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    New AI tool generates realistic satellite images of future flooding

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    Visualizing the potential impacts of a hurricane on people’s homes before it hits can help residents prepare and decide whether to evacuate.MIT scientists have developed a method that generates satellite imagery from the future to depict how a region would look after a potential flooding event. The method combines a generative artificial intelligence model with a physics-based flood model to create realistic, birds-eye-view images of a region, showing where flooding is likely to occur given the strength of an oncoming storm.As a test case, the team applied the method to Houston and generated satellite images depicting what certain locations around the city would look like after a storm comparable to Hurricane Harvey, which hit the region in 2017. The team compared these generated images with actual satellite images taken of the same regions after Harvey hit. They also compared AI-generated images that did not include a physics-based flood model.The team’s physics-reinforced method generated satellite images of future flooding that were more realistic and accurate. The AI-only method, in contrast, generated images of flooding in places where flooding is not physically possible.The team’s method is a proof-of-concept, meant to demonstrate a case in which generative AI models can generate realistic, trustworthy content when paired with a physics-based model. In order to apply the method to other regions to depict flooding from future storms, it will need to be trained on many more satellite images to learn how flooding would look in other regions.“The idea is: One day, we could use this before a hurricane, where it provides an additional visualization layer for the public,” says Björn Lütjens, a postdoc in MIT’s Department of Earth, Atmospheric and Planetary Sciences, who led the research while he was a doctoral student in MIT’s Department of Aeronautics and Astronautics (AeroAstro). “One of the biggest challenges is encouraging people to evacuate when they are at risk. Maybe this could be another visualization to help increase that readiness.”To illustrate the potential of the new method, which they have dubbed the “Earth Intelligence Engine,” the team has made it available as an online resource for others to try.The researchers report their results today in the journal IEEE Transactions on Geoscience and Remote Sensing. The study’s MIT co-authors include Brandon Leshchinskiy; Aruna Sankaranarayanan; and Dava Newman, professor of AeroAstro and director of the MIT Media Lab; along with collaborators from multiple institutions.Generative adversarial imagesThe new study is an extension of the team’s efforts to apply generative AI tools to visualize future climate scenarios.“Providing a hyper-local perspective of climate seems to be the most effective way to communicate our scientific results,” says Newman, the study’s senior author. “People relate to their own zip code, their local environment where their family and friends live. Providing local climate simulations becomes intuitive, personal, and relatable.”For this study, the authors use a conditional generative adversarial network, or GAN, a type of machine learning method that can generate realistic images using two competing, or “adversarial,” neural networks. The first “generator” network is trained on pairs of real data, such as satellite images before and after a hurricane. The second “discriminator” network is then trained to distinguish between the real satellite imagery and the one synthesized by the first network.Each network automatically improves its performance based on feedback from the other network. The idea, then, is that such an adversarial push and pull should ultimately produce synthetic images that are indistinguishable from the real thing. Nevertheless, GANs can still produce “hallucinations,” or factually incorrect features in an otherwise realistic image that shouldn’t be there.“Hallucinations can mislead viewers,” says Lütjens, who began to wonder whether such hallucinations could be avoided, such that generative AI tools can be trusted to help inform people, particularly in risk-sensitive scenarios. “We were thinking: How can we use these generative AI models in a climate-impact setting, where having trusted data sources is so important?”Flood hallucinationsIn their new work, the researchers considered a risk-sensitive scenario in which generative AI is tasked with creating satellite images of future flooding that could be trustworthy enough to inform decisions of how to prepare and potentially evacuate people out of harm’s way.Typically, policymakers can get an idea of where flooding might occur based on visualizations in the form of color-coded maps. These maps are the final product of a pipeline of physical models that usually begins with a hurricane track model, which then feeds into a wind model that simulates the pattern and strength of winds over a local region. This is combined with a flood or storm surge model that forecasts how wind might push any nearby body of water onto land. A hydraulic model then maps out where flooding will occur based on the local flood infrastructure and generates a visual, color-coded map of flood elevations over a particular region.“The question is: Can visualizations of satellite imagery add another level to this, that is a bit more tangible and emotionally engaging than a color-coded map of reds, yellows, and blues, while still being trustworthy?” Lütjens says.The team first tested how generative AI alone would produce satellite images of future flooding. They trained a GAN on actual satellite images taken by satellites as they passed over Houston before and after Hurricane Harvey. When they tasked the generator to produce new flood images of the same regions, they found that the images resembled typical satellite imagery, but a closer look revealed hallucinations in some images, in the form of floods where flooding should not be possible (for instance, in locations at higher elevation).To reduce hallucinations and increase the trustworthiness of the AI-generated images, the team paired the GAN with a physics-based flood model that incorporates real, physical parameters and phenomena, such as an approaching hurricane’s trajectory, storm surge, and flood patterns. With this physics-reinforced method, the team generated satellite images around Houston that depict the same flood extent, pixel by pixel, as forecasted by the flood model.“We show a tangible way to combine machine learning with physics for a use case that’s risk-sensitive, which requires us to analyze the complexity of Earth’s systems and project future actions and possible scenarios to keep people out of harm’s way,” Newman says. “We can’t wait to get our generative AI tools into the hands of decision-makers at the local community level, which could make a significant difference and perhaps save lives.”The research was supported, in part, by the MIT Portugal Program, the DAF-MIT Artificial Intelligence Accelerator, NASA, and Google Cloud. 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      Applying risk and reliability analysis across industries

