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      in Environment

      Study finds natural sources of air pollution exceed air quality guidelines in many regions

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      Alongside climate change, air pollution is one of the biggest environmental threats to human health. Tiny particles known as particulate matter or PM2.5 (named for their diameter of just 2.5 micrometers or less) are a particularly hazardous type of pollutant. These particles are produced from a variety of sources, including wildfires and the burning of fossil fuels, and can enter our bloodstream, travel deep into our lungs, and cause respiratory and cardiovascular damage. Exposure to particulate matter is responsible for millions of premature deaths globally every year.

      In response to the increasing body of evidence on the detrimental effects of PM2.5, the World Health Organization (WHO) recently updated its air quality guidelines, lowering its recommended annual PM2.5 exposure guideline by 50 percent, from 10 micrograms per meter cubed (μm3) to 5 μm3. These updated guidelines signify an aggressive attempt to promote the regulation and reduction of anthropogenic emissions in order to improve global air quality.

      A new study by researchers in the MIT Department of Civil and Environmental Engineering explores if the updated air quality guideline of 5 μm3 is realistically attainable across different regions of the world, particularly if anthropogenic emissions are aggressively reduced. 

      The first question the researchers wanted to investigate was to what degree moving to a no-fossil-fuel future would help different regions meet this new air quality guideline.

      “The answer we found is that eliminating fossil-fuel emissions would improve air quality around the world, but while this would help some regions come into compliance with the WHO guidelines, for many other regions high contributions from natural sources would impede their ability to meet that target,” says senior author Colette Heald, the Germeshausen Professor in the MIT departments of Civil and Environmental Engineering, and Earth, Atmospheric and Planetary Sciences. 

      The study by Heald, Professor Jesse Kroll, and graduate students Sidhant Pai and Therese Carter, published June 6 in the journal Environmental Science and Technology Letters, finds that over 90 percent of the global population is currently exposed to average annual concentrations that are higher than the recommended guideline. The authors go on to demonstrate that over 50 percent of the world’s population would still be exposed to PM2.5 concentrations that exceed the new air quality guidelines, even in the absence of all anthropogenic emissions.

      This is due to the large natural sources of particulate matter — dust, sea salt, and organics from vegetation — that still exist in the atmosphere when anthropogenic emissions are removed from the air. 

      “If you live in parts of India or northern Africa that are exposed to large amounts of fine dust, it can be challenging to reduce PM2.5 exposures below the new guideline,” says Sidhant Pai, co-lead author and graduate student. “This study challenges us to rethink the value of different emissions abatement controls across different regions and suggests the need for a new generation of air quality metrics that can enable targeted decision-making.”

      The researchers conducted a series of model simulations to explore the viability of achieving the updated PM2.5 guidelines worldwide under different emissions reduction scenarios, using 2019 as a representative baseline year. 

      Their model simulations used a suite of different anthropogenic sources that could be turned on and off to study the contribution of a particular source. For instance, the researchers conducted a simulation that turned off all human-based emissions in order to determine the amount of PM2.5 pollution that could be attributed to natural and fire sources. By analyzing the chemical composition of the PM2.5 aerosol in the atmosphere (e.g., dust, sulfate, and black carbon), the researchers were also able to get a more accurate understanding of the most important PM2.5 sources in a particular region. For example, elevated PM2.5 concentrations in the Amazon were shown to predominantly consist of carbon-containing aerosols from sources like deforestation fires. Conversely, nitrogen-containing aerosols were prominent in Northern Europe, with large contributions from vehicles and fertilizer usage. The two regions would thus require very different policies and methods to improve their air quality. 

      “Analyzing particulate pollution across individual chemical species allows for mitigation and adaptation decisions that are specific to the region, as opposed to a one-size-fits-all approach, which can be challenging to execute without an understanding of the underlying importance of different sources,” says Pai. 

      When the WHO air quality guidelines were last updated in 2005, they had a significant impact on environmental policies. Scientists could look at an area that was not in compliance and suggest high-level solutions to improve the region’s air quality. But as the guidelines have tightened, globally-applicable solutions to manage and improve air quality are no longer as evident. 

      “Another benefit of speciating is that some of the particles have different toxicity properties that are correlated to health outcomes,” says Therese Carter, co-lead author and graduate student. “It’s an important area of research that this work can help motivate. Being able to separate out that piece of the puzzle can provide epidemiologists with more insights on the different toxicity levels and the impact of specific particles on human health.”

      The authors view these new findings as an opportunity to expand and iterate on the current guidelines.  

      “Routine and global measurements of the chemical composition of PM2.5 would give policymakers information on what interventions would most effectively improve air quality in any given location,” says Jesse Kroll, a professor in the MIT departments of Civil and Environmental Engineering and Chemical Engineering. “But it would also provide us with new insights into how different chemical species in PM2.5 affect human health.”

      “I hope that as we learn more about the health impacts of these different particles, our work and that of the broader atmospheric chemistry community can help inform strategies to reduce the pollutants that are most harmful to human health,” adds Heald. More

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      in Energy

      MIT Climate and Sustainability Consortium announces recipients of inaugural MCSC Seed Awards

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      The MIT Climate and Sustainability Consortium (MCSC) has awarded 20 projects a total of $5 million over two years in its first-ever 2022 MCSC Seed Awards program. The winning projects are led by principal investigators across all five of MIT’s schools.

