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    Study finds lands used for grazing can worsen or help climate change

    When it comes to global climate change, livestock grazing can be either a blessing or a curse, according to a new study, which offers clues on how to tell the difference.

    If managed properly, the study shows, grazing can actually increase the amount of carbon from the air that gets stored in the ground and sequestered for the long run. But if there is too much grazing, soil erosion can result, and the net effect is to cause more carbon losses, so that the land becomes a net carbon source, instead of a carbon sink. And the study found that the latter is far more common around the world today.

    The new work, published today in the journal Nature Climate Change, provides ways to determine the tipping point between the two, for grazing lands in a given climate zone and soil type. It also provides an estimate of the total amount of carbon that has been lost over past decades due to livestock grazing, and how much could be removed from the atmosphere if grazing optimization management implemented. The study was carried out by Cesar Terrer, an assistant professor of civil and environmental engineering at MIT; Shuai Ren, a PhD student at the Chinese Academy of Sciences whose thesis is co-supervised by Terrer; and four others.

    “This has been a matter of debate in the scientific literature for a long time,” Terrer says. “In general experiments, grazing decreases soil carbon stocks, but surprisingly, sometimes grazing increases soil carbon stocks, which is why it’s been puzzling.”

    What happens, he explains, is that “grazing could stimulate vegetation growth through easing resource constraints such as light and nutrients, thereby increasing root carbon inputs to soils, where carbon can stay there for centuries or millennia.”

    But that only works up to a certain point, the team found after a careful analysis of 1,473 soil carbon observations from different grazing studies from many locations around the world. “When you cross a threshold in grazing intensity, or the amount of animals grazing there, that is when you start to see sort of a tipping point — a strong decrease in the amount of carbon in the soil,” Terrer explains.

    That loss is thought to be primarily from increased soil erosion on the denuded land. And with that erosion, Terrer says, “basically you lose a lot of the carbon that you have been locking in for centuries.”

    The various studies the team compiled, although they differed somewhat, essentially used similar methodology, which is to fence off a portion of land so that livestock can’t access it, and then after some time take soil samples from within the enclosure area, and from comparable nearby areas that have been grazed, and compare the content of carbon compounds.

    “Along with the data on soil carbon for the control and grazed plots,” he says, “we also collected a bunch of other information, such as the mean annual temperature of the site, mean annual precipitation, plant biomass, and properties of the soil, like pH and nitrogen content. And then, of course, we estimate the grazing intensity — aboveground biomass consumed, because that turns out to be the key parameter.”  

    With artificial intelligence models, the authors quantified the importance of each of these parameters, those drivers of intensity — temperature, precipitation, soil properties — in modulating the sign (positive or negative) and magnitude of the impact of grazing on soil carbon stocks. “Interestingly, we found soil carbon stocks increase and then decrease with grazing intensity, rather than the expected linear response,” says Ren.

    Having developed the model through AI methods and validated it, including by comparing its predictions with those based on underlying physical principles, they can then apply the model to estimating both past and future effects. “In this case,” Terrer says, “we use the model to quantify the historical loses in soil carbon stocks from grazing. And we found that 46 petagrams [billion metric tons] of soil carbon, down to a depth of one meter, have been lost in the last few decades due to grazing.”

    By way of comparison, the total amount of greenhouse gas emissions per year from all fossil fuels is about 10 petagrams, so the loss from grazing equals more than four years’ worth of all the world’s fossil emissions combined.

    What they found was “an overall decline in soil carbon stocks, but with a lot of variability.” Terrer says. The analysis showed that the interplay between grazing intensity and environmental conditions such as temperature could explain the variability, with higher grazing intensity and hotter climates resulting in greater carbon loss. “This means that policy-makers should take into account local abiotic and biotic factors to manage rangelands efficiently,” Ren notes. “By ignoring such complex interactions, we found that using IPCC [Intergovernmental Panel on Climate Change] guidelines would underestimate grazing-induced soil carbon loss by a factor of three globally.”

    Using an approach that incorporates local environmental conditions, the team produced global, high-resolution maps of optimal grazing intensity and the threshold of intensity at which carbon starts to decrease very rapidly. These maps are expected to serve as important benchmarks for evaluating existing grazing practices and provide guidance to local farmers on how to effectively manage their grazing lands.

    Then, using that map, the team estimated how much carbon could be captured if all grazing lands were limited to their optimum grazing intensity. Currently, the authors found, about 20 percent of all pasturelands have crossed the thresholds, leading to severe carbon losses. However, they found that under the optimal levels, global grazing lands would sequester 63 petagrams of carbon. “It is amazing,” Ren says. “This value is roughly equivalent to a 30-year carbon accumulation from global natural forest regrowth.”

    That would be no simple task, of course. To achieve optimal levels, the team found that approximately 75 percent of all grazing areas need to reduce grazing intensity. Overall, if the world seriously reduces the amount of grazing, “you have to reduce the amount of meat that’s available for people,” Terrer says.

    “Another option is to move cattle around,” he says, “from areas that are more severely affected by grazing intensity, to areas that are less affected. Those rotations have been suggested as an opportunity to avoid the more drastic declines in carbon stocks without necessarily reducing the availability of meat.”

    This study didn’t delve into these social and economic implications, Terrer says. “Our role is to just point out what would be the opportunity here. It shows that shifts in diets can be a powerful way to mitigate climate change.”

