Innovation for Impact Fund (IIF)

Innovation for Impact Fund (IIF) is sponsored by Cornell Atkinson Center for Sustainability. The Innovation for Impact Fund supports use-inspired research co-created with non-academic partners, focusing on sustainability issues.

Innovation for Impact Fund | Cornell Atkinson Center for Sustainability Innovation for Impact Fund | Cornell Atkinson Center for Sustainability Innovation for Impact Fund All RFPs Currently Closed Innovation for Impact Fund The 2030 Project: Fast Grants The 2030 Project: Climate Solutions Fund Summer Undergraduate Mentored Research Grants Postdoctoral Fellowships Application Sustainable Biodiversity Fund Semlitz Family Sustainability Fellows Use-Inspired Research Co-Created With Non-Academic Partners Cornell Atkinson leverages our Innovation for Impact Fund (IIF) to build partnerships and consortia that co-create research agendas, execute unconventional projects between researchers and practitioners, and bridge the gap between scientific knowledge and action on the most important sustainability issues.

We support basic and applied research with a clear pathway to impact and an emphasis on actionable, near-term results.

Our Strategic Partnerships team leverages the IIF to: Run competitive funding programs for collaborative proposals co-designed with our partners Facilitate strategic projects and initiatives co-designed with partners and executed by blended work teams of Cornell faculty, professional staff, and external collaborators Enable participation in multi-stakeholder consortia, such as CPIC , TSC , and Field to Market IIF-supported interdisciplinary teams comprising academics and practitioners collaborate to develop actionable insights, demonstrate new concepts, design useful tools, pilot applications of scientific discoveries, and implement practices that can shape real-world policies and outcomes.

All Cornell PIs and CoPIs must meet Cornell’s principal investigator (PI) eligibility criteria Jacobs Center & Cornell Atkinson Joint Seed Grants The 2026 cycle is closed: EDF & Cornell Atkinson Rolling Fast Grants EDF & Cornell Atkinson Joint Research The 2026 cycle is closed: The 2030 Project “AI & Climate” Research-to-Impact Fast Grants The 2025 cycle is closed: TNC & Cornell Atkinson Joint Research The 2026 cycle is closed: Modeling the Joint Distribution of Wind and Rain Risk from Tropical Cyclones This project will improve how hurricane/cyclone risks are estimated in a changing climate by modeling the combined danger of extreme wind and heavy rain.

Tropical cyclones often cause both hazards at the same time, but detailed storm models are too costly to run for the many events needed in risk planning. The researchers will use faster physics-based models, historical storm tracks, climate data, and large sets of simulated storms to estimate how wind and rain risks may change in past and future climates.

A postdoctoral researcher will help expand the code, test methods, and turn results into useful tools. The project will support better insurance, planning, and resilience decisions for communities facing stronger climate hazards.

Cornell: Jonathan Lin (Cornell CALS/Earth and Atmospheric Sciences) Data Science to Build Resilience and Improve Humanitarian Response This project will gather leading researchers and policy experts to explore how data science advances can strengthen responses to climate emergencies and food security crises.

The summit will examine three key areas: creating better data systems in regions with limited information, improving prediction models using machine learning, and designing early warning systems that help organizations make faster decisions during humanitarian emergencies.

Representatives from international organizations, development banks, and research institutions will participate in discussions that bridge the gap between technical innovation and real-world disaster response. The project will produce a comprehensive white paper identifying research priorities and opportunities for future collaboration.

By connecting data science capabilities with humanitarian needs, this initiative aims to improve decision-making and resource allocation during climate-related disasters, ultimately helping vulnerable communities prepare for and respond to environmental threats more effectively.

Cornell: Christopher Barrett (Cornell SC Johnson College of Business/Dyson School of Applied Economics and Management) UN World Food Programme (WFP): Kyriacos Kouppari (Head of Hunger Monitoring Unit) UN Refugee Agency (UNHCR): Rebeca Moreno Jimenez (Lead Data Scientist) From Subsurface Potential to System-Level Reality: Assessing the Strategic Role of Geologic Hydrogen in a Net-Zero Energy System This project will assess whether geologic hydrogen, a naturally formed gas found underground, can become a practical low-carbon fuel for industry and transportation.