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      On Feb. 1, 2003, the space shuttle Columbia disintegrated as it returned to Earth, killing all seven astronauts on board. The tragic incident compelled NASA to amp up their risk safety assessments and protocols. They knew whom to call: Curtis Smith PhD ’02, who is now the KEPCO Professor of the Practice of Nuclear Science and Engineering at MIT.The nuclear community has always been a leader in probabilistic risk analysis and Smith’s work in risk-related research had made him an established expert in the field. When NASA came knocking, Smith had been working for the Nuclear Regulatory Commission (NRC) at the Idaho National Laboratory (INL). He pivoted quickly. For the next decade, Smith worked with NASA’s Office of Safety and Mission Assurance supporting their increased use of risk analysis. It was a software tool that Smith helped develop, SAPHIRE, that NASA would adopt to bolster its own risk analysis program.At MIT, Smith’s focus is on both sides of system operation: risk and reliability. A research project he has proposed involves evaluating the reliability of 3D-printed components and parts for nuclear reactors.Growing up in IdahoMIT is a distance from where Smith grew up on the Shoshone-Bannock Native American reservation in Fort Hall, Idaho. His father worked at a chemical manufacturing plant, while his mother and grandmother operated a small restaurant on the reservation.Southeast Idaho had a significant population of migrant workers and Smith grew up with a diverse group of friends, mostly Native American and Hispanic. “It was a largely positive time and set a worldview for me in many wonderful ways,” Smith remembers. When he was a junior in high school, the family moved to Pingree, Idaho, a small town of barely 500. Smith attended Snake River High, a regional school, and remembered the deep impact his teachers had. “I learned a lot in grade school and had great teachers, so my love for education probably started there. I tried to emulate my teachers,” Smith says.Smith went to Idaho State University in Pocatello for college, a 45-minute drive from his family. Drawn to science, he decided he wanted to study a subject that would benefit humanity the most: nuclear engineering. Fortunately, Idaho State has a strong nuclear engineering program. Smith completed a master’s degree in the same field at ISU while working for the Federal Bureau of Investigation in the security department during the swing shift — 5 p.m. to 1 a.m. — at the FBI offices in Pocatello. “It was a perfect job while attending grad school,” Smith says.His KEPCO Professor of the Practice appointment is the second stint for Smith at MIT: He completed his PhD in the Department of Nuclear Science and Engineering (NSE) under the advisement of Professor George Apostolakis in 2002.A career in risk analysis and managementAfter a doctorate at MIT, Smith returned to Idaho, conducting research in risk analysis for the NRC. He also taught technical courses and developed risk analysis software. “We did a whole host of work that supported the current fleet of nuclear reactors that we have,” Smith says.He was 10 years into his career at INL when NASA recruited him, leaning on his expertise in risk analysis to translate it into space missions. “I didn’t really have a background in aerospace, but I was able to bring all the engineering I knew, conducting risk analysis for nuclear missions. It was really exciting and I learned a lot about aerospace,” Smith says.Risk analysis uses statistics and data to answer complex questions involving safety. Among his projects: analyzing the risk involved in a Mars rover mission with a radioisotope-generated power source for the rover. Even if the necessary plutonium is encased in really strong material, calculations for risk have to factor in all eventualities, including the rocket blowing up.When the Fukushima incident happened in 2011, the Department of Energy (DoE) was more supportive of safety and risk analysis research. Smith found himself in the center of the action again, supporting large DoE research programs. He then moved to become the director of the Nuclear Safety and Regulatory Research Division at the INL. Smith found he loved the role, mentoring and nurturing the careers of a diverse set of scientists. “It turned out to be much more rewarding than I had expected,” Smith says. Under his leadership, the division grew from 45 to almost 90 research staff and won multiple national awards.Return to MITMIT NSE came calling in 2022, looking to fill the position of professor of the practice, an offer Smith couldn’t refuse. The department was looking to bulk up its risk and reliability offerings and Smith made a great fit. The DoE division he had been supervising had grown wings enough for Smith to seek out something new.“Just getting back to Boston is exciting,” Smith says. The last go-around involved bringing the family to the city and included a lot of sleepless nights. Smith’s wife, Jacquie, is also excited about being closer to the New England fan base. The couple has invested in season tickets for the Patriots and look to attend as many sporting events as possible.Smith is most excited about adding to the risk and reliability offerings at MIT at a time when the subject has become especially important for nuclear power. “I’m grateful for the opportunity to bring my knowledge and expertise from the last 30 years to the field,” he says. Being a professor of the practice of NSE carries with it a responsibility to unite theory and practice, something Smith is especially good at. “We always have to answer the question of, ‘How do I take the research and make that practical,’ especially for something important like nuclear power, because we need much more of these ideas in industry,” he says.He is particularly excited about developing the next generation of nuclear scientists. “Having the ability to do this at a place like MIT is especially fulfilling and something I have been desiring my whole career,” Smith says. More