      The goal of the MCSC Seed Awards is to engage MIT researchers and link the economy-wide work of the consortium to ongoing and emerging climate and sustainability efforts across campus. The program offers further opportunity to build networks among the awarded projects to deepen the impact of each and ensure the total is greater than the sum of its parts.

      For example, to drive progress under the awards category Circularity and Materials, the MCSC can facilitate connections between the technologists at MIT who are developing recovery approaches for metals, plastics, and fiber; the urban planners who are uncovering barriers to reuse; and the engineers, who will look for efficiency opportunities in reverse supply chains.

      “The MCSC Seed Awards are designed to complement actions previously outlined in Fast Forward: MIT’s Climate Action Plan for the Decade and, more specifically, the Climate Grand Challenges,” says Anantha P. Chandrakasan, dean of the MIT School of Engineering, Vannevar Bush Professor of Electrical Engineering and Computer Science, and chair of the MIT Climate and Sustainability Consortium. “In collaboration with seed award recipients and MCSC industry members, we are eager to engage in interdisciplinary exploration and propel urgent advancements in climate and sustainability.” 

      By supporting MIT researchers with expertise in economics, infrastructure, community risk assessment, mobility, and alternative fuels, the MCSC will accelerate implementation of cross-disciplinary solutions in the awards category Decarbonized and Resilient Value Chains. Enhancing Natural Carbon Sinks and building connections to local communities will require associations across experts in ecosystem change, biodiversity, improved agricultural practice and engagement with farmers, all of which the consortium can begin to foster through the seed awards.

      “Funding opportunities across campus has been a top priority since launching the MCSC,” says Jeremy Gregory, MCSC executive director. “It is our honor to support innovative teams of MIT researchers through the inaugural 2022 MCSC Seed Awards program.”

      The winning projects are tightly aligned with the MCSC’s areas of focus, which were derived from a year of highly engaged collaborations with MCSC member companies. The projects apply across the member’s climate and sustainability goals.

      The MCSC’s 16 member companies span many industries, and since early 2021, have met with members of the MIT community to define focused problem statements for industry-specific challenges, identify meaningful partnerships and collaborations, and develop clear and scalable priorities. Outcomes from these collaborations laid the foundation for the focus areas, which have shaped the work of the MCSC. Specifically, the MCSC Industry Advisory Board engaged with MIT on key strategic directions, and played a critical role in the MCSC’s series of interactive events. These included virtual workshops hosted last summer, each on a specific topic that allowed companies to work with MIT and each other to align key assumptions, identify blind spots in corporate goal-setting, and leverage synergies between members, across industries. The work continued in follow-up sessions and an annual symposium.

      “We are excited to see how the seed award efforts will help our member companies reach or even exceed their ambitious climate targets, find new cross-sector links among each other, seek opportunities to lead, and ripple key lessons within their industry, while also deepening the Institute’s strong foundation in climate and sustainability research,” says Elsa Olivetti, the Esther and Harold E. Edgerton Associate Professor in Materials Science and Engineering and MCSC co-director.

      As the seed projects take shape, the MCSC will provide ongoing opportunities for awardees to engage with the Industry Advisory Board and technical teams from the MCSC member companies to learn more about the potential for linking efforts to support and accelerate their climate and sustainability goals. Awardees will also have the chance to engage with other members of the MCSC community, including its interdisciplinary Faculty Steering Committee.

      “One of our mantras in the MCSC is to ‘amplify and extend’ existing efforts across campus; we’re always looking for ways to connect the collaborative industry relationships we’re building and the work we’re doing with other efforts on campus,” notes Jeffrey Grossman, the Morton and Claire Goulder and Family Professor in Environmental Systems, head of the Department of Materials Science and Engineering, and MCSC co-director. “We feel the urgency as well as the potential, and we don’t want to miss opportunities to do more and go faster.”

      The MCSC Seed Awards complement the Climate Grand Challenges, a new initiative to mobilize the entire MIT research community around developing the bold, interdisciplinary solutions needed to address difficult, unsolved climate problems. The 27 finalist teams addressed four broad research themes, which align with the MCSC’s focus areas. From these finalist teams, five flagship projects were announced in April 2022.

      The parallels between MCSC’s focus areas and the Climate Grand Challenges themes underscore an important connection between the shared long-term research interests of industry and academia. The challenges that some of the world’s largest and most influential companies have identified are complementary to MIT’s ongoing research and innovation — highlighting the tremendous opportunity to develop breakthroughs and scalable solutions quickly and effectively. Special Presidential Envoy for Climate John Kerry underscored the importance of developing these scalable solutions, including critical new technology, during a conversation with MIT President L. Rafael Reif at MIT’s first Climate Grand Challenges showcase event last month.

      Both the MCSC Seed Awards and the Climate Grand Challenges are part of MIT’s larger commitment and initiative to combat climate change; this was underscored in “Fast Forward: MIT’s Climate Action Plan for the Decade,” which the Institute published in May 2021.

      The project titles and research leads for each of the 20 awardees listed below are categorized by MCSC focus area.

      Decarbonized and resilient value chains

      “Collaborative community mapping toolkit for resilience planning,” led by Miho Mazereeuw, associate professor of architecture and urbanism in the Department of Architecture and director of the Urban Risk Lab (a research lead on Climate Grand Challenges flagship project) and Nicholas de Monchaux, professