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      in Environment

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

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      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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      in Energy

      Tests show high-temperature superconducting magnets are ready for fusion

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      In the predawn hours of Sept. 5, 2021, engineers achieved a major milestone in the labs of MIT’s Plasma Science and Fusion Center (PSFC), when a new type of magnet, made from high-temperature superconducting material, achieved a world-record magnetic field strength of 20 tesla for a large-scale magnet. That’s the intensity needed to build a fusion power plant that is expected to produce a net output of power and potentially usher in an era of virtually limitless power production.

      The test was immediately declared a success, having met all the criteria established for the design of the new fusion device, dubbed SPARC, for which the magnets are the key enabling technology. Champagne corks popped as the weary team of experimenters, who had labored long and hard to make the achievement possible, celebrated their accomplishment.

      But that was far from the end of the process. Over the ensuing months, the team tore apart and inspected the components of the magnet, pored over and analyzed the data from hundreds of instruments that recorded details of the tests, and performed two additional test runs on the same magnet, ultimately pushing it to its breaking point in order to learn the details of any possible failure modes.

      All of this work has now culminated in a detailed report by researchers at PSFC and MIT spinout company Commonwealth Fusion Systems (CFS), published in a collection of six peer-reviewed papers in a special edition of the March issue of IEEE Transactions on Applied Superconductivity. Together, the papers describe the design and fabrication of the magnet and the diagnostic equipment needed to evaluate its performance, as well as the lessons learned from the process. Overall, the team found, the predictions and computer modeling were spot-on, verifying that the magnet’s unique design elements could serve as the foundation for a fusion power plant.

      Enabling practical fusion power

      The successful test of the magnet, says Hitachi America Professor of Engineering Dennis Whyte, who recently stepped down as director of the PSFC, was “the most important thing, in my opinion, in the last 30 years of fusion research.”

      Before the Sept. 5 demonstration, the best-available superconducting magnets were powerful enough to potentially achieve fusion energy — but only at sizes and costs that could never be practical or economically viable. Then, when the tests showed the practicality of such a strong magnet at a greatly reduced size, “overnight, it basically changed the cost per watt of a fusion reactor by a factor of almost 40 in one day,” Whyte says.

      “Now fusion has a chance,” Whyte adds. Tokamaks, the most widely used design for experimental fusion devices, “have a chance, in my opinion, of being economical because you’ve got a quantum change in your ability, with the known confinement physics rules, about being able to greatly reduce the size and the cost of objects that would make fusion possible.”

      The comprehensive data and analysis from the PSFC’s magnet test, as detailed in the six new papers, has demonstrated that plans for a new generation of fusion devices — the one designed by MIT and CFS, as well as similar designs by other commercial fusion companies — are built on a solid foundation in science.

      The superconducting breakthrough

      Fusion, the process of combining light atoms to form heavier ones, powers the sun and stars, but harnessing that process on Earth has proved to be a daunting challenge, with decades of hard work and many billions of dollars spent on experimental devices. The long-sought, but never yet achieved, goal is to build a fusion power plant that produces more energy than it consumes. Such a power plant could produce electricity without emitting greenhouse gases during operation, and generating very little radioactive waste. Fusion’s fuel, a form of hydrogen that can be derived from seawater, is virtually limitless.

      But to make it work requires compressing the fuel at extraordinarily high temperatures and pressures, and since no known material could withstand such temperatures, the fuel must be held in place by extremely powerful magnetic fields. Producing such strong fields requires superconducting magnets, but all previous fusion magnets have been made with a superconducting material that requires frigid temperatures of about 4 degrees above absolute zero (4 kelvins, or -270 degrees Celsius). In the last few years, a newer material nicknamed REBCO, for rare-earth barium copper oxide, was added to fusion magnets, and allows them to operate at 20 kelvins, a temperature that despite being only 16 kelvins warmer, brings significant advantages in terms of material properties and practical engineering.