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      in Environment

      Study evaluates impacts of summer heat in U.S. prison environments

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      When summer temperatures spike, so does our vulnerability to heat-related illness or even death. For the most part, people can take measures to reduce their heat exposure by opening a window, turning up the air conditioning, or simply getting a glass of water. But for people who are incarcerated, freedom to take such measures is often not an option. Prison populations therefore are especially vulnerable to heat exposure, due to their conditions of confinement.A new study by MIT researchers examines summertime heat exposure in prisons across the United States and identifies characteristics within prison facilities that can further contribute to a population’s vulnerability to summer heat.The study’s authors used high-spatial-resolution air temperature data to determine the daily average outdoor temperature for each of 1,614 prisons in the U.S., for every summer between the years 1990 and 2023. They found that the prisons that are exposed to the most extreme heat are located in the southwestern U.S., while prisons with the biggest changes in summertime heat, compared to the historical record, are in the Pacific Northwest, the Northeast, and parts of the Midwest.Those findings are not entirely unique to prisons, as any non-prison facility or community in the same geographic locations would be exposed to similar outdoor air temperatures. But the team also looked at characteristics specific to prison facilities that could further exacerbate an incarcerated person’s vulnerability to heat exposure. They identified nine such facility-level characteristics, such as highly restricted movement, poor staffing, and inadequate mental health treatment. People living and working in prisons with any one of these characteristics may experience compounded risk to summertime heat. The team also looked at the demographics of 1,260 prisons in their study and found that the prisons with higher heat exposure on average also had higher proportions of non-white and Hispanic populations. The study, appearing today in the journal GeoHealth, provides policymakers and community leaders with ways to estimate, and take steps to address, a prison population’s heat risk, which they anticipate could worsen with climate change.“This isn’t a problem because of climate change. It’s becoming a worse problem because of climate change,” says study lead author Ufuoma Ovienmhada SM ’20, PhD ’24, a graduate of the MIT Media Lab, who recently completed her doctorate in MIT’s Department of Aeronautics and Astronautics (AeroAstro). “A lot of these prisons were not built to be comfortable or humane in the first place. Climate change is just aggravating the fact that prisons are not designed to enable incarcerated populations to moderate their own exposure to environmental risk factors such as extreme heat.”The study’s co-authors include Danielle Wood, MIT associate professor of media arts and sciences, and of AeroAstro; and Brent Minchew, MIT associate professor of geophysics in the Department of Earth, Atmospheric and Planetary Sciences; along with Ahmed Diongue ’24, Mia Hines-Shanks of Grinnell College, and Michael Krisch of Columbia University.Environmental intersectionsThe new study is an extension of work carried out at the Media Lab, where Wood leads the Space Enabled research group. The group aims to advance social and environmental justice issues through the use of satellite data and other space-enabled technologies.The group’s motivation to look at heat exposure in prisons came in 2020 when, as co-president of MIT’s Black Graduate Student Union, Ovienmhada took part in community organizing efforts following the murder of George Floyd by Minneapolis police.“We started to do more organizing on campus around policing and reimagining public safety. Through that lens I learned more about police and prisons as interconnected systems, and came across this intersection between prisons and environmental hazards,” says Ovienmhada, who is leading an effort to map the various environmental hazards that prisons, jails, and detention centers face. “In terms of environmental hazards, extreme heat causes some of the most acute impacts for incarcerated people.”She, Wood, and their colleagues set out to use Earth observation data to characterize U.S. prison populations’ vulnerability, or their risk of experiencing negative impacts, from heat.The team first looked through a database maintained by the U.S. Department of Homeland Security that lists the location and boundaries of carceral facilities in the U.S. From the database’s more than 6,000 prisons, jails, and detention centers, the researchers highlighted 1,614 prison-specific facilities, which together incarcerate nearly 1.4 million people, and employ about 337,000 staff.They then looked to Daymet, a detailed weather and climate database that tracks daily temperatures across the United States, at a 1-kilometer resolution. For each of the 1,614 prison locations, they mapped the daily outdoor temperature, for every summer between the years 1990 to 2023, noting that the majority of current state and federal correctional facilities in the U.S. were built by 1990.The team also obtained U.S. Census data on each facility’s demographic and facility-level characteristics, such as prison labor activities and conditions of confinement. One limitation of the study that the researchers acknowledge is a lack of information regarding a prison’s climate control.“There’s no comprehensive public resource where you can look up whether a facility has air conditioning,” Ovienmhada notes. “Even in facilities with air conditioning, incarcerated people may not have regular access to those cooling systems, so our measurements of outdoor air temperature may not be far off from reality.”Heat factorsFrom their analysis, the researchers found that more than 98 percent of all prisons in the U.S. experienced at least 10 days in the summer that were hotter than every previous summer, on average, for a given location. Their analysis also revealed the most heat-exposed prisons, and the prisons that experienced the highest temperatures on average, were mostly in the Southwestern U.S. The researchers note that with the exception of New Mexico, the Southwest is a region where there are no universal air conditioning regulations in state-operated prisons.“States run their own prison systems, and there is no uniformity of data collection or policy regarding air conditioning,” says Wood, who notes that there is some information on cooling systems in some states and individual prison facilities, but the data is sparse overall, and too inconsistent to include in the group’s nationwide study.While the researchers could not incorporate air conditioning data, they did consider other facility-level factors that could worsen the effects that outdoor heat triggers. They looked through the scientific literature on heat, health impacts, and prison conditions, and focused on 17 measurable facility-level variables that contribute to heat-related health problems. These include factors such as overcrowding and understaffing.“We know that whenever you’re in a room that has a lot of people, it’s going to feel hotter, even if there’s air conditioning in that environment,” Ovienmhada says. “Also, staffing is a huge factor. Facilities that don’t have air conditioning but still try to do heat risk-mitigation procedures might rely on staff to distribute ice or water every few hours. If that facility is understaffed or has neglectful staff, that may increase people’s susceptibility to hot days.”The study found that prisons with any of nine of the 17 variables showed statistically significant greater heat exposures than the prisons without those variables. Additionally, if a prison exhibits any one of the nine variables, this could worsen people’s heat risk through the combination of elevated heat exposure and vulnerability. The variables, they say, could help state regulators and activists identify prisons to prioritize for heat interventions.“The prison population is aging, and even if you’re not in a ‘hot state,’ every state has responsibility to respond,” Wood emphasizes. “For instance, areas in the Northwest, where you might expect to be temperate overall, have experienced a number of days in recent years of increasing heat risk. A few days out of the year can still be dangerous, particularly for a population with reduced agency to regulate their own exposure to heat.”This work was supported, in part, by NASA, the MIT Media Lab, and MIT’s Institute for Data, Systems and Society’s Research Initiative on Combatting Systemic Racism. More