    “This is a rigorous and careful analysis that provides our best look to date at soil carbon changes due to livestock grazing practiced worldwide,” say Ben Bond-Lamberty, a terrestrial ecosystem research scientist at Pacific Northwest National Laboratory, who was not associated with this work. “The authors’ analysis gives us a unique estimate of soil carbon losses due to grazing and, intriguingly, where and how the process might be reversed.”

    He adds: “One intriguing aspect to this work is the discrepancies between its results and the guidelines currently used by the IPCC — guidelines that affect countries’ commitments, carbon-market pricing, and policies.” However, he says, “As the authors note, the amount of carbon historically grazed soils might be able to take up is small relative to ongoing human emissions. But every little bit helps!”

    “Improved management of working lands can be a powerful tool to combat climate change,” says Jonathan Sanderman, carbon program director of the Woodwell Climate Research Center in Falmouth, Massachusetts, who was not associated with this work. He adds, “This work demonstrates that while, historically, grazing has been a large contributor to climate change, there is significant potential to decrease the climate impact of livestock by optimizing grazing intensity to rebuild lost soil carbon.”

    Terrer states that for now, “we have started a new study, to evaluate the consequences of shifts in diets for carbon stocks. I think that’s the million-dollar question: How much carbon could you sequester, compared to business as usual, if diets shift to more vegan or vegetarian?” The answers will not be simple, because a shift to more vegetable-based diets would require more cropland, which can also have different environmental impacts. Pastures take more land than crops, but produce different kinds of emissions. “What’s the overall impact for climate change? That is the question we’re interested in,” he says.

    The research team included Juan Li, Yingfao Cao, Sheshan Yang, and Dan Liu, all with the  Chinese Academy of Sciences. The work was supported by the Second Tibetan Plateau Scientific Expedition and Research Program, and the Science and Technology Major Project of Tibetan Autonomous Region of China. More

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    Letting the Earth answer back: Designing better planetary conversations

    For Chen Chu MArch ’21, the invitation to join the 2023-24 cohort of Morningside Academy for Design Design Fellows has been an unparalleled opportunity to investigate the potential of design as an alternative method of problem-solving.

    After earning a master’s degree in architecture at MIT and gaining professional experience as a researcher at an environmental nongovernmental organization, Chu decided to pursue a PhD in the Department of Urban Studies and Planning. “I discovered that I needed to engage in a deeper way with the most difficult ethical challenges of our time, especially those arising from the fact of climate change,” he explains. “For me, MIT has always represented this wonderful place where people are inherently intellectually curious — it’s a very rewarding community to be part of.”

    Chu’s PhD research, guided by his doctoral advisor Delia Wendel, assistant professor of urban studies and international development, focuses on how traditional practices of floodplain agriculture can inform local and global strategies for sustainable food production and distribution in response to climate change. 

    Typically located alongside a river or stream, floodplains arise from seasonal flooding patterns that distribute nutrient-rich silt and create connectivity between species. This results in exceptionally high levels of biodiversity and microbial richness, generating the ideal conditions for agriculture. It’s no accident that the first human civilizations were founded on floodplains, including Mesopotamia (named for its location poised between two rivers, the Euphrates and Tigris), the Indus River Civilization, and the cultures of Ancient Egypt based around the Nile. Riverine transportation networks and predictable flooding rhythms provide a framework for trade and cultivation; nonetheless, floodplain communities must learn to live with risk, subject to the sudden disruptions of high waters, drought, and ecological disequilibrium. 

    For Chu, the “unstable and ungovernable” status of floodplains makes them fertile ground for thinking about. “I’m drawn to these so-called ‘wet landscapes’ — edge conditions that act as transitional spaces between land and water, between humans and nature, between city and river,” he reflects. “The development of extensively irrigated agricultural sites is typically a collective effort, which raises intriguing questions about how communities establish social organizations that simultaneously negotiate top-down state control and adapt to the uncertainty of nature.”

    Chu is in the process of honing the focus of his dissertation and refining his data collection methods, which will include archival research and fieldwork, as well as interviews with floodplain inhabitants to gain an understanding of sociopolitical nuances. Meanwhile, his role as a design fellow gives him the space to address the big questions that fire his imagination. How can we live well on shared land? How can we take responsibility for the lives of future generations? What types of political structures are required to get everyone on board? 

    These are just a few of the questions that Chu recently put to his cohort in a presentation. During the weekly seminars for the fellowship, he has the chance to converse with peers and mentors of multiple disciplines — from researchers rethinking the pedagogy of design to entrepreneurs applying design thinking to new business models to architects and engineers developing new habitats to heal our relationship with the natural world. 

    “I’ll admit — I’m wary of the human instinct to problem-solve,” says Chu. “When it comes to the material conditions and lived experience of people and planet, there’s a limit to our economic and political reasoning, and to conventional architectural practice. That said, I do believe that the mindset of a designer can open up new ways of thinking. At its core, design is an interdisciplinary practice based on the understanding that a problem can’t be solved from a narrow, singular perspective.” 

    The stimulating structure of a MAD Fellowship — free from immediate obligations to publish or produce, fellows learn from one another and engage with visiting speakers via regular seminars and events — has prompted Chu to consider what truly makes for generative conversation in the contexts of academia and the private and public sectors. In his opinion, discussions around climate change often fail to take account of one important voice; an absence he describes as “that silent being, the Earth.”

    “You can’t ask the Earth, ‘What does justice mean to you?’ Nature will not respond,” he reflects. To bridge the gap, Chu believes it’s important to combine the study of specific political and social conditions with broader existential questions raised by the environmental humanities. His own research draws upon the perspectives of thinkers including Dipesh Chakrabarty, Donna Haraway, Peter Singer,  Anna Tsing, and Michael Watts, among others. He cites James C. Scott’s lecture “In Praise of Floods” as one of his most important influences.