      Taking advantage of this new higher-temperature superconducting material was not just a matter of substituting it in existing magnet designs. Instead, “it was a rework from the ground up of almost all the principles that you use to build superconducting magnets,” Whyte says. The new REBCO material is “extraordinarily different than the previous generation of superconductors. You’re not just going to adapt and replace, you’re actually going to innovate from the ground up.” The new papers in Transactions on Applied Superconductivity describe the details of that redesign process, now that patent protection is in place.

      A key innovation: no insulation

      One of the dramatic innovations, which had many others in the field skeptical of its chances of success, was the elimination of insulation around the thin, flat ribbons of superconducting tape that formed the magnet. Like virtually all electrical wires, conventional superconducting magnets are fully protected by insulating material to prevent short-circuits between the wires. But in the new magnet, the tape was left completely bare; the engineers relied on REBCO’s much greater conductivity to keep the current flowing through the material.

      “When we started this project, in let’s say 2018, the technology of using high-temperature superconductors to build large-scale high-field magnets was in its infancy,” says Zach Hartwig, the Robert N. Noyce Career Development Professor in the Department of Nuclear Science and Engineering. Hartwig has a co-appointment at the PSFC and is the head of its engineering group, which led the magnet development project. “The state of the art was small benchtop experiments, not really representative of what it takes to build a full-size thing. Our magnet development project started at benchtop scale and ended up at full scale in a short amount of time,” he adds, noting that the team built a 20,000-pound magnet that produced a steady, even magnetic field of just over 20 tesla — far beyond any such field ever produced at large scale.

      “The standard way to build these magnets is you would wind the conductor and you have insulation between the windings, and you need insulation to deal with the high voltages that are generated during off-normal events such as a shutdown.” Eliminating the layers of insulation, he says, “has the advantage of being a low-voltage system. It greatly simplifies the fabrication processes and schedule.” It also leaves more room for other elements, such as more cooling or more structure for strength.

      The magnet assembly is a slightly smaller-scale version of the ones that will form the donut-shaped chamber of the SPARC fusion device now being built by CFS in Devens, Massachusetts. It consists of 16 plates, called pancakes, each bearing a spiral winding of the superconducting tape on one side and cooling channels for helium gas on the other.

      But the no-insulation design was considered risky, and a lot was riding on the test program. “This was the first magnet at any sufficient scale that really probed what is involved in designing and building and testing a magnet with this so-called no-insulation no-twist technology,” Hartwig says. “It was very much a surprise to the community when we announced that it was a no-insulation coil.”

      Pushing to the limit … and beyond

      The initial test, described in previous papers, proved that the design and manufacturing process not only worked but was highly stable — something that some researchers had doubted. The next two test runs, also performed in late 2021, then pushed the device to the limit by deliberately creating unstable conditions, including a complete shutoff of incoming power that can lead to a catastrophic overheating. Known as quenching, this is considered a worst-case scenario for the operation of such magnets, with the potential to destroy the equipment.

      Part of the mission of the test program, Hartwig says, was “to actually go off and intentionally quench a full-scale magnet, so that we can get the critical data at the right scale and the right conditions to advance the science, to validate the design codes, and then to take the magnet apart and see what went wrong, why did it go wrong, and how do we take the next iteration toward fixing that. … It was a very successful test.”

      That final test, which ended with the melting of one corner of one of the 16 pancakes, produced a wealth of new information, Hartwig says. For one thing, they had been using several different computational models to design and predict the performance of various aspects of the magnet’s performance, and for the most part, the models agreed in their overall predictions and were well-validated by the series of tests and real-world measurements. But in predicting the effect of the quench, the model predictions diverged, so it was necessary to get the experimental data to evaluate the models’ validity.

      “The highest-fidelity models that we had predicted almost exactly how the magnet would warm up, to what degree it would warm up as it started to quench, and where would the resulting damage to the magnet would be,” he says. As described in detail in one of the new reports, “That test actually told us exactly the physics that was going on, and it told us which models were useful going forward and which to leave by the wayside because they’re not right.”

