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      in Environment

      Shining a light on oil fields to make them more sustainable

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      Operating an oil field is complex and there is a staggeringly long list of things that can go wrong.

      One of the most common problems is spills of the salty brine that’s a toxic byproduct of pumping oil. Another is over- or under-pumping that can lead to machine failure and methane leaks. (The oil and gas industry is the largest industrial emitter of methane in the U.S.) Then there are extreme weather events, which range from winter frosts to blazing heat, that can put equipment out of commission for months. One of the wildest problems Sebastien Mannai SM ’14, PhD ’18 has encountered are hogs that pop open oil tanks with their snouts to enjoy on-demand oil baths.

      Mannai helps oil field owners detect and respond to these problems while optimizing the operation of their machinery to prevent the issues from occurring in the first place. He is the founder and CEO of Amplified Industries, a company selling oil field monitoring and control tools that help make the industry more efficient and sustainable.

      Amplified Industries’ sensors and analytics give oil well operators real-time alerts when things go wrong, allowing them to respond to issues before they become disasters.

      “We’re able to find 99 percent of the issues affecting these machines, from mechanical failures to human errors, including issues happening thousands of feet underground,” Mannai explains. “With our AI solution, operators can put the wells on autopilot, and the system automatically adjusts or shuts the well down as soon as there’s an issue.”

      Amplified currently works with private companies in states spanning from Texas to Wyoming, that own and operate as many as 3,000 wells. Such companies make up the majority of oil well operators in the U.S. and operate both new and older, more failure-prone equipment that has been in the field for decades.

      Such operators also have a harder time responding to environmental regulations like the Environmental Protection Agency’s new methane guidelines, which seek to dramatically reduce emissions of the potent greenhouse gas in the industry over the next few years.

      “These operators don’t want to be releasing methane,” Mannai explains. “Additionally, when gas gets into the pumping equipment, it leads to premature failures. We can detect gas and slow the pump down to prevent it. It’s the best of both worlds: The operators benefit because their machines are working better, saving them money while also giving them a smaller environmental footprint with fewer spills and methane leaks.”

      Leveraging “every MIT resource I possibly could”

      Mannai learned about the cutting-edge technology used in the space and aviation industries as he pursued his master’s degree at the Gas Turbine Laboratory in MIT’s Department of Aeronautics and Astronautics. Then, during his PhD at MIT, he worked with an oil services company and discovered the oil and gas industry was still relying on decades-old technologies and equipment.

      “When I first traveled to the field, I could not believe how old-school the actual operations were,” says Mannai, who has previously worked in rocket engine and turbine factories. “A lot of oil wells have to be adjusted by feel and rules of thumb. The operators have been let down by industrial automation and data companies.”

      Monitoring oil wells for problems typically requires someone in a pickup truck to drive hundreds of miles between wells looking for obvious issues, Mannai says. The sensors that are deployed are expensive and difficult to replace. Over time, they’re also often damaged in the field to the point of being unusable, forcing technicians to make educated guesses about the status of each well.

      “We often see that equipment unplugged or programmed incorrectly because it is incredibly over-complicated and ill-designed for the reality of the field,” Mannai says. “Workers on the ground often have to rip it out and bypass the control system to pump by hand. That’s how you end up with so many spills and wells pumping at suboptimal levels.”

      To build a better oil field monitoring system, Mannai received support from the MIT Sandbox Innovation Fund and the Venture Mentoring Service (VMS). He also participated in the delta V summer accelerator at the Martin Trust Center for MIT Entrepreneurship, the fuse program during IAP, and the MIT I-Corps program, and took a number of classes at the MIT Sloan School of Management. In 2019, Amplified Industries — which operated under the name Acoustic Wells until recently — won the MIT $100K Entrepreneurship competition.

      “My approach was to sign up to every possible entrepreneurship related program and to leverage every MIT resource I possibly could,” Mannai says. “MIT was amazing for us.”

      Mannai officially launched the company after his postdoc at MIT, and Amplified raised its first round of funding in early 2020. That year, Amplified’s small team moved into the Greentown Labs startup incubator in Somerville.

      Mannai says building the company’s battery-powered, low-cost sensors was a huge challenge. The sensors run machine-learning inference models and their batteries last for 10 years. They also had to be able to handle extreme conditions, from the scorching hot New Mexico desert to the swamps of Louisiana and the freezing cold winters in North Dakota.

      “We build very rugged, resilient hardware; it’s a must in those environments” Mannai says. “But it’s also very simple to deploy, so if a device does break, it’s like changing a lightbulb: We ship them a new one and it takes them a couple of minutes to swap it out.”

