Georgia Tech researchers have developed a mathematical formula to predict the size of lakes that form on melting ice sheets — discovering their depth and span are linked to the topography of the ice sheet itself. 

The team leveraged physics, model simulations, and satellite imagery to develop simple mathematical equations that can easily be integrated into existing climate models. It’s a first-of-it’s-kind tool that is already improving climate models.

“Melt lakes play an important role in ice sheet stability, but previously, there were no constraints on what we would expect their maximum size to be in Antarctica,” says study lead Danielle Grau, a Ph.D. student in the School of Earth and Atmospheric Sciences. “I was intrigued by the idea of quantifying how much of a role we could expect them to play in the future.”

The paper, “Predicting mean depth and area fraction of Antarctic supraglacial melt lakes with physics-based parameterizations,” was published in Nature Communications. In addition to Grau, the research team includes School of Earth and Atmospheric Sciences Professor Alexander Robel, who is Grau’s advisor, and Azeez Hussain (PHYS 2025).

Their predictions show that the majority of these lakes will be less than a meter deep and span up to 40% of the ice sheet surface area.

“Many models don’t include any data about lakes on the surface of ice sheets, while others simulate these melt lakes growing until the ice collapses,” Robel says. “Our results show that the reality is somewhere in between — and that the maximum size of these lakes can be predicted using these new equations. This gives us real, concrete numbers to use in climate models.”

From summer project to satellite discovery 

Grau first started working on the project as an undergraduate student when she applied for a Summer Research Experiences for Undergraduates program hosted by the School of Earth and Atmospheric Sciences.

Inspired by terrestrial lake research, Grau and Robel investigated the “self-affinity” of the Antarctic ice sheet — a property associated with surface roughness across various scales. For example, a landscape like Badlands National Park, with many rolling hills of a wide range of sizes, would have a different self-affinity than a flat prairie with three large volcanoes.

“A previous study had used this property to predict the size of terrestrial lakes and ponds, and we were curious if we could use a similar approach for supraglacial lakes in Antarctica,” Grau says. “Establishing that the Antarctic ice sheet also has this property was the first step in pursuing this research in more depth.” 

The mathematics of melt

Grau continued the investigation as a Ph.D. student in Robel’s lab. Together, they unraveled the physics of how meltwater moves across the ice surface, designing a ‘glacier in a computer’ that mimics meltwater accumulation and movement across various topographies.

“We designed an algorithm and integrated it into a model that the GT Ice & Climate Group has used in the past,” Grau says. “From that, we were able to see how lakes would form on different surfaces across thousands of scenarios. This was the foundation for the mathematical equations I developed, which can predict the lake depth and lake surface area based on the self-affinity property.”

To check their results, Grau enlisted the help of Hussain — then an undergraduate in the School of Physics — to examine satellite data from the Landsat satellite program (which captures detailed photography of the Earth’s surface from space) to measure existing supraglacial lakes and surface topography. 

“It was exciting to see how our predictions lined up with what we were seeing in the satellite imagery,” Robel explains. “This shows that our solution is a concrete avenue for climate models to realistically incorporate supraglacial lakes.”

Grau is already working to incorporate the team’s equations into an atmospheric model used by NASA in addition to an ice sheet model developed by the NASA Jet Propulsion Laboratory and Dartmouth College. 

“By turning complicated models and satellite data into simple predictive equations, we’re giving climate models a new lens to see the future,” she says. “It’s a small piece of the puzzle,  but one that helps us understand how ice sheets respond to a warming world.”

 

Funding: NASA Modeling, Analysis, and Prediction Program

DOI: https://doi.org/10.1038/s41467-025-61798-8 

Researchers at Georgia Tech have analyzed the seasonal differences of sulfate aerosols — a major pollutant in the United States — to examine the long-term impact from sulfur dioxide (SO₂) emission reductions since the enactment of the Clean Air Act amendments in 1990. 

School of Earth and Atmospheric Sciences Professor Yuhang Wang and his team studied the factors affecting SO₂ and sulfate concentrations during winter and summer in the “Rust Belt” — from New York through the Midwest — and the Southeast regions of the U.S. over two decades (2004 to 2023). Supported by the National Science Foundation and Georgia Tech’s Brook Byers Institute for Sustainable Systems, the team also developed an ensemble machine learning approach to project seasonal patterns until 2050. 

“Power plants, particularly those burning coal and oil, are a major source of SO₂ emissions in these regions,” says Wang, who co-authored, with Ph.D. students Fanghe Zhao and Shengjun Xi, the study recently published in Environmental Science & Technology Letters. 