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      in Energy

      MIT students combat climate anxiety through extracurricular teams

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      Climate anxiety affects nearly half of young people aged 16-25. Students like second-year Rachel Mohammed find hope and inspiration through her involvement in innovative climate solutions, working alongside peers who share her determination. “I’ve met so many people at MIT who are dedicated to finding climate solutions in ways that I had never imagined, dreamed of, or heard of. That is what keeps me going, and I’m doing my part,” she says.Hydrogen-fueled enginesHydrogen offers the potential for zero or near-zero emissions, with the ability to reduce greenhouse gases and pollution by 29 percent. However, the hydrogen industry faces many challenges related to storage solutions and costs.Mohammed leads the hydrogen team on MIT’s Electric Vehicle Team (EVT), which is dedicated to harnessing hydrogen power to build a cleaner, more sustainable future. EVT is one of several student-led build teams at the Edgerton Center focused on innovative climate solutions. Since its founding in 1992, the Edgerton Center has been a hub for MIT students to bring their ideas to life.Hydrogen is mostly used in large vehicles like trucks and planes because it requires a lot of storage space. EVT is building their second iteration of a motorcycle based on what Mohammed calls a “goofy hypothesis” that you can use hydrogen to power a small vehicle. The team employs a hydrogen fuel cell system, which generates electricity by combining hydrogen with oxygen. However, the technology faces challenges, particularly in storage, which EVT is tackling with innovative designs for smaller vehicles.Presenting at the 2024 World Hydrogen Summit reaffirmed Mohammed’s confidence in this project. “I often encounter skepticism, with people saying it’s not practical. Seeing others actively working on similar initiatives made me realize that we can do it too,” Mohammed says.The team’s first successful track test last October allowed them to evaluate the real-world performance of their hydrogen-powered motorcycle, marking a crucial step in proving the feasibility and efficiency of their design.MIT’s Sustainable Engine Team (SET), founded by junior Charles Yong, uses the combustion method to generate energy with hydrogen. This is a promising technology route for high-power-density applications, like aviation, but Yong believes it hasn’t received enough attention. Yong explains, “In the hydrogen power industry, startups choose fuel cell routes instead of combustion because gas turbine industry giants are 50 years ahead. However, these giants are moving very slowly toward hydrogen due to its not-yet-fully-developed infrastructure. Working under the Edgerton Center allows us to take risks and explore advanced tech directions to demonstrate that hydrogen combustion can be readily available.”Both EVT and SET are publishing their research and providing detailed instructions for anyone interested in replicating their results.Running on sunshineThe Solar Electric Vehicle Team powers a car built from scratch with 100 percent solar energy.The team’s single-occupancy car Nimbus won the American Solar Challenge two years in a row. This year, the team pushed boundaries further with Gemini, a multiple-occupancy vehicle that challenges conventional perceptions of solar-powered cars.Senior Andre Greene explains, “the challenge comes from minimizing how much energy you waste because you work with such little energy. It’s like the equivalent power of a toaster.”Gemini looks more like a regular car and less like a “spaceship,” as NBC’s 1st Look affectionately called Nimbus. “It more resembles what a fully solar-powered car could look like versus the single-seaters. You don’t see a lot of single-seater cars on the market, so it’s opening people’s minds,” says rising junior Tessa Uviedo, team captain.All-electric since 2013The MIT Motorsports team switched to an all-electric powertrain in 2013. Captain Eric Zhou takes inspiration from China, the world’s largest market for electric vehicles. “In China, there is a large government push towards electric, but there are also five or six big companies almost as large as Tesla size, building out these electric vehicles. The competition drives the majority of vehicles in China to become electric.”The team is also switching to four-wheel drive and regenerative braking next year, which reduces the amount of energy needed to run. “This is more efficient and better for power consumption because the torque from the motors is applied straight to the tires. It’s more efficient than having a rear motor that must transfer torque to both rear tires. Also, you’re taking advantage of all four tires in terms of producing grip, while you can only rely on the back tires in a rear-wheel-drive car,” Zhou says.Zhou adds that Motorsports wants to help prepare students for the electric vehicle industry. “A large majority of upperclassmen on the team have worked, or are working, at Tesla or Rivian.”Former Motorsports powertrain lead Levi Gershon ’23, SM ’24 recently founded CRABI Robotics — a fully autonomous marine robotic system designed to conduct in-transit cleaning of marine vessels by removing biofouling, increasing vessels’ fuel efficiency.An Indigenous approach to sustainable rocketsFirst Nations Launch, the all-Indigenous student rocket team, recently won the Grand Prize in the 2024 NASA First Nations Launch High-Power Rocket Competition. Using Indigenous methodologies, this team considers the environment in the materials and methods they employ.“The environmental impact is always something that we consider when we’re making design decisions and operational decisions. We’ve thought about things like biodegradable composites and parachutes,” says rising junior Hailey Polson, team captain. “Aerospace has been a very wasteful industry in the past. There are huge leaps and bounds being made with forward progress in regard to reusable rockets, which is definitely lowering the environmental impact.”Collecting climate change data with autonomous boatsArcturus, the recent first-place winner in design at the 16th Annual RoboBoat Competition, is developing autonomous surface vehicles that can greatly aid in marine research. “The ocean is one of our greatest resources to combat climate change; thus, the accessibility of data will help scientists understand climate patterns and predict future trends. This can help people learn how to prepare for potential disasters and how to reduce each of our carbon footprints,” says Arcturus captain and rising junior Amy Shi.“We are hoping to expand our outreach efforts to incorporate more sustainability-related programs. This can include more interactions with local students to introduce them to how engineering can make a positive impact in the climate space or other similar programs,” Shi says.Shi emphasizes that hope is a crucial force in the battle against climate change. “There are great steps being taken every day to combat this seemingly impending doom we call the climate crisis. It’s important to not give up hope, because this hope is what’s driving the leaps and bounds of innovation happening in the climate community. The mainstream media mostly reports on the negatives, but the truth is there is a lot of positive climate news every day. Being more intentional about where you seek your climate news can really help subside this feeling of doom about our planet.” More

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      in Environment

      Study: Rocks from Mars’ Jezero Crater, which likely predate life on Earth, contain signs of water