      Customers equip each well with four or five of Amplified’s sensors, which attach to the well’s cables and pipes to measure variables like tension, pressure, and amps. Vast amounts of data are then sent to Amplified’s cloud and processed by their analytics engine. Signal processing methods and AI models are used to diagnose problems and control the equipment in real-time, while generating notifications for the operators when something goes wrong. Operators can then remotely adjust the well or shut it down.

      “That’s where AI is important, because if you just record everything and put it in a giant dashboard, you create way more work for people,” Mannai says. “The critical part is the ability to process and understand this newly recorded data and make it readily usable in the real world.”

      Amplified’s dashboard is customized for different people in the company, so field technicians can quickly respond to problems and managers or owners can get a high-level view of how everything is running.

      Mannai says often when Amplified’s sensors are installed, they’ll immediately start detecting problems that were unknown to engineers and technicians in the field. To date, Amplified has prevented hundreds of thousands of gallons worth of brine water spills, which are particularly damaging to surrounding vegetation because of their high salt and sulfur content.

      Preventing those spills is only part of Amplified’s positive environmental impact; the company is now turning its attention toward the detection of methane leaks.

      Helping a changing industry

      The EPA’s proposed new Waste Emissions Charge for oil and gas companies would start at $900 per metric ton of reported methane emissions in 2024 and increase to $1,500 per metric ton in 2026 and beyond.

      Mannai says Amplified is well-positioned to help companies comply with the new rules. Its equipment has already showed it can detect various kinds of leaks across the field, purely based on analytics of existing data.

      “Detecting methane leaks typically requires someone to walk around every valve and piece of piping with a thermal camera or sniffer, but these operators often have thousands of valves and hundreds of miles of pipes,” Mannai says. “What we see in the field is that a lot of times people don’t know where the pipes are because oil wells change owners so frequently, or they will miss an intermittent leak.”

      Ultimately Mannai believes a strong data backend and modernized sensing equipment will become the backbone of the industry, and is a necessary prerequisite to both improving efficiency and cleaning up the industry.

      “We’re selling a service that ensures your equipment is working optimally all the time,” Mannai says. “That means a lot fewer fines from the EPA, but it also means better-performing equipment. There’s a mindset change happening across the industry, and we’re helping make that transition as easy and affordable as possible.” More

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      in Environment

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

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

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

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

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

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

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

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

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

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

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      in Energy

      A delicate dance

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      In early 2022, economist Catherine Wolfram was at her desk in the U.S. Treasury building. She could see the east wing of the White House, just steps away.

      Russia had just invaded Ukraine, and Wolfram was thinking about Russia, oil, and sanctions. She and her colleagues had been tasked with figuring out how to restrict the revenues that Russia was using to fuel its brutal war while keeping Russian oil available and affordable to the countries that depended on it.

      Now the William F. Pounds Professor of Energy Economics at MIT, Wolfram was on leave from academia to serve as deputy assistant secretary for climate and energy economics.

      Working for Treasury Secretary Janet L. Yellen, Wolfram and her colleagues developed dozens of models and forecasts and projections. It struck her, she said later, that “huge decisions [affecting the global economy] would be made on the basis of spreadsheets that I was helping create.” Wolfram composed a memo to the Biden administration and hoped her projections would pan out the way she believed they would.

      Tackling conundrums that weigh competing, sometimes contradictory, interests has defined much of Wolfram’s career.

      Wolfram specializes in the economics of energy markets. She looks at ways to decarbonize global energy systems while recognizing that energy drives economic development, especially in the developing world.

      “The way we’re currently making energy is contributing to climate change. There’s a delicate dance we have to do to make sure that we treat this important industry carefully, but also transform it rapidly to a cleaner, decarbonized system,” she says.

      Economists as influencers

      While Wolfram was growing up in a suburb of St. Paul, Minnesota, her father was a law professor and her mother taught English as a second language. Her mother helped spawn Wolfram’s interest in other cultures and her love of travel, but it was an experience closer to home that sparked her awareness of the effect of human activities on the state of the planet.

      Minnesota’s nickname is “Land of 10,000 Lakes.” Wolfram remembers swimming in a nearby lake sometimes covered by a thick sludge of algae. “Thinking back on it, it must’ve had to do with fertilizer runoff,” she says. “That was probably the first thing that made me think about the environment and policy.”

      In high school, Wolfram liked “the fact that you could use math to understand the world. I also was interested in the types of questions about human behavior that economists were thinking about.

      “I definitely think economics is good at sussing out how different actors are likely to react to a particular policy and then designing policies with that in mind.”

      After receiving a bachelor’s degree in economics from Harvard University in 1989, Wolfram worked with a Massachusetts agency that governed rate hikes for utilities. Seeing its reliance on research, she says, illuminated the role academics could play in policy setting. It made her think she could make a difference from within academia.

