On the day of its launch, the Institute for Climate and Sustainable Growth awarded 11 grants to frontier research projects aimed at tackling some of the most pivotal climate and energy topics. The faculty spearheading these projects come from nine different units across campus—typically with faculty working on the same project coming from different units—showing both the diversity of expertise and the collaboration across disciplines to tackle the multilayered challenges of climate change.
The winning projects were chosen through a competitive process out of 30 total submissions, representing 23 University units. The scale of the interest and wide variety of disciplines engaged emphasize the intense interest in studying the climate challenge at the University of Chicago, and the variety of ways in which climate change intersects with different topics.
The awardees are part of two funding programs. Two of the 11 winners were awarded Venture Funds. The Venture Fund program aims to foster an ecosystem of scholars from across UChicago around a central challenge to conduct advanced research. These projects often include external collaborators such as government or industry entities to pilot and scale real-world solutions and provide impactful tools. Nine of the winners received grants from the Seed Fund program, which provides support for early-stage research. Both programs provide funding to traditional climate and energy researchers and those who do not typically study climate and energy topics but who see connections between climate and energy and their areas of expertise. In doing so, the programs encourage highly experienced scholars from different areas of study to apply their expertise to this deeply complex challenge to spur innovative, outside-the-box thinking.
Venture Fund Awardees
Human-Centered Weather Forecasts
Awardees: Michael Kremer, Amir Jina, Pedram Hassanzadeh
High-quality weather forecasts help vulnerable populations adapt to increased weather uncertainty and extremes. Innovations, especially in AI, are driving a second revolution in weather forecasting. However, the benefits are yet to be realized in low- and middle-income countries. The Human-Centered Weather Forecasts (HCF) initiative will bridge this gap, leveraging UChicago’s interdisciplinary strengths as well as the research group’s track record of engaging policymakers, funders, multilateral development banks, researchers, firms, and NGOs to transform access to this vital climate adaptation tool. HCF will a) develop novel techniques to produce forecasts tailored to the specific adaptation needs of farmers and individuals exposed to extreme heat; b) work with implementers to disseminate forecasts to 100 million people in low- and middle-income countries; c) conduct rigorous testing to optimize dissemination and generate lessons to further scale these advances; d) strengthen global forecasting systems, including through benchmarking and validation; and (e) work to establish an ongoing initiative.
Establishing the Center for Advanced Materials for Climate Mitigation
Awardees: Laura Gagliardi, John Anderson, Max Delferro, Ian Foster, Guilia Galli, Nancy Kawalek, Doug Weinberg
We propose establishing a multidisciplinary center at the University of Chicago to develop innovative materials that significantly reduce the impact of climate change. The Center for Advanced Materials for Climate Mitigation (CAMCM) will initially focus on porous materials, whose cage-like structures are remarkably effective for trapping and releasing CO2 and other substances. In addition to seeking new materials, CAMCM aims to revolutionize the materials discovery process by using artificial intelligence (AI), machine learning, and robotics. Applying these tools can dramatically accelerate materials discovery, potentially reducing research timelines from years to months and helping to meet urgent climate deadlines. CAMCM will prioritize projects likely to yield practical breakthroughs, so scientific advancements translate into real-world benefits. The Center’s multidisciplinary team includes experts in materials science, chemistry, computer science, science communication through artistic endeavors, and other fields. Besides research, the Center will serve as a global hub for education and outreach in this field.