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      In a new study appearing today in the journal AGU Advances, scientists at MIT and NASA report that seven rock samples collected along the “fan front” of Mars’ Jezero Crater contain minerals that are typically formed in water. The findings suggest that the rocks were originally deposited by water, or may have formed in the presence of water.The seven samples were collected by NASA’s Perseverance rover in 2022 during its exploration of the crater’s western slope, where some rocks were hypothesized to have formed in what is now a dried-up ancient lake. Members of the Perseverance science team, including MIT scientists, have studied the rover’s images and chemical analyses of the samples, and confirmed that the rocks indeed contain signs of water, and that the crater was likely once a watery, habitable environment.Whether the crater was actually inhabited is yet unknown. The team found that the presence of organic matter — the starting material for life — cannot be confirmed, at least based on the rover’s measurements. But judging from the rocks’ mineral content, scientists believe the samples are their best chance of finding signs of ancient Martian life once the rocks are returned to Earth for more detailed analysis.“These rocks confirm the presence, at least temporarily, of habitable environments on Mars,” says the study’s lead author, Tanja Bosak, professor of geobiology in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). “What we’ve found is that indeed there was a lot of water activity. For how long, we don’t know, but certainly for long enough to create these big sedimentary deposits.”What’s more, some of the collected samples may have originally been deposited in the ancient lake more than 3.5 billion years ago — before even the first signs of life on Earth.“These are the oldest rocks that may have been deposited by water, that we’ve ever laid hands or rover arms on,” says co-author Benjamin Weiss, the Robert R. Shrock Professor of Earth and Planetary Sciences at MIT. “That’s exciting, because it means these are the most promising rocks that may have preserved fossils, and signatures of life.”The study’s MIT co-authors include postdoc Eva Scheller, and research scientist Elias Mansbach, along with members of the Perseverance science team.At the front

      NASA’s Perseverance rover collected rock samples from two locations seen in this image of Mars’ Jezero Crater: “Wildcat Ridge” (lower left) and “Skinner Ridge” (upper right).

      Credit: NASA/JPL-Caltech/ASU/MSSS

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      The new rock samples were collected in 2022 as part of the rover’s Fan Front Campaign — an exploratory phase during which Perseverance traversed Jezero Crater’s western slope, where a fan-like region contains sedimentary, layered rocks. Scientists suspect that this “fan front” is an ancient delta that was created by sediment that flowed with a river and settled into a now bone-dry lakebed. If life existed on Mars, scientists believe that it could be preserved in the layers of sediment along the fan front.In the end, Perseverance collected seven samples from various locations along the fan front. The rover obtained each sample by drilling into the Martian bedrock and extracting a pencil-sized core, which it then sealed in a tube to one day be retrieved and returned to Earth for detailed analysis.

      Composed of multiple images from NASA’s Perseverance Mars rover, this mosaic shows a rocky outcrop called “Wildcat Ridge,” where the rover extracted two rock cores and abraded a circular patch to investigate the rock’s composition.

      Credit: NASA/JPL-Caltech/ASU/MSSS

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      Prior to extracting the cores, the rover took images of the surrounding sediments at each of the seven locations. The science team then processed the imaging data to estimate a sediment’s average grain size and mineral composition. This analysis showed that all seven collected samples likely contain signs of water, suggesting that they were initially deposited by water.Specifically, Bosak and her colleagues found evidence of certain minerals in the sediments that are known to precipitate out of water.“We found lots of minerals like carbonates, which are what make reefs on Earth,” Bosak says. “And it’s really an ideal material that can preserve fossils of microbial life.”Interestingly, the researchers also identified sulfates in some samples that were collected at the base of the fan front. Sulfates are minerals that form in very salty water — another sign that water was present in the crater at one time — though very salty water, Bosak notes, “is not necessarily the best thing for life.” If the entire crater was once filled with very salty water, then it would be difficult for any form of life to thrive. But if only the bottom of the lake were briny, that could be an advantage, at least for preserving any signs of life that may have lived further up, in less salty layers, that eventually died and drifted down to the bottom.“However salty it was, if there were any organics present, it’s like pickling something in salt,” Bosak says. “If there was life that fell into the salty layer, it would be very well-preserved.”Fuzzy fingerprintsBut the team emphasizes that organic matter has not been confidently detected by the rover’s instruments. Organic matter can be signs of life, but can also be produced by certain geological processes that have nothing to do with living matter. Perseverance’s predecessor, the Curiosity rover, had detected organic matter throughout Mars’ Gale Crater, which scientists suspect may have come from asteroids that made impact with Mars in the past.And in a previous campaign, Perseverance detected what appeared to be organic molecules at multiple locations along Jezero Crater’s floor. These observations were taken by the rover’s Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) instrument, which uses ultraviolet light to scan the Martian surface. If organics are present, they can glow, similar to material under a blacklight. The wavelengths at which the material glows act as a sort of fingerprint for the kind of organic molecules that are present.In Perseverance’s previous exploration of the crater floor, SHERLOC appeared to pick up signs of organic molecules throughout the region, and later, at some locations along the fan front. But a careful analysis, led by MIT’s Eva Scheller, has found that while the particular wavelengths observed could be signs of organic matter, they could just as well be signatures of substances that have nothing to do with organic matter.“It turns out that cerium metals incorporated in minerals actually produce very similar signals as the organic matter,” Scheller says. “When investigated, the potential organic signals were strongly correlated with phosphate minerals, which always contain some cerium.”Scheller’s work shows that the rover’s measurements cannot be interpreted definitively as organic matter.“This is not bad news,” Bosak says. “It just tells us there is not very abundant organic matter. It’s still possible that it’s there. It’s just below the rover’s detection limit.”When the collected samples are finally sent back to Earth, Bosak says laboratory instruments will have more than enough sensitivity to detect any organic matter that might lie within.“On Earth, once we have microscopes with nanometer-scale resolution, and various types of instruments that we cannot staff on one rover, then we can actually attempt to look for life,” she says.This work was supported, in part, by NASA. More