      While pursuing a PhD in economics from MIT, Wolfram counted Paul L. Joskow, the Elizabeth and James Killian Professor of Economics and former director of the MIT Center for Energy and Environmental Policy Research, and Nancy L. Rose, the Charles P. Kindleberger Professor of Applied Economics, among her mentors and influencers.

      After spending 1996 to 2000 as an assistant professor of economics at Harvard, she joined the faculty at the Haas School of Business at the University of California at Berkeley.

      At Berkeley, it struck Wolfram that while she labored over ways to marginally boost the energy efficiency of U.S. power plants, the economies of China and India were growing rapidly, with a corresponding growth in energy use and carbon dioxide emissions. “It hit home that to understand the climate issue, I needed to understand energy demand in the developing world,” she says.

      The problem was that the developing world didn’t always offer up the kind of neatly packaged, comprehensive data economists relied on. She wondered if, by relying on readily accessible data, the field was looking under the lamppost — while losing sight of what the rest of the street looked like.

      To make up for a lack of available data on the state of electrification in sub-Saharan Africa, for instance, Wolfram developed and administered surveys to individual, remote rural households using on-the-ground field teams.

      Her results suggested that in the world’s poorest countries, the challenges involved in expanding the grid in rural areas should be weighed against potentially greater economic and social returns on investments in the transportation, education, or health sectors.

      Taking the lead

      Within months of Wolfram’s memo to the Biden administration, leaders of the intergovernmental political forum Group of Seven (G7) agreed to the price cap. Tankers from coalition countries would only transport Russian crude sold at or below the price cap level, initially set at $60 per barrel.

      “A price cap was not something that had ever been done before,” Wolfram says. “In some ways, we were making it up out of whole cloth. It was exciting to see that I wrote one of the original memos about it, and then literally three-and-a-half months later, the G7 was making an announcement.

      “As economists and as policymakers, we must set the parameters and get the incentives right. The price cap was basically asking developing countries to buy cheap oil, which was consistent with their incentives.”

      In May 2023, the U.S. Department of the Treasury reported that despite widespread initial skepticism about the price cap, market participants and geopolitical analysts believe it is accomplishing its goals of restricting Russia’s oil revenues while maintaining the supply of Russian oil and keeping energy costs in check for consumers and businesses around the world.

      Wolfram held the U.S. Treasury post from March 2021 to October 2022 while on leave from UC Berkeley. In July 2023, she joined MIT Sloan School of Management partly to be geographically closer to the policymakers of the nation’s capital. She’s also excited about the work taking place elsewhere at the Institute to stay ahead of climate change.

      Her time in D.C. was eye-opening, particularly in terms of the leadership power of the United States. She worries that the United States is falling prey to “lost opportunities” in terms of addressing climate change. “We were showing real leadership on the price cap, and if we could only do that on climate, I think we could make faster inroads on a global agreement,” she says.

      Now focused on structuring global agreements in energy policy among developed and developing countries, she’s considering how the United States can take advantage of its position as a world leader. “We need to be thinking about how what we do in the U.S. affects the rest of the world from a climate perspective. We can’t go it alone.

      “The U.S. needs to be more aligned with the European Union, Canada, and Japan to try to find areas where we’re taking a common approach to addressing climate change,” she says. She will touch on some of those areas in the class she will teach in spring 2024 titled “Climate and Energy in the Global Economy,” offered through MIT Sloan.

      Looking ahead, she says, “I’m a techno optimist. I believe in human innovation. I’m optimistic that we’ll find ways to live with climate change and, hopefully, ways to minimize it.”

      This article appears in the Winter 2024 issue of Energy Futures, the magazine of the MIT Energy Initiative. More

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      in Energy

      Engineers find a new way to convert carbon dioxide into useful products

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      MIT chemical engineers have devised an efficient way to convert carbon dioxide to carbon monoxide, a chemical precursor that can be used to generate useful compounds such as ethanol and other fuels.

      If scaled up for industrial use, this process could help to remove carbon dioxide from power plants and other sources, reducing the amount of greenhouse gases that are released into the atmosphere.

      “This would allow you to take carbon dioxide from emissions or dissolved in the ocean, and convert it into profitable chemicals. It’s really a path forward for decarbonization because we can take CO2, which is a greenhouse gas, and turn it into things that are useful for chemical manufacture,” says Ariel Furst, the Paul M. Cook Career Development Assistant Professor of Chemical Engineering and the senior author of the study.

      The new approach uses electricity to perform the chemical conversion, with help from a catalyst that is tethered to the electrode surface by strands of DNA. This DNA acts like Velcro to keep all the reaction components in close proximity, making the reaction much more efficient than if all the components were floating in solution.

      Furst has started a company called Helix Carbon to further develop the technology. Former MIT postdoc Gang Fan is the lead author of the paper, which appears in the Journal of the American Chemical Society Au. Other authors include Nathan Corbin PhD ’21, Minju Chung PhD ’23, former MIT postdocs Thomas Gill and Amruta Karbelkar, and Evan Moore ’23.