The researchers will combine maps of possible hydrogen deposits with data on pipelines, drilling capacity, skilled workers, industrial users, policy rules, and seismic risk. They will also build computer models to test how hydrogen could be produced from deep rock under different operating conditions. The project will review key factors that affect cost, safety, gas cleanup, emissions, and environmental value.

Its results will identify the regions most ready for responsible early testing and will give policymakers, companies, and researchers clear guidance on where geologic hydrogen may help cut emissions in hard-to-electrify sectors.

Cornell: Chloé Arson (Cornell Duffield Engineering/Earth and Atmospheric Sciences) Clean Air Task Force (CATF): Amy Ouyang (U.S. Associate, Hydrogen) A Roadmap for Overcoming Barriers and Accelerating Conservation Agriculture at Scale This interdisciplinary research project will investigate how artificial intelligence can transform conservation agriculture technical assistance for farmers.

The research team will collaborate with the Keystone Policy Center to develop innovative solutions that address the current shortage of experienced conservation advisors and fragmented support systems. Researchers will explore how AI tools can complement existing technical assistance programs and make conservation practices more accessible to farmers nationwide.

The project will expand beyond creating a white paper to map emerging technologies and identify promising pilot programs. The team will analyze how AI can streamline bureaucratic processes, improve data infrastructure, and create more efficient delivery models for conservation support.

The research will focus on developing concrete solutions that funders and organizations can implement to better serve farmers’ conservation goals and improve agricultural sustainability outcomes.

Cornell: Louis Longchamps (Cornell CALS / School of Integrative Plant Science / Soil and Crop Sciences) Partner: Keystone Policy Center Leveraging AI and Forecast Models for Anticipatory Action Response Analysis To Reduce Acute Child Malnutrition Through this collaboration between Cornell Atkinson and the Cornell Joan Klein Jacobs Center for Precision Nutrition and Health , this project addresses acute child malnutrition as a climate-sensitive threat by bridging the gap between advanced forecasting and effective humanitarian response.

Building on machine-learning models that predict malnutrition risk months in advance, the project will design the scientific and technical foundations of an AI-enabled response analysis system. The system will integrate climate-informed forecasts with curated evidence on nutrition, cost-effectiveness, and operational feasibility to guide anticipatory action.

Seed funding will support a Nairobi-based stakeholder workshop to define priority use cases, evidence requirements, system architecture, and safeguards, enabling future climate-resilient, timely, and cost-effective responses in high-risk settings across Kenya’s arid regions globally.

Cornell: Chris Barrett (Dyson School), Aditya Vashistha (Cornell Bowers), Julia Finkelstein (Human Ecology/Nutritional Sciences), Elizabeth Tennant (Dyson School) International Food Policy Research Institute (IFPRI): Rebecca Brander (Nairobi) Precision Nutrition Under Climate Change: An AI-Driven Framework for Household Vulnerability and Climate Resilience Through this collaboration between Cornell Atkinson and the Cornell Joan Klein Jacobs Center for Precision Nutrition and Health , researchers will develop an AI-driven precision nutrition framework to understand how climate shocks disrupt food security and health at the household level.

By integrating longitudinal data from the Panel Study of Income Dynamics Child Development Supplement with linked family socioeconomic, cultural, activity, health, and rare genetic information, the study captures intergenerational and heterogeneous vulnerability. These data are combined with NOAA climate disaster exposure and analyzed using causal machine learning to estimate differential impacts across households.

Counterfactual simulations of climate risks and policy responses will inform targeted, climate-resilient nutrition policies and strengthen future external funding applications. Cornell: Harry M. Kaiser (Dyson School) U.

Kentucky: Yuqing Zheng (Agricultural Economics) Isotopic Constraints on In Situ Carbonate Precipitation and the Control on Potential Enhanced Weathering Fluxes in an Upper Mississippi Watershed Enhanced rock weathering (EW) is proposed as a scalable carbon dioxide removal strategy, yet uncertainty remains regarding the fate of weathering-derived alkalinity within river networks.