    In addition to his instinctive appreciation for theory, Chu’s outlook is grounded by an attention to innovation at the local level. He is currently establishing the parameters of his research, examining case studies of agricultural systems and flood mitigation strategies that have been sustained for centuries. 

    “One example is the polder system that is practiced in the Netherlands, China, Bangladesh, and many parts of the world: small, low-lying tracts of land submerged in water and surrounded by dykes and canals,” he explains. “You’ll find a different but comparable strategy in the colder regions of Japan. Crops are protected from the winter winds by constructing a spatial unit with the house at the center; trees behind the house serve as windbreakers and paddy fields for rice are located in front of the house, providing an integrated system of food and livelihood security.”

    Chu observes that there is a tendency for international policymakers to overlook local solutions in favor of grander visions and ambitious climate pledges — but he is equally keen not to romanticize vernacular practices. “Realistically, it’s always a two-way interaction. Unless you already have a workable local system in place, it’s difficult to implement a solution without top-down support. On the other hand, the large-scale technocratic dreams are empty if ignorant of local traditions and histories.” 

    By navigating between the global and the local, the theoretical and the practical, the visionary and the cautionary, Chu has hope in the possibility of gradually finding a way toward long-term solutions that adapt to specific conditions over time. It’s a model of ambition and criticality that Chu sees played out during dialogue at MAD and within his department; at root, he’s aware that the outcome of these conversations depends on the ethical context that shapes them.

    “I’ve been fortunate to have many mentors who have taught me the power of humility; a respect for the finitude, fragility,  and uncertainty of life,” he recalls. “It’s a mindset that’s barely apparent in today’s push for economic growth.” The flip-side of hubristic growth is an assumption that technological ingenuity will be enough to solve the climate crisis, but Chu’s optimism arises from a different source: “When I feel overwhelmed by the weight of the problems we’re facing, I just need to look around me,” he says. “Here on campus — at MAD, in my home department, and increasingly among the new generations of students — there’s a powerful ethos of political sensitivity, ethical compassion, and an attention to clear and critical judgment. That always gives me hope for the planet.” More

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    Reducing pesticide use while increasing effectiveness

    Farming can be a low-margin, high-risk business, subject to weather and climate patterns, insect population cycles, and other unpredictable factors. Farmers need to be savvy managers of the many resources they deal, and chemical fertilizers and pesticides are among their major recurring expenses.

    Despite the importance of these chemicals, a lack of technology that monitors and optimizes sprays has forced farmers to rely on personal experience and rules of thumb to decide how to apply these chemicals. As a result, these chemicals tend to be over-sprayed, leading to their runoff into waterways and buildup up in the soil.

    That could change, thanks to a new approach of feedback-optimized spraying, invented by AgZen, an MIT spinout founded in 2020 by Professor Kripa Varanasi and Vishnu Jayaprakash SM ’19, PhD ’22.

    Play video

    AgZen has developed a system for farming that can monitor exactly how much of the sprayed chemicals adheres to plants, in real time, as the sprayer drives through a field. Built-in software running on a tablet shows the operator exactly how much of each leaf has been covered by the spray.

    Over the past decade, AgZen’s founders have developed products and technologies to control the interactions of droplets and sprays with plant surfaces. The Boston-based venture-backed company launched a new commercial product in 2024 and is currently piloting another related product. Field tests of both have shown the products can help farmers spray more efficiently and effectively, using fewer chemicals overall.

    “Worldwide, farms spend approximately $60 billion a year on pesticides. Our objective is to reduce the number of pesticides sprayed and lighten the financial burden on farms without sacrificing effective pest management,” Varanasi says.

    Getting droplets to stick

    While the world pesticide market is growing rapidly, a lot of the pesticides sprayed don’t reach their target. A significant portion bounces off the plant surfaces, lands on the ground, and becomes part of the runoff that flows to streams and rivers, often causing serious pollution. Some of these pesticides can be carried away by wind over very long distances.

    “Drift, runoff, and poor application efficiency are well-known, longstanding problems in agriculture, but we can fix this by controlling and monitoring how sprayed droplets interact with leaves,” Varanasi says.

    With support from MIT Tata Center and the Abdul Latif Jameel Water and Food Systems Lab, Varanasi and his team analyzed how droplets strike plant surfaces, and explored ways to increase application efficiency. This research led them to develop a novel system of nozzles that cloak droplets with compounds that enhance the retention of droplets on the leaves, a product they call EnhanceCoverage.

    Field studies across regions — from Massachusetts to California to Italy and France —showed that this droplet-optimization system could allow farmers to cut the amount of chemicals needed by more than half because more of the sprayed substances would stick to the leaves.

    Measuring coverage

    However, in trying to bring this technology to market, the researchers faced a sticky problem: Nobody knew how well pesticide sprays were adhering to the plants in the first place, so how could AgZen say that the coverage was better with its new EnhanceCoverage system?

    “I had grown up spraying with a backpack on a small farm in India, so I knew this was an issue,” Jayaprakash says. “When we spoke to growers, they told me how complicated spraying is when you’re on a large machine. Whenever you spray, there are so many things that can influence how effective your spray is. How fast do you drive the sprayer? What flow rate are you using for the chemicals? What chemical are you using? What’s the age of the plants, what’s the nozzle you’re using, what is the weather at the time? All these things influence agrochemical efficiency.”