      Breaking down CO2

      Converting carbon dioxide into useful products requires first turning it into carbon monoxide. One way to do this is with electricity, but the amount of energy required for that type of electrocatalysis is prohibitively expensive.

      To try to bring down those costs, researchers have tried using electrocatalysts, which can speed up the reaction and reduce the amount of energy that needs to be added to the system. One type of catalyst used for this reaction is a class of molecules known as porphyrins, which contain metals such as iron or cobalt and are similar in structure to the heme molecules that carry oxygen in blood. 

      During this type of electrochemical reaction, carbon dioxide is dissolved in water within an electrochemical device, which contains an electrode that drives the reaction. The catalysts are also suspended in the solution. However, this setup isn’t very efficient because the carbon dioxide and the catalysts need to encounter each other at the electrode surface, which doesn’t happen very often.

      To make the reaction occur more frequently, which would boost the efficiency of the electrochemical conversion, Furst began working on ways to attach the catalysts to the surface of the electrode. DNA seemed to be the ideal choice for this application.

      “DNA is relatively inexpensive, you can modify it chemically, and you can control the interaction between two strands by changing the sequences,” she says. “It’s like a sequence-specific Velcro that has very strong but reversible interactions that you can control.”

      To attach single strands of DNA to a carbon electrode, the researchers used two “chemical handles,” one on the DNA and one on the electrode. These handles can be snapped together, forming a permanent bond. A complementary DNA sequence is then attached to the porphyrin catalyst, so that when the catalyst is added to the solution, it will bind reversibly to the DNA that’s already attached to the electrode — just like Velcro.

      Once this system is set up, the researchers apply a potential (or bias) to the electrode, and the catalyst uses this energy to convert carbon dioxide in the solution into carbon monoxide. The reaction also generates a small amount of hydrogen gas, from the water. After the catalysts wear out, they can be released from the surface by heating the system to break the reversible bonds between the two DNA strands, and replaced with new ones.

      An efficient reaction

      Using this approach, the researchers were able to boost the Faradaic efficiency of the reaction to 100 percent, meaning that all of the electrical energy that goes into the system goes directly into the chemical reactions, with no energy wasted. When the catalysts are not tethered by DNA, the Faradaic efficiency is only about 40 percent.

      This technology could be scaled up for industrial use fairly easily, Furst says, because the carbon electrodes the researchers used are much less expensive than conventional metal electrodes. The catalysts are also inexpensive, as they don’t contain any precious metals, and only a small concentration of the catalyst is needed on the electrode surface.

      By swapping in different catalysts, the researchers plan to try making other products such as methanol and ethanol using this approach. Helix Carbon, the company started by Furst, is also working on further developing the technology for potential commercial use.

      The research was funded by the U.S. Army Research Office, the CIFAR Azrieli Global Scholars Program, the MIT Energy Initiative, and the MIT Deshpande Center. More

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      in Environment

      MIT-derived algorithm helps forecast the frequency of extreme weather

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      To assess a community’s risk of extreme weather, policymakers rely first on global climate models that can be run decades, and even centuries, forward in time, but only at a coarse resolution. These models might be used to gauge, for instance, future climate conditions for the northeastern U.S., but not specifically for Boston.

      To estimate Boston’s future risk of extreme weather such as flooding, policymakers can combine a coarse model’s large-scale predictions with a finer-resolution model, tuned to estimate how often Boston is likely to experience damaging floods as the climate warms. But this risk analysis is only as accurate as the predictions from that first, coarser climate model.

      “If you get those wrong for large-scale environments, then you miss everything in terms of what extreme events will look like at smaller scales, such as over individual cities,” says Themistoklis Sapsis, the William I. Koch Professor and director of the Center for Ocean Engineering in MIT’s Department of Mechanical Engineering.

      Sapsis and his colleagues have now developed a method to “correct” the predictions from coarse climate models. By combining machine learning with dynamical systems theory, the team’s approach “nudges” a climate model’s simulations into more realistic patterns over large scales. When paired with smaller-scale models to predict specific weather events such as tropical cyclones or floods, the team’s approach produced more accurate predictions for how often specific locations will experience those events over the next few decades, compared to predictions made without the correction scheme.

      Play video

      This animation shows the evolution of storms around the northern hemisphere, as a result of a high-resolution storm model, combined with the MIT team’s corrected global climate model. The simulation improves the modeling of extreme values for wind, temperature, and humidity, which typically have significant errors in coarse scale models. Credit: Courtesy of Ruby Leung and Shixuan Zhang, PNNL

      Sapsis says the new correction scheme is general in form and can be applied to any global climate model. Once corrected, the models can help to determine where and how often extreme weather will strike as global temperatures rise over the coming years. 

