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      Amy Moran-Thomas receives the Edgerton Faculty Achievement Award

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      Amy Moran-Thomas, the Alfred Henry and Jean Morrison Hayes Career Development Associate Professor of Anthropology, has received the 2021-22 Harold E. Edgerton Faculty Achievement Award in recognition of her “exceptional commitment to innovative and collaborative interdisciplinary approaches to resolving inequitable impacts on human health,” according to a statement by the  selection committee.A medical anthropologist, Moran-Thomas investigates linkages between human and environmental health, with a focus on health disparities. She is the author of the award-winning book “Traveling with Sugar: Chronicles of a Global Epidemic” (University of California Press, 2019), which frames the diabetes epidemic in Belize within the context of 500 years of colonialism.

      On human and planetary well-being Moran-Thomas “stands out in this field by bringing a humanistic approach into dialogue with environmental and science studies to investigate how bodily health is shaped by social well-being at the community level and further conditioned by localized planetary imbalances,” the selection committee’s statement said. “Professor Moran-Thomas shows how diabetes resides not only within human bodies but also across toxic environments, crumbling healthcare infrastructures, and stress-inducing economic inequalities.”Heather Paxson, the William R. Kenan, Jr. Professor of Anthropology and head of the MIT Anthropology program, calls Moran-Thomas “a fast-rising star in her field.” Paxson, who nominated Moran-Thomas for the award, adds, “She is also a highly effective teacher and student mentor, an engaged member of our Institute community, and a budding public intellectual.” A profound discovery for medical equity

      “Professor Moran-Thomas’s work has an extraordinarily profound and impactful reach,” according to the committee, which highlighted a widely read 2020 essay in Boston Review in which Moran-Thomas revealed that the fingertip pulse oximeter — a key tool in monitoring the effects of respiratory distress due to Covid-19 and other illness — gives misleading readings with darkly complected skin. This essay inspired a subsequent medical research study and ultimately led to an alert from the U.S. Food and Drug Administration spotlighting the limitations of pulse oximeters.

      The selection committee further lauded Moran-Thomas for her pedagogy, including her work developing the new subject 21A.311 (The Social Lives of Medical Objects). She was also commended for her service, notably her work on the MIT Climate Action Advisory Committee and with the Social and Ethical Responsibilities of Computing group within MIT’s Schwarzman College of Computing.

      Moran-Thomas earned her bachelor’s degree in literature from American University and her PhD in anthropology from Princeton University. She joined MIT Anthropology in 2015, following postdocs at the Woodrow Institute for Public and International Affairs and at Brown University’s Cogut Humanities Center. She was promoted to associate professor without tenure in 2019.

      The annual Edgerton Faculty Award, established in 1982 as a tribute to Institute Professor Emeritus Harold E. Edgerton, honors achievement in research, teaching, and service by a nontenured member of the faculty.The 2019-20 Edgerton Award Selection Committee was chaired by T.L. Taylor, a professor of Comparative Media Studies/Writing. Other members were Geoffrey Beach, a professor in the Department of Materials Science and Engineering; Mircea Dinca, the W.M. Keck Professor of Energy in the Department of Chemistry; Hazhir Rahmandad, an associate professor of system dynamics in the Sloan School of Management; and Rafi Segal, an associate professor in the Department of Architecture.

      Story prepared by MIT SHASS CommunicationsSenior Writer: Kathryn O’NeillEditorial and Design Director: Emily Hiestand More

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      Looking forward to forecast the risks of a changing climate

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      On April 11, MIT announced five multiyear flagship projects in the first-ever Climate Grand Challenges, a new initiative to tackle complex climate problems and deliver breakthrough solutions to the world as quickly as possible. This article is the third in a five-part series highlighting the most promising concepts to emerge from the competition, and the interdisciplinary research teams behind them.

      Extreme weather events that were once considered rare have become noticeably less so, from intensifying hurricane activity in the North Atlantic to wildfires generating massive clouds of ozone-damaging smoke. But current climate models are unprepared when it comes to estimating the risk that these increasingly extreme events pose — and without adequate modeling, governments are left unable to take necessary precautions to protect their communities.

      MIT Department of Earth, Atmospheric and Planetary Science (EAPS) Professor Paul O’Gorman researches this trend by studying how climate affects the atmosphere and incorporating what he learns into climate models to improve their accuracy. One particular focus for O’Gorman has been changes in extreme precipitation and midlatitude storms that hit areas like New England.

      “These extreme events are having a lot of impact, but they’re also difficult to model or study,” he says. Seeing the pressing need for better climate models that can be used to develop preparedness plans and climate change mitigation strategies, O’Gorman and collaborators Kerry Emanuel, the Cecil and Ida Green Professor of Atmospheric Science in EAPS, and Miho Mazereeuw, associate professor in MIT’s Department of Architecture, are leading an interdisciplinary group of scientists, engineers, and designers to tackle this problem with their MIT Climate Grand Challenges flagship project, “Preparing for a new world of weather and climate extremes.”

      “We know already from observations and from climate model predictions that weather and climate extremes are changing and will change more,” O’Gorman says. “The grand challenge is preparing for those changing extremes.”

      Their proposal is one of five flagship projects recently announced by the MIT Climate Grand Challenges initiative — an Institute-wide effort catalyzing novel research and engineering innovations to address the climate crisis. Selected from a field of almost 100 submissions, the team will receive additional funding and exposure to help accelerate and scale their project goals. Other MIT collaborators on the proposal include researchers from the School of Engineering, the School of Architecture and Planning, the Office of Sustainability, the Center for Global Change Science, and the Institute for Data, Systems and Society.

      Weather risk modeling

      Fifteen years ago, Kerry Emanuel developed a simple hurricane model. It was based on physics equations, rather than statistics, and could run in real time, making it useful for modeling risk assessment. Emanuel wondered if similar models could be used for long-term risk assessment of other things, such as changes in extreme weather because of climate change.

      “I discovered, somewhat to my surprise and dismay, that almost all extant estimates of long-term weather risks in the United States are based not on physical models, but on historical statistics of the hazards,” says Emanuel. “The problem with relying on historical records is that they’re too short; while they can help estimate common events, they don’t contain enough information to make predictions for more rare events.”

      Another limitation of weather risk models which rely heavily on statistics: They have a built-in assumption that the climate is static.

      “Historical records rely on the climate at the time they were recorded; they can’t say anything about how hurricanes grow in a warmer climate,” says Emanuel. The models rely on fixed relationships between events; they assume that hurricane activity will stay the same, even while science is showing that warmer temperatures will most likely push typical hurricane activity beyond the tropics and into a much wider band of latitudes.