In agricultural watersheds developed in sedimentary basins, secondary carbonate precipitation can remove alkalinity and return CO₂ to the atmosphere, reducing net CO₂ removal efficiency. This project will apply calcium and strontium stable isotopes to empirically quantify carbonate precipitation and alkalinity loss in the Sangamon River–Lake Decatur system.

Integrating isotope data with solute chemistry, alkalinity measurements, and high-frequency monitoring, this proof-of-concept study will provide data-driven constraints on carbonate “leakage” and inform robust measurement, monitoring, reporting, and verification of EW CO₂ removal.

Cornell: Louis Derry (Cornell Duffield Engineering / Earth and Atmospheric Sciences) EDF: Emily Oldfield (Agricultural Soil Carbon Scientist) Identifying Pathways to Reduce Absolute Methane Emissions and Emission Intensity From Smallholder Dairies in Maharashtra Significant investments have been made to reduce methane emissions from India’s dairy sector by incentivizing adoption of productivity-enhancing practices.

However, efficiency gains often generate environmental rebound effects, whereby absolute emissions increase due to expanded production and consumption. This proposal augments methane and animal performance measurements from ongoing methane mitigation efforts in Maharashtra, India, with socioeconomic data to model decision-mediated relationships between efficiency, production, and consumption in the dairy sector.

We test whether enhanced productivity reduces emissions and identify conditions under which profitability becomes a driver of environmental rebound effects. This project identifies when and how efficiency-based mitigation can reduce emissions without triggering environmental rebound effects driven by household decision-making.

Cornell: Jasmine Dillon (Cornell CALS / Animal Science) EDF: Abhinav Gaurav (Lead Advisor, Sustainable Dairy) An Intelligent Natural Language Processing Pipeline for Public Procurement Data: Enabling Predictive Policy Analysis This project addresses a critical bottleneck in evidence-based food policy: the severe fragmentation and inconsistency of public procurement data.

We propose to develop and validate an open-source, intelligent data-cleaning pipeline that uses AI to automate the transformation of raw, unstructured bid data into a unified, analysis-ready resource. To demonstrate its utility, we will conduct a proof-of-concept case study, applying an econometric model to the cleansed data to derive initial insights into bidding dynamics.

This foundational infrastructure will directly unlock timely, rigorous analysis of values-based procurement policies, empowering municipalities to design strategies that effectively support local economies, disadvantaged vendors, and environmental goals.

Cornell: Houtian (Frank) Ge (Cornell SC Johnson College of Business / Dyson School) EDF: Daniel Kaiser (Director of Agriculture Innovation, Climate-Smart Agriculture) Clean Energy, Stable Climate, Thriving Communities: A Systematic Review and Case-Based Models for Achieving Equitable, Durable Environmental Progress EDF and Cornell’s Center for Conservation Social Sciences will conduct a project that synthesizes research on inclusive and equitable technology, policy, and market-based approaches to climate and energy transitions.

The team will translate key findings into practical criteria and actions for organizations like EDF to advance effective, inclusive and durable climate interventions in U.S. and global contexts.

We will publish the results, create case studies, share the findings, and integrate the criteria into EDF’s planning, training, and accountability processes, including the new Planning, Monitoring, Evaluation, and Learning framework; annual Environmental and Climate Justice Intensive training; and the Environmental Justice Principles that guide EDF’s work.

Cornell: Reem Hajjar (Cornell CALS / Ashley School of Global Development and the Environment / Natural Resources and the Environment Section) EDF: Allison Cobb (Associate Vice President, Equity and Justice) Methane Emitting Infrastructure and Activity Mapping This project aims to map methane-emitting infrastructure and activity across China using two key approaches: high-resolution satellite imagery and machine learning to identify methane-emitting infrastructure on the ground; and publicly available data sources (e.g., peer-reviewed studies, government yearbooks) and web scraping to extract methane-related activity data.