      “Climate change will have an effect on every aspect of human life, and every type of life on the planet, from biodiversity to food security to the economy,” Sapsis says. “If we have capabilities to know accurately how extreme weather will change, especially over specific locations, it can make a lot of difference in terms of preparation and doing the right engineering to come up with solutions. This is the method that can open the way to do that.”

      The team’s results appear today in the Journal of Advances in Modeling Earth Systems. The study’s MIT co-authors include postdoc Benedikt Barthel Sorensen and Alexis-Tzianni Charalampopoulos SM ’19, PhD ’23, with Shixuan Zhang, Bryce Harrop, and Ruby Leung of the Pacific Northwest National Laboratory in Washington state.

      Over the hood

      Today’s large-scale climate models simulate weather features such as the average temperature, humidity, and precipitation around the world, on a grid-by-grid basis. Running simulations of these models takes enormous computing power, and in order to simulate how weather features will interact and evolve over periods of decades or longer, models average out features every 100 kilometers or so.

      “It’s a very heavy computation requiring supercomputers,” Sapsis notes. “But these models still do not resolve very important processes like clouds or storms, which occur over smaller scales of a kilometer or less.”

      To improve the resolution of these coarse climate models, scientists typically have gone under the hood to try and fix a model’s underlying dynamical equations, which describe how phenomena in the atmosphere and oceans should physically interact.

      “People have tried to dissect into climate model codes that have been developed over the last 20 to 30 years, which is a nightmare, because you can lose a lot of stability in your simulation,” Sapsis explains. “What we’re doing is a completely different approach, in that we’re not trying to correct the equations but instead correct the model’s output.”

      The team’s new approach takes a model’s output, or simulation, and overlays an algorithm that nudges the simulation toward something that more closely represents real-world conditions. The algorithm is based on a machine-learning scheme that takes in data, such as past information for temperature and humidity around the world, and learns associations within the data that represent fundamental dynamics among weather features. The algorithm then uses these learned associations to correct a model’s predictions.

      “What we’re doing is trying to correct dynamics, as in how an extreme weather feature, such as the windspeeds during a Hurricane Sandy event, will look like in the coarse model, versus in reality,” Sapsis says. “The method learns dynamics, and dynamics are universal. Having the correct dynamics eventually leads to correct statistics, for example, frequency of rare extreme events.”

      Climate correction

      As a first test of their new approach, the team used the machine-learning scheme to correct simulations produced by the Energy Exascale Earth System Model (E3SM), a climate model run by the U.S. Department of Energy, that simulates climate patterns around the world at a resolution of 110 kilometers. The researchers used eight years of past data for temperature, humidity, and wind speed to train their new algorithm, which learned dynamical associations between the measured weather features and the E3SM model. They then ran the climate model forward in time for about 36 years and applied the trained algorithm to the model’s simulations. They found that the corrected version produced climate patterns that more closely matched real-world observations from the last 36 years, not used for training.

      “We’re not talking about huge differences in absolute terms,” Sapsis says. “An extreme event in the uncorrected simulation might be 105 degrees Fahrenheit, versus 115 degrees with our corrections. But for humans experiencing this, that is a big difference.”

      When the team then paired the corrected coarse model with a specific, finer-resolution model of tropical cyclones, they found the approach accurately reproduced the frequency of extreme storms in specific locations around the world.

      “We now have a coarse model that can get you the right frequency of events, for the present climate. It’s much more improved,” Sapsis says. “Once we correct the dynamics, this is a relevant correction, even when you have a different average global temperature, and it can be used for understanding how forest fires, flooding events, and heat waves will look in a future climate. Our ongoing work is focusing on analyzing future climate scenarios.”

      “The results are particularly impressive as the method shows promising results on E3SM, a state-of-the-art climate model,” says Pedram Hassanzadeh, an associate professor who leads the Climate Extremes Theory and Data group at the University of Chicago and was not involved with the study. “It would be interesting to see what climate change projections this framework yields once future greenhouse-gas emission scenarios are incorporated.”

      This work was supported, in part, by the U.S. Defense Advanced Research Projects Agency. More

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      in Environment

      Artificial reef designed by MIT engineers could protect marine life, reduce storm damage

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      The beautiful, gnarled, nooked-and-crannied reefs that surround tropical islands serve as a marine refuge and natural buffer against stormy seas. But as the effects of climate change bleach and break down coral reefs around the world, and extreme weather events become more common, coastal communities are left increasingly vulnerable to frequent flooding and erosion.

      An MIT team is now hoping to fortify coastlines with “architected” reefs — sustainable, offshore structures engineered to mimic the wave-buffering effects of natural reefs while also providing pockets for fish and other marine life.