      As a flagship project, the goal is to eliminate this reliance on the historical record by emphasizing physical principles (e.g., the laws of thermodynamics and fluid mechanics) in next-generation models. The downside to this is that there are many variables that have to be included. Not only are there planetary-scale systems to consider, such as the global circulation of the atmosphere, but there are also small-scale, extremely localized events, like thunderstorms, that influence predictive outcomes.

      Trying to compute all of these at once is costly and time-consuming — and the results often can’t tell you the risk in a specific location. But there is a way to correct for this: “What’s done is to use a global model, and then use a method called downscaling, which tries to infer what would happen on very small scales that aren’t properly resolved by the global model,” explains O’Gorman. The team hopes to improve downscaling techniques so that they can be used to calculate the risk of very rare but impactful weather events.

      Global climate models, or general circulation models (GCMs), Emanuel explains, are constructed a bit like a jungle gym. Like the playground bars, the Earth is sectioned in an interconnected three-dimensional framework — only it’s divided 100 to 200 square kilometers at a time. Each node comprises a set of computations for characteristics like wind, rainfall, atmospheric pressure, and temperature within its bounds; the outputs of each node are connected to its neighbor. This framework is useful for creating a big picture idea of Earth’s climate system, but if you tried to zoom in on a specific location — like, say, to see what’s happening in Miami or Mumbai — the connecting nodes are too far apart to make predictions on anything specific to those areas.

      Scientists work around this problem by using downscaling. They use the same blueprint of the jungle gym, but within the nodes they weave a mesh of smaller features, incorporating equations for things like topography and vegetation or regional meteorological models to fill in the blanks. By creating a finer mesh over smaller areas they can predict local effects without needing to run the entire global model.

      Of course, even this finer-resolution solution has its trade-offs. While we might be able to gain a clearer picture of what’s happening in a specific region by nesting models within models, it can still make for a computing challenge to crunch all that data at once, with the trade-off being expense and time, or predictions that are limited to shorter windows of duration — where GCMs can be run considering decades or centuries, a particularly complex local model may be restricted to predictions on timescales of just a few years at a time.

      “I’m afraid that most of the downscaling at present is brute force, but I think there’s room to do it in better ways,” says Emanuel, who sees the problem of finding new and novel methods of achieving this goal as an intellectual challenge. “I hope that through the Grand Challenges project we might be able to get students, postdocs, and others interested in doing this in a very creative way.”

      Adapting to weather extremes for cities and renewable energy

      Improving climate modeling is more than a scientific exercise in creativity, however. There’s a very real application for models that can accurately forecast risk in localized regions.

      Another problem is that progress in climate modeling has not kept up with the need for climate mitigation plans, especially in some of the most vulnerable communities around the globe.

      “It is critical for stakeholders to have access to this data for their own decision-making process. Every community is composed of a diverse population with diverse needs, and each locality is affected by extreme weather events in unique ways,” says Mazereeuw, the director of the MIT Urban Risk Lab. 

      A key piece of the team’s project is building on partnerships the Urban Risk Lab has developed with several cities to test their models once they have a usable product up and running. The cities were selected based on their vulnerability to increasing extreme weather events, such as tropical cyclones in Broward County, Florida, and Toa Baja, Puerto Rico, and extratropical storms in Boston, Massachusetts, and Cape Town, South Africa.

      In their proposal, the team outlines a variety of deliverables that the cities can ultimately use in their climate change preparations, with ideas such as online interactive platforms and workshops with stakeholders — such as local governments, developers, nonprofits, and residents — to learn directly what specific tools they need for their local communities. By doing so, they can craft plans addressing different scenarios in their region, involving events such as sea-level rise or heat waves, while also providing information and means of developing adaptation strategies for infrastructure under these conditions that will be the most effective and efficient for them.

      “We are acutely aware of the inequity of resources both in mitigating impacts and recovering from disasters. Working with diverse communities through workshops allows us to engage a lot of people, listen, discuss, and collaboratively design solutions,” says Mazereeuw.

      By the end of five years, the team is hoping that they’ll have better risk assessment and preparedness tool kits, not just for the cities that they’re partnering with, but for others as well.

      “MIT is well-positioned to make progress in this area,” says O’Gorman, “and I think it’s an important problem where we can make a difference.” More

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      Computing our climate future

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      On Monday, MIT announced five multiyear flagship projects in the first-ever Climate Grand Challenges, a new initiative to tackle complex climate problems and deliver breakthrough solutions to the world as quickly as possible. This article is the first in a five-part series highlighting the most promising concepts to emerge from the competition, and the interdisciplinary research teams behind them.

      With improvements to computer processing power and an increased understanding of the physical equations governing the Earth’s climate, scientists are continually working to refine climate models and improve their predictive power. But the tools they’re refining were originally conceived decades ago with only scientists in mind. When it comes to developing tangible climate action plans, these models remain inscrutable to the policymakers, public safety officials, civil engineers, and community organizers who need their predictive insight most.

      “What you end up having is a gap between what’s typically used in practice, and the real cutting-edge science,” says Noelle Selin, a professor in the Institute for Data, Systems and Society and the Department of Earth, Atmospheric and Planetary Sciences (EAPS), and co-lead with Professor Raffaele Ferrari on the MIT Climate Grand Challenges flagship project “Bringing Computation to the Climate Crisis.” “How can we use new computational techniques, new understandings, new ways of thinking about modeling, to really bridge that gap between state-of-the-art scientific advances and modeling, and people who are actually needing to use these models?”

      Using this as a driving question, the team won’t just be trying to refine current climate models, they’re building a new one from the ground up.

      This kind of game-changing advancement is exactly what the MIT Climate Grand Challenges is looking for, which is why the proposal has been named one of the five flagship projects in the ambitious Institute-wide program aimed at tackling the climate crisis. The proposal, which was selected from 100 submissions and was among 27 finalists, will receive additional funding and support to further their goal of reimagining the climate modeling system. It also brings together contributors from across the Institute, including the MIT Schwarzman College of Computing, the School of Engineering, and the Sloan School of Management.

      When it comes to pursuing high-impact climate solutions that communities around the world can use, “it’s great to do it at MIT,” says Ferrari, EAPS Cecil and Ida Green Professor of Oceanography. “You’re not going to find many places in the world where you have the cutting-edge climate science, the cutting-edge computer science, and the cutting-edge policy science experts that we need to work together.”

      The climate model of the future

      The proposal builds on work that Ferrari began three years ago as part of a joint project with Caltech, the Naval Postgraduate School, and NASA’s Jet Propulsion Lab. Called the Climate Modeling Alliance (CliMA), the consortium of scientists, engineers, and applied mathematicians is constructing a climate model capable of more accurately projecting future changes in critical variables, such as clouds in the atmosphere and turbulence in the ocean, with uncertainties at least half the size of those in existing models.

