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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

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      in Energy

      Cobalt-free batteries could power cars of the future

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      Many electric vehicles are powered by batteries that contain cobalt — a metal that carries high financial, environmental, and social costs.

      MIT researchers have now designed a battery material that could offer a more sustainable way to power electric cars. The new lithium-ion battery includes a cathode based on organic materials, instead of cobalt or nickel (another metal often used in lithium-ion batteries).

      In a new study, the researchers showed that this material, which could be produced at much lower cost than cobalt-containing batteries, can conduct electricity at similar rates as cobalt batteries. The new battery also has comparable storage capacity and can be charged up faster than cobalt batteries, the researchers report.

      “I think this material could have a big impact because it works really well,” says Mircea Dincă, the W.M. Keck Professor of Energy at MIT. “It is already competitive with incumbent technologies, and it can save a lot of the cost and pain and environmental issues related to mining the metals that currently go into batteries.”

      Dincă is the senior author of the study, which appears today in the journal ACS Central Science. Tianyang Chen PhD ’23 and Harish Banda, a former MIT postdoc, are the lead authors of the paper. Other authors include Jiande Wang, an MIT postdoc; Julius Oppenheim, an MIT graduate student; and Alessandro Franceschi, a research fellow at the University of Bologna.

      Alternatives to cobalt

      Most electric cars are powered by lithium-ion batteries, a type of battery that is recharged when lithium ions flow from a positively charged electrode, called a cathode, to a negatively electrode, called an anode. In most lithium-ion batteries, the cathode contains cobalt, a metal that offers high stability and energy density.

      However, cobalt has significant downsides. A scarce metal, its price can fluctuate dramatically, and much of the world’s cobalt deposits are located in politically unstable countries. Cobalt extraction creates hazardous working conditions and generates toxic waste that contaminates land, air, and water surrounding the mines.

      “Cobalt batteries can store a lot of energy, and they have all of features that people care about in terms of performance, but they have the issue of not being widely available, and the cost fluctuates broadly with commodity prices. And, as you transition to a much higher proportion of electrified vehicles in the consumer market, it’s certainly going to get more expensive,” Dincă says.

      Because of the many drawbacks to cobalt, a great deal of research has gone into trying to develop alternative battery materials. One such material is lithium-iron-phosphate (LFP), which some car manufacturers are beginning to use in electric vehicles. Although still practically useful, LFP has only about half the energy density of cobalt and nickel batteries.

      Another appealing option are organic materials, but so far most of these materials have not been able to match the conductivity, storage capacity, and lifetime of cobalt-containing batteries. Because of their low conductivity, such materials typically need to be mixed with binders such as polymers, which help them maintain a conductive network. These binders, which make up at least 50 percent of the overall material, bring down the battery’s storage capacity.

      About six years ago, Dincă’s lab began working on a project, funded by Lamborghini, to develop an organic battery that could be used to power electric cars. While working on porous materials that were partly organic and partly inorganic, Dincă and his students realized that a fully organic material they had made appeared that it might be a strong conductor.

      This material consists of many layers of TAQ (bis-tetraaminobenzoquinone), an organic small molecule that contains three fused hexagonal rings. These layers can extend outward in every direction, forming a structure similar to graphite. Within the molecules are chemical groups called quinones, which are the electron reservoirs, and amines, which help the material to form strong hydrogen bonds.

      Those hydrogen bonds make the material highly stable and also very insoluble. That insolubility is important because it prevents the material from dissolving into the battery electrolyte, as some organic battery materials do, thereby extending its lifetime.

      “One of the main methods of degradation for organic materials is that they simply dissolve into the battery electrolyte and cross over to the other side of the battery, essentially creating a short circuit. If you make the material completely insoluble, that process doesn’t happen, so we can go to over 2,000 charge cycles with minimal degradation,” Dincă says.