      Whyte says, “Basically we did the worst thing possible to a coil, on purpose, after we had tested all other aspects of the coil performance. And we found that most of the coil survived with no damage,” while one isolated area sustained some melting. “It’s like a few percent of the volume of the coil that got damaged.” And that led to revisions in the design that are expected to prevent such damage in the actual fusion device magnets, even under the most extreme conditions.

      Hartwig emphasizes that a major reason the team was able to accomplish such a radical new record-setting magnet design, and get it right the very first time and on a breakneck schedule, was thanks to the deep level of knowledge, expertise, and equipment accumulated over decades of operation of the Alcator C-Mod tokamak, the Francis Bitter Magnet Laboratory, and other work carried out at PSFC. “This goes to the heart of the institutional capabilities of a place like this,” he says. “We had the capability, the infrastructure, and the space and the people to do these things under one roof.”

      The collaboration with CFS was also key, he says, with MIT and CFS combining the most powerful aspects of an academic institution and private company to do things together that neither could have done on their own. “For example, one of the major contributions from CFS was leveraging the power of a private company to establish and scale up a supply chain at an unprecedented level and timeline for the most critical material in the project: 300 kilometers (186 miles) of high-temperature superconductor, which was procured with rigorous quality control in under a year, and integrated on schedule into the magnet.”

      The integration of the two teams, those from MIT and those from CFS, also was crucial to the success, he says. “We thought of ourselves as one team, and that made it possible to do what we did.” More

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      in Energy

      With just a little electricity, MIT researchers boost common catalytic reactions

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      A simple technique that uses small amounts of energy could boost the efficiency of some key chemical processing reactions, by up to a factor of 100,000, MIT researchers report. These reactions are at the heart of petrochemical processing, pharmaceutical manufacturing, and many other industrial chemical processes.

      The surprising findings are reported today in the journal Science, in a paper by MIT graduate student Karl Westendorff, professors Yogesh Surendranath and Yuriy Roman-Leshkov, and two others.

      “The results are really striking,” says Surendranath, a professor of chemistry and chemical engineering. Rate increases of that magnitude have been seen before but in a different class of catalytic reactions known as redox half-reactions, which involve the gain or loss of an electron. The dramatically increased rates reported in the new study “have never been observed for reactions that don’t involve oxidation or reduction,” he says.

      The non-redox chemical reactions studied by the MIT team are catalyzed by acids. “If you’re a first-year chemistry student, probably the first type of catalyst you learn about is an acid catalyst,” Surendranath says. There are many hundreds of such acid-catalyzed reactions, “and they’re super important in everything from processing petrochemical feedstocks to making commodity chemicals to doing transformations in pharmaceutical products. The list goes on and on.”

      “These reactions are key to making many products we use daily,” adds Roman-Leshkov, a professor of chemical engineering and chemistry.

      But the people who study redox half-reactions, also known as electrochemical reactions, are part of an entirely different research community than those studying non-redox chemical reactions, known as thermochemical reactions. As a result, even though the technique used in the new study, which involves applying a small external voltage, was well-known in the electrochemical research community, it had not been systematically applied to acid-catalyzed thermochemical reactions.

      People working on thermochemical catalysis, Surendranath says, “usually don’t consider” the role of the electrochemical potential at the catalyst surface, “and they often don’t have good ways of measuring it. And what this study tells us is that relatively small changes, on the order of a few hundred millivolts, can have huge impacts — orders of magnitude changes in the rates of catalyzed reactions at those surfaces.”

      “This overlooked parameter of surface potential is something we should pay a lot of attention to because it can have a really, really outsized effect,” he says. “It changes the paradigm of how we think about catalysis.”

      Chemists traditionally think about surface catalysis based on the chemical binding energy of molecules to active sites on the surface, which influences the amount of energy needed for the reaction, he says. But the new findings show that the electrostatic environment is “equally important in defining the rate of the reaction.”

      The team has already filed a provisional patent application on parts of the process and is working on ways to apply the findings to specific chemical processes. Westendorff says their findings suggest that “we should design and develop different types of reactors to take advantage of this sort of strategy. And we’re working right now on scaling up these systems.”