      To do this, however, requires a new approach. For one thing, current models are too coarse in resolution — at the 100-to-200-kilometer scale — to resolve small-scale processes like cloud cover, rainfall, and sea ice extent. But also, explains Ferrari, part of this limitation in resolution is due to the fundamental architecture of the models themselves. The languages most global climate models are coded in were first created back in the 1960s and ’70s, largely by scientists for scientists. Since then, advances in computing driven by the corporate world and computer gaming have given rise to dynamic new computer languages, powerful graphics processing units, and machine learning.

      For climate models to take full advantage of these advancements, there’s only one option: starting over with a modern, more flexible language. Written in Julia, a part of Julialab’s Scientific Machine Learning technology, and spearheaded by Alan Edelman, a professor of applied mathematics in MIT’s Department of Mathematics, CliMA will be able to harness far more data than the current models can handle.

      “It’s been real fun finally working with people in computer science here at MIT,” Ferrari says. “Before it was impossible, because traditional climate models are in a language their students can’t even read.”

      The result is what’s being called the “Earth digital twin,” a climate model that can simulate global conditions on a large scale. This on its own is an impressive feat, but the team wants to take this a step further with their proposal.

      “We want to take this large-scale model and create what we call an ‘emulator’ that is only predicting a set of variables of interest, but it’s been trained on the large-scale model,” Ferrari explains. Emulators are not new technology, but what is new is that these emulators, being referred to as the “Earth digital cousins,” will take advantage of machine learning.

      “Now we know how to train a model if we have enough data to train them on,” says Ferrari. Machine learning for projects like this has only become possible in recent years as more observational data become available, along with improved computer processing power. The goal is to create smaller, more localized models by training them using the Earth digital twin. Doing so will save time and money, which is key if the digital cousins are going to be usable for stakeholders, like local governments and private-sector developers.

      Adaptable predictions for average stakeholders

      When it comes to setting climate-informed policy, stakeholders need to understand the probability of an outcome within their own regions — in the same way that you would prepare for a hike differently if there’s a 10 percent chance of rain versus a 90 percent chance. The smaller Earth digital cousin models will be able to do things the larger model can’t do, like simulate local regions in real time and provide a wider range of probabilistic scenarios.

      “Right now, if you wanted to use output from a global climate model, you usually would have to use output that’s designed for general use,” says Selin, who is also the director of the MIT Technology and Policy Program. With the project, the team can take end-user needs into account from the very beginning while also incorporating their feedback and suggestions into the models, helping to “democratize the idea of running these climate models,” as she puts it. Doing so means building an interactive interface that eventually will give users the ability to change input values and run the new simulations in real time. The team hopes that, eventually, the Earth digital cousins could run on something as ubiquitous as a smartphone, although developments like that are currently beyond the scope of the project.

      The next thing the team will work on is building connections with stakeholders. Through participation of other MIT groups, such as the Joint Program on the Science and Policy of Global Change and the Climate and Sustainability Consortium, they hope to work closely with policymakers, public safety officials, and urban planners to give them predictive tools tailored to their needs that can provide actionable outputs important for planning. Faced with rising sea levels, for example, coastal cities could better visualize the threat and make informed decisions about infrastructure development and disaster preparedness; communities in drought-prone regions could develop long-term civil planning with an emphasis on water conservation and wildfire resistance.

      “We want to make the modeling and analysis process faster so people can get more direct and useful feedback for near-term decisions,” she says.

      The final piece of the challenge is to incentivize students now so that they can join the project and make a difference. Ferrari has already had luck garnering student interest after co-teaching a class with Edelman and seeing the enthusiasm students have about computer science and climate solutions.

      “We’re intending in this project to build a climate model of the future,” says Selin. “So it seems really appropriate that we would also train the builders of that climate model.” More

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      MIT announces five flagship projects in first-ever Climate Grand Challenges competition

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      MIT today announced the five flagship projects selected in its first-ever Climate Grand Challenges competition. These multiyear projects will define a dynamic research agenda focused on unraveling some of the toughest unsolved climate problems and bringing high-impact, science-based solutions to the world on an accelerated basis.

      Representing the most promising concepts to emerge from the two-year competition, the five flagship projects will receive additional funding and resources from MIT and others to develop their ideas and swiftly transform them into practical solutions at scale.

      “Climate Grand Challenges represents a whole-of-MIT drive to develop game-changing advances to confront the escalating climate crisis, in time to make a difference,” says MIT President L. Rafael Reif. “We are inspired by the creativity and boldness of the flagship ideas and by their potential to make a significant contribution to the global climate response. But given the planet-wide scale of the challenge, success depends on partnership. We are eager to work with visionary leaders in every sector to accelerate this impact-oriented research, implement serious solutions at scale, and inspire others to join us in confronting this urgent challenge for humankind.”

      Brief descriptions of the five Climate Grand Challenges flagship projects are provided below.

      Bringing Computation to the Climate Challenge

      This project leverages advances in artificial intelligence, machine learning, and data sciences to improve the accuracy of climate models and make them more useful to a variety of stakeholders — from communities to industry. The team is developing a digital twin of the Earth that harnesses more data than ever before to reduce and quantify uncertainties in climate projections.

      Research leads: Raffaele Ferrari, the Cecil and Ida Green Professor of Oceanography in the Department of Earth, Atmospheric and Planetary Sciences, and director of the Program in Atmospheres, Oceans, and Climate; and Noelle Eckley Selin, director of the Technology and Policy Program and professor with a joint appointment in the Institute for Data, Systems, and Society and the Department of Earth, Atmospheric and Planetary Sciences

      Center for Electrification and Decarbonization of Industry

      This project seeks to reinvent and electrify the processes and materials behind hard-to-decarbonize industries like steel, cement, ammonia, and ethylene production. A new innovation hub will perform targeted fundamental research and engineering with urgency, pushing the technological envelope on electricity-driven chemical transformations.

      Research leads: Yet-Ming Chiang, the Kyocera Professor of Materials Science and Engineering, and Bilge Yıldız, the Breene M. Kerr Professor in the Department of Nuclear Science and Engineering and professor in the Department of Materials Science and Engineering

      Preparing for a new world of weather and climate extremes

      This project addresses key gaps in knowledge about intensifying extreme events such as floods, hurricanes, and heat waves, and quantifies their long-term risk in a changing climate. The team is developing a scalable climate-change adaptation toolkit to help vulnerable communities and low-carbon energy providers prepare for these extreme weather events.