Seed Fund Awardees
Forecasts at Scale: General Equilibrium Impacts of Climate Adaptation
Awardees: Amir Jina, Fiona Burlig, Erin Kelley, Gregory Lane
Climate change will increase weather risk for small-holder farmers in low-income countries. This project will use a novel approach to addressing this risk: accurate, long-range forecasts, which provide farmers information well in advance of the growing season about seasonal weather realizations. This project builds on Burlig et al (2024), a successful RCT in 250 villages which demonstrated that forecasts of the timing of the Indian summer monsoon’s onset led farmers to substantially adjust up-front investments such as land use, crop choice, and inputs. In this scaling proposal, the researchers will partner with the Indian Ministry of Agriculture and Farmers’ Welfare to deliver monsoon onset forecasts to millions of farmers across Telangana, using a low-cost SMS platform operated by the government. The project will embed a randomized saturation design into this scale-up, enabling the researchers to measure general equilibrium impacts of these forecasts, including information transfer between farmers and impacts on crop prices. The results from this experiment have the potential to both direct significant investment into the development of new forecasting technology for farmers across the tropics and encourage governments worldwide to disseminate this information at scale.
Using Technology, Artificial Intelligence, and Economics to Induce Smart Demand Response
Awardees: Koichiro Ito, David Brown, Erica Myers, Blake Shaffer
One of the most important climate and energy challenges is how to achieve reliable energy access to a broader population without imposing increases in pollution and pressure on the electricity grid. Smart demand response—an approach that uses technology to help consumers to use energy efficiently—is promising to address this challenging problem, but evidence from academic research is still very limited. To address this question, the researchers have recently established a full partnership with Optiwatt, a company that helps consumers to engage in smart charging for electric vehicles (EVs) and smart use of AC (air conditioning) to conduct a series of randomized controlled trials (RCTs). The experiments aim to test how we can use automation, AI, and economic theory to enhance smart use of energy in the context of EV charging and peak-hour electricity usage for AC. The researchers first theoretically show that it is ambiguous which of the three methods (automation, AI, and allocation based on economic theory) best enhances consumer and social welfare. Then, they conduct two field experiments with over 65,000 customers, one for EV and another for smart AC, to empirically test our theoretical predictions. The project is unique in that the researchers have already established partnership with the partner company and developed detailed experimental designs to test their hypothesis.
Developing a Feasibility Assessment Framework for Carbon Dioxide Removal Through Integration of Engineering and Social Science Knowledge
Awardees: Kim Wolske, Udayan Singh
Models of future climate scenarios under deep decarbonization indicate that carbon dioxide removal (CDR) approaches will likely be essential for meeting net-zero emission goals. The Inflation Reduction Act prioritizes investments in several CDR approaches such as direct air capture (DAC), and the Department of Energy has already announced funding for DAC hubs across the United States. While considerable work has been carried out on engineering process modeling for these demonstrations, CDR scalability requires improved understanding of public acceptance of such projects. The proposal aims to develop an integrative framework to gauge public acceptance of CDR, drawing on both engineering and social science literatures. This will entail a systematic review of the theories, methods, and indicators used in each field to enable researchers to identify testable hypotheses as well as new areas of research on public acceptance of CDR.
Quantum Sensors to Probe Interfaces in Electrochemical Systems
Awardees: Chibueze Amanchukwu, Joseph Heremans
Electrochemical energy technologies such as batteries, water electrolysis, and carbon dioxide/carbon monoxide reduction are required for clean energy and to transform manufacturing. The challenges facing electrochemical devices could be solved if we improved our fundamental understanding of interfacial phenomena at solid/liquid interfaces that then allows us to optimally control electrochemical transformations under applied potentials. Quantum sensing methodologies have been shown in other fields such as biology and physics to have exquisite sensitivity with excellent spatial resolution. Unfortunately, these sensors have not been studied for electrochemistry. Here, the researchers propose to develop quantum sensors for energy technologies and use these sensors to extract fundamental insights into electrochemical processes ranging from heterogeneity in electric fields to spectroscopic determination of intermediates. The work will open up a new field poised to accelerate the development of energy technologies and usher in new classes of materials and devices to mitigate carbon.