Our goal is to create a comprehensive geospatial dataset of methane emissions sources, including the oil and gas supply chain, coal mines, wastewater treatment facilities, landfills, dairy farms, rice paddies, and wetlands. This work is critical for measurement-based methane source attribution, emissions tracking, and ultimately for supporting the development of effective methane mitigation policies.

Cornell: Bharath Hariharan (Cornell Bowers Computing and Information Science / Computer Science) EDF: Donglai Xie (Senior Scientist II, China & Canada Methane); Yuyan Cui (Methane Scientist) Electricity Rate Design and Heat Electrification Electrification of space heating is central to achieving deep decarbonization targets, but its success depends on how electricity is priced at the retail level.

While subsidies reduce upfront barriers to heat pump adoption, electricity rates determine operating costs, distributional impacts, and incentives for load flexibility. This project develops and applies a comprehensive modeling framework to evaluate how alternative residential electricity rate designs affect heat pump economics, adoption patterns, and system-level outcomes under evolving load shapes.

The results will support evidence-based policy advocacy for innovative rate designs that make electrification affordable, equitable, and beneficial to the electric grid, with methods applicable across jurisdictions.

Cornell: Jacob Mays (Cornell Duffield Engineering / Civil and Environmental Engineering) EDF: Erin Murphy (Director & Sr. Attorney, Clean Air & Energy Markets); Magdalen Sullivan (Attorney, Energy Markets & Utility Regulation) Open-path Fourier Transform Infrared Spectroscopy for Continuous Monitoring of Ammonia and Greenhouse Gases From Manure Systems (EDF) Manure management processes at dairy farms produce about 15% of all ammonia emissions in the U.S. – a major source of greenhouse gases.

Open-path Fourier Transform Infrared Spectroscopy (OP‑FTIR) systems are currently the only tools that can continuously measure multiple gases from entire manure systems. USDA Agricultural Research Service will provide Cornell with two OP‑FTIR systems for more than three years. This will allow researchers to collect much‑needed baseline data on ammonia and greenhouse gas emissions at the Cornell Dairy Research and Education Center.

These data are essential for improving models, testing emission‑reduction technologies, and supporting policies and incentives that help farms reduce emissions.

Cornell: Jason Oliver (Cornell CALS / Animal Science) EDF: Joe Rudek (Lead Senior Scientist) Bridging Economics and Climate to Build a Durable Case for Mitigating Hydrogen Emissions The project will provide the first-ever quantification of the social cost of hydrogen to inform hydrogen-industry best practices, regulations, and energy policy.

We will estimate the cost by integrating the H2 cycle and impacts on other greenhouse gases into the FaIR simple climate model. After calibrating this updated model, we will estimate the cost and develop an understanding of the environmental impacts of emitting H2 by itself and along with other GHGs.

We will use this estimate to provide a monetary estimate of the environmental harms from existing H2 supply chain emissions (tracked by EDF), facilitating cost-benefit analyses of H2 abatement options.

Cornell: Vivek Srikrishnan (Cornell CALS / Biological and Environmental Engineering) EDF: Nichole Saunders (Senior Director and Senior Attorney, Energy Transition), Tianyi Sun (Senior Climate Scientist) Towards Battery Circularity: Blockchain-Enabled Semantic Traceability and Incentive Design for EV Battery Recycling Millions of electric vehicle batteries will soon reach end of life as early-generation fleets retire, posing resource recovery challenges and toxicological risks.

Current recycling systems suffer from fragmented data, opaque provenance, and misaligned incentives. We propose a Blockchain-enabled Lithium-ion Battery Circularity System (LiBchain) integrating a layered access control and a Resource–Event–Agent (REA)-based traceability schema to standardize life cycle data, including chemical safety attributes.

A tokenized pricing mechanism will convert verified state-of-health, recoverable mineral content, and toxicity profiles into economic signals to incentivize compliant recycling. The project will ensure that research outcomes inform adoption pathways, support regulatory frameworks, and boost educational resources for a circular battery economy. Cornell: Charlle Sy (Cornell Duffield Engineering / Systems Engineering), H.