      Research leads: Kerry Emanuel, the Cecil and Ida Green Professor of Atmospheric Science in the Department of Earth, Atmospheric and Planetary Sciences and co-director of the MIT Lorenz Center; Miho Mazereeuw, associate professor of architecture and urbanism in the Department of Architecture and director of the Urban Risk Lab; and Paul O’Gorman, professor in the Program in Atmospheres, Oceans, and Climate in the Department of Earth, Atmospheric and Planetary Sciences

      The Climate Resilience Early Warning System

      The CREWSnet project seeks to reinvent climate change adaptation with a novel forecasting system that empowers underserved communities to interpret local climate risk, proactively plan for their futures incorporating resilience strategies, and minimize losses. CREWSnet will initially be demonstrated in southwestern Bangladesh, serving as a model for similarly threatened regions around the world.

      Research leads: John Aldridge, assistant leader of the Humanitarian Assistance and Disaster Relief Systems Group at MIT Lincoln Laboratory, and Elfatih Eltahir, the H.M. King Bhumibol Professor of Hydrology and Climate in the Department of Civil and Environmental Engineering

      Revolutionizing agriculture with low-emissions, resilient crops

      This project works to revolutionize the agricultural sector with climate-resilient crops and fertilizers that have the ability to dramatically reduce greenhouse gas emissions from food production.

      Research lead: Christopher Voigt, the Daniel I.C. Wang Professor in the Department of Biological Engineering

      “As one of the world’s leading institutions of research and innovation, it is incumbent upon MIT to draw on our depth of knowledge, ingenuity, and ambition to tackle the hard climate problems now confronting the world,” says Richard Lester, MIT associate provost for international activities. “Together with collaborators across industry, finance, community, and government, the Climate Grand Challenges teams are looking to develop and implement high-impact, path-breaking climate solutions rapidly and at a grand scale.”

      The initial call for ideas in 2020 yielded nearly 100 letters of interest from almost 400 faculty members and senior researchers, representing 90 percent of MIT departments. After an extensive evaluation, 27 finalist teams received a total of $2.7 million to develop comprehensive research and innovation plans. The projects address four broad research themes:

      To select the winning projects, research plans were reviewed by panels of international experts representing relevant scientific and technical domains as well as experts in processes and policies for innovation and scalability.

      “In response to climate change, the world really needs to do two things quickly: deploy the solutions we already have much more widely, and develop new solutions that are urgently needed to tackle this intensifying threat,” says Maria Zuber, MIT vice president for research. “These five flagship projects exemplify MIT’s strong determination to bring its knowledge and expertise to bear in generating new ideas and solutions that will help solve the climate problem.”

      “The Climate Grand Challenges flagship projects set a new standard for inclusive climate solutions that can be adapted and implemented across the globe,” says MIT Chancellor Melissa Nobles. “This competition propels the entire MIT research community — faculty, students, postdocs, and staff — to act with urgency around a worsening climate crisis, and I look forward to seeing the difference these projects can make.”

      “MIT’s efforts on climate research amid the climate crisis was a primary reason that I chose to attend MIT, and remains a reason that I view the Institute favorably. MIT has a clear opportunity to be a thought leader in the climate space in our own MIT way, which is why CGC fits in so well,” says senior Megan Xu, who served on the Climate Grand Challenges student committee and is studying ways to make the food system more sustainable.

      The Climate Grand Challenges competition is a key initiative of “Fast Forward: MIT’s Climate Action Plan for the Decade,” which the Institute published in May 2021. Fast Forward outlines MIT’s comprehensive plan for helping the world address the climate crisis. It consists of five broad areas of action: sparking innovation, educating future generations, informing and leveraging government action, reducing MIT’s own climate impact, and uniting and coordinating all of MIT’s climate efforts. More

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      Q&A: Climate Grand Challenges finalists on using data and science to forecast climate-related risk

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      Note: This is the final article in a four-part interview series featuring the work of the 27 MIT Climate Grand Challenges finalist teams, which received a total of $2.7 million in startup funding to advance their projects. This month, the Institute will name a subset of the finalists as multiyear flagship projects.

      Advances in computation, artificial intelligence, robotics, and data science are enabling a new generation of observational tools and scientific modeling with the potential to produce timely, reliable, and quantitative analysis of future climate risks at a local scale. These projections can increase the accuracy and efficacy of early warning systems, improve emergency planning, and provide actionable information for climate mitigation and adaptation efforts, as human actions continue to change planetary conditions.

      In conversations prepared for MIT News, faculty from four Climate Grand Challenges teams with projects in the competition’s “Using data and science to forecast climate-related risk” category describe the promising new technologies that can help scientists understand the Earth’s climate system on a finer scale than ever before. (The other Climate Grand Challenges research themes include building equity and fairness into climate solutions, removing, managing, and storing greenhouse gases, and decarbonizing complex industries and processes.) The following responses have been edited for length and clarity.

      An observational system that can initiate a climate risk forecasting revolution

      Despite recent technological advances and massive volumes of data, climate forecasts remain highly uncertain. Gaps in observational capabilities create substantial challenges to predicting extreme weather events and establishing effective mitigation and adaptation strategies. R. John Hansman, the T. Wilson Professor of Aeronautics and Astronautics and director of the MIT International Center for Air Transportation, discusses the Stratospheric Airborne Climate Observatory System (SACOS) being developed together with Brent Minchew, the Cecil and Ida Green Career Development Professor in the Department of Earth, Atmospheric and Planetary Sciences (EAPS), and a team that includes researchers from MIT Lincoln Laboratory and Harvard University.

      Q: How does SACOS reduce uncertainty in climate risk forecasting?

      A: There is a critical need for higher spatial and temporal resolution observations of the climate system than are currently available through remote (satellite or airborne) and surface (in-situ) sensing. We are developing an ensemble of high-endurance, solar-powered aircraft with instrument systems capable of performing months-long climate observing missions that satellites or aircraft alone cannot fulfill. Summer months are ideal for SACOS operations, as many key climate phenomena are active and short night periods reduce the battery mass, vehicle size, and technical risks. These observations hold the potential to inform and predict, allowing emergency planners, policymakers, and the rest of society to better prepare for the changes to come.

      Q: Describe the types of observing missions where SACOS could provide critical improvements.

      A: The demise of the Antarctic Ice Sheet, which is leading to rising sea levels around the world and threatening the displacement of millions of people, is one example. Current sea level forecasts struggle to account for giant fissures that create massive icebergs and cause the Antarctic Ice Sheet to flow more rapidly into the ocean. SACOS can track these fissures to accurately forecast ice slippage and give impacted populations enough time to prepare or evacuate. Elsewhere, widespread droughts cause rampant wildfires and water shortages. SACOS has the ability to monitor soil moisture and humidity in critically dry regions to identify where and when wildfires and droughts are imminent. SACOS also offers the most effective method to measure, track, and predict local ozone depletion over North America, which has resulted in increasingly severe summer thunderstorms.