Seasonal differences in atmospheric chemistry 

In the U.S., the chemistry in the atmosphere varies among the seasons. During summer, solar radiation from ample sunlight activates oxidant reactions that produce hydrogen peroxide (H₂O₂) in the atmosphere. The supply of H₂O₂ is determined by the amount of emitted air pollution, and once in the atmosphere, H₂O₂ can oxidize SO₂ quickly into sulfate aerosols in the aqueous phase. 

Sulfate aerosols from the oxidation of SO₂ contribute to the formation of particulate matter less than 2.5 micrometers in diameter (PM2.5). Particulate sulfate poses significant environmental and public health risks, including air pollution, acid rain, and circulatory and respiratory issues. 

“The supply of H₂O₂ in summer is eight times greater than in winter — a huge difference — which means sulfate concentrations are generally higher in summer and a reduction in SO₂ emissions leads to a proportional decrease in sulfate concentrations,” explains Wang. “When SO₂ emissions exceed the available supply of H₂O₂ in winter, the reduction in sulfate concentrations can be much smaller because of a ‘chemical damping’ effect that causes sulfate levels to decline more slowly than SO₂ emissions.” 

Narrowing the disparities between seasonal sulfate levels 

The study’s two-decade observations revealed distinct patterns in the reduction of SO₂ emissions and sulfate concentrations during winter and summer. 

While SO₂ emissions significantly decreased in both seasons­ over time — primarily from the Clean Air Act and more power plants transitioning from coal to natural gas — the reduction of sulfate concentrations initially showed large seasonal differences. However, over the past decade, the disparity between winter and summer sulfate levels narrowed as SO₂ emissions decreased.

According to Wang, the seasonal disparity of sulfate was caused by changing chemical regimes in winter over time. Although the lower supply of H₂O₂ remained stable in winter, SO₂ wintertime emissions were higher from 2004 to 2013, then dropped below the level of H₂O₂ after 2013 — reaching parity with the levels of reduced SO₂ emissions in the summer. 

“When you have this complexity of atmospheric chemistry, there is a non-linear effect in winter — as SO₂ emissions decreased, sulfate aerosol production efficiency increased until 2013, then flattened as of today. The reduction in sulfate aerosols initially lagged behind the decrease in SO₂ emissions but eventually caught up as a result of sustained air quality control efforts,” says Wang. “Conversely, there is a simple, linear effect in summer — the more SO₂ emissions, the more sulfate aerosols in the atmosphere — and if you reduce one, the other is reduced by the same proportion.”

Decades-long full impact 

From now until 2050, the researchers’ machine learning projections indicate a continuing decrease of winter and summer sulfate levels, which are currently around 20 percent, as SO₂ emission controls achieve comparable efficacy across the seasons. 

“We’re now seeing the full impact from the Clean Air Act,” concludes Wang, “and the nation’s sustained effort in pollution reduction is key to improving air quality and health outcomes.”

Scientists at Georgia Tech have teamed up with researchers at Johns Hopkins Medicine and Columbia University to better understand how certain types of air pollution increase the risk of developing dementia. 

Their findings, published this month in the journal Science, help explain how small particle pollution — think industrial emissions and car exhaust, wildfires and burning wood for heat and cooking — can lead to Lewy body dementia, a devastating disease that causes toxic clumps of protein to destroy nerve cells in the brain. 

"Epidemiological studies have suggested a strong link between air pollution and dementia, but what sets this study apart is that we also provide a convincing biological mechanism,” says Pengfei Liu, assistant professor School of Earth and Atmospheric Sciences and one of the study’s co-authors. “This collaborative work shows that fine particulate matter from different geographic regions consistently triggers a specific stain of misfolded protein that drives Lewy body dementia." 

The work has “profound implications” for helping scientists and policy makers better understand measures to prevent this type of dementia, which is among the most common forms of the disease and affects millions of people around the world.

Along with Liu, the research team from Georgia Tech includes Rodney Weber, professor in the School of Earth and Atmospheric Sciences; Minhan Park, a postdoctoral research fellow co-advised by Liu and Weber; Bin Bai, a graduate student in Liu’s lab; and Ma Cristine Faye Denna, a graduate student in Weber’s lab.

“Figuring out how exposure to atmospheric aerosols might be linked to dementia, and what mechanisms are involved, is a complex and challenging problem — and as this study shows, it takes a large team with many different areas of expertise,” Weber adds.