      Strong performance

      Tests of this material showed that its conductivity and storage capacity were comparable to that of traditional cobalt-containing batteries. Also, batteries with a TAQ cathode can be charged and discharged faster than existing batteries, which could speed up the charging rate for electric vehicles.

      To stabilize the organic material and increase its ability to adhere to the battery’s current collector, which is made of copper or aluminum, the researchers added filler materials such as cellulose and rubber. These fillers make up less than one-tenth of the overall cathode composite, so they don’t significantly reduce the battery’s storage capacity.

      These fillers also extend the lifetime of the battery cathode by preventing it from cracking when lithium ions flow into the cathode as the battery charges.

      The primary materials needed to manufacture this type of cathode are a quinone precursor and an amine precursor, which are already commercially available and produced in large quantities as commodity chemicals. The researchers estimate that the material cost of assembling these organic batteries could be about one-third to one-half the cost of cobalt batteries.

      Lamborghini has licensed the patent on the technology. Dincă’s lab plans to continue developing alternative battery materials and is exploring possible replacement of lithium with sodium or magnesium, which are cheaper and more abundant than lithium. More

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      in Environment

      K. Lisa Yang Global Engineering and Research Center will prioritize innovations for resource-constrained communities

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      Billions of people worldwide face threats to their livelihood, health, and well-being due to poverty. These problems persist because solutions offered in developed countries often do not meet the requirements — related to factors like price, performance, usability, robustness, and culture — of poor or developing countries. Academic labs frequently try to tackle these challenges, but often to no avail because they lack real-world, on-the-ground knowledge from key stakeholders, and because they do not have an efficient, reliable means of converting breakthroughs to real-world impact.

      The new K. Lisa Yang Global Engineering and Research (GEAR) Center at MIT, founded with a $28 million gift from philanthropist and investor Lisa Yang, aims to rethink how products and technologies for resource-constrained communities are conceived, designed, and commercialized. A collaboration between MIT’s School of Engineering and School of Science, the Yang GEAR Center will bring together a multidisciplinary team of MIT researchers to assess today’s most pressing global challenges in three critical areas: global health, climate change mitigation and adaptation, and the water-energy-food nexus.

      “As she has shown over and over through her philanthropy, Lisa Yang shares MIT’s passion for connecting fundamental research and real-world data to create positive impact,” says MIT president Sally Kornbluth. “I’m grateful for her powerful vision and incredible generosity in founding the K. Lisa Yang GEAR Center. I can’t imagine a better use of MIT’s talents than working to improve the lives and health of people around the world.”

      Yang’s gift expands her exceptional philanthropic support of human health and basic science research at MIT over the past six years. Yang GEAR Center will join MIT’s Yang Tan Collective, an assemblage of six major research centers focused on accelerating collaboration in basic science, research, and engineering to realize translational strategies that improve human health and well-being at a global scale.

      “Billions of people face daily life-or-death challenges that could be improved with elegant technologies,” says Yang. “And yet I’ve learned how many products and tools created by top engineers don’t make it out of the lab. They may look like clever ideas during the prototype phase, but they are entirely ill-suited to the communities they were designed for. I am very excited about the potential of a deliberate and thoughtful engineering effort that will prioritize the design of technologies for use in impoverished communities.”

      Cost, material availability, cultural suitability, and other market mismatches hinder many major innovations in global health, food, and water from being translated to use in resource-constrained communities. Yang GEAR Center will support a major research and design program with its mission to strategically identify compelling challenges and associated scientific knowledge gaps in resource-constrained communities then address them through academic innovation to create and translate transformative technologies.

      The center will be led by Amos Winter, associate professor of mechanical engineering, whose lab focuses on creating technologies that marry innovative, low-cost design with an in-depth understanding of the unique socioeconomic constraints of emerging markets.

