As one of the nation’s largest private philanthropic foundations since 1978, the MacArthur Foundation awards fellowships directly to individuals like ASC Director Kaiyu Guan rather than through institutions. Photo by Chris Brown Photography, courtesy of National Center for Supercomputing Applications
Kaiyu Guan, a Levenick endowed professor of natural resources and environmental sciences at the University of Illinois at Urbana-Champaign, has been named a 2026 MacArthur Fellow, commonly known as a “genius grant,” from the John D. and Catherine T. MacArthur Foundation.
According to a statement from the MacArthur Foundation, the fellows are chosen as “talented individuals in a variety of fields who have shown exceptional originality in and dedication to their creative pursuits.”
Satellite observations of average atmospheric ammonia (top) and estimated ammonia movement between the land and air (bottom) across the contiguous United States (Fig. 2 from Li et al., 2026).
URBANA, Ill. – A team of researchers led by the University of Illinois Urbana-Champaign has developed a new method to quantify ammonia pollution across the United States in unprecedented detail. The new study published in Atmospheric Chemistry and Physics details the use of satellite observations to track where emissions are produced, how they change over time, and where they ultimately end up. The findings pinpoint several major agricultural ammonia hotspots across the country and reveal a 15-year rising trend in ammonia flux.
Agriculture is the primary source of atmospheric ammonia, which originates from both livestock operations and fertilizer use. Once in the atmosphere, it contributes to fine particulate air pollution, degrades ecosystems through nitrogen deposition, and can harm human health. Despite its importance, ammonia has been difficult to monitor because emissions vary dramatically across space and time, and ground-based measurements are sparse. The new work provides critical new insights into a largely overlooked but highly impactful form of air pollution tied closely to modern food production.
To address this gap, researchers combined more than a decade of satellite observations from two atmospheric sensors with a novel analytical method to estimate ammonia emissions and deposition across the contiguous United States. The approach allows scientists to move beyond simply observing atmospheric concentrations to directly estimating how much ammonia is being released and where it is being removed from the atmosphere.
The researchers identified five clear and consistent emission hotspots in major agricultural regions, including California’s San Joaquin Valley, the Snake River Valley in Idaho, the Texas Panhandle, the Great Plains, and parts of Pennsylvania and North Carolina. These regions are known for intensive livestock production and fertilizer use, and the satellite data confirms their major role in ammonia emissions.
Additionally, the study determined the fate of those ammonia emissions, revealing that much of it is deposited in nearby forests, grasslands, and wetlands, demonstrating that the gas is rapidly absorbed through deposition near its source rather than becoming chemically transformed higher in the atmosphere. This localized deposition can disrupt ecosystems by overloading them with nitrogen, contributing to soil acidification, water quality issues, and biodiversity loss. These seasonal and daily patterns could also help farmers fine-tune when they apply fertilizer, reducing how much nitrogen is lost to the atmosphere as ammonia.
Another key finding is the strong seasonal pattern in ammonia emissions. Emissions peak during warmer months, when higher temperatures increase volatilization from fertilizers and animal waste. In contrast, winter emissions are significantly lower. By combining data from satellites that pass over the Earth at different times of day, the study also captures previously unseen daily variations in emissions, offering a more complete picture of ammonia dynamics. Senior author Kaiyu Guan, the founding director of the Agroecosystem Sustainability Center and the Levenick Endowed Professor in Agroecosystem Modeling and Sensing, noted “This approach lets researchers move beyond simply estimating ammonia emissions to directly observing them, offering a clearer and more accurate picture than was previously possible.”
The study also highlights the advantages of satellite-based monitoring compared to traditional “bottom-up” emission inventories. While such inventories rely on reported agricultural activity and emission factors, satellite observations provide an independent, observation-based perspective that can capture fine-scale variability and reveal patterns that models may miss. “Satellite data allows us to see both the big picture and the local details,” explained the lead author Zitong Li, a PhD student under Guan’s supervision. “It complements existing approaches and helps reduce uncertainties in emission estimates.”
Importantly, the long-term record suggests that ammonia emissions may be increasing in several regions, likely driven by intensifying agricultural activity.These findings have important implications for environmental policy and air quality management. Because ammonia plays a key role in forming fine particulate pollution, reducing emissions could be a cost-effective strategy for improving air quality. At the same time, better understanding where and when emissions occur can help target mitigation efforts more effectively, particularly in agricultural systems.
As satellite technology and analytical methods continue to improve, researchers expect even more precise and timely monitoring of ammonia and other pollutants. This study represents a significant step toward integrating satellite data into routine environmental monitoring and decision-making. Ultimately, the work underscores the growing importance of combining advanced remote sensing with data-driven modeling to address complex environmental challenges and highlights the need for coordinated strategies to manage the impacts of modern agriculture on air quality and ecosystems.