Learn more:

• Science: Lewy body dementia promotion by air pollutants
• Johns Hopkins Medicine newsroom
• Columbia University newsroom
• Press: The Guardian

 

Between a third and half of all soil carbon on Earth is stored in peatlands, says Tom and Marie Patton Distinguished Professor Joel Kostka. These wetlands — formed from layers and layers of decaying plant matter — span from the Arctic to the tropics, supporting biodiversity and regulating global climate.

“Peatlands are essential carbon stores, but as temperatures warm, this carbon is in danger of being released as carbon dioxide and methane,” says Kostka, who is also the associate chair for Research in the School of Biological Sciences and the director of Georgia Tech for Georgia’s Tomorrow. Understanding the ratio of carbon dioxide to methane is critical, he adds, because while both are greenhouse gasses, methane is significantly more potent.

Kostka is the corresponding author of a new study unearthing how and why peatlands are producing carbon dioxide and methane. 

The research, “Northern peatland microbial communities exhibit resistance to warming and acquire electron acceptors from soil organic matter,” was published this summer in Nature Communications, and was led by co-first authors Borja Aldeguer-Riquelme, a postdoctoral research associate in the Environmental Microbial Genomics Laboratory, and Katherine Duchesneau, a Ph.D. student in the School of Biological Sciences.

The study builds on a decade of research at the Oak Ridge National Lab’s Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment, a long-term research project in Minnesota that allows researchers to warm whole sections of wetland from tree top to bog bottom.

“Over the past 10 years, we’ve shown that warming in this large-scale climate experiment increases greenhouse gas production,” Kostka says. “But while warming makes the bog produce more methane, we still observe a lot more CO2 production than methane. In this paper, we take a critical step towards discovering why — and describing the mechanisms that determine which gases are released and in what amounts.”

Methane mystery

The subdued methane production in peatlands has been a long-standing mystery. In water-saturated wetlands, oxygen is scarce, but microbes still need to respire — a type of ‘breathing’ that allows them to produce energy for metabolic function. Without oxygen, microbes use nitrate, sulfate, or metals to respire — still releasing carbon dioxide in the process. However, if these ingredients aren’t present, microbes ‘breathe’ in a way that releases methane.

Since nitrate, sulfate, and metals are relatively rare in peatlands, methane production should be the most likely pathway, but surprisingly, observations show the opposite. “In both fieldwork and lab experiments, peatlands produce much more carbon dioxide than methane,” Kostka explains. “It’s puzzling because the soil conditions should help methane production dominate.”

To solve this mystery, the team leveraged a suite of cutting-edge genetic tools called “omics” —  metagenomics (studying DNA), metatranscriptomics (studying RNA), and metabolomics (a technique used to study the “leftovers” of metabolism), providing a detailed look under the hood of the microbial “engine” that cycles organic matter in wetlands. It also gave a new window into the diversity of soil microbes in wetlands: 80 percent of the organisms identified in the study were new at the genus level.

‘Omics’ innovations

Over the course of several years, the team collected samples from a peatland enclosed in an experimental chamber that was slowly warmed, then analyzed the samples using omics to see how they changed. Initially, they hypothesized that warming the soil would cause microbial communities to change quickly. “Microbes can evolve and grow rapidly,” Kostka says. “But that didn’t happen.”

The DNA-based methods showed that while the microbial communities stayed largely stable, the bog did release more greenhouse gasses as it warmed. To assess the metabolic potential of the microbes, Duchesneau and Aldeguer-Riquelme constructed microbial genomes, investigating how they were decomposing the organic matter in peatlands and cycling carbon.

“We found that microbial activity increases with warming, but the growth response of microbial communities lags behind these changes in physiological or metabolic activity,” Kostka says. He cautions that this doesn’t necessarily mean that wetland communities won’t change as climates warm — just that these shifts might come behind metabolic ones. 

A diversity of discoveries

And the methane? The team believes that microbes may be breaking down organic matter to access the key ingredients for producing carbon dioxide — nitrate, sulfate, and metals — though more research is currently underway to investigate this.

“Doing this type of integrated omics research in soil systems is still incredibly difficult,” Kostka says. The challenge is multifaceted: the research leverages years of experiments, long-term datasets, advanced laboratory techniques, and fieldwork innovations. 

At SPRUCE, experimental chambers are about 1,000 square feet. While it’s an impressive experimental setup, researchers still must be careful: “We need to take soil samples for many years, so if we take too many, there’d be no soil left!” Kostka explains. “Part of our research involves developing better, non-destructive sampling techniques.”

The other challenge lies in what makes these peatlands so unique: it’s very hard to detect small changes because of the sheer diversity of organisms present. “Every time we conduct this type of research, we learn more about these incredible systems,” he says. “There’s always something new.”