      While their experiments so far were done with a two-dimensional planar electrode, most industrial reactions are run in three-dimensional vessels filled with powders. Catalysts are distributed through those powders, providing a lot more surface area for the reactions to take place. “We’re looking at how catalysis is currently done in industry and how we can design systems that take advantage of the already existing infrastructure,” Westendorff says.

      Surendranath adds that these new findings “raise tantalizing possibilities: Is this a more general phenomenon? Does electrochemical potential play a key role in other reaction classes as well? In our mind, this reshapes how we think about designing catalysts and promoting their reactivity.”

      Roman-Leshkov adds that “traditionally people who work in thermochemical catalysis would not associate these reactions with electrochemical processes at all. However, introducing this perspective to the community will redefine how we can integrate electrochemical characteristics into thermochemical catalysis. It will have a big impact on the community in general.”

      While there has typically been little interaction between electrochemical and thermochemical catalysis researchers, Surendranath says, “this study shows the community that there’s really a blurring of the line between the two, and that there is a huge opportunity in cross-fertilization between these two communities.”

      Westerndorff adds that to make it work, “you have to design a system that’s pretty unconventional to either community to isolate this effect.” And that helps explain why such a dramatic effect had never been seen before. He notes that even their paper’s editor asked them why this effect hadn’t been reported before. The answer has to do with “how disparate those two ideologies were before this,” he says. “It’s not just that people don’t really talk to each other. There are deep methodological differences between how the two communities conduct experiments. And this work is really, we think, a great step toward bridging the two.”

      In practice, the findings could lead to far more efficient production of a wide variety of chemical materials, the team says. “You get orders of magnitude changes in rate with very little energy input,” Surendranath says. “That’s what’s amazing about it.”

      The findings, he says, “build a more holistic picture of how catalytic reactions at interfaces work, irrespective of whether you’re going to bin them into the category of electrochemical reactions or thermochemical reactions.” He adds that “it’s rare that you find something that could really revise our foundational understanding of surface catalytic reactions in general. We’re very excited.”

      “This research is of the highest quality,” says Costas Vayenas, a professor of engineering at the university of Patras, in Greece, who was not associated with the study. The work “is very promising for practical applications, particularly since it extends previous related work in redox catalytic systems,” he says.

      The team included MIT postdoc Max Hulsey PhD ’22 and graduate student Thejas Wesley PhD ’23, and was supported by the Air Force Office of Scientific Research and the U.S. Department of Energy Basic Energy Sciences. More

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      in Environment

      MIT researchers remotely map crops, field by field

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      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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      in Environment

      Study measures the psychological toll of wildfires

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      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

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      in Environment

      Study: Global deforestation leads to more mercury pollution

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      About 10 percent of human-made mercury emissions into the atmosphere each year are the result of global deforestation, according to a new MIT study.

      The world’s vegetation, from the Amazon rainforest to the savannahs of sub-Saharan Africa, acts as a sink that removes the toxic pollutant from the air. However, if the current rate of deforestation remains unchanged or accelerates, the researchers estimate that net mercury emissions will keep increasing.

      “We’ve been overlooking a significant source of mercury, especially in tropical regions,” says Ari Feinberg, a former postdoc in the Institute for Data, Systems, and Society (IDSS) and lead author of the study.

      The researchers’ model shows that the Amazon rainforest plays a particularly important role as a mercury sink, contributing about 30 percent of the global land sink. Curbing Amazon deforestation could thus have a substantial impact on reducing mercury pollution.

      The team also estimates that global reforestation efforts could increase annual mercury uptake by about 5 percent. While this is significant, the researchers emphasize that reforestation alone should not be a substitute for worldwide pollution control efforts.

      “Countries have put a lot of effort into reducing mercury emissions, especially northern industrialized countries, and for very good reason. But 10 percent of the global anthropogenic source is substantial, and there is a potential for that to be even greater in the future. [Addressing these deforestation-related emissions] needs to be part of the solution,” says senior author Noelle Selin, a professor in IDSS and MIT’s Department of Earth, Atmospheric and Planetary Sciences.