The study titled “Ammonia emissions and depositions over the contiguous United States derived from IASI and CrIS using the directional derivative approach” is published in Atmospheric Chemistry and Physics (https://doi.org/10.5194/acp-26-703-2026), with support from NASA’s Interdisciplinary Science (IDS) program, USDA NIFA, and NSF.
For more information, contact:
Kaiyu Guan, Levenick Endowed Professor Department of Natural Resources and Environmental Sciences Founding Director, Agroecosystem Sustainability Center University of Illinois Urbana-Champaign kaiyug@illinois.edu
By Lesly Goh
We just concluded an inspiring Big Bets on Rice Methane Convening at the Rockefeller Foundation’s Bellagio Center in Italy, bringing together philanthropies, researchers, farmers’ organizations, development institutions, climate leaders, and private sector agribusiness partners to tackle one of the world’s most underfunded climate opportunities: transforming rice ecosystem in terms of mitigation, adaptation and livelihood.
Rice cultivation generates greenhouse gas emissions comparable to the global aviation sector, while supporting the livelihoods and food security of more than 140 million smallholder farmers across Asia. Yet the sector remains fragmented, with too many pilots and too little coordinated investment. This convening focused on a critical question: How do we move from fragmented efforts to a shared strategy capable of delivering greater impact at scale?
We explored rice transformation through the following interventions:
✅ Research & development for methane reduction ✅ Policy reforms and enabling environments ✅ Farmer-centered, on-the-ground interventions ✅ Innovative finance and incentives to accelerate adoption and scale
For me personally, this was especially meaningful. The seeds for this convening were planted during my 2023 Rockefeller Bellagio Residency, where I began envisioning a multi-stakeholder global rice ecosystem. Over the years, it was encouraging to see leaders from across the rice value chain come together with a shared commitment to move from ideas to action.
Deep gratitude to The Rockefeller Foundation, the dedication of our co-organizers, and the esteemed participants for their leadership, open and constructive dialogue to collaborate on solutions that can benefit both people and the planet.
The opportunity ahead is enormous. Rice methane may be one of the most actionable climate solutions available today—but success will depend on our collective ability to build meaningful partnerships, align catalytic funding, and put farmers at the center of our solution.
On July 7, 2026, Can Tho University’s Faculty of Environment and Natural Resources launched the field trial for SIGMA’s low-emission rice cultivation project in Thạnh An commune. Over three consecutive crop seasons, the project will compare continuous flooding, mid-season drainage, and Alternate Wetting and Drying (AWD) irrigation to measure greenhouse gas emissions and rice yield, building the field dataset needed for a robust MRV system.
The Agroecosystem Sustainability Center, in collaboration with the Levenick Center for a Climate-Smart Circular Bioeconomy, hosted a symposium on April 28th titled The Frontiers of Agricultural Nitrogen: Geopolitics, Industry, Innovation, and Farming Management symposium at the Beckman Institute for Advanced Science and Technology on the University of Illinois Urbana-Champaign campus. The event brought together internationally recognized researchers, policy experts, and UIUC faculty to examine the science, economics, and regulations around nitrogen, a substance which is both essential to modern food production and the source of pressing environmental challenges.
The symposium kicked off with an introduction by Dr. Kaiyu Guan, director of the Agroecosystem Sustainability Center, followed by keynote presentations by two distinguished visitors. Dr. David Kanter (New York University; Chair of the International Nitrogen Initiative) gave a talk titled “Nitrogen Governance in a World at War”, which discussed the growing need for more intelligent policy guidance and consideration when considering the global nitrogen fertilizer economy, and its impacts, in both the short and long term to the development of the field. Dr. Xin Zhang (University of Maryland Center for Environmental Science; Director, NICCEE) delivered a talk on “Decarbonization in a Eutrophic World”. Dr. Zhang described the challenges in attempting to reduce the carbon intensity of agricultural nitrogen,due to its exceptional interconnectedness, while also describing how canny innovation can create opportunities that benefit multiple sectors in their adoption.
Two prominent University of Illinois researchers also shared their expertise on agricultural nitrogen. Dr. Wendy Yang spoke on “New International Initiatives to Advance Nitrogen Sustainability in Agriculture”, highlighting recent projects aimed at improving and advancing global nitrogen cycle data that have received funding from Novo Nordisk and FFAR. These projects form a core component of the aims of the Agricultural Nitrogen Use Efficiency Platform, or AgNUE, which is an international research initiative aimed at enhancing nitrogen management in agriculture . Dr. Angela Kent’s talk, “NSAVE Maize: Building the Future of Bioenergy from the Ground Up“, discussed the reintroduction and breeding of ancient strains of maize with current hybrids to improve nitrogen efficiency by changing soil microbiology. The keynote speakers then took part in a Q & A panel mediated by Dr. Kaiyu Guan.
An afternoon panel discussion on Agricultural Nitrogen Measurement was moderated by Dr. Wendy Yang, including Dr. John Jones (UIUC), Dr. Zhang, and Dr. Bin Peng (UIUC). Discussions centered on improving management processes and collaborating with farmers and land managers to better design innovations and implement science-backed solutions for nitrogen application and use. The need for flexibility in nitrogen use and acquisition was introduced in an increasingly volatile market. Dr. Peng emphasized the value of proactively engaging with younger generations of farmers to better co-manage the trajectory and implications of innovation within the agricultural space.
Looking Ahead
The symposium reflected a growing recognition within the research community that nitrogen is not merely a soil chemistry problem, it poses geopolitical, economic, ecological, and social challenges. The April 28 conversations demonstrated that meaningful progress will require the kind of cross-disciplinary, cross-border, and cross-sector collaboration that events like this help catalyze. With initiatives like AgNUE now underway and UIUC researchers playing leading roles in international nitrogen science, the Agroecology Sustainability Center looks forward to continuing this vital work in the field, in the lab, and at the policy table.
URBANA, Ill. – Predicting how water and nutrients move through agricultural landscapes is essential for protecting water quality, managing fertilizers, and preparing for extreme weather. Yet scientists have long struggled to forecast these dynamics across entire watersheds. Monitoring networks are sparse, and traditional models often struggle to capture the complex interactions among climate, land use, and river systems.
A new study from researchers at the University of Illinois Urbana-Champaign shows that artificial intelligence can significantly improve predictions of both streamflow and nitrogen pollution across agricultural watersheds. The study was recently published in the journal Water Research.
The research team developed a new AI system, HydroGraphNet, that combines machine learning with scientific knowledge of how water and nutrients move through river networks. The method represents a watershed as a connected system of upstream and downstream areas, allowing the model to better capture how water and pollutants move through the landscape.
“Our goal is to bridge the gap between traditional hydrologic models and modern artificial intelligence,” said first author Jie Yang, a researcher in the Agroecosystem Sustainability Center at Illinois. “By embedding scientific knowledge into AI models, we can make predictions that are both more accurate and more consistent with how real watersheds behave.”
Unlike many previous AI models that treat each watershed as a single unit, the new approach can generate daily predictions for individual sub-watersheds across an entire river network. This allows scientists to identify where water and nitrogen pollution originate and how they move downstream.
The Illinois team tested their model in the Upper Sangamon River Basin, a largely agricultural watershed in central Illinois dominated by corn and soybean production. The AI system was trained using both existing monitoring data and results from hydrologic simulations, allowing it to learn patterns from observations while also incorporating scientific understanding of water movement.
The results showed that the new approach substantially improved predictions of both streamflow and nitrogen export, especially in areas with limited monitoring data. The model also revealed clear seasonal patterns in nitrogen losses, with large pulses of nitrogen leaving fields during wet periods when runoff and drainage rapidly carry nutrients into streams.
“Hydrologic systems are inherently connected,” said Bin Peng, a professor of crop sciences at Illinois. “By explicitly representing those connections in an AI framework, we can better understand how upstream conditions influence downstream water quality.”
Beyond improving predictions, the researchers say the approach reflects a broader shift in environmental science. “Artificial intelligence is rapidly transforming Earth system science,” said Kaiyu Guan, founding director of the Agroecosystem Sustainability Center. “By combining physical understanding with AI, we can generate high-resolution predictions of water and nutrient dynamics across large landscapes.”
Such capabilities could help scientists and policymakers design more targeted strategies to reduce nutrient pollution, manage water resources, and adapt agriculture to a changing climate. By providing detailed daily predictions across entire river networks, the new system could support next-generation monitoring and decision tools for sustainable watershed management.
Why this matters: Nitrogen runoff from agricultural landscapes is a major contributor to the Gulf “Dead Zone.” Better information about when and where nitrogen leaves fields could help farmers and policymakers target conservation practices more effectively.
The paper, “Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics,” is published in Water Research [DOI: 10.1016/j.watres.2026.125613]. The research was supported by the U.S. Department of Energy, the National Science Foundation, and the U.S. Department of Agriculture.
For more information, contact:
Bin Peng, Assistant Professor Department of Crop Sciences University of Illinois Urbana-Champaign binpeng@illinois.edu
Jie Yang, PhD Postdoctoral Research Associate Department of Crop Sciences University of Illinois Urbana-Champaign jieyang7@illinois.edu
Kaiyu Guan, Professor Department of Natural Resources and Environmental Sciences University of Illinois Urbana-Champaign kaiyug@illinois.edu