      Quantifying and managing the risks of sea-level rise

      Prevailing estimates of sea-level rise range from approximately 20 centimeters to 2 meters by the end of the century, with the associated costs on the order of trillions of dollars. The instability of certain portions of the world’s ice sheets creates vast uncertainties, complicating how the world prepares for and responds to these potential changes. EAPS Professor Brent Minchew is leading another Climate Grand Challenges finalist team working on an integrated, multidisciplinary effort to improve the scientific understanding of sea-level rise and provide actionable information and tools to manage the risks it poses.

      Q: What have been the most significant challenges to understanding the potential rates of sea-level rise?

      A: West Antarctica is one of the most remote, inaccessible, and hostile places on Earth — to people and equipment. Thus, opportunities to observe the collapse of the West Antarctic Ice Sheet, which contains enough ice to raise global sea levels by about 3 meters, are limited and current observations crudely resolved. It is essential that we understand how the floating edge of the ice sheets, often called ice shelves, fracture and collapse because they provide critical forces that govern the rate of ice mass loss and can stabilize the West Antarctic Ice Sheet.

      Q: How will your project advance what is currently known about sea-level rise?

      A: We aim to advance global-scale projections of sea-level rise through novel observational technologies and computational models of ice sheet change and to link those predictions to region- to neighborhood-scale estimates of costs and adaptation strategies. To do this, we propose two novel instruments: a first-of-its-kind drone that can fly for months at a time over Antarctica making continuous observations of critical areas and an airdropped seismometer and GPS bundle that can be deployed to vulnerable and hard-to-reach areas of the ice sheet. This technology will provide greater data quality and density and will observe the ice sheet at frequencies that are currently inaccessible — elements that are essential for understanding the physics governing the evolution of the ice sheet and sea-level rise.

      Changing flood risk for coastal communities in the developing world

      Globally, more than 600 million people live in low-elevation coastal areas that face an increasing risk of flooding from sea-level rise. This includes two-thirds of cities with populations of more than 5 million and regions that conduct the vast majority of global trade. Dara Entekhabi, the Bacardi and Stockholm Water Foundations Professor in the Department of Civil and Environmental Engineering and professor in the Department of Earth, Atmospheric, and Planetary Sciences, outlines an interdisciplinary partnership that leverages data and technology to guide short-term and chart long-term adaptation pathways with Miho Mazereeuw, associate professor of architecture and urbanism and director of the Urban Risk Lab in the School of Architecture and Planning, and Danielle Wood, assistant professor in the Program in Media Arts and Sciences and the Department of Aeronautics and Astronautics.

      Q: What is the key problem this program seeks to address?

      A: The accumulated heating of the Earth system due to fossil burning is largely absorbed by the oceans, and the stored heat expands the ocean volume leading to increased base height for tides. When the high tides inundate a city, the condition is referred to as “sunny day” flooding, but the saline waters corrode infrastructure and wreak havoc on daily routines. The danger ahead for many coastal cities in the developing world is the combination of increasing high tide intrusions, coupled with heavy precipitation storm events.

      Q: How will your proposed solutions impact flood risk management?

      A: We are producing detailed risk maps for coastal cities in developing countries using newly available, very high-resolution remote-sensing data from space-borne instruments, as well as historical tides records and regional storm characteristics. Using these datasets, we aim to produce street-by-street risk maps that provide local decision-makers and stakeholders with a way to estimate present and future flood risks. With the model of future tides and probabilistic precipitation events, we can forecast future inundation by a flooding event, decadal changes with various climate-change and sea-level rise projections, and an increase in the likelihood of sunny-day flooding. Working closely with local partners, we will develop toolkits to explore short-term emergency response, as well as long-term mitigation and adaptation techniques in six pilot locations in South and Southeast Asia, Africa, and South America.

      Ocean vital signs

      On average, every person on Earth generates fossil fuel emissions equivalent to an 8-pound bag of carbon, every day. Much of this is absorbed by the ocean, but there is wide variability in the estimates of oceanic absorption, which translates into differences of trillions of dollars in the required cost of mitigation. In the Department of Earth, Atmospheric and Planetary Sciences, Christopher Hill, a principal research engineer specializing in Earth and planetary computational science, works with Ryan Woosley, a principal research scientist focusing on the carbon cycle and ocean acidification. Hill explains that they hope to use artificial intelligence and machine learning to help resolve this uncertainty.

      Q: What is the current state of knowledge on air-sea interactions?

      A: Obtaining specific, accurate field measurements of critical physical, chemical, and biological exchanges between the ocean and the planet have historically entailed expensive science missions with large ship-based infrastructure that leave gaps in real-time data about significant ocean climate processes. Recent advances in highly scalable in-situ autonomous observing and navigation combined with airborne, remote sensing, and machine learning innovations have the potential to transform data gathering, provide more accurate information, and address fundamental scientific questions around air-sea interaction.

      Q: How will your approach accelerate real-time, autonomous surface ocean observing from an experimental research endeavor to a permanent and impactful solution?

      A: Our project seeks to demonstrate how a scalable surface ocean observing network can be launched and operated, and to illustrate how this can reduce uncertainties in estimates of air-sea carbon dioxide exchange. With an initial high-impact goal of substantially eliminating the vast uncertainties that plague our understanding of ocean uptake of carbon dioxide, we will gather critical measurements for improving extended weather and climate forecast models and reducing climate impact uncertainty. The results have the potential to more accurately identify trillions of dollars worth of economic activity. More

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      New program bolsters innovation in next-generation artificial intelligence hardware

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      The MIT AI Hardware Program is a new academia and industry collaboration aimed at defining and developing translational technologies in hardware and software for the AI and quantum age. A collaboration between the MIT School of Engineering and MIT Schwarzman College of Computing, involving the Microsystems Technologies Laboratories and programs and units in the college, the cross-disciplinary effort aims to innovate technologies that will deliver enhanced energy efficiency systems for cloud and edge computing.

      “A sharp focus on AI hardware manufacturing, research, and design is critical to meet the demands of the world’s evolving devices, architectures, and systems,” says Anantha Chandrakasan, dean of the MIT School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science. “Knowledge-sharing between industry and academia is imperative to the future of high-performance computing.”

      Based on use-inspired research involving materials, devices, circuits, algorithms, and software, the MIT AI Hardware Program convenes researchers from MIT and industry to facilitate the transition of fundamental knowledge to real-world technological solutions. The program spans materials and devices, as well as architecture and algorithms enabling energy-efficient and sustainable high-performance computing.