      Feinberg and Selin are joined on the paper by co-authors Martin Jiskra, a former Swiss National Science Foundation Ambizione Fellow at the University of Basel; Pasquale Borrelli, a professor at Roma Tre University in Italy; and Jagannath Biswakarma, a postdoc at the Swiss Federal Institute of Aquatic Science and Technology. The paper appears today in Environmental Science and Technology.

      Modeling mercury

      Over the past few decades, scientists have generally focused on studying deforestation as a source of global carbon dioxide emissions. Mercury, a trace element, hasn’t received the same attention, partly because the terrestrial biosphere’s role in the global mercury cycle has only recently been better quantified.

      Plant leaves take up mercury from the atmosphere, in a similar way as they take up carbon dioxide. But unlike carbon dioxide, mercury doesn’t play an essential biological function for plants. Mercury largely stays within a leaf until it falls to the forest floor, where the mercury is absorbed by the soil.

      Mercury becomes a serious concern for humans if it ends up in water bodies, where it can become methylated by microorganisms. Methylmercury, a potent neurotoxin, can be taken up by fish and bioaccumulated through the food chain. This can lead to risky levels of methylmercury in the fish humans eat.

      “In soils, mercury is much more tightly bound than it would be if it were deposited in the ocean. The forests are doing a sort of ecosystem service, in that they are sequestering mercury for longer timescales,” says Feinberg, who is now a postdoc in the Blas Cabrera Institute of Physical Chemistry in Spain.

      In this way, forests reduce the amount of toxic methylmercury in oceans.

      Many studies of mercury focus on industrial sources, like burning fossil fuels, small-scale gold mining, and metal smelting. A global treaty, the 2013 Minamata Convention, calls on nations to reduce human-made emissions. However, it doesn’t directly consider impacts of deforestation.

      The researchers launched their study to fill in that missing piece.

      In past work, they had built a model to probe the role vegetation plays in mercury uptake. Using a series of land use change scenarios, they adjusted the model to quantify the role of deforestation.

      Evaluating emissions

      This chemical transport model tracks mercury from its emissions sources to where it is chemically transformed in the atmosphere and then ultimately to where it is deposited, mainly through rainfall or uptake into forest ecosystems.

      They divided the Earth into eight regions and performed simulations to calculate deforestation emissions factors for each, considering elements like type and density of vegetation, mercury content in soils, and historical land use.

      However, good data for some regions were hard to come by.

      They lacked measurements from tropical Africa or Southeast Asia — two areas that experience heavy deforestation. To get around this gap, they used simpler, offline models to simulate hundreds of scenarios, which helped them improve their estimations of potential uncertainties.

      They also developed a new formulation for mercury emissions from soil. This formulation captures the fact that deforestation reduces leaf area, which increases the amount of sunlight that hits the ground and accelerates the outgassing of mercury from soils.

      The model divides the world into grid squares, each of which is a few hundred square kilometers. By changing land surface and vegetation parameters in certain squares to represent deforestation and reforestation scenarios, the researchers can capture impacts on the mercury cycle.

      Overall, they found that about 200 tons of mercury are emitted to the atmosphere as the result of deforestation, or about 10 percent of total human-made emissions. But in tropical and sub-tropical countries, deforestation emissions represent a higher percentage of total emissions. For example, in Brazil deforestation emissions are 40 percent of total human-made emissions.

      In addition, people often light fires to prepare tropical forested areas for agricultural activities, which causes more emissions by releasing mercury stored by vegetation.

      “If deforestation was a country, it would be the second highest emitting country, after China, which emits around 500 tons of mercury a year,” Feinberg adds.

      And since the Minamata Convention is now addressing primary mercury emissions, scientists can expect deforestation to become a larger fraction of human-made emissions in the future.

      “Policies to protect forests or cut them down have unintended effects beyond their target. It is important to consider the fact that these are systems, and they involve human activities, and we need to understand them better in order to actually solve the problems that we know are out there,” Selin says.

      By providing this first estimate, the team hopes to inspire more research in this area.

