The existence of Titan’s large seas and smaller lakes was confirmed in 2007, with images taken by NASA’s Cassini spacecraft. Since then, scientists have pored over those and other images for clues to the moon’s mysterious liquid environment.

Now, MIT geologists have studied Titan’s shorelines and shown through simulations that the moon’s large seas have likely been shaped by waves. Until now, scientists have found indirect and conflicting signs of wave activity, based on remote images of Titan’s surface.

The MIT team took a different approach to investigate the presence of waves on Titan, by first modeling the ways in which a lake can erode on Earth. They then applied their modeling to Titan’s seas to determine what form of erosion could have produced the shorelines in Cassini’s images. Waves, they found, were the most likely explanation.

The researchers emphasize that their results are not definitive; to confirm that there are waves on Titan will require direct observations of wave activity on the moon’s surface.

“We can say, based on our results, that if the coastlines of Titan’s seas have eroded, waves are the most likely culprit,” says Taylor Perron, the Cecil and Ida Green Professor of Earth, Atmospheric and Planetary Sciences at MIT. “If we could stand at the edge of one of Titan’s seas, we might see waves of liquid methane and ethane lapping on the shore and crashing on the coasts during storms. And they would be capable of eroding the material that the coast is made of.”

Perron and his colleagues, including first author Rose Palermo, a former MIT-WHOI Joint Program graduate student and a research geologist at the U.S. Geological Survey, will publish their study in a forthcoming issue of Science Advances. Their co-authors include MIT research scientist Jason Soderblom, former MIT postdoc Sam Birch, now an assistant professor at Brown University, Andrew Ashton at the Woods Hole Oceanographic Institution, and Alexander Hayes of Cornell University.

“Taking a different tack”

The presence of waves on Titan has been a somewhat controversial topic ever since Cassini spotted bodies of liquid on the moon’s surface.

“Some people who tried to see evidence for waves didn’t see any, and said, ‘These seas are mirror-smooth,'” Palermo says. “Others said they did see some roughness on the liquid surface but weren’t sure if waves caused it.”

Knowing whether Titan’s seas host wave activity could give scientists information about the moon’s climate, such as the strength of the winds that could whip up such waves. Wave information could also help scientists predict how the shape of Titan’s seas might evolve over time.

Rather than look for direct signs of wave-like features in images of Titan, Perron says the team had to “take a different tack, and see, just by looking at the shape of the shoreline, if we could tell what’s been eroding the coasts.”

Titan’s seas are thought to have formed as rising levels of liquid flooded a landscape crisscrossed by river valleys. The researchers zeroed in on three scenarios for what could have happened next: no coastal erosion; erosion driven by waves; and “uniform erosion,” driven either by “dissolution,” in which liquid passively dissolves a coast’s material, or a mechanism in which the coast gradually sloughs off under its own weight.

The researchers simulated how various shoreline shapes would evolve under each of the three scenarios. To simulate wave-driven erosion, they took into account a variable known as “fetch,” which describes the physical distance from one point on a shoreline to the opposite side of a lake or sea.

“Wave erosion is driven by the height and angle of the wave,” Palermo explains. “We used fetch to approximate wave height because the bigger the fetch, the longer the distance over which wind can blow and waves can grow.”

To test how shoreline shapes would differ between the three scenarios, the researchers started with a simulated sea with flooded river valleys around its edges. For wave-driven erosion, they calculated the fetch distance from every single point along the shoreline to every other point, and converted these distances to wave heights. Then, they ran their simulation to see how waves would erode the starting shoreline over time. They compared this to how the same shoreline would evolve under erosion driven by uniform erosion. The team repeated this comparative modeling for hundreds of different starting shoreline shapes.

They found that the end shapes were very different depending on the underlying mechanism. Most notably, uniform erosion produced inflated shorelines that widened evenly all around, even in the flooded river valleys, whereas wave erosion mainly smoothed the parts of the shorelines exposed to long fetch distances, leaving the flooded valleys narrow and rough.

“We had the same starting shorelines, and we saw that you get a really different final shape under uniform erosion versus wave erosion,” Perron says. “They all kind of look like the flying spaghetti monster because of the flooded river valleys, but the two types of erosion produce very different endpoints.”

The team checked their results by comparing their simulations to actual lakes on Earth. They found the same difference in shape between Earth lakes known to have been eroded by waves and lakes affected by uniform erosion, such as dissolving limestone.