      The team’s reef design centers on a cylindrical structure surrounded by four rudder-like slats. The engineers found that when this structure stands up against a wave, it efficiently breaks the wave into turbulent jets that ultimately dissipate most of the wave’s total energy. The team has calculated that the new design could reduce as much wave energy as existing artificial reefs, using 10 times less material.

      The researchers plan to fabricate each cylindrical structure from sustainable cement, which they would mold in a pattern of “voxels” that could be automatically assembled, and would provide pockets for fish to explore and other marine life to settle in. The cylinders could be connected to form a long, semipermeable wall, which the engineers could erect along a coastline, about half a mile from shore. Based on the team’s initial experiments with lab-scale prototypes, the architected reef could reduce the energy of incoming waves by more than 95 percent.

      “This would be like a long wave-breaker,” says Michael Triantafyllou, the Henry L. and Grace Doherty Professor in Ocean Science and Engineering in the Department of Mechanical Engineering. “If waves are 6 meters high coming toward this reef structure, they would be ultimately less than a meter high on the other side. So, this kills the impact of the waves, which could prevent erosion and flooding.”

      Details of the architected reef design are reported today in a study appearing in the open-access journal PNAS Nexus. Triantafyllou’s MIT co-authors are Edvard Ronglan SM ’23; graduate students Alfonso Parra Rubio, Jose del Auila Ferrandis, and Erik Strand; research scientists Patricia Maria Stathatou and Carolina Bastidas; and Professor Neil Gershenfeld, director of the Center for Bits and Atoms; along with Alexis Oliveira Da Silva at the Polytechnic Institute of Paris, Dixia Fan of Westlake University, and Jeffrey Gair Jr. of Scinetics, Inc.

      Leveraging turbulence

      Some regions have already erected artificial reefs to protect their coastlines from encroaching storms. These structures are typically sunken ships, retired oil and gas platforms, and even assembled configurations of concrete, metal, tires, and stones. However, there’s variability in the types of artificial reefs that are currently in place, and no standard for engineering such structures. What’s more, the designs that are deployed tend to have a low wave dissipation per unit volume of material used. That is, it takes a huge amount of material to break enough wave energy to adequately protect coastal communities.

      The MIT team instead looked for ways to engineer an artificial reef that would efficiently dissipate wave energy with less material, while also providing a refuge for fish living along any vulnerable coast.

      “Remember, natural coral reefs are only found in tropical waters,” says Triantafyllou, who is director of the MIT Sea Grant. “We cannot have these reefs, for instance, in Massachusetts. But architected reefs don’t depend on temperature, so they can be placed in any water, to protect more coastal areas.”

      MIT researchers test the wave-breaking performance of two artificial reef structures in the MIT Towing Tank.Credit: Courtesy of the researchers

      The new effort is the result of a collaboration between researchers in MIT Sea Grant, who developed the reef structure’s hydrodynamic design, and researchers at the Center for Bits and Atoms (CBA), who worked to make the structure modular and easy to fabricate on location. The team’s architected reef design grew out of two seemingly unrelated problems. CBA researchers were developing ultralight cellular structures for the aerospace industry, while Sea Grant researchers were assessing the performance of blowout preventers in offshore oil structures — cylindrical valves that are used to seal off oil and gas wells and prevent them from leaking.

      The team’s tests showed that the structure’s cylindrical arrangement generated a high amount of drag. In other words, the structure appeared to be especially efficient in dissipating high-force flows of oil and gas. They wondered: Could the same arrangement dissipate another type of flow, in ocean waves?

      The researchers began to play with the general structure in simulations of water flow, tweaking its dimensions and adding certain elements to see whether and how waves changed as they crashed against each simulated design. This iterative process ultimately landed on an optimized geometry: a vertical cylinder flanked by four long slats, each attached to the cylinder in a way that leaves space for water to flow through the resulting structure. They found this setup essentially breaks up any incoming wave energy, causing parts of the wave-induced flow to spiral to the sides rather than crashing ahead.

      “We’re leveraging this turbulence and these powerful jets to ultimately dissipate wave energy,” Ferrandis says.

      Standing up to storms

      Once the researchers identified an optimal wave-dissipating structure, they fabricated a laboratory-scale version of an architected reef made from a series of the cylindrical structures, which they 3D-printed from plastic. Each test cylinder measured about 1 foot wide and 4 feet tall. They assembled a number of cylinders, each spaced about a foot apart, to form a fence-like structure, which they then lowered into a wave tank at MIT. They then generated waves of various heights and measured them before and after passing through the architected reef.

      “We saw the waves reduce substantially, as the reef destroyed their energy,” Triantafyllou says.

      The team has also looked into making the structures more porous, and friendly to fish. They found that, rather than making each structure from a solid slab of plastic, they could use a more affordable and sustainable type of cement.