    Agricultural spraying essentially comes down to dissolving a chemical in water and then spraying droplets onto the plants. “But the interaction between a droplet and the leaf is complex,” Varanasi says. “We were coming in with ways to optimize that, but what the growers told us is, hey, we’ve never even really looked at that in the first place.”

    Although farmers have been spraying agricultural chemicals on a large scale for about 80 years, they’ve “been forced to rely on general rules of thumb and pick all these interlinked parameters, based on what’s worked for them in the past. You pick a set of these parameters, you go spray, and you’re basically praying for outcomes in terms of how effective your pest control is,” Varanasi says.

    Before AgZen could sell farmers on the new system to improve droplet coverage, the company had to invent a way to measure precisely how much spray was adhering to plants in real-time.

    Comparing before and after

    The system they came up with, which they tested extensively on farms across the country last year, involves a unit that can be bolted onto the spraying arm of virtually any sprayer. It carries two sensor stacks, one just ahead of the sprayer nozzles and one behind. Then, built-in software running on a tablet shows the operator exactly how much of each leaf has been covered by the spray. It also computes how much those droplets will spread out or evaporate, leading to a precise estimate of the final coverage.

    “There’s a lot of physics that governs how droplets spread and evaporate, and this has been incorporated into software that a farmer can use,” Varanasi says. “We bring a lot of our expertise into understanding droplets on leaves. All these factors, like how temperature and humidity influence coverage, have always been nebulous in the spraying world. But now you have something that can be exact in determining how well your sprays are doing.”

    “We’re not only measuring coverage, but then we recommend how to act,” says Jayaprakash, who is AgZen’s CEO. “With the information we collect in real-time and by using AI, RealCoverage tells operators how to optimize everything on their sprayer, from which nozzle to use, to how fast to drive, to how many gallons of spray is best for a particular chemical mix on a particular acre of a crop.”

    The tool was developed to prove how much AgZen’s EnhanceCoverage nozzle system (which will be launched in 2025) improves coverage. But it turns out that monitoring and optimizing droplet coverage on leaves in real-time with this system can itself yield major improvements.

    “We worked with large commercial farms last year in specialty and row crops,” Jayaprakash says. “When we saved our pilot customers up to 50 percent of their chemical cost at a large scale, they were very surprised.” He says the tool has reduced chemical costs and volume in fallow field burndowns, weed control in soybeans, defoliation in cotton, and fungicide and insecticide sprays in vegetables and fruits. Along with data from commercial farms, field trials conducted by three leading agricultural universities have also validated these results.

    “Across the board, we were able to save between 30 and 50 percent on chemical costs and increase crop yields by enabling better pest control,” Jayaprakash says. “By focusing on the droplet-leaf interface, our product can help any foliage spray throughout the year, whereas most technological advancements in this space recently have been focused on reducing herbicide use alone.” The company now intends to lease the system across thousands of acres this year.

    And these efficiency gains can lead to significant returns at scale, he emphasizes: In the U.S., farmers currently spend $16 billion a year on chemicals, to protect about $200 billion of crop yields.

    The company launched its first product, the coverage optimization system called RealCoverage, this year, reaching a wide variety of farms with different crops and in different climates. “We’re going from proof-of-concept with pilots in large farms to a truly massive scale on a commercial basis with our lease-to-own program,” Jayaprakash says.

    “We’ve also been tapped by the USDA to help them evaluate practices to minimize pesticides in watersheds,” Varanasi says, noting that RealCoverage can also be useful for regulators, chemical companies, and agricultural equipment manufacturers.

    Once AgZen has proven the effectiveness of using coverage as a decision metric, and after the RealCoverage optimization system is widely in practice, the company will next roll out its second product, EnhanceCoverage, designed to maximize droplet adhesion. Because that system will require replacing all the nozzles on a sprayer, the researchers are doing pilots this year but will wait for a full rollout in 2025, after farmers have gained experience and confidence with their initial product.

    “There is so much wastage,” Varanasi says. “Yet farmers must spray to protect crops, and there is a lot of environmental impact from this. So, after all this work over the years, learning about how droplets stick to surfaces and so on, now the culmination of it in all these products for me is amazing, to see all this come alive, to see that we’ll finally be able to solve the problem we set out to solve and help farmers.” More

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    A new sensor detects harmful “forever chemicals” in drinking water

    MIT chemists have designed a sensor that detects tiny quantities of perfluoroalkyl and polyfluoroalkyl substances (PFAS) — chemicals found in food packaging, nonstick cookware, and many other consumer products.

    These compounds, also known as “forever chemicals” because they do not break down naturally, have been linked to a variety of harmful health effects, including cancer, reproductive problems, and disruption of the immune and endocrine systems.

    Using the new sensor technology, the researchers showed that they could detect PFAS levels as low as 200 parts per trillion in a water sample. The device they designed could offer a way for consumers to test their drinking water, and it could also be useful in industries that rely heavily on PFAS chemicals, including the manufacture of semiconductors and firefighting equipment.

    “There’s a real need for these sensing technologies. We’re stuck with these chemicals for a long time, so we need to be able to detect them and get rid of them,” says Timothy Swager, the John D. MacArthur Professor of Chemistry at MIT and the senior author of the study, which appears this week in the Proceedings of the National Academy of Sciences.

    Other authors of the paper are former MIT postdoc and lead author Sohyun Park and MIT graduate student Collette Gordon.

    Detecting PFAS

    Coatings containing PFAS chemicals are used in thousands of consumer products. In addition to nonstick coatings for cookware, they are also commonly used in water-repellent clothing, stain-resistant fabrics, grease-resistant pizza boxes, cosmetics, and firefighting foams.