      “Academia has a key role to play in solving the historically unsolvable challenges in resource-constrained communities,” says Winter. “However, academic research is often disconnected from the real-world requirements that must be satisfied to make meaningful change. Yang GEAR Center will be a catalyst for innovation to impact by helping colleagues identify compelling problems and focus their talents on realizing real-world solutions, and by providing mechanisms for commercial dissemination. I am extremely grateful to find in Lisa a partner who shares a vision for how academic research can play a more efficient and targeted role in addressing the needs of the world’s most disadvantaged populations.”

      The backbone of the Yang GEAR Center will be a team of seasoned research scientists and engineers. These individuals will scout real-world problems and distill the relevant research questions then help assemble collaborative teams. As projects develop, center staff will mentor students, build and conduct field pilots, and foster relationships with stakeholders around the world. They will be strategically positioned to translate technology at the end of projects through licensing and startups. Center staff and collaborators will focus on creating products and services for climate-driven migrants, such as solar-powered energy and water networks; technologies for reducing atmospheric carbon and promoting the hydrogen economy; brackish water desalination and irrigation solutions; and high-performance, global health diagnostics and devices.

      For instance, a Yang GEAR Center team focused on creating water-saving and solar-powered irrigation solutions for farmers in the Middle East and North Africa will continue its work in the region. They will conduct exploratory research; build a team of stakeholders, including farmers, agricultural outreach organizations, irrigation hardware manufacturers, retailers, water and agriculture scientists, and local government officials; design, rigorously test, and iterate prototypes both in the lab and in the field; and conduct large-scale field trials to garner user feedback and pave the way to product commercialization.

      “Grounded in foundational scientific research and blended with excellence in the humanities, MIT provides a framework that integrates people, economics, research, and innovation. By incorporating multiple perspectives — and being attentive to the needs and cultures of the people who will ultimately rely on research outcomes — MIT can have the greatest impact in areas of health, climate science, and resource security,” says Nergis Mavalvala, dean of the School of Science and the Curtis and Kathleen Marble Professor of Astrophysics.

      An overarching aim for the center will be to educate graduates who are global engineers, designers, and researchers positioned for a career of addressing compelling, high-impact challenges. The center includes four endowed Hock E. Tan GEAR Center Fellowships that will support graduate students and/or postdoctoral fellows eager to enter the field of global engineering. The fellowships are named for MIT alumnus and Broadcom CEO Hock E. Tan ’75 SM ’75.

      “I am thrilled that the Yang GEAR Center is taking a leading role in training problem-solvers who will rethink how products and inventions can help communities facing the most pressing challenges of our time,” adds Anantha Chandrakasan, dean of the School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “These talented young students,  postdocs, and staff have the potential to reach across disciplines — and across the globe — to truly transform the impact engineering can have in the future.” More

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      in Energy

      Study reveals a reaction at the heart of many renewable energy technologies

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      A key chemical reaction — in which the movement of protons between the surface of an electrode and an electrolyte drives an electric current — is a critical step in many energy technologies, including fuel cells and the electrolyzers used to produce hydrogen gas.

      For the first time, MIT chemists have mapped out in detail how these proton-coupled electron transfers happen at an electrode surface. Their results could help researchers design more efficient fuel cells, batteries, or other energy technologies.

      “Our advance in this paper was studying and understanding the nature of how these electrons and protons couple at a surface site, which is relevant for catalytic reactions that are important in the context of energy conversion devices or catalytic reactions,” says Yogesh Surendranath, a professor of chemistry and chemical engineering at MIT and the senior author of the study.

      Among their findings, the researchers were able to trace exactly how changes in the pH of the electrolyte solution surrounding an electrode affect the rate of proton motion and electron flow within the electrode.

      MIT graduate student Noah Lewis is the lead author of the paper, which appears today in Nature Chemistry. Ryan Bisbey, a former MIT postdoc; Karl Westendorff, an MIT graduate student; and Alexander Soudackov, a research scientist at Yale University, are also authors of the paper.