Oliver Gao (Cornell Duffield Engineering / Civil and Environmental Engineering) EDF: Maria Doa (Senior Director, Chemicals Policy); Abhinand Krishnashankar (Manager, Economics and Policy) The Half Ocean Conservation Initiative: Conserving the Hidden Depths of the World’s Ocean via a 3-D Biodiversity Assessment for the Mesopelagic Realm The ocean’s mesopelagic zone provides critical global climate and ecosystem functions but is neglected in most conservation frameworks.

New international ocean policy developments provide a timely window to protect mesopelagic organisms, but we need novel tools to translate the 3-D structure and linkages of mesopelagic communities to operational spatial management advice. We will leverage a global high-resolution marine species distribution model to identify priority areas for mesopelagic protection.

Based on these outcomes, we will incorporate mesopelagic priority areas into ongoing high seas protected area proposals, and develop guidance for incorporating 3-D mesopelagic ecosystems and functions into international and national biodiversity conservation commitments. and stabilizing the climate.

Cornell: Gary Tabor (Cornell CALS / Ashley School of Global Development and the Environment / Natural Resources and the Environment Section) EDF: Julia Mason (Social-ecological Systems Scientist) AI-Enhanced Differentiable Computational Fluid Dynamics (CFD) for Urban Airflow Modeling and Pollution Source Inference Urban air pollution can vary dramatically from one block to the next, but today’s tools either operate at kilometer scales or are so computationally expensive they cannot be used routinely for source identification.

We propose an AI-enhanced, differentiable “neural-CFD” framework that fuses urban airflow physics with dense sensor observations to infer local pollution sources with quantified uncertainty. Cornell will build a new, fast modeling approach that combines GPU-accelerated simulation with physics-informed generative AI.

EDF will guide use cases, provide dense sensor datasets, and ensure alignment with Air Tracker and Healthy Communities priorities. This project will give communities and local governments a practical way to identify the most likely sources of neighborhood-scale pollution.

Cornell: Jian-Xun Wang (Cornell Duffield Engineering / Mechanical and Aerospace Engineering) Environmental Defense Fund: Tammy Thompson (Senior Air Quality Scientist) Designing a Curtailment Credit Market: Leveraging Data Center Development to Incentivize Grid-Wide Decarbonization and Affordability The project aims to develop and test a novel mechanism, named Curtailment Credit Market (CCM), that leverages AI data centers’ willingness to pay for uninterrupted power to unlock grid-wide demand flexibility.

This willingness to pay is driven by the exceptionally high value of computation. Under CCM, when grid operators issue curtailment instructions, data centers can purchase tradeable credits from flexible loads that reduce consumption on their behalf. This transfers capital from high-profit tech operators to ratepayers while activating underutilized flexibility.

Using network-constrained simulations and industry collaboration, we will test how this market mechanism can achieve simultaneous decarbonization and affordability goals while addressing growing AI data center power demand.

Cornell: Max Zhang (Cornell Duffield Engineering / Mechanical and Aerospace Engineering) EDF: Thomas Brindle (Director, Legislative & Regulatory Analysis, U.S. Region) Managing Ground-Nesting Bee Aggregations for Agriculture in North America This project unites community science, ecological research, and applied management to study, protect, and enhance ground-nesting bee aggregations within agricultural landscapes.

Researchers from Cornell and The Nature Conservancy will document robust nesting aggregations of ground nesting bees, identify the soil and landscape factors driving nesting success, and develop evidence-based best management practices to sustain, restore, and enhance these vital habitats on and around working farms.

By integrating field data with geospatial modeling, they will build the first U.S. framework for incorporating ground-nesting bee conservation into agricultural planning. Ultimately, this project will connect pollinator habitat with on-farm decision-making, offering farmers practical, evidence-driven strategies to support native bees while strengthening the resilience and sustainability of agricultural systems.