    These fluorinated chemicals, which have been in widespread use since the 1950s, can be released into water, air, and soil, from factories, sewage treatment plants, and landfills. They have been found in drinking water sources in all 50 states.

    In 2023, the Environmental Protection Agency created an “advisory health limit” for two of the most hazardous PFAS chemicals, known as perfluorooctanoic acid (PFOA) and perfluorooctyl sulfonate (PFOS). These advisories call for a limit of 0.004 parts per trillion for PFOA and 0.02 parts per trillion for PFOS in drinking water.

    Currently, the only way that a consumer could determine if their drinking water contains PFAS is to send a water sample to a laboratory that performs mass spectrometry testing. However, this process takes several weeks and costs hundreds of dollars.

    To create a cheaper and faster way to test for PFAS, the MIT team designed a sensor based on lateral flow technology — the same approach used for rapid Covid-19 tests and pregnancy tests. Instead of a test strip coated with antibodies, the new sensor is embedded with a special polymer known as polyaniline, which can switch between semiconducting and conducting states when protons are added to the material.

    The researchers deposited these polymers onto a strip of nitrocellulose paper and coated them with a surfactant that can pull fluorocarbons such as PFAS out of a drop of water placed on the strip. When this happens, protons from the PFAS are drawn into the polyaniline and turn it into a conductor, reducing the electrical resistance of the material. This change in resistance, which can be measured precisely using electrodes and sent to an external device such as a smartphone, gives a quantitative measurement of how much PFAS is present.

    This approach works only with PFAS that are acidic, which includes two of the most harmful PFAS — PFOA and perfluorobutanoic acid (PFBA).

    A user-friendly system

    The current version of the sensor can detect concentrations as low as 200 parts per trillion for PFBA, and 400 parts per trillion for PFOA. This is not quite low enough to meet the current EPA guidelines, but the sensor uses only a fraction of a milliliter of water. The researchers are now working on a larger-scale device that would be able to filter about a liter of water through a membrane made of polyaniline, and they believe this approach should increase the sensitivity by more than a hundredfold, with the goal of meeting the very low EPA advisory levels.

    “We do envision a user-friendly, household system,” Swager says. “You can imagine putting in a liter of water, letting it go through the membrane, and you have a device that measures the change in resistance of the membrane.”

    Such a device could offer a less expensive, rapid alternative to current PFAS detection methods. If PFAS are detected in drinking water, there are commercially available filters that can be used on household drinking water to reduce those levels. The new testing approach could also be useful for factories that manufacture products with PFAS chemicals, so they could test whether the water used in their manufacturing process is safe to release into the environment.

    The research was funded by an MIT School of Science Fellowship to Gordon, a Bose Research Grant, and a Fulbright Fellowship to Park. More

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    Gosha Geogdzhayev and Sadhana Lolla named 2024 Gates Cambridge Scholars

    This article was updated on April 23 to reflect the promotion of Gosha Geogdzhayev from alternate to winner of the Gates Cambridge Scholarship.

    MIT seniors Gosha Geogdzhayev and Sadhana Lolla have won the prestigious Gates Cambridge Scholarship, which offers students an opportunity to pursue graduate study in the field of their choice at Cambridge University in the U.K.

    Established in 2000, Gates Cambridge offers full-cost post-graduate scholarships to outstanding applicants from countries outside of the U.K. The mission of Gates Cambridge is to build a global network of future leaders committed to improving the lives of others.

    Gosha Geogdzhayev

    Originally from New York City, Geogdzhayev is a senior majoring in physics with minors in mathematics and computer science. At Cambridge, Geogdzhayev intends to pursue an MPhil in quantitative climate and environmental science. He is interested in applying these subjects to climate science and intends to spend his career developing novel statistical methods for climate prediction.

    At MIT, Geogdzhayev researches climate emulators with Professor Raffaele Ferrari’s group in the Department of Earth, Atmospheric and Planetary Sciences and is part of the “Bringing Computation to the Climate Challenge” Grand Challenges project. He is currently working on an operator-based emulator for the projection of climate extremes. Previously, Geogdzhayev studied the statistics of changing chaotic systems, work that has recently been published as a first-author paper.

    As a recipient of the National Oceanic and Atmospheric Agency (NOAA) Hollings Scholarship, Geogdzhayev has worked on bias correction methods for climate data at the NOAA Geophysical Fluid Dynamics Laboratory. He is the recipient of several other awards in the field of earth and atmospheric sciences, notably the American Meteorological Society Ward and Eileen Seguin Scholarship.

    Outside of research, Geogdzhayev enjoys writing poetry and is actively involved with his living community, Burton 1, for which he has previously served as floor chair.

    Sadhana Lolla

    Lolla, a senior from Clarksburg, Maryland, is majoring in computer science and minoring in mathematics and literature. At Cambridge, she will pursue an MPhil in technology policy.

    In the future, Lolla aims to lead conversations on deploying and developing technology for marginalized communities, such as the rural Indian village that her family calls home, while also conducting research in embodied intelligence.

    At MIT, Lolla conducts research on safe and trustworthy robotics and deep learning at the Distributed Robotics Laboratory with Professor Daniela Rus. Her research has spanned debiasing strategies for autonomous vehicles and accelerating robotic design processes. At Microsoft Research and Themis AI, she works on creating uncertainty-aware frameworks for deep learning, which has impacts across computational biology, language modeling, and robotics. She has presented her work at the Neural Information Processing Systems (NeurIPS) conference and the International Conference on Machine Learning (ICML). 