      Passing protons

      Proton-coupled electron transfer occurs when a molecule, often water or an acid, transfers a proton to another molecule or to an electrode surface, which stimulates the proton acceptor to also take up an electron. This kind of reaction has been harnessed for many energy applications.

      “These proton-coupled electron transfer reactions are ubiquitous. They are often key steps in catalytic mechanisms, and are particularly important for energy conversion processes such as hydrogen generation or fuel cell catalysis,” Surendranath says.

      In a hydrogen-generating electrolyzer, this approach is used to remove protons from water and add electrons to the protons to form hydrogen gas. In a fuel cell, electricity is generated when protons and electrons are removed from hydrogen gas and added to oxygen to form water.

      Proton-coupled electron transfer is common in many other types of chemical reactions, for example, carbon dioxide reduction (the conversion of carbon dioxide into chemical fuels by adding electrons and protons). Scientists have learned a great deal about how these reactions occur when the proton acceptors are molecules, because they can precisely control the structure of each molecule and observe how electrons and protons pass between them. However, when proton-coupled electron transfer occurs at the surface of an electrode, the process is much more difficult to study because electrode surfaces are usually very heterogenous, with many different sites that a proton could potentially bind to.

      To overcome that obstacle, the MIT team developed a way to design electrode surfaces that gives them much more precise control over the composition of the electrode surface. Their electrodes consist of sheets of graphene with organic, ring-containing compounds attached to the surface. At the end of each of these organic molecules is a negatively charged oxygen ion that can accept protons from the surrounding solution, which causes an electron to flow from the circuit into the graphitic surface.

      “We can create an electrode that doesn’t consist of a wide diversity of sites but is a uniform array of a single type of very well-defined sites that can each bind a proton with the same affinity,” Surendranath says. “Since we have these very well-defined sites, what this allowed us to do was really unravel the kinetics of these processes.”

      Using this system, the researchers were able to measure the flow of electrical current to the electrodes, which allowed them to calculate the rate of proton transfer to the oxygen ion at the surface at equilibrium — the state when the rates of proton donation to the surface and proton transfer back to solution from the surface are equal. They found that the pH of the surrounding solution has a significant effect on this rate: The highest rates occurred at the extreme ends of the pH scale — pH 0, the most acidic, and pH 14, the most basic.

      To explain these results, researchers developed a model based on two possible reactions that can occur at the electrode. In the first, hydronium ions (H3O+), which are in high concentration in strongly acidic solutions, deliver protons to the surface oxygen ions, generating water. In the second, water delivers protons to the surface oxygen ions, generating hydroxide ions (OH-), which are in high concentration in strongly basic solutions.

      However, the rate at pH 0 is about four times faster than the rate at pH 14, in part because hydronium gives up protons at a faster rate than water.

      A reaction to reconsider

      The researchers also discovered, to their surprise, that the two reactions have equal rates not at neutral pH 7, where hydronium and hydroxide concentrations are equal, but at pH 10, where the concentration of hydroxide ions is 1 million times that of hydronium. The model suggests this is because the forward reaction involving proton donation from hydronium or water contributes more to the overall rate than the backward reaction involving proton removal by water or hydroxide.

      Existing models of how these reactions occur at electrode surfaces assume that the forward and backward reactions contribute equally to the overall rate, so the new findings suggest that those models may need to be reconsidered, the researchers say.

      “That’s the default assumption, that the forward and reverse reactions contribute equally to the reaction rate,” Surendranath says. “Our finding is really eye-opening because it means that the assumption that people are using to analyze everything from fuel cell catalysis to hydrogen evolution may be something we need to revisit.”

      The researchers are now using their experimental setup to study how adding different types of ions to the electrolyte solution surrounding the electrode may speed up or slow down the rate of proton-coupled electron flow.

      “With our system, we know that our sites are constant and not affecting each other, so we can read out what the change in the solution is doing to the reaction at the surface,” Lewis says.

      The research was funded by the U.S. Department of Energy Office of Basic Energy Sciences. More