      “We’ve worked with biologists to test the cement we intend to use, and it’s benign to fish, and ready to go,” he adds.

      They identified an ideal pattern of “voxels,” or microstructures, that cement could be molded into, in order to fabricate the reefs while creating pockets in which fish could live. This voxel geometry resembles individual egg cartons, stacked end to end, and appears to not affect the structure’s overall wave-dissipating power.

      “These voxels still maintain a big drag while allowing fish to move inside,” Ferrandis says.

      The team is currently fabricating cement voxel structures and assembling them into a lab-scale architected reef, which they will test under various wave conditions. They envision that the voxel design could be modular, and scalable to any desired size, and easy to transport and install in various offshore locations. “Now we’re simulating actual sea patterns, and testing how these models will perform when we eventually have to deploy them,” says Anjali Sinha, a graduate student at MIT who recently joined the group.

      Going forward, the team hopes to work with beach towns in Massachusetts to test the structures on a pilot scale.

      “These test structures would not be small,” Triantafyllou emphasizes. “They would be about a mile long, and about 5 meters tall, and would cost something like 6 million dollars per mile. So it’s not cheap. But it could prevent billions of dollars in storm damage. And with climate change, protecting the coasts will become a big issue.”

      This work was funded, in part, by the U.S. Defense Advanced Research Projects Agency. More

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      in Environment

      A new way to quantify climate change impacts: “Outdoor days”

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      For most people, reading about the difference between a global average temperature rise of 1.5 C versus 2 C doesn’t conjure up a clear image of how their daily lives will actually be affected. So, researchers at MIT have come up with a different way of measuring and describing what global climate change patterns, in specific regions around the world, will mean for people’s daily activities and their quality of life.

      The new measure, called “outdoor days,” describes the number of days per year that outdoor temperatures are neither too hot nor too cold for people to go about normal outdoor activities, whether work or leisure, in reasonable comfort. Describing the impact of rising temperatures in those terms reveals some significant global disparities, the researchers say.

      The findings are described in a research paper written by MIT professor of civil and environmental engineering Elfatih Eltahir and postdocs Yeon-Woo Choi and Muhammad Khalifa, and published in the Journal of Climate.

      Eltahir says he got the idea for this new system during his hourlong daily walks in the Boston area. “That’s how I interface with the temperature every day,” he says. He found that there have been more winter days recently when he could walk comfortably than in past years. Originally from Sudan, he says that when he returned there for visits, the opposite was the case: In winter, the weather tends to be relatively comfortable, but the number of these clement winter days has been declining. “There are fewer days that are really suitable for outdoor activity,” Eltahir says.

      Rather than predefine what constitutes an acceptable outdoor day, Eltahir and his co-authors created a website where users can set their own definition of the highest and lowest temperatures they consider comfortable for their outside activities, then click on a country within a world map, or a state within the U.S., and get a forecast of how the number of days meeting those criteria will change between now and the end of this century. The website is freely available for anyone to use.

      “This is actually a new feature that’s quite innovative,” he says. “We don’t tell people what an outdoor day should be; we let the user define an outdoor day. Hence, we invite them to participate in defining how future climate change will impact their quality of life, and hopefully, this will facilitate deeper understanding of how climate change will impact individuals directly.”

      After deciding that this was a way of looking at the issue of climate change that might be useful, Eltahir says, “we started looking at the data on this, and we made several discoveries that I think are pretty significant.”

      First of all, there will be winners and losers, and the losers tend to be concentrated in the global south. “In the North, in a place like Russia or Canada, you gain a significant number of outdoor days. And when you go south to places like Bangladesh or Sudan, it’s bad news. You get significantly fewer outdoor days. It is very striking.”

      To derive the data, the software developed by the team uses all of the available climate models, about 50 of them, and provides output showing all of those projections on a single graph to make clear the range of possibilities, as well as the average forecast.

      When we think of climate change, Eltahir says, we tend to look at maps that show that virtually everywhere, temperatures will rise. “But if you think in terms of outdoor days, you see that the world is not flat. The North is gaining; the South is losing.”

      While North-South disparity in exposure and vulnerability has been broadly recognized in the past, he says, this way of quantifying the effects on the hazard (change in weather patterns) helps to bring home how strong the uneven risks from climate change on quality of life will be. “When you look at places like Bangladesh, Colombia, Ivory Coast, Sudan, Indonesia — they are all losing outdoor days.”

      The same kind of disparity shows up in Europe, he says. The effects are already being felt, and are showing up in travel patterns: “There is a shift to people spending time in northern European states. They go to Sweden and places like that instead of the Mediterranean, which is showing a significant drop,” he says.

      Placing this kind of detailed and localized information at people’s fingertips, he says, “I think brings the issue of communication of climate change to a different level.” With this tool, instead of looking at global averages, “we are saying according to your own definition of what a pleasant day is, [this is] how climate change is going to impact you, your activities.”