Cornell: Bryan Danforth (Cornell CALS, Entomology) TNC: Lesley Atwood (Agriculture and Climate Scientist) Evaluating the Effects of Pesticide Reductions and Restrictions on Biodiversity As populations of birds and butterflies continue to plummet across North America, a growing body of evidence points to pesticides as one important driver.

Though multiple incentives to restrict or reduce the use of pesticides have been implemented from local to state levels, outcomes for biodiversity remain poorly tracked.

Researchers from Cornell and The Nature Conservancy will (1) evaluate the effectiveness of pesticide restrictions and mitigation strategies, (2) identify which approaches and scales of implementation can best deliver positive outcomes for biodiversity, and (3) work with partners to develop outreach materials for municipalities, state agencies, input companies, and decision-makers.

Cornell: Laura Melissa Guzman (Cornell CALS/Entomology), Catherine Kling (Dyson School of Applied Economics and Management), and Amanda Rodewald (Cornell CALS/Ashley School of Global Development and the Environment; Cornell Lab of Ornithology) TNC: Kris Johnson (Director of Agriculture, North America) Modeling and Validating Restoration Site Priorities Based on Population Connectivity Coastal marine environments have suffered from historical overfishing, eutrophication and other pollution.

Researchers from Cornell and The Nature Conservancy seek to restore and protect these ecosystems and their services by developing spatially explicit approaches to predict ecosystem-scale processes. Restoration often focuses on a few species with an outsized foundational role in building habitat that supports whole communities.

In the case of oysters and other bivalves, their filter-feeding also provides water clarification and nutrient cycling ecosystem services, helping to reduce coastal eutrophication.

Few other foundational species pack as much ecosystem punch as native eastern oysters, as well as important One Health links: the growing US oyster aquaculture industry, a coastal economic engine, contributes ecosystem services described above, generates an eco-friendly dietary protein, and is highly regulated for food safety.

Cornell: Matthew Hare (Cornell CALS/Ashley School of Global Development and the Environment) TNC: Boze Hancock (Senior Marine Habitat Restoration Scientist), Carl Lobue (NY Ocean Programs Director), Marta Ribera (Spatial Ecologist) Smart Flow Sensors For Smart Stormwater Management Climate change and growing urbanization are intensifying pressures on water resources. Urban watershed runoff leads to pollution and increased flood risk.

The Nature Conservancy’s Brightstorm project addresses these challenges by implementing Digital Water Solutions (DWS), automating stormwater infrastructure operation. However, existing flow monitoring technologies that they rely on require physical water contact, are expensive and labor-intensive, and need specialized expertise and frequent calibration visits.

Cornell and TNC researchers will develop a non-contact, image-based system to gauge surface water flow in small waterways, including natural and engineered channels. They will utilize infrared and visible-light images of the flowing water surface to calculate flow velocity and discharge, building on previous Cornell work using small, low-cost cameras.

Unlike existing technologies, this system minimizes disruption at measurement locations, greatly expanding deployment possibilities, particularly on privately owned land. This will enable the expansion of DWS sites and flow gauging at other locations.

Cornell: Seth A Schweitzer (Cornell Duffield Engineering/Civil and Environmental Engineering) and Todd Cowen (Cornell Duffield Engineering/Civil and Environmental Engineering) TNC: Matthew Rea (Director of Water Technology) and Craig Holland (Senior Director of Investments) No Bull: Understanding Real and Perceived Barriers to Scaling Cattlevoltaics ‘Cattlevoltaics’ combines solar energy production with cattle grazing beneath photovoltaic arrays.

Social research specific to cattlevoltaics and grazing agrivoltaic systems is sparse. However, to scale up cattlevoltaics projects, real and perceived barriers to deploying cattlevoltaics within the agricultural community and solar industry must be identified.

This mixed-methods social science project from Cornell and The Nature Conservancy researchers will feature in-person workshops with agricultural producers and solar developers hosted in different U.S. regions. Qualitative and quantitative data collection and analysis will capture key beliefs and attitudes, perceived opportunities and barriers, and interest level in cattlevoltaics.