A shore’s shape

Their modeling revealed clear, characteristic shoreline shapes, depending on the mechanism by which they evolved. The team then wondered: Where would Titan’s shorelines fit, within these characteristic shapes?

In particular, they focused on four of Titan’s largest, most well-mapped seas: Kraken Mare, which is comparable in size to the Caspian Sea; Ligeia Mare, which is larger than Lake Superior; Punga Mare, which is longer than Lake Victoria; and Ontario Lacus, which is about 20 percent the size of its terrestrial namesake.

The team mapped the shorelines of each Titan sea using Cassini’s radar images, and then applied their modeling to each of the sea’s shorelines to see which erosion mechanism best explained their shape. They found that all four seas fit solidly in the wave-driven erosion model, meaning that waves produced shorelines that most closely resembled Titan’s four seas.

“We found that if the coastlines have eroded, their shapes are more consistent with erosion by waves than by uniform erosion or no erosion at all,” Perron says.

The researchers are working to determine how strong Titan’s winds must be in order to stir up waves that could repeatedly chip away at the coasts. They also hope to decipher, from the shape of Titan’s shorelines, from which directions the wind is predominantly blowing.

“Titan presents this case of a completely untouched system,” Palermo says. “It could help us learn more fundamental things about how coasts erode without the influence of people, and maybe that can help us better manage our coastlines on Earth in the future.”

This work was supported in part by NASA, the National Science Foundation, the USGS, and the Heising-Simons Foundation.

The latest NOvA data provide a very precise measurement of the bigger splitting between the squared neutrino masses and slightly favor the normal mass ordering. That precision on the mass splitting means that, when coupled with data from other experiments performed at nuclear reactors, the data favor the normal ordering at almost 7:1 odds. This suggests that neutrinos adhere to the normal ordering, but physicists have not met the high threshold of certainty required to declare a discovery.

NOvA, short for NuMI Off-axis ν_e Appearance, is an experiment managed by the U.S. Department of Energy’s Fermi National Accelerator Laboratory, located outside of Chicago. Fermilab sends a beam of neutrinos 500 miles north to a 14,000-ton detector in Ash River, Minnesota. By measuring the neutrinosand their antimatter partners, antineutrinos, in both locations, physicists can study how these particles change their type as they travel, a phenomenon known as neutrino oscillation.

NOvA aims to learn more about the ordering of neutrino masses. Physicists know that there are three types of neutrinos with different masses, but they don’t know the absolute mass, nor which is heaviest. Theoretical models predict two possible mass orderings, normal or inverted. In the normal ordering, there are two light neutrinos and one heavier neutrino; in inverted, there is one light neutrino and two heavier ones.

“Getting additional information from reactor experiments enhances our knowledge of the mass ordering and gets us close to exciting territory,” said Erika Catano-Mur, a postdoctoral research associate at William & Mary and co-convener of the analysis. “We almost have an answer to one of those big questions that we have in neutrino physics. But we’re not there yet.”

The solution to neutrino oscillation remains ambiguous in the new results. Physicists don’t currently have enough data to disentangle two effects on the oscillation: mass ordering and a property called Charge Parity violation. The collaboration observed a moderate amount of oscillation that could be explained in either mass ordering scenario with different amounts of CP violation, so they cannot tease apart the mass ordering and CP violation. However, the physicists were able to rule out specific combinations of the two properties.

“It really takes more than one measurement for us to learn everything we need to know,” said Jeremy Wolcott, a postdoctoral fellow at Tufts University, one of NOvA’s analysis coordinators and the speaker at the conference.

“NOvA is an important player in this because there are unique aspects to all of the various experiments that are trying to measure the same parameters,” said Wolcott. “We’re starting to see a picture come together, but it’s murky. Having different measurements that all work together is really important.”

The NOvA experiment started taking data in 2014 and will continue running through early 2027, during which time the collaboration hopes to double their antineutrino dataset. They also continue to implement analysis improvements to maximize the sensitivity of the experiment.

Their efforts are also paving the way for future experiments that will seek to contribute even more to solving the mysteries around neutrino properties.

“We want to make the most that we can out of the data,” said Catano-Mur. “What we learn — not only from the results themselves, but in the process, what we’re learning about the analysis methods — is going to be useful for the next generation of experiments that right now are under construction.