    Outside of research, Lolla leads initiatives to make computer science education more accessible globally. She is an instructor for class 6.s191 (MIT Introduction to Deep Learning), one of the largest AI courses in the world, which reaches millions of students annually. She serves as the curriculum lead for Momentum AI, the only U.S. program that teaches AI to underserved students for free, and she has taught hundreds of students in Northern Scotland as part of the MIT Global Teaching Labs program.

    Lolla was also the director for xFair, MIT’s largest student-run career fair, and is an executive board member for Next Sing, where she works to make a cappella more accessible for students across musical backgrounds. In her free time, she enjoys singing, solving crossword puzzles, and baking. More

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    MIT researchers remotely map crops, field by field

    Crop maps help scientists and policymakers track global food supplies and estimate how they might shift with climate change and growing populations. But getting accurate maps of the types of crops that are grown from farm to farm often requires on-the-ground surveys that only a handful of countries have the resources to maintain.

    Now, MIT engineers have developed a method to quickly and accurately label and map crop types without requiring in-person assessments of every single farm. The team’s method uses a combination of Google Street View images, machine learning, and satellite data to automatically determine the crops grown throughout a region, from one fraction of an acre to the next. 

    The researchers used the technique to automatically generate the first nationwide crop map of Thailand — a smallholder country where small, independent farms make up the predominant form of agriculture. The team created a border-to-border map of Thailand’s four major crops — rice, cassava, sugarcane, and maize — and determined which of the four types was grown, at every 10 meters, and without gaps, across the entire country. The resulting map achieved an accuracy of 93 percent, which the researchers say is comparable to on-the-ground mapping efforts in high-income, big-farm countries.

    The team is applying their mapping technique to other countries such as India, where small farms sustain most of the population but the type of crops grown from farm to farm has historically been poorly recorded.

    “It’s a longstanding gap in knowledge about what is grown around the world,” says Sherrie Wang, the d’Arbeloff Career Development Assistant Professor in MIT’s Department of Mechanical Engineering, and the Institute for Data, Systems, and Society (IDSS). “The final goal is to understand agricultural outcomes like yield, and how to farm more sustainably. One of the key preliminary steps is to map what is even being grown — the more granularly you can map, the more questions you can answer.”

    Wang, along with MIT graduate student Jordi Laguarta Soler and Thomas Friedel of the agtech company PEAT GmbH, will present a paper detailing their mapping method later this month at the AAAI Conference on Artificial Intelligence.

    Ground truth

    Smallholder farms are often run by a single family or farmer, who subsist on the crops and livestock that they raise. It’s estimated that smallholder farms support two-thirds of the world’s rural population and produce 80 percent of the world’s food. Keeping tabs on what is grown and where is essential to tracking and forecasting food supplies around the world. But the majority of these small farms are in low to middle-income countries, where few resources are devoted to keeping track of individual farms’ crop types and yields.

    Crop mapping efforts are mainly carried out in high-income regions such as the United States and Europe, where government agricultural agencies oversee crop surveys and send assessors to farms to label crops from field to field. These “ground truth” labels are then fed into machine-learning models that make connections between the ground labels of actual crops and satellite signals of the same fields. They then label and map wider swaths of farmland that assessors don’t cover but that satellites automatically do.

    “What’s lacking in low- and middle-income countries is this ground label that we can associate with satellite signals,” Laguarta Soler says. “Getting these ground truths to train a model in the first place has been limited in most of the world.”

    The team realized that, while many developing countries do not have the resources to maintain crop surveys, they could potentially use another source of ground data: roadside imagery, captured by services such as Google Street View and Mapillary, which send cars throughout a region to take continuous 360-degree images with dashcams and rooftop cameras.

    In recent years, such services have been able to access low- and middle-income countries. While the goal of these services is not specifically to capture images of crops, the MIT team saw that they could search the roadside images to identify crops.

    Cropped image

    In their new study, the researchers worked with Google Street View (GSV) images taken throughout Thailand — a country that the service has recently imaged fairly thoroughly, and which consists predominantly of smallholder farms.

    Starting with over 200,000 GSV images randomly sampled across Thailand, the team filtered out images that depicted buildings, trees, and general vegetation. About 81,000 images were crop-related. They set aside 2,000 of these, which they sent to an agronomist, who determined and labeled each crop type by eye. They then trained a convolutional neural network to automatically generate crop labels for the other 79,000 images, using various training methods, including iNaturalist — a web-based crowdsourced  biodiversity database, and GPT-4V, a “multimodal large language model” that enables a user to input an image and ask the model to identify what the image is depicting. For each of the 81,000 images, the model generated a label of one of four crops that the image was likely depicting — rice, maize, sugarcane, or cassava.

    The researchers then paired each labeled image with the corresponding satellite data taken of the same location throughout a single growing season. These satellite data include measurements across multiple wavelengths, such as a location’s greenness and its reflectivity (which can be a sign of water). 

    “Each type of crop has a certain signature across these different bands, which changes throughout a growing season,” Laguarta Soler notes.

    The team trained a second model to make associations between a location’s satellite data and its corresponding crop label. They then used this model to process satellite data taken of the rest of the country, where crop labels were not generated or available. From the associations that the model learned, it then assigned crop labels across Thailand, generating a country-wide map of crop types, at a resolution of 10 square meters.

    This first-of-its-kind crop map included locations corresponding to the 2,000 GSV images that the researchers originally set aside, that were labeled by arborists. These human-labeled images were used to validate the map’s labels, and when the team looked to see whether the map’s labels matched the expert, “gold standard” labels, it did so 93 percent of the time.