      In the future, they want to incorporate more dynamic Earth system models into their analysis, which would enable them to interactively track mercury uptake and better model the timescale of vegetation regrowth.

      “This paper represents an important advance in our understanding of global mercury cycling by quantifying a pathway that has long been suggested but not yet quantified. Much of our research to date has focused on primary anthropogenic emissions — those directly resulting from human activity via coal combustion or mercury-gold amalgam burning in artisanal and small-scale gold mining,” says Jackie Gerson, an assistant professor in the Department of Earth and Environmental Sciences at Michigan State University, who was not involved with this research. “This research shows that deforestation can also result in substantial mercury emissions and needs to be considered both in terms of global mercury models and land management policies. It therefore has the potential to advance our field scientifically as well as to promote policies that reduce mercury emissions via deforestation.

      This work was funded, in part, by the U.S. National Science Foundation, the Swiss National Science Foundation, and Swiss Federal Institute of Aquatic Science and Technology. More

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      in Energy

      MIT researchers map the energy transition’s effects on jobs

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      A new analysis by MIT researchers shows the places in the U.S. where jobs are most linked to fossil fuels. The research could help policymakers better identify and support areas affected over time by a switch to renewable energy.

      While many of the places most potentially affected have intensive drilling and mining operations, the study also measures how areas reliant on other industries, such as heavy manufacturing, could experience changes. The research examines the entire U.S. on a county-by-county level.

      “Our result is that you see a higher carbon footprint for jobs in places that drill for oil, mine for coal, and drill for natural gas, which is evident in our maps,” says Christopher Knittel, an economist at the MIT Sloan School of Management and co-author of a new paper detailing the findings. “But you also see high carbon footprints in areas where we do a lot of manufacturing, which is more likely to be missed by policymakers when examining how the transition to a zero-carbon economy will affect jobs.”

      So, while certain U.S. areas known for fossil-fuel production would certainly be affected — including west Texas, the Powder River Basin of Montana and Wyoming, parts of Appalachia, and more — a variety of industrial areas in the Great Plains and Midwest could see employment evolve as well.

      The paper, “Assessing the distribution of employment vulnerability to the energy transition using employment carbon footprints,” is published this week in Proceedings of the National Academy of Sciences. The authors are Kailin Graham, a master’s student in MIT’s Technology and Policy Program and graduate research assistant at MIT’s Center for Energy and Environmental Policy Research; and Knittel, who is the George P. Shultz Professor at MIT Sloan.

      “Our results are unique in that we cover close to the entire U.S. economy and consider the impacts on places that produce fossil fuels but also on places that consume a lot of coal, oil, or natural gas for energy,” says Graham. “This approach gives us a much more complete picture of where communities might be affected and how support should be targeted.”

      Adjusting the targets

      The current study stems from prior research Knittel has conducted, measuring carbon footprints at the household level across the U.S. The new project takes a conceptually related approach, but for jobs in a given county. To conduct the study, the researchers used several data sources measuring energy consumption by businesses, as well as detailed employment data from the U.S. Census Bureau.

      The study takes advantage of changes in energy supply and demand over time to estimate how strongly a full range of jobs, not just those in energy production, are linked to use of fossil fuels. The sectors accounted for in the study comprise 86 percent of U.S. employment, and 94 percent of U.S. emissions apart from the transportation sector.

      The Inflation Reduction Act, passed by Congress and signed into law by President Joe Biden in August 2022, is the first federal legislation seeking to provide an economic buffer for places affected by the transition away from fossil fuels. The act provides expanded tax credits for economic projects located in “energy community” areas — defined largely as places with high fossil-fuel industry employment or tax revenue and with high unemployment. Areas with recently closed or downsized coal mines or power plants also qualify.

      Graham and Knittel measured the “employment carbon footprint” (ECF) of each county in the U.S., producing new results. Out of more than 3,000 counties in the U.S., the researchers found that 124 are at the 90th percentile or above in ECF terms, while not qualifying for Inflation Reduction Act assistance. Another 79 counties are eligible for Inflation Reduction Act assistance, while being in the bottom 20 percent nationally in ECF terms.