      And, he adds, “hopefully that will help society make decisions about what to do with this global challenge.”

      The project received support from the MIT Climate Grand Challenges project “Jameel Observatory – Climate Resilience Early Warning System Network,” as well as from the Abdul Latif Jameel Water and Food Systems Lab. More

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      in Environment

      Think globally, rebuild locally

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      Building construction accounts for a huge chunk of greenhouse gas emissions: About 36 percent of carbon dioxide emissions and 40 percent of energy consumption in Europe, for instance. That’s why the European Union has developed regulations about the reuse of building materials.

      Some cities are adding more material reuse into construction already. Amsterdam, for example, is attempting to slash its raw material use by half by 2030. The Netherlands as a whole aims for a “circular economy” of completely reused materials by 2050.

      But the best way to organize the reuse of construction waste is still being determined. For one thing: Where should reusable building materials be stored before they are reused? A newly published study focusing on Amsterdam finds the optimal material reuse system for construction has many local storage “hubs” that keep materials within a few miles of where they will be needed.

      “Our findings provide a starting point for policymakers in Amsterdam to strategize land use effectively,” says Tanya Tsui, a postdoc at MIT and a co-author of the new paper. “By identifying key locations repeatedly favored across various hub scenarios, we underscore the importance of prioritizing these areas for future circular economy endeavors in Amsterdam.”

      The study adds to an emerging research area that connects climate change and urban planning.

      “The issue is where you put material in between demolition and new construction,” says Fábio Duarte, a principal researcher at MIT’s Senseable City Lab and a co-author of the new paper. “It will have huge impacts in terms of transportation. So you have to define the best sites. Should there be only one? Should we hold materials across a wide number of sites? Or is there an optimal number, even if it changes over time? This is what we examined in the paper.”

      The paper, “Spatial optimization of circular timber hubs,” is published in NPJ Nature Urban Sustainability. The authors are Tsui, who is a postdoc at the MIT Senseable Amsterdam Lab in the Amsterdam Institute for Advanced Metropolitan Solutions (AMS); Titus Venverloo, a research fellow at MIT Senseable Amsterdam Lab and AMS; Tom Benson, a researcher at the Senseable City Lab; and Duarte, who is also a lecturer in MIT’s Department of Urban Studies and Planning and the MIT Center for Real Estate.

      Numerous experts have previously studied at what scale the “circular economy” of reused materials might best operate. Some have suggested that very local circuits of materials recycling make the most sense; others have proposed that building-materials recycling will work best at a regional scale, with a radius of distribution covering 30 or more miles. Some analyses contend that global-scale reuse will be necessary to an extent.

      The current study adds to this examination of the best geographic scale for using construction materials again. Currently the storage hubs that do exist for such reused materials are chosen by individual companies, but those locations might not be optimal either economically or environmentally. 

      To conduct the study, the researchers essentially conducted a series of simulations of the Amsterdam metropolitan area, focused exclusively on timber reuse. The simulations examined how the system would work if anywhere from one to 135 timber storage hubs existed in greater Amsterdam. The modeling accounted for numerous variables, such as emissions reductions, logistical factors, and even how changing supply-and-demand scenarios would affect the viability of the reusehubs.

      Ultimately, the research found that Amsterdam’s optimal system would have 29 timber hubs, each serving a radius of about 2 miles. That setup generated 95 percent of the maximum reduction in CO2 emissions, while retaining logistical and economic benefits.

      That results also lands firmly on the side of having more localized networks for keeping construction materials in use.

      “If we have demolition happening in certain sites, then we can project where the best spots around the city are to have these circular economy hubs, as we call them,” Duarte says. “It’s not only one big hub — or one hub per construction site.”

      The study seeks to identify not only the optimal number of storage sites, but to identify where those sites might be.

      “[We hope] our research sparks discussions regarding the location and scale of circular hubs,” Tsui says. “While much attention has been given to governance aspects of the circular economy in cities, our study demonstrates the potential of utilizing location data on materials to inform decisions in urban planning.”

      The simulations also illuminated the dynamics of materials reuse. In scenarios where Amsterdam had from two to 20 timber recycling hubs, the costs involved lowered as the number of hubs increased — because having more hubs reduces transportation costs. But when the number of hubs went about 40, the system as a whole became more expensive — because each timber depot was not storing enough material to justify the land use.

      As such, the results may be of interest to climate policymakers, urban planners, and business interests getting involved in implementing the circular economy in the construction industry.

      “Ultimately,” Tsui says, “we envision our research catalyzing meaningful discussions and guiding policymakers toward more informed decisions in advancing the circular economy agenda in urban contexts.”

      The research was supported, in part, by the European Union’s Horizon 2020 research and innovation program. More