The research will build a deeper understanding of how different stakeholders approach cattlevoltaics, help foster ideas to solve cattlevoltaic project challenges, and pave the way to more quickly achieve conservation and socioeconomic benefits from projects at scale.

Cornell: Richard Stedman and Kathryn Walsh (both Cornell CALS/Ashley School of Global Development and the Environment) TNC: Morgan Higman (Climate Strategy Director) and Jakob Lindaas (Director of Climate Action, TNC Colorado) Strategic Advisory Support and Decision Framework Development of Natural Climate Solutions This project will help decision-makers choose Natural Climate Solutions (NCS) that can cut greenhouse gases from farms, forests, and other working lands.

It will focus on practices in cool, moist regions, such as adding trees to working lands and improving manure management, while considering carbon dioxide, methane, and nitrous oxide together. The researchers will use a decision matrix to compare each option by benefits, ease of measurement, cost, practicality, and time needed for lasting results.

They will also advise public, private, and nonprofit partners on goals, monitoring, policy, and investment choices. The project will produce clear guidance, presentations, and public materials to support smarter climate action and more reliable long-term results.

Cornell: Jenifer Wightman , Peter Woodbury (both Cornell CALS/School of Integrative Plant Science/Soil and Crop Sciences Section) Tracking RMI’s CDR Applied Innovation Roadmap Implementation In the first phase of this project, Cornell University researchers will create an interactive digital dashboard to track progress in direct air capture technology development.

The team will work with the Rocky Mountain Institute and the Direct Air Capture Coalition to monitor key milestones and achievements in Carbon Dioxide Removal (CDR) from the atmosphere. Scientists will update the dashboard regularly with new data about technological advances, funding, and policy changes affecting direct air capture systems.

In the project’s second phase, the team will expand the dashboard with analyses of all other types of CDR covered in the roadmap and complete a status review of global academic research on unlocking the major research barriers within each approach.

By bringing together information from industry, environmental groups, and universities, researchers will help investors and policymakers make better decisions about supporting climate solutions. This project will serve as a model for tracking other CDR technologies in the future.

Cornell: Phillip Milner (Arts and Sciences/Chemistry and Chemical Biology), Tobias Hanrath (Cornell Duffield Engineering/Chemical and Biomolecular Engineering) External Partners: Rocky Mountain Institute , Direct Air Capture Coalition Beyond Soil: Towards a Full GHG Accounting for Regenerative Agriculture Researchers will study how regenerative farming practices affect greenhouse gas emissions and crop production across the United States.

The team will use computer models to predict how different farming methods impact soil carbon storage, gas emissions, and food yields over the next 100 years. Scientists will examine various techniques, including no-till farming, cover crops, and crop rotations for major crops like corn, soybeans, and wheat.

By mapping results across different regions, researchers will identify which sustainable farming practices work best in specific locations. This study will help farmers choose methods that both reduce climate change impacts and maintain strong crop production for food security.

Cornell: Dominic Woolf (Cornell CALS/School of Integrative Plant Science/Soil and Crop Sciences) Environmental Defense Fund (EDF): Alison Eagle (Senior Scientist, Climate-Smart Agriculture), Doria Gordon (Lead Senior Scientist II), Emily Oldfield (Agricultural Soil Carbon Scientist), Jocelyn Lavallee (Agricultural Soil Carbon Scientist) Transition Finance for Regenerative Agriculture Systems Cornell researchers and staff launched the Transition Financing for Regenerative Agriculture Systems project in 2024.

The effort was originally funded by the Great Lakes Protection Fund and received additional gift funding in 2024 from Cargill via AgOutcomes. The project supports research and development of financial solutions and roadmaps that would lead to demonstration projects in the Great Lakes.

The team is currently piloting the New York Outcomes Fund and exploring further innovations that could accelerate regenerative agriculture adoption in the Great Lakes region. To strengthen the team this project engages Cornell Cooperative Extension team members through the end of April 2025.