      Those may not seem like colossal differences, but the findings identify real communities potentially being left out of federal policy, and highlight the need for new targeting of such programs. The research by Graham and Knittel offers a precise way to assess the industrial composition of U.S. counties, potentially helping to target economic assistance programs.

      “The impact on jobs of the energy transition is not just going to be where oil and natural gas are drilled, it’s going to be all the way up and down the value chain of things we make in the U.S.,” Knittel says. “That’s a more extensive, but still focused, problem.”

      Graham adds: “It’s important that policymakers understand these economy-wide employment impacts. Our aim in providing these data is to help policymakers incorporate these considerations into future policies like the Inflation Reduction Act.”

      Adapting policy

      Graham and Knittel are still evaluating what the best policy measures might be to help places in the U.S. adapt to a move away from fossil fuels.

      “What we haven’t necessarily closed the loop on is the right way to build a policy that takes account of these factors,” Knittel says. “The Inflation Reduction Act is the first policy to think about a [fair] energy transition because it has these subsidies for energy-dependent counties.” But given enough political backing, there may be room for additional policy measures in this area.

      One thing clearly showing through in the study’s data is that many U.S. counties are in a variety of situations, so there may be no one-size-fits-all approach to encouraging economic growth while making a switch to clean energy. What suits west Texas or Wyoming best may not work for more manufacturing-based local economies. And even among primary energy-production areas, there may be distinctions, among those drilling for oil or natural gas and those producing coal, based on the particular economics of those fuels. The study includes in-depth data about each county, characterizing its industrial portfolio, which may help tailor approaches to a range of economic situations.

      “The next step is using this data more specifically to design policies to protect these communities,” Knittel says. More

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      in Environment

      New tool predicts flood risk from hurricanes in a warming climate

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      Coastal cities and communities will face more frequent major hurricanes with climate change in the coming years. To help prepare coastal cities against future storms, MIT scientists have developed a method to predict how much flooding a coastal community is likely to experience as hurricanes evolve over the next decades.

      When hurricanes make landfall, strong winds whip up salty ocean waters that generate storm surge in coastal regions. As the storms move over land, torrential rainfall can induce further flooding inland. When multiple flood sources such as storm surge and rainfall interact, they can compound a hurricane’s hazards, leading to significantly more flooding than would result from any one source alone. The new study introduces a physics-based method for predicting how the risk of such complex, compound flooding may evolve under a warming climate in coastal cities.

      One example of compound flooding’s impact is the aftermath from Hurricane Sandy in 2012. The storm made landfall on the East Coast of the United States as heavy winds whipped up a towering storm surge that combined with rainfall-driven flooding in some areas to cause historic and devastating floods across New York and New Jersey.

      In their study, the MIT team applied the new compound flood-modeling method to New York City to predict how climate change may influence the risk of compound flooding from Sandy-like hurricanes over the next decades.  

      They found that, in today’s climate, a Sandy-level compound flooding event will likely hit New York City every 150 years. By midcentury, a warmer climate will drive up the frequency of such flooding, to every 60 years. At the end of the century, destructive Sandy-like floods will deluge the city every 30 years — a fivefold increase compared to the present climate.

      “Long-term average damages from weather hazards are usually dominated by the rare, intense events like Hurricane Sandy,” says study co-author Kerry Emanuel, professor emeritus of atmospheric science at MIT. “It is important to get these right.”

      While these are sobering projections, the researchers hope the flood forecasts can help city planners prepare and protect against future disasters. “Our methodology equips coastal city authorities and policymakers with essential tools to conduct compound flooding risk assessments from hurricanes in coastal cities at a detailed, granular level, extending to each street or building, in both current and future decades,” says study author Ali Sarhadi, a postdoc in MIT’s Department of Earth, Atmospheric and Planetary Sciences.

      The team’s open-access study appears online today in the Bulletin of the American Meteorological Society. Co-authors include Raphaël Rousseau-Rizzi at MIT’s Lorenz Center, Kyle Mandli at Columbia University, Jeffrey Neal at the University of Bristol, Michael Wiper at the Charles III University of Madrid, and Monika Feldmann at the Swiss Federal Institute of Technology Lausanne.