      “As AI systems become more sophisticated, new solutions are sorely needed to enable more advanced applications and deliver greater performance,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and Henry Ellis Warren Professor of Electrical Engineering and Computer Science. “Our aim is to devise real-world technological solutions and lead the development of technologies for AI in hardware and software.”

      The inaugural members of the program are companies from a wide range of industries including chip-making, semiconductor manufacturing equipment, AI and computing services, and information systems R&D organizations. The companies represent a diverse ecosystem, both nationally and internationally, and will work with MIT faculty and students to help shape a vibrant future for our planet through cutting-edge AI hardware research.

      The five inaugural members of the MIT AI Hardware Program are:  

      Amazon, a global technology company whose hardware inventions include the Kindle, Amazon Echo, Fire TV, and Astro; 
      Analog Devices, a global leader in the design and manufacturing of analog, mixed signal, and DSP integrated circuits; 
      ASML, an innovation leader in the semiconductor industry, providing chipmakers with hardware, software, and services to mass produce patterns on silicon through lithography; 
      NTT Research, a subsidiary of NTT that conducts fundamental research to upgrade reality in game-changing ways that improve lives and brighten our global future; and 
      TSMC, the world’s leading dedicated semiconductor foundry.

      The MIT AI Hardware Program will create a roadmap of transformative AI hardware technologies. Leveraging MIT.nano, the most advanced university nanofabrication facility anywhere, the program will foster a unique environment for AI hardware research.  

      “We are all in awe at the seemingly superhuman capabilities of today’s AI systems. But this comes at a rapidly increasing and unsustainable energy cost,” says Jesús del Alamo, the Donner Professor in MIT’s Department of Electrical Engineering and Computer Science. “Continued progress in AI will require new and vastly more energy-efficient systems. This, in turn, will demand innovations across the entire abstraction stack, from materials and devices to systems and software. The program is in a unique position to contribute to this quest.”

      The program will prioritize the following topics:

      analog neural networks;
      new roadmap CMOS designs;
      heterogeneous integration for AI systems;
      onolithic-3D AI systems;
      analog nonvolatile memory devices;
      software-hardware co-design;
      intelligence at the edge;
      intelligent sensors;
      energy-efficient AI;
      intelligent internet of things (IIoT);
      neuromorphic computing;
      AI edge security;
      quantum AI;
      wireless technologies;
      hybrid-cloud computing; and
      high-performance computation.

      “We live in an era where paradigm-shifting discoveries in hardware, systems communications, and computing have become mandatory to find sustainable solutions — solutions that we are proud to give to the world and generations to come,” says Aude Oliva, senior research scientist in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and director of strategic industry engagement in the MIT Schwarzman College of Computing.

      The new program is co-led by Jesús del Alamo and Aude Oliva, and Anantha Chandrakasan serves as chair. More

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      Q&A: Climate Grand Challenges finalists on new pathways to decarbonizing industry

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      Note: This is the third article in a four-part interview series highlighting the work of the 27 MIT Climate Grand Challenges finalist teams, which received a total of $2.7 million in startup funding to advance their projects. In April, the Institute will name a subset of the finalists as multiyear flagship projects.

      The industrial sector is the backbone of today’s global economy, yet its activities are among the most energy-intensive and the toughest to decarbonize. Efforts to reach net-zero targets and avert runaway climate change will not succeed without new solutions for replacing sources of carbon emissions with low-carbon alternatives and developing scalable nonemitting applications of hydrocarbons.

      In conversations prepared for MIT News, faculty from three of the teams with projects in the competition’s “Decarbonizing complex industries and processes” category discuss strategies for achieving impact in hard-to-abate sectors, from long-distance transportation and building construction to textile manufacturing and chemical refining. The other Climate Grand Challenges research themes include using data and science to forecast climate-related risk, building equity and fairness into climate solutions, and removing, managing, and storing greenhouse gases. The following responses have been edited for length and clarity.

      Moving toward an all-carbon material approach to building

      Faced with the prospect of building stock doubling globally by 2050, there is a great need for sustainable alternatives to conventional mineral- and metal-based construction materials. Mark Goulthorpe, associate professor in the Department of Architecture, explains the methods behind Carbon >Building, an initiative to develop energy-efficient building materials by reorienting hydrocarbons from current use as fuels to environmentally benign products, creating an entirely new genre of lightweight, all-carbon buildings that could actually drive decarbonization.

      Q: What are all-carbon buildings and how can they help mitigate climate change?

      A: Instead of burning hydrocarbons as fuel, which releases carbon dioxide and other greenhouse gases that contribute to atmospheric pollution, we seek to pioneer a process that uses carbon materially to build at macro scale. New forms of carbon — carbon nanotube, carbon foam, etc. — offer salient properties for building that might effectively displace the current material paradigm. Only hydrocarbons offer sufficient scale to beat out the billion-ton mineral and metal markets, and their perilous impact. Carbon nanotube from methane pyrolysis is of special interest, as it offers hydrogen as a byproduct.

      Q: How will society benefit from the widespread use of all-carbon buildings?

      A: We anticipate reducing costs and timelines in carbon composite buildings, while increasing quality, longevity, and performance, and diminishing environmental impact. Affordability of buildings is a growing problem in all global markets as the cost of labor and logistics in multimaterial assemblies creates a burden that is very detrimental to economic growth and results in overcrowding and urban blight.

      Alleviating these challenges would have huge societal benefits, especially for those in lower income brackets who cannot afford housing, but the biggest benefit would be in drastically reducing the environmental footprint of typical buildings, which account for nearly 40 percent of global energy consumption.

      An all-carbon building sector will not only reduce hydrocarbon extraction, but can produce higher value materials for building. We are looking to rethink the building industry by greatly streamlining global production and learning from the low-labor methods pioneered by composite manufacturing such as wind turbine blades, which are quick and cheap to produce. This technology can improve the sustainability and affordability of buildings — and holds the promise of faster, cheaper, greener, and more resilient modes of dwelling.

      Emissions reduction through innovation in the textile industry

      Collectively, the textile industry is responsible for over 4 billion metric tons of carbon dioxide equivalent per year, or 5 to 10 percent of global greenhouse gas emissions — more than aviation and maritime shipping combined. And the problem is only getting worse with the industry’s rapid growth. Under the current trajectory, consumption is projected to increase 30 percent by 2030, reaching 102 million tons. A diverse group of faculty and researchers led by Gregory Rutledge, the Lammot du Pont Professor in the Department of Chemical Engineering, and Yuly Fuentes-Medel, project manager for fiber technologies and research advisor to the MIT Innovation Initiative, is developing groundbreaking innovations to reshape how textiles are selected, sourced, designed, manufactured, and used, and to create the structural changes required for sustained reductions in emissions by this industry.