    “In the U.S., we’re also looking at over 90 percent accuracy, whereas with previous work in India, we’ve only seen 75 percent because ground labels are limited,” Wang says. “Now we can create these labels in a cheap and automated way.”

    The researchers are moving to map crops across India, where roadside images via Google Street View and other services have recently become available.

    “There are over 150 million smallholder farmers in India,” Wang says. “India is covered in agriculture, almost wall-to-wall farms, but very small farms, and historically it’s been very difficult to create maps of India because there are very sparse ground labels.”

    The team is working to generate crop maps in India, which could be used to inform policies having to do with assessing and bolstering yields, as global temperatures and populations rise.

    “What would be interesting would be to create these maps over time,” Wang says. “Then you could start to see trends, and we can try to relate those things to anything like changes in climate and policies.” More

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    Anushree Chaudhuri: Involving local communities in renewable energy planning

    Anushree Chaudhuri has a history of making bold decisions. In fifth grade, she biked across her home state of California with little prior experience. In her first year at MIT, she advocated for student recommendations in the preparation of the Institute’s Climate Action Plan for the Decade. And recently, she led a field research project throughout California to document the perspectives of rural and Indigenous populations affected by climate change and clean energy projects.

    “It doesn’t matter who you are or how young you are, you can get involved with something and inspire others to do so,” the senior says.

    Initially a materials science and engineering major, Chaudhuri was quickly drawn to environmental policy issues and later decided to double-major in urban studies and planning and in economics. Chaudhuri will receive her bachelor’s degrees this month, followed by a master’s degree in city planning in the spring.

    The importance of community engagement in policymaking has become one of Chaudhuri’s core interests. A 2024 Marshall Scholar, she is headed to the U.K. next year to pursue a PhD related to environment and development. She hopes to build on her work in California and continue to bring attention to impacts that energy transitions can have on local communities, which tend to be rural and low-income. Addressing resistance to these projects can be challenging, but “ignoring it leaves these communities in the dust and widens the urban-rural divide,” she says.

    Silliness and sustainability 

    Chaudhuri classifies her many activities into two groups: those that help her unwind, like her living community, Conner Two, and those that require intensive deliberation, like her sustainability-related organizing.

    Conner Two, in the Burton-Conner residence hall, is where Chaudhuri feels most at home on campus. She describes the group’s activities as “silly” and emphasizes their love of jokes, even in the floor’s nickname, “the British Floor,” which is intentionally absurd, as the residents are rarely British.

    Chaudhuri’s first involvement with sustainability issues on campus was during the preparation of MIT’s Fast Forward Climate Action Plan in the 2020-2021 academic year. As a co-lead of one of several student working groups, she helped organize key discussions between the administration, climate experts, and student government to push for six main goals in the plan, including an ethical investing framework. Being involved with a significant student movement so early on in her undergraduate career was a learning opportunity for Chaudhuri and impressed upon her that young people can play critical roles in making far-reaching structural changes.

    The experience also made her realize how many organizations on campus shared similar goals even if their perspectives varied, and she saw the potential for more synergy among them.

    Chaudhuri went on to co-lead the Student Sustainability Coalition to help build community across the sustainability-related organizations on campus and create a centralized system that would make it easier for outsiders and group members to access information and work together. Through the coalition, students have collaborated on efforts including campus events, and off-campus matters such as the Cambridge Green New Deal hearings.

    Another benefit to such a network: It creates a support system that recognizes even small-scale victories. “Community is so important to avoid burnout when you’re working on something that can be very frustrating and an uphill battle like negotiating with leadership or seeking policy changes,” Chaudhuri says.

    Fieldwork

    For the past year, Chaudhuri has been doing independent research in California with the support of several advisory organizations to host conversations with groups affected by renewable energy projects, which, as she has documented, are often concentrated in rural, low-income, and Indigenous communities. The introduction of renewable energy facilities, such as wind and solar farms, can perpetuate existing inequities if they ignore serious community concerns, Chaudhuri says.

    As state or federal policymakers and private developers carry out the permitting process for these projects, “they can repeat histories of extraction, sometimes infringing on the rights of a local or Tribal government to decide what happens with their land,” she says.

    In her site visits, she is documenting community opposition to controversial solar and wind proposals and collecting oral histories. Doing fieldwork for the first time as an outsider was difficult for Chaudhuri, as she dealt with distrust, unpredictability, and needing to be completely flexible for her sources. “A lot of it was just being willing to drop everything and go and be a little bit adventurous and take some risks,” she says.

    Role models and reading

    Chaudhuri is quick to credit many of the role models and other formative influences in her life.

    After working on the Climate Action Plan, Chaudhuri attended a public narrative workshop at Harvard University led by Marshall Ganz, a grassroots community organizer who worked with Cesar Chavez and on the 2008 Obama presidential campaign. “That was a big inspiration and kind of shaped how I viewed leadership in, for example, campus advocacy, but also in other projects and internships.”

    Reading has also influenced Chaudhuri’s perspective on community organizing, “After the Climate Action Plan campaign, I realized that a lot of what made the campaign successful or not could track well with organizing and social change theories, and histories of social movements. So, that was a good experience for me, being able to critically reflect on it and tie it into these other things I was learning about.”