Cornell: John Tobin (SC Johnson College of Business/Dyson School), Alan Martinez (Cornell Atkinson/Strategic Partnerships, Climate and Nature Finance Lead) Cornell Cooperative Extension (CCE): Jarmila Haseler (Monroe County, Agriculture and Food System Educator), Kitty O’Neil (CCE North Country Regional Agriculture, Team Lead & Regional Field Crops and Soils Specialist) Bridging the Gaps: Comparative Case Studies of SuperHot Rock (SHR) Geothermal Demonstration Sites Across Diverse Geodynamic Settings The researchers will investigate SuperHot Rock (SHR) geothermal resources across multiple countries to advance clean energy development.

They will study demonstration sites in the United States, Iceland, New Zealand, Japan, and Canada, comparing their geological features and extraction technologies. The team will also examine sites in Italy, Mexico, and Kenya to validate their findings. By analyzing similarities and differences between locations, scientists will identify the best practices for developing these extremely hot underground resources.

This collaboration with Clean Air Task Force (CATF) will help reduce costs and risks associated with exploring and extracting geothermal energy from SuperHot Rock formations, ultimately supporting cleaner energy solutions worldwide.

This effort follows on a successful 2024 project with CATF, which performed a literature review to determine the characteristics of potential SHR sites and technologies needed to constrain these properties across a range of geologic settings.

Cornell: Seth Avram Saltiel (Cornell Duffield Engineering/Earth & Atmospheric Sciences) Clean Air Task Force (CATF): Angela Seligman (Senior Geoscientist), Terra Rogers (Superhot Rock Geothermal Program Director) Analysis of Carbon Dioxide Removal Policy Impact Pathways Cornell researchers study how to grow carbon removal technologies across the United States.

They will work with the Clean Air Task Force to find the best policies that can help the country remove one gigaton of carbon dioxide each year by 2050. The team will use computer models to test different approaches, including planting trees, capturing carbon from farms, and using machines that pull carbon from the air. They will figure out which government policies work best while costing taxpayers the least money.

The scientists will examine options like government funding, research support, and business incentives to make these technologies more popular. Their findings will help lawmakers create better climate change solutions and build support for carbon removal programs.

Cornell: Fengqi You (Cornell Duffield Engineering / Chemical and Biomolecular Engineering) Clean Air Task Force (CATF): John Thompson (Technology and Markets Director), Darryle Ulma (Associate Director, Industrial Innovation) Sorghum for Sustainability?

Enabling Water Savings From Crop Switching in Kansas The research team will address water scarcity challenges in Kansas, a major agricultural region where farming contributes $57 billion annually and employs over 140,000 people. The project examines how farmers can switch from growing corn to sorghum, a crop that requires significantly less water, to help conserve this precious resource during increasingly severe droughts.

Since corn typically generates higher profits than sorghum, the researcher is developing market incentives and financial support systems that would make crop switching economically viable for farmers.

Working directly with farming communities and agricultural supply chain partners, the team aims to create practical solutions that will help Kansas maintain its agricultural productivity while adapting to climate change and water limitations. The ultimate goal is to demonstrate that water-efficient crops like sorghum can provide both environmental benefits and economic stability for rural communities facing mounting water stress.

Cornell: Chuan Liao (Cornell CALS / Ashley School of Global Development and the Environment / Global Development) Environmental Defense Fund (EDF): Alison Eagle (Senior Scientist, Climate-Smart Agriculture), Leah Beaulac (Senior Manager, Climate Resilient Water Systems) Harnessing the Power of Electrified Transportation Systems as Virtual Power Plants Through AI-driven Learning, Optimization, and Control Energy storage is critical to decarbonizing the power grid, but high capital costs have limited large-scale deployment.

The rapid adoption of plug-in electric vehicles (EVs) offers a transformative alternative: using EV batteries as distributed, mobile energy storage. Through bidirectional charging, millions of EVs can collectively function as a massive virtual battery—absorbing surplus renewable energy and supplying power during shortages. This project leverages artificial intelligence to enable the real-time coordination of EV charging at scale.

By aligning EV flexibility with grid needs and renewable supply, the research enhances