      Q: Why has the textile industry been difficult to decarbonize?

      A: The industry currently operates under a linear model that relies heavily on virgin feedstock, at roughly 97 percent, yet recycles or downcycles less than 15 percent. Furthermore, recent trends in “fast fashion” have led to massive underutilization of apparel, such that products are discarded on average after only seven to 10 uses. In an industry with high volume and low margins, replacement technologies must achieve emissions reduction at scale while maintaining performance and economic efficiency.

      There are also technical barriers to adopting circular business models, from the challenge of dealing with products comprising fiber blends and chemical additives to the low maturity of recycling technologies. The environmental impacts of textiles and apparel have been estimated using life cycle analysis, and industry-standard indexes are under development to assess sustainability throughout the life cycle of a product, but information and tools are needed to model how new solutions will alter those impacts and include the consumer as an active player to keep our planet safe. This project seeks to deliver both the new solutions and the tools to evaluate their potential for impact.

      Q: Describe the five components of your program. What is the anticipated timeline for implementing these solutions?

      A: Our plan comprises five programmatic sections, which include (1) enabling a paradigm shift to sustainable materials using nontraditional, carbon-negative polymers derived from biomass and additives that facilitate recycling; (2) rethinking manufacturing with processes to structure fibers and fabrics for performance, waste reduction, and increased material efficiency; (3) designing textiles for value by developing products that are customized, adaptable, and multifunctional, and that interact with their environment to reduce energy consumption; (4) exploring consumer behavior change through human interventions that reduce emissions by encouraging the adoption of new technologies, increased utilization of products, and circularity; and (5) establishing carbon transparency with systems-level analyses that measure the impact of these strategies and guide decision making.

      We have proposed a five-year timeline with annual targets for each project. Conservatively, we estimate our program could reduce greenhouse gas emissions in the industry by 25 percent by 2030, with further significant reductions to follow.

      Tough-to-decarbonize transportation

      Airplanes, transoceanic ships, and freight trucks are critical to transporting people and delivering goods, and the cornerstone of global commerce, manufacturing, and tourism. But these vehicles also emit 3.7 billion tons of carbon dioxide annually and, left unchecked, they could take up a quarter of the remaining carbon budget by 2050. William Green, the Hoyt C. Hottel Professor in the Department Chemical Engineering, co-leads a multidisciplinary team with Steven Barrett, professor of aeronautics and astronautics and director of the MIT Laboratory for Aviation and the Environment, that is working to identify and advance economically viable technologies and policies for decarbonizing heavy duty trucking, shipping, and aviation. The Tough to Decarbonize Transportation research program aims to design and optimize fuel chemistry and production, vehicles, operations, and policies to chart the course to net-zero emissions by midcentury.

      Q: What are the highest priority focus areas of your research program?

      A: Hydrocarbon fuels made from biomass are the least expensive option, but it seems impractical, and probably damaging to the environment, to harvest the huge amount of biomass that would be needed to meet the massive and growing energy demands from these sectors using today’s biomass-to-fuel technology. We are exploring strategies to increase the amount of useful fuel made per ton of biomass harvested, other methods to make low-climate-impact hydrocarbon fuels, such as from carbon dioxide, and ways to make fuels that do not contain carbon at all, such as with hydrogen, ammonia, and other hydrogen carriers.

      These latter zero-carbon options free us from the need for biomass or to capture gigatons of carbon dioxide, so they could be a very good long-term solution, but they would require changing the vehicles significantly, and the construction of new refueling infrastructure, with high capital costs.

      Q: What are the scientific, technological, and regulatory barriers to scaling and implementing potential solutions?

      A: Reimagining an aviation, trucking, and shipping sector that connects the world and increases equity without creating more environmental damage is challenging because these vehicles must operate disconnected from the electrical grid and have energy requirements that cannot be met by batteries alone. Some of the concepts do not even exist in prototype yet, and none of the appealing options have been implemented at anywhere near the scale required.

      In most cases, we do not know the best way to make the fuel, and for new fuels the vehicles and refueling systems all need to be developed. Also, new fuels, or large-scale use of biomass, will introduce new environmental problems that need to be carefully considered, to ensure that decarbonization solutions do not introduce big new problems.

      Perhaps most difficult are the policy, economic, and equity issues. A new long-haul transportation system will be expensive, and everyone will be affected by the increased cost of shipping freight. To have the desired climate impact, the transport system must change in almost every country. During the transition period, we will need both the existing vehicle and fuel system to keep running smoothly, even as a new low-greenhouse system is introduced. We will also examine what policies could make that work and how we can get countries around the world to agree to implement them. More

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      Q&A: Climate Grand Challenges finalists on accelerating reductions in global greenhouse gas emissions

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      This is the second article in a four-part interview series highlighting the work of the 27 MIT Climate Grand Challenges finalists, which received a total of $2.7 million in startup funding to advance their projects. In April, the Institute will name a subset of the finalists as multiyear flagship projects.

      Last month, the Intergovernmental Panel on Climate Change (IPCC), an expert body of the United Nations representing 195 governments, released its latest scientific report on the growing threats posed by climate change, and called for drastic reductions in greenhouse gas emissions to avert the most catastrophic outcomes for humanity and natural ecosystems.

      Bringing the global economy to net-zero carbon dioxide emissions by midcentury is complex and demands new ideas and novel approaches. The first-ever MIT Climate Grand Challenges competition focuses on four problem areas including removing greenhouse gases from the atmosphere and identifying effective, economic solutions for managing and storing these gases. The other Climate Grand Challenges research themes address using data and science to forecast climate-related risk, decarbonizing complex industries and processes, and building equity and fairness into climate solutions.

      In the following conversations prepared for MIT News, faculty from three of the teams working to solve “Removing, managing, and storing greenhouse gases” explain how they are drawing upon geological, biological, chemical, and oceanic processes to develop game-changing techniques for carbon removal, management, and storage. Their responses have been edited for length and clarity.

      Directed evolution of biological carbon fixation

      Agricultural demand is estimated to increase by 50 percent in the coming decades, while climate change is simultaneously projected to drastically reduce crop yield and predictability, requiring a dramatic acceleration of land clearing. Without immediate intervention, this will have dire impacts on wild habitat, rob the livelihoods of hundreds of millions of subsistence farmers, and create hundreds of gigatons of new emissions. Matthew Shoulders, associate professor in the Department of Chemistry, talks about the working group he is leading in partnership with Ed Boyden, the Y. Eva Tan professor of neurotechnology and Howard Hughes Medical Institute investigator at the McGovern Institute for Brain Research, that aims to massively reduce carbon emissions from agriculture by relieving core biochemical bottlenecks in the photosynthetic process using the most sophisticated synthetic biology available to science.