    Since beginning her studies at MIT, Chaudhuri has become especially interested in social theory and political philosophy, starting with ancient forms of Western and Eastern ethic, and up to 20th and 21st century philosophers who inspire her. Chaudhuri cites Amartya Sen and Olúfẹ́mi Táíwò as particularly influential. “I think [they’ve] provided a really compelling framework to guide a lot of my own values,” she says.

    Another role model is Brenda Mallory, the current chair of the U.S. Council on Environmental Quality, who Chaudhuri was grateful to meet at the United Nations COP27 Climate Conference. As an intern at the U.S. Department of Energy, Chaudhuri worked within a team on implementing the federal administration’s Justice40 initiative, which commits 40 percent of federal climate investments to disadvantaged communities. This initiative was largely directed by Mallory, and Chaudhuri admires how Mallory was able to make an impact at different levels of government through her leadership. Chaudhuri hopes to follow in Mallory’s footsteps someday, as a public official committed to just policies and programs.

     “Good leaders are those who empower good leadership in others,” Chaudhuri says. More

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    Study measures the psychological toll of wildfires

    Wildfires in Southeast Asia significantly affect peoples’ moods, especially if the fires originate outside a person’s own country, according to a new study.

    The study, which measures sentiment by analyzing large amounts of social media data, helps show the psychological toll of wildfires that result in substantial air pollution, at a time when such fires are becoming a high-profile marker of climate change.  

    “It has a substantial negative impact on people’s subjective well-being,” says Siqi Zheng, an MIT professor and co-author of a new paper detailing the results. “This is a big effect.”

    The magnitude of the effect is about the same as another shift uncovered through large-scale studies of sentiment expressed online: When the weekend ends and the work week starts, people’s online postings reflect a sharp drop in mood. The new study finds that daily exposure to typical wildfire smoke levels in the region produces an equivalently large change in sentiment.

    “People feel anxious or sad when they have to go to work on Monday, and what we find with the fires is that this is, in fact, comparable to a Sunday-to-Monday sentiment drop,” says co-author Rui Du, a former MIT postdoct who is now an economist at Oklahoma State University.

    The paper, “Transboundary Vegetation Fire Smoke and Expressed Sentiment: Evidence from Twitter,” has been published online in the Journal of Environmental Economics and Management.

    The authors are Zheng, who is the STL Champion Professor of Urban and Real Estate Sustainability in the Center for Real Estate and the Department of Urban Studies and Planning at MIT; Du, an assistant professor of economics at Oklahoma State University’s Spears School of Business; Ajkel Mino, of the Department of Data Science and Knowledge Engineering at Maastricht University; and Jianghao Wang, of the Institute of Geographic Sciences and Natural Resources Research at the Chinese Academy of Sciences.

    The research is based on an examination of the events of 2019 in Southeast Asia, in which a huge series of Indonesian wildfires, seemingly related to climate change and deforestation for the palm oil industry, produced a massive amount of haze in the region. The air-quality problems affected seven countries: Brunei, Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam.

    To conduct the study, the scholars produced a large-scale analysis of postings from 2019 on X (formerly known as Twitter) to sample public sentiment. The study involved 1,270,927 tweets from 378,300 users who agreed to have their locations made available. The researchers compiled the data with a web crawler program and multilingual natural language processing applications that review the content of tweets and rate them in affective terms based on the vocabulary used. They also used satellite data from NASA and NOAA to create a map of wildfires and haze over time, linking that to the social media data.

    Using this method creates an advantage that regular public-opinion polling does not have: It creates a measurement of mood that is effectively a real-time metric rather than an after-the-fact assessment. Moreover, substantial wind shifts in the region at the time in 2019 essentially randomize which countries were exposed to more haze at various points, making the results less likely to be influenced by other factors.

    The researchers also made a point to disentangle the sentiment change due to wildfire smoke and that due to other factors. After all, people experience mood changes all the time from various natural and socioeconomic events. Wildfires may be correlated with some of them, which makes it hard to tease out the singular effect of the smoke. By comparing only the difference in exposure to wildfire smoke, blown in by wind, within the same locations over time, this study is able to isolate the impact of local wildfire haze on mood, filtering out nonpollution influences.

    “What we are seeing from our estimates is really just the pure causal effect of the transboundary wildfire smoke,” Du says.

    The study also revealed that people living near international borders are much more likely to be upset when affected by wildfire smoke that comes from a neighboring country. When similar conditions originate in their own country, there is a considerably more muted reaction.

    “Notably, individuals do not seem to respond to domestically produced fire plumes,” the authors write in the paper. The small size of many countries in the region, coupled with a fire-prone climate, make this an ongoing source of concern, however.

    “In Southeast Asia this is really a big problem, with small countries clustered together,” Zheng observes.

    Zheng also co-authored a 2022 study using a related methodology to study the impact of the Covid-19 pandemic on the moods of residents in about 100 countries. In that case, the research showed that the global pandemic depressed sentiment about 4.7 times as much as the normal Sunday-to-Monday shift.

    “There was a huge toll of Covid on people’s sentiment, and while the impact of the wildfires was about one-fifth of Covid, that’s still quite large,” Du says.

    In policy terms, Zheng suggests that the global implications of cross-border smoke pollution could give countries a shared incentive to cooperate further. If one country’s fires become another country’s problem, they may all have reason to limit them. Scientists warn of a rising number of wildfires globally, fueled by climate change conditions in which more fires can proliferate, posing a persistent threat across societies.

    “If they don’t work on this collaboratively, it could be damaging to everyone,” Zheng says.

    The research at MIT was supported, in part, by the MIT Sustainable Urbanization Lab. Jianghao Wang was supported by the National Natural Science Foundation of China. More