Still, NOvA has the potential to reveal more about the elusive neutrino. “This result is an important reminder that the current generation of experiments, including NOvA, continues to collect valuable data and produce physics insights,” said Zoya Vallari, postdoctoral researcher at CalTech and co-convener of the analysis. “They are our best shot at a discovery right now.”

The NOvA collaborationis made up of more than 200 scientists from 50 institutions in eight countries. With the additional data and further analysis improvements, NOvA will bring physicists closer to understanding the identity-changing behavior of neutrinos.

“I was shocked at how many households were above the new 200 ppm guideline,” said Gabriel Filippelli, a biochemist at Indiana University who led the new study. “I assumed it was going to be a more modest number. And results for the 100 ppm guideline are even worse.”

Remediating the roughly 29 million affected households using traditional “dig and dump” soil removal methods could cost upward of $1 trillion, the study calculated. The study was published in GeoHealth, an open-access AGU journal that publishes research investigating the intersection of human and planetary health for a sustainable future. Filippelli is the former editor-in-chief of GeoHealth.

National lead problem “nowhere near over”

Lead is a heavy metal that can accumulate in the human body, with toxic effects. In children, exposure to lead is associated with lower educational outcomes. In the United States, the burden of lead exposure has historically fallen on lower-income communities and communities of color because of redlining and other discriminatory practices. Lead pollution can come from aging water pipes, old paint, and remnant gasoline and industrial pollution, but today, most lead exposure are from contaminated soils and dust, even after lead-containing infrastructure was removed.

The Centers for Disease Control and Prevention first set a limit on the concentration of lead in blood in 1991 at 10 micrograms per deciliter, and it lowered that limit several times until reaching the current limit of 3.5 micrograms per deciliter. But the EPA’s soil lead screening level remained unchanged for more than 30 years until the January announcement. Some states had established their own lower guidelines; California has the lowest screening level, at 80 ppm.

The lag is likely due to “the immensity and ubiquity of the problem,” the study authors wrote. “The scale is astounding, and the nation’s lead and remediation efforts just became substantially more complicated.” That’s because once the EPA lowers a screening limit, they need to tell people what to do if their soils exceed it.

When the EPA lowered the screening level, Filippelli and his co-authors decided to make use of the database of 15,595 residential soil samples from the contiguous United States that they’d collected over the years to find out how many exceeded the new guideline.

Household health hazard

About 25% of the residential soil samples, collected from yards, gardens, alleys, and other residential spots, exceeded the new 200 ppm level, the study found. (Only 12% of samples had exceeded the older, 400 ppm level.) Extrapolating across the country, that equates to roughly 29 million households.

The EPA issued separate guidance for households with multiple sources of exposure, such as both lead-contaminated soil and lead pipes, setting the level in those situations at 100 ppm. In practice, that’s most urban households, Filippelli said. Forty percent of households exceed that limit, increasing the number of affected households to nearly 50 million, the study found.

Typically, contaminated soils are remediated with removal — colloquially, “dig and dump.” But the practice is costly and typically only used after an area is placed on the National Priority List for remediation, a process that can take years. To remediate all contaminated households with “dig and dump” would cost between $290 billion and $1.2 trillion, the authors calculated.

A cheaper option is “capping”: burying the contaminated soil with about a foot of soil or mulch. A geotechnical fabric barrier can also be installed. Most lead contamination is in the top 10 to 12 inches of soil, Filippelli said, so this simple method either covers up the problem or dilutes it to an acceptable level.

“Urban gardeners have been doing this forever anyway, with raised beds, because they’re intuitively concerned about the history of land use at their house,” Filippelli said.

And capping is quicker.

“A huge advantage of capping is speed. It immediately reduces exposure,” Filippelli said. “You’re not waiting two years on a list to have your yard remediated while your child is getting poisoned. It’s done in a weekend.“

Capping still requires time and effort; residents must find clean soil, transport it to their home and spread it out. But the health benefits likely outweigh those costs, Filippelli said.

Because capping has been done more informally, there’s still a lot to be learned about its lifespan and sustainability, Filippelli said. That’s where the research will go next.

Despite the “staggering” scale of the problem, “I’m really optimistic,” Filippelli said. “Lead is the most easily solvable problem that we have. We know where it is, and we know how to avoid it. It’s just a matter of taking action.”

Maps: https://www.mapmyenvironment.com/