of Food Waste Abatement via the Peer-to-Peer Sharing Economy
In this research, we aim to reveal insights into the nature and dynamics of the sharing economy through a deep dive into a real-world food sharing network that aims to reduce household food waste. For more details and project results, see the full paper and accompanying presentation.
Project leads:
Dr. Marian Chertow, Yale School of the Environment
Dr. Jonathan Krones, Boston College
Dr. Tamar Makov, Ben-Gurion University of the Negev
Dr. Alon Shepon, Harvard TH Chan School of Public Health
Sustainability Implications of the Rural-Urban Digital Divide
Principal investigator Prof. Shelie Miller will use life cycle assessment (LCA) to compare the energy and environmental impacts of online grocery delivery in rural and urban environments. The research will determine a suite of best practices and potential interventions to reduce the environmental impacts and provide insights into how these services can best be adapted to rural communities. This research will help determine the extent to which the environmental impacts of e-commerce adoption are within the industry’s control (e.g., vehicle type), the extent to which environmental impacts rely on consumer adoption patterns (e.g., last-mile density), and the differences observed in rural and urban contexts.
Project lead(s):
Dr. Shelie Miller, University of Michigan
The Carbon Footprint of Airbnb
This project seeks to address the lack of research on the transportation-related climate impacts of the sharing platform Airbnb. This will be the first study of the changing distribution of Airbnb listings and the associated mobility patterns of Airbnb guests, comparing the ten largest Airbnb urban markets and providing data and recommendations for municipal authorities and ride hailing firms to reduce greenhouse gas emissions.
Project leads:
Dr. Juliet Schor, Boston College
Dr. Özlem Ergun, Northeastern University
Dr. Qi Wang, Northeastern University
Dr. Mehmet Cansoy, Fairfield University
The Carbon Footprint of Ride-Hailing: GHG Inventory Methodology
Our goal is to provide a path for creating locally specific analysis to inform policy and planning. Specifically, we aim to produce tools for communities to generate initial answers for themselves. For more details and project results, see the full paper.
Project leads:
Joshua Skov, University of Oregon
Aaron Toneys, Good Company
Dr. Anne Brown, University of Oregon
What Happens to My Product Returns: The Hidden Environmental Cost of Online Sales
This project seeks to quantify the full life cycle of environmental impacts of product returns and reveal how returns might affect the environmental performance of e-commerce more broadly.
Project leads:
Dr. Tamar Makov, Ben-Gurion University of the Negev
Dr. Vered Blass, Tel Aviv University
Prof. Charles Corbett, UCLA