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      in Environment

      “They can see themselves shaping the world they live in”

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      During the journey from the suburbs to the city, the tree canopy often dwindles down as skyscrapers rise up. A group of New England Innovation Academy students wondered why that is.“Our friend Victoria noticed that where we live in Marlborough there are lots of trees in our own backyards. But if you drive just 30 minutes to Boston, there are almost no trees,” said high school junior Ileana Fournier. “We were struck by that duality.”This inspired Fournier and her classmates Victoria Leeth and Jessie Magenyi to prototype a mobile app that illustrates Massachusetts deforestation trends for Day of AI, a free, hands-on curriculum developed by the MIT Responsible AI for Social Empowerment and Education (RAISE) initiative, headquartered in the MIT Media Lab and in collaboration with the MIT Schwarzman College of Computing and MIT Open Learning. They were among a group of 20 students from New England Innovation Academy who shared their projects during the 2024 Day of AI global celebration hosted with the Museum of Science.The Day of AI curriculum introduces K-12 students to artificial intelligence. Now in its third year, Day of AI enables students to improve their communities and collaborate on larger global challenges using AI. Fournier, Leeth, and Magenyi’s TreeSavers app falls under the Telling Climate Stories with Data module, one of four new climate-change-focused lessons.“We want you to be able to express yourselves creatively to use AI to solve problems with critical-thinking skills,” Cynthia Breazeal, director of MIT RAISE, dean for digital learning at MIT Open Learning, and professor of media arts and sciences, said during this year’s Day of AI global celebration at the Museum of Science. “We want you to have an ethical and responsible way to think about this really powerful, cool, and exciting technology.”Moving from understanding to actionDay of AI invites students to examine the intersection of AI and various disciplines, such as history, civics, computer science, math, and climate change. With the curriculum available year-round, more than 10,000 educators across 114 countries have brought Day of AI activities to their classrooms and homes.The curriculum gives students the agency to evaluate local issues and invent meaningful solutions. “We’re thinking about how to create tools that will allow kids to have direct access to data and have a personal connection that intersects with their lived experiences,” Robert Parks, curriculum developer at MIT RAISE, said at the Day of AI global celebration.Before this year, first-year Jeremie Kwapong said he knew very little about AI. “I was very intrigued,” he said. “I started to experiment with ChatGPT to see how it reacts. How close can I get this to human emotion? What is AI’s knowledge compared to a human’s knowledge?”In addition to helping students spark an interest in AI literacy, teachers around the world have told MIT RAISE that they want to use data science lessons to engage students in conversations about climate change. Therefore, Day of AI’s new hands-on projects use weather and climate change to show students why it’s important to develop a critical understanding of dataset design and collection when observing the world around them.“There is a lag between cause and effect in everyday lives,” said Parks. “Our goal is to demystify that, and allow kids to access data so they can see a long view of things.”Tools like MIT App Inventor — which allows anyone to create a mobile application — help students make sense of what they can learn from data. Fournier, Leeth, and Magenyi programmed TreeSavers in App Inventor to chart regional deforestation rates across Massachusetts, identify ongoing trends through statistical models, and predict environmental impact. The students put that “long view” of climate change into practice when developing TreeSavers’ interactive maps. Users can toggle between Massachusetts’s current tree cover, historical data, and future high-risk areas.Although AI provides fast answers, it doesn’t necessarily offer equitable solutions, said David Sittenfeld, director of the Center for the Environment at the Museum of Science. The Day of AI curriculum asks students to make decisions on sourcing data, ensuring unbiased data, and thinking responsibly about how findings could be used.“There’s an ethical concern about tracking people’s data,” said Ethan Jorda, a New England Innovation Academy student. His group used open-source data to program an app that helps users track and reduce their carbon footprint.Christine Cunningham, senior vice president of STEM Learning at the Museum of Science, believes students are prepared to use AI responsibly to make the world a better place. “They can see themselves shaping the world they live in,” said Cunningham. “Moving through from understanding to action, kids will never look at a bridge or a piece of plastic lying on the ground in the same way again.”Deepening collaboration on earth and beyondThe 2024 Day of AI speakers emphasized collaborative problem solving at the local, national, and global levels.“Through different ideas and different perspectives, we’re going to get better solutions,” said Cunningham. “How do we start young enough that every child has a chance to both understand the world around them but also to move toward shaping the future?”Presenters from MIT, the Museum of Science, and NASA approached this question with a common goal — expanding STEM education to learners of all ages and backgrounds.“We have been delighted to collaborate with the MIT RAISE team to bring this year’s Day of AI celebration to the Museum of Science,” says Meg Rosenburg, manager of operations at the Museum of Science Centers for Public Science Learning. “This opportunity to highlight the new climate modules for the curriculum not only perfectly aligns with the museum’s goals to focus on climate and active hope throughout our Year of the Earthshot initiative, but it has also allowed us to bring our teams together and grow a relationship that we are very excited to build upon in the future.”Rachel Connolly, systems integration and analysis lead for NASA’s Science Activation Program, showed the power of collaboration with the example of how human comprehension of Saturn’s appearance has evolved. From Galileo’s early telescope to the Cassini space probe, modern imaging of Saturn represents 400 years of science, technology, and math working together to further knowledge.“Technologies, and the engineers who built them, advance the questions we’re able to ask and therefore what we’re able to understand,” said Connolly, research scientist at MIT Media Lab.New England Innovation Academy students saw an opportunity for collaboration a little closer to home. Emmett Buck-Thompson, Jeff Cheng, and Max Hunt envisioned a social media app to connect volunteers with local charities. Their project was inspired by Buck-Thompson’s father’s difficulties finding volunteering opportunities, Hunt’s role as the president of the school’s Community Impact Club, and Cheng’s aspiration to reduce screen time for social media users. Using MIT App Inventor, ​their combined ideas led to a prototype with the potential to make a real-world impact in their community.The Day of AI curriculum teaches the mechanics of AI, ethical considerations and responsible uses, and interdisciplinary applications for different fields. It also empowers students to become creative problem solvers and engaged citizens in their communities and online. From supporting volunteer efforts to encouraging action for the state’s forests to tackling the global challenge of climate change, today’s students are becoming tomorrow’s leaders with Day of AI.“We want to empower you to know that this is a tool you can use to make your community better, to help people around you with this technology,” said Breazeal.Other Day of AI speakers included Tim Ritchie, president of the Museum of Science; Michael Lawrence Evans, program director of the Boston Mayor’s Office of New Urban Mechanics; Dava Newman, director of the MIT Media Lab; and Natalie Lao, executive director of the App Inventor Foundation. More