      Q: Describe the two pathways you have identified for improving agricultural productivity and climate resiliency.

      A: First, cyanobacteria grow millions of times faster than plants and dozens of times faster than microalgae. Engineering these cyanobacteria as a source of key food products using synthetic biology will enable food production using less land, in a fundamentally more climate-resilient manner. Second, carbon fixation, or the process by which carbon dioxide is incorporated into organic compounds, is the rate-limiting step of photosynthesis and becomes even less efficient under rising temperatures. Enhancements to Rubisco, the enzyme mediating this central process, will both improve crop yields and provide climate resilience to crops needed by 2050. Our team, led by Robbie Wilson and Max Schubert, has created new directed evolution methods tailored for both strategies, and we have already uncovered promising early results. Applying directed evolution to photosynthesis, carbon fixation, and food production has the potential to usher in a second green revolution.

      Q: What partners will you need to accelerate the development of your solutions?

      A: We have already partnered with leading agriculture institutes with deep experience in plant transformation and field trial capacity, enabling the integration of our improved carbon-dioxide-fixing enzymes into a wide range of crop plants. At the deployment stage, we will be positioned to partner with multiple industry groups to achieve improved agriculture at scale. Partnerships with major seed companies around the world will be key to leverage distribution channels in manufacturing supply chains and networks of farmers, agronomists, and licensed retailers. Support from local governments will also be critical where subsidies for seeds are necessary for farmers to earn a living, such as smallholder and subsistence farming communities. Additionally, our research provides an accessible platform that is capable of enabling and enhancing carbon dioxide sequestration in diverse organisms, extending our sphere of partnership to a wide range of companies interested in industrial microbial applications, including algal and cyanobacterial, and in carbon capture and storage.

      Strategies to reduce atmospheric methane

      One of the most potent greenhouse gases, methane is emitted by a range of human activities and natural processes that include agriculture and waste management, fossil fuel production, and changing land use practices — with no single dominant source. Together with a diverse group of faculty and researchers from the schools of Humanities, Arts, and Social Sciences; Architecture and Planning; Engineering; and Science; plus the MIT Schwarzman College of Computing, Desiree Plata, associate professor in the Department of Civil and Environmental Engineering, is spearheading the MIT Methane Network, an integrated approach to formulating scalable new technologies, business models, and policy solutions for driving down levels of atmospheric methane.

      Q: What is the problem you are trying to solve and why is it a “grand challenge”?

      A: Removing methane from the atmosphere, or stopping it from getting there in the first place, could change the rates of global warming in our lifetimes, saving as much as half a degree of warming by 2050. Methane sources are distributed in space and time and tend to be very dilute, making the removal of methane a challenge that pushes the boundaries of contemporary science and engineering capabilities. Because the primary sources of atmospheric methane are linked to our economy and culture — from clearing wetlands for cultivation to natural gas extraction and dairy and meat production — the social and economic implications of a fundamentally changed methane management system are far-reaching. Nevertheless, these problems are tractable and could significantly reduce the effects of climate change in the near term.

      Q: What is known about the rapid rise in atmospheric methane and what questions remain unanswered?

      A: Tracking atmospheric methane is a challenge in and of itself, but it has become clear that emissions are large, accelerated by human activity, and cause damage right away. While some progress has been made in satellite-based measurements of methane emissions, there is a need to translate that data into actionable solutions. Several key questions remain around improving sensor accuracy and sensor network design to optimize placement, improve response time, and stop leaks with autonomous controls on the ground. Additional questions involve deploying low-level methane oxidation systems and novel catalytic materials at coal mines, dairy barns, and other enriched sources; evaluating the policy strategies and the socioeconomic impacts of new technologies with an eye toward decarbonization pathways; and scaling technology with viable business models that stimulate the economy while reducing greenhouse gas emissions.

      Deploying versatile carbon capture technologies and storage at scale

      There is growing consensus that simply capturing current carbon dioxide emissions is no longer sufficient — it is equally important to target distributed sources such as the oceans and air where carbon dioxide has accumulated from past emissions. Betar Gallant, the American Bureau of Shipping Career Development Associate Professor of Mechanical Engineering, discusses her work with Bradford Hager, the Cecil and Ida Green Professor of Earth Sciences in the Department of Earth, Atmospheric and Planetary Sciences, and T. Alan Hatton, the Ralph Landau Professor of Chemical Engineering and director of the School of Chemical Engineering Practice, to dramatically advance the portfolio of technologies available for carbon capture and permanent storage at scale. (A team led by Assistant Professor Matěj Peč of EAPS is also addressing carbon capture and storage.)

      Q: Carbon capture and storage processes have been around for several decades. What advances are you seeking to make through this project?

      A: Today’s capture paradigms are costly, inefficient, and complex. We seek to address this challenge by developing a new generation of capture technologies that operate using renewable energy inputs, are sufficiently versatile to accommodate emerging industrial demands, are adaptive and responsive to varied societal needs, and can be readily deployed to a wider landscape.

      New approaches will require the redesign of the entire capture process, necessitating basic science and engineering efforts that are broadly interdisciplinary in nature. At the same time, incumbent technologies have been optimized largely for integration with coal- or natural gas-burning power plants. Future applications must shift away from legacy emitters in the power sector towards hard-to-mitigate sectors such as cement, iron and steel, chemical, and hydrogen production. It will become equally important to develop and optimize systems targeted for much lower concentrations of carbon dioxide, such as in oceans or air. Our effort will expand basic science studies as well as human impacts of storage, including how public engagement and education can alter attitudes toward greater acceptance of carbon dioxide geologic storage.

      Q: What are the expected impacts of your proposed solution, both positive and negative?

      A: Renewable energy cannot be deployed rapidly enough everywhere, nor can it supplant all emissions sources, nor can it account for past emissions. Carbon capture and storage (CCS) provides a demonstrated method to address emissions that will undoubtedly occur before the transition to low-carbon energy is completed. CCS can succeed even if other strategies fail. It also allows for developing nations, which may need to adopt renewables over longer timescales, to see equitable economic development while avoiding the most harmful climate impacts. And, CCS enables the future viability of many core industries and transportation modes, many of which do not have clear alternatives before 2050, let alone 2040 or 2030.

      The perceived risks of potential leakage and earthquakes associated with geologic storage can be minimized by choosing suitable geologic formations for storage. Despite CCS providing a well-understood pathway for removing enough of the carbon dioxide already emitted into the atmosphere, some environmentalists vigorously oppose it, fearing that CCS rewards oil companies and disincentivizes the transition away from fossil fuels. We believe that it is more important to keep in mind the necessity of meeting key climate targets for the sake of the planet, and welcome those who can help. More