Designing Descriptors and Experimental Methods for High-throughput Electrolyte Discovery
Awardees: Ke-Hsin Wang, Chibueze Amanchukwu
Enabling energy-dense and cheap energy storage devices is critical to achieving decarbonization and tackling climate change. Developing advanced batteries requires electrolytes with optimal properties, but traditional trial-and-error methods are inefficient for exploring the vast space of electrolytes composed of various solvents, salts, and their combinations. To address this, the researchers propose to use machine learning (ML) and high throughput (HT) experimentation to accelerate electrolyte discovery. Their approach involves defining descriptors that accurately represent the desired electrolyte properties and ensuring compatibility with HT measurement systems. The proposed strategy addresses the issue of insufficient data for the training of ML models and unveils a new class of solvation-related descriptors that are relevant for battery chemistries. The interdisciplinary integration of ML, HT system, and electrochemistry promises to revolutionize the process of electrolyte discovery for next-generation batteries.
Computational Tools to Support the Repair, Reuse, and Recycling of Devices
Awardees: Jasmine Lu, Pedro Lopes
With the advancement of computing technologies, computational devices have become increasingly ubiquitous. However, this rapid growth in number of computing devices has also generated significant hidden costs, namely for our environment. Electronic waste or e-waste is the fastest growing consumer waste stream in the world. Unfortunately, strategies for remediating this waste stream (through actions like repair, reuse, and recycling) are limited. This project aims to expand methods to repair, reuse, and recycle common e-waste by developing computational tools for such processes. Compared to existing strategies, the researchers develop their tools by taking a layered approach to the e-waste problem, considering e-waste devices not as a homogenous mass but as made up of a stack of modules, components, and substrates (which can each be repurposed through different methods). The project also aims to empower end-users to engage with repairing, reusing, and recycling their e-waste, allowing for broader participation in sustainable computing.
Climate Change Impacts on Population Mobility in the United States
Awardees: Kate Burrows, Prachi Sanghavi
Climate change is reshaping population dynamics across the United States, as disasters, rising temperatures, and increased risk of flooding influence patterns of displacement and migration. Despite growing concern, our understanding of climate-induced mobility remains limited, particularly for vulnerable populations. This study will explore the impact of climate-related exposures on mobility using individual-level data from Medicare and Medicaid beneficiaries. By analyzing a comprehensive dataset covering 40% of the U.S. population from 2005- 2020, the researchers will track annual ZIP code-level mobility to understand responses to various climate events, such as floods, heatwaves, and wildfires. This research will offer nuanced insights into how different disasters affect long-term mobility and will help identify vulnerable populations who are disproportionately impacted. The findings will be instrumental for developing effective climate adaptation strategies, enhancing disaster preparedness, and informing U.S. climate policy. This study will also lay the groundwork for future research and funding opportunities and will provide a new data resource that can be used by other scholars at the University of Chicago.
The Geography of Climate Change: Developing Frameworks to Assess the Economic Impact of Climate Change Across Time and Space
Awardees: Esteban Rossi Hansberg, Rodrigo Adao, Adrian Bilal, Jose-Luis Cruz, Klaus Desmet
Climate change is a global phenomenon with heterogeneous local economic consequences. Understanding its economic impact across time and space, the forms of adaptation it generates, and the policies to address its causes and consequences require the development of dynamic global integrated assessment models that incorporate the geography of the world at a high spatial resolution. This project aims to develop economic frameworks that incorporate a rich set of realistic interactions between locations and over time (including migration, trade, investments, technology transfers, and energy production and transmission systems), a rich set of environmental implications of carbon emissions and the resulting temperature changes (including heat waves, storms, sea level rise, and deforestation), and the associated risk and uncertainty. Developing accurate frameworks that properly incorporate the interactions between all these components is essential to evaluating and designing effective policies and should become an essential assessment tool for climate-related risks for the corporate, financial, and government sectors.
Predicting Microbial CO2 Production from Soils on a Global Scale
Awardees: Seppe Kuehn, Pamela Weisenhorn, Vaibhhav Sinha
The objective of this project is to remove uncertainties in global climate model carbon fluxes from soils by crossing disciplinary boundaries between microbiome and earth science to use AI for predicting soil carbon fluxes from sequencing data.