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      Using deep learning to image the Earth’s planetary boundary layer

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      Although the troposphere is often thought of as the closest layer of the atmosphere to the Earth’s surface, the planetary boundary layer (PBL) — the lowest layer of the troposphere — is actually the part that most significantly influences weather near the surface. In the 2018 planetary science decadal survey, the PBL was raised as an important scientific issue that has the potential to enhance storm forecasting and improve climate projections.  

      “The PBL is where the surface interacts with the atmosphere, including exchanges of moisture and heat that help lead to severe weather and a changing climate,” says Adam Milstein, a technical staff member in Lincoln Laboratory’s Applied Space Systems Group. “The PBL is also where humans live, and the turbulent movement of aerosols throughout the PBL is important for air quality that influences human health.” 

      Although vital for studying weather and climate, important features of the PBL, such as its height, are difficult to resolve with current technology. In the past four years, Lincoln Laboratory staff have been studying the PBL, focusing on two different tasks: using machine learning to make 3D-scanned profiles of the atmosphere, and resolving the vertical structure of the atmosphere more clearly in order to better predict droughts.  

      This PBL-focused research effort builds on more than a decade of related work on fast, operational neural network algorithms developed by Lincoln Laboratory for NASA missions. These missions include the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission as well as Aqua, a satellite that collects data about Earth’s water cycle and observes variables such as ocean temperature, precipitation, and water vapor in the atmosphere. These algorithms retrieve temperature and humidity from the satellite instrument data and have been shown to significantly improve the accuracy and usable global coverage of the observations over previous approaches. For TROPICS, the algorithms help retrieve data that are used to characterize a storm’s rapidly evolving structures in near-real time, and for Aqua, it has helped increase forecasting models, drought monitoring, and fire prediction. 

      These operational algorithms for TROPICS and Aqua are based on classic “shallow” neural networks to maximize speed and simplicity, creating a one-dimensional vertical profile for each spectral measurement collected by the instrument over each location. While this approach has improved observations of the atmosphere down to the surface overall, including the PBL, laboratory staff determined that newer “deep” learning techniques that treat the atmosphere over a region of interest as a three-dimensional image are needed to improve PBL details further.

      “We hypothesized that deep learning and artificial intelligence (AI) techniques could improve on current approaches by incorporating a better statistical representation of 3D temperature and humidity imagery of the atmosphere into the solutions,” Milstein says. “But it took a while to figure out how to create the best dataset — a mix of real and simulated data; we needed to prepare to train these techniques.”

      The team collaborated with Joseph Santanello of the NASA Goddard Space Flight Center and William Blackwell, also of the Applied Space Systems Group, in a recent NASA-funded effort showing that these retrieval algorithms can improve PBL detail, including more accurate determination of the PBL height than the previous state of the art. 

      While improved knowledge of the PBL is broadly useful for increasing understanding of climate and weather, one key application is prediction of droughts. According to a Global Drought Snapshot report released last year, droughts are a pressing planetary issue that the global community needs to address. Lack of humidity near the surface, specifically at the level of the PBL, is the leading indicator of drought. While previous studies using remote-sensing techniques have examined the humidity of soil to determine drought risk, studying the atmosphere can help predict when droughts will happen.  

      In an effort funded by Lincoln Laboratory’s Climate Change Initiative, Milstein, along with laboratory staff member Michael Pieper, are working with scientists at NASA’s Jet Propulsion Laboratory (JPL) to use neural network techniques to improve drought prediction over the continental United States. While the work builds off of existing operational work JPL has done incorporating (in part) the laboratory’s operational “shallow” neural network approach for Aqua, the team believes that this work and the PBL-focused deep learning research work can be combined to further improve the accuracy of drought prediction. 

      “Lincoln Laboratory has been working with NASA for more than a decade on neural network algorithms for estimating temperature and humidity in the atmosphere from space-borne infrared and microwave instruments, including those on the Aqua spacecraft,” Milstein says. “Over that time, we have learned a lot about this problem by working with the science community, including learning about what scientific challenges remain. Our long experience working on this type of remote sensing with NASA scientists, as well as our experience with using neural network techniques, gave us a unique perspective.”

      According to Milstein, the next step for this project is to compare the deep learning results to datasets from the National Oceanic and Atmospheric Administration, NASA, and the Department of Energy collected directly in the PBL using radiosondes, a type of instrument flown on a weather balloon. “These direct measurements can be considered a kind of ‘ground truth’ to quantify the accuracy of the techniques we have developed,” Milstein says.

      This improved neural network approach holds promise to demonstrate drought prediction that can exceed the capabilities of existing indicators, Milstein says, and to be a tool that scientists can rely on for decades to come. More

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      Atmospheric observations in China show rise in emissions of a potent greenhouse gas

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      To achieve the aspirational goal of the Paris Agreement on climate change — limiting the increase in global average surface temperature to 1.5 degrees Celsius above preindustrial levels — will require its 196 signatories to dramatically reduce their greenhouse gas (GHG) emissions. Those greenhouse gases differ widely in their global warming potential (GWP), or ability to absorb radiative energy and thereby warm the Earth’s surface. For example, measured over a 100-year period, the GWP of methane is about 28 times that of carbon dioxide (CO2), and the GWP of sulfur hexafluoride (SF6) is 24,300 times that of CO2, according to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. 