      The seeds of floods

      To forecast a region’s flood risk, weather modelers typically look to the past. Historical records contain measurements of previous hurricanes’ wind speeds, rainfall, and spatial extent, which scientists use to predict where and how much flooding may occur with coming storms. But Sarhadi believes that the limitations and brevity of these historical records are insufficient for predicting future hurricanes’ risks.

      “Even if we had lengthy historical records, they wouldn’t be a good guide for future risks because of climate change,” he says. “Climate change is changing the structural characteristics, frequency, intensity, and movement of hurricanes, and we cannot rely on the past.”

      Sarhadi and his colleagues instead looked to predict a region’s risk of hurricane flooding in a changing climate using a physics-based risk assessment methodology. They first paired simulations of hurricane activity with coupled ocean and atmospheric models over time. With the hurricane simulations, developed originally by Emanuel, the researchers virtually scatter tens of thousands of “seeds” of hurricanes into a simulated climate. Most seeds dissipate, while a few grow into category-level storms, depending on the conditions of the ocean and atmosphere.

      When the team drives these hurricane simulations with climate models of ocean and atmospheric conditions under certain global temperature projections, they can see how hurricanes change, for instance in terms of intensity, frequency, and size, under past, current, and future climate conditions.

      The team then sought to precisely predict the level and degree of compound flooding from future hurricanes in coastal cities. The researchers first used rainfall models to simulate rain intensity for a large number of simulated hurricanes, then applied numerical models to hydraulically translate that rainfall intensity into flooding on the ground during landfalling of hurricanes, given information about a region such as its surface and topography characteristics. They also simulated the same hurricanes’ storm surges, using hydrodynamic models to translate hurricanes’ maximum wind speed and sea level pressure into surge height in coastal areas. The simulation further assessed the propagation of ocean waters into coastal areas, causing coastal flooding.

      Then, the team developed a numerical hydrodynamic model to predict how two sources of hurricane-induced flooding, such as storm surge and rain-driven flooding, would simultaneously interact through time and space, as simulated hurricanes make landfall in coastal regions such as New York City, in both current and future climates.  

      “There’s a complex, nonlinear hydrodynamic interaction between saltwater surge-driven flooding and freshwater rainfall-driven flooding, that forms compound flooding that a lot of existing methods ignore,” Sarhadi says. “As a result, they underestimate the risk of compound flooding.”

      Amplified risk

      With their flood-forecasting method in place, the team applied it to a specific test case: New York City. They used the multipronged method to predict the city’s risk of compound flooding from hurricanes, and more specifically from Sandy-like hurricanes, in present and future climates. Their simulations showed that the city’s odds of experiencing Sandy-like flooding will increase significantly over the next decades as the climate warms, from once every 150 years in the current climate, to every 60 years by 2050, and every 30 years by 2099.

      Interestingly, they found that much of this increase in risk has less to do with how hurricanes themselves will change with warming climates, but with how sea levels will increase around the world.

      “In future decades, we will experience sea level rise in coastal areas, and we also incorporated that effect into our models to see how much that would increase the risk of compound flooding,” Sarhadi explains. “And in fact, we see sea level rise is playing a major role in amplifying the risk of compound flooding from hurricanes in New York City.”

      The team’s methodology can be applied to any coastal city to assess the risk of compound flooding from hurricanes and extratropical storms. With this approach, Sarhadi hopes decision-makers can make informed decisions regarding the implementation of adaptive measures, such as reinforcing coastal defenses to enhance infrastructure and community resilience.

      “Another aspect highlighting the urgency of our research is the projected 25 percent increase in coastal populations by midcentury, leading to heightened exposure to damaging storms,” Sarhadi says. “Additionally, we have trillions of dollars in assets situated in coastal flood-prone areas, necessitating proactive strategies to reduce damages from compound flooding from hurricanes under a warming climate.”

      This research was supported, in part, by Homesite Insurance. More