      Used primarily in high-voltage electrical switchgear in electric power grids, SF6 is one of the most potent greenhouse gases on Earth. In the 21st century, atmospheric concentrations of SF6 have risen sharply along with global electric power demand, threatening the world’s efforts to stabilize the climate. This heightened demand for electric power is particularly pronounced in China, which has dominated the expansion of the global power industry in the past decade. Quantifying China’s contribution to global SF6 emissions — and pinpointing its sources in the country — could lead that nation to implement new measures to reduce them, and thereby reduce, if not eliminate, an impediment to the Paris Agreement’s aspirational goal. 

      To that end, a new study by researchers at the MIT Joint Program on the Science and Policy of Global Change, Fudan University, Peking University, University of Bristol, and Meteorological Observation Center of China Meteorological Administration determined total SF6 emissions in China over 2011-21 from atmospheric observations collected from nine stations within a Chinese network, including one station from the Advanced Global Atmospheric Gases Experiment (AGAGE) network. For comparison, global total emissions were determined from five globally distributed, relatively unpolluted “background” AGAGE stations, involving additional researchers from the Scripps Institution of Oceanography and CSIRO, Australia’s National Science Agency.

      The researchers found that SF6 emissions in China almost doubled from 2.6 gigagrams (Gg) per year in 2011, when they accounted for 34 percent of global SF6 emissions, to 5.1 Gg per year in 2021, when they accounted for 57 percent of global total SF6 emissions. This increase from China over the 10-year period — some of it emerging from the country’s less-populated western regions — was larger than the global total SF6 emissions rise, highlighting the importance of lowering SF6 emissions from China in the future.

      The open-access study, which appears in the journal Nature Communications, explores prospects for future SF6 emissions reduction in China.

      “Adopting maintenance practices that minimize SF6 leakage rates or using SF6-free equipment or SF6 substitutes in the electric power grid will benefit greenhouse-gas mitigation in China,” says Minde An, a postdoc at the MIT Center for Global Change Science (CGCS) and the study’s lead author. “We see our findings as a first step in quantifying the problem and identifying how it can be addressed.”

      Emissions of SF6 are expected to last more than 1,000 years in the atmosphere, raising the stakes for policymakers in China and around the world.

      “Any increase in SF6 emissions this century will effectively alter our planet’s radiative budget — the balance between incoming energy from the sun and outgoing energy from the Earth — far beyond the multi-decadal time frame of current climate policies,” says MIT Joint Program and CGCS Director Ronald Prinn, a coauthor of the study. “So it’s imperative that China and all other nations take immediate action to reduce, and ultimately eliminate, their SF6 emissions.”

      The study was supported by the National Key Research and Development Program of China and Shanghai B&R Joint Laboratory Project, the U.S. National Aeronautics and Space Administration, and other funding agencies.   More

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      Researchers release open-source space debris model

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      MIT’s Astrodynamics, Space Robotics, and Controls Laboratory (ARCLab) announced the public beta release of the MIT Orbital Capacity Assessment Tool (MOCAT) during the 2023 Organization for Economic Cooperation and Development (OECD) Space Forum Workshop on Dec. 14. MOCAT enables users to model the long-term future space environment to understand growth in space debris and assess the effectiveness of debris-prevention mechanisms.

      With the escalating congestion in low Earth orbit, driven by a surge in satellite deployments, the risk of collisions and space debris proliferation is a pressing concern. Conducting thorough space environment studies is critical for developing effective strategies for fostering responsible and sustainable use of space resources. 

      MOCAT stands out among orbital modeling tools for its capability to model individual objects, diverse parameters, orbital characteristics, fragmentation scenarios, and collision probabilities. With the ability to differentiate between object categories, generalize parameters, and offer multi-fidelity computations, MOCAT emerges as a versatile and powerful tool for comprehensive space environment analysis and management.

      MOCAT is intended to provide an open-source tool to empower stakeholders including satellite operators, regulators, and members of the public to make data-driven decisions. The ARCLab team has been developing these models for the last several years, recognizing that the lack of open-source implementation of evolutionary modeling tools limits stakeholders’ ability to develop consensus on actions to help improve space sustainability. This beta release is intended to allow users to experiment with the tool and provide feedback to help guide further development.

      Richard Linares, the principal investigator for MOCAT and an MIT associate professor of aeronautics and astronautics, expresses excitement about the tool’s potential impact: “MOCAT represents a significant leap forward in orbital capacity assessment. By making it open-source and publicly available, we hope to engage the global community in advancing our understanding of satellite orbits and contributing to the sustainable use of space.”

      MOCAT consists of two main components. MOCAT-MC evaluates space environment evolution with individual trajectory simulation and Monte Carlo parameter analysis, providing both a high-level overall view for the environment and a fidelity analysis into the individual space objects evolution. MOCAT Source Sink Evolutionary Model (MOCAT-SSEM), meanwhile, uses a lower-fidelity modeling approach that can run on personal computers within seconds to minutes. MOCAT-MC and MOCAT-SSEM can be accessed separately via GitHub.

      MOCAT’s initial development has been supported by the Defense Advanced Research Projects Agency (DARPA) and NASA’s Office of Technology and Strategy.

      “We are thrilled to support this groundbreaking orbital debris modeling work and the new knowledge it created,” says Charity Weeden, associate administrator for the Office of Technology, Policy, and Strategy at NASA headquarters in Washington. “This open-source modeling tool is a public good that will advance space sustainability, improve evidence-based policy analysis, and help all users of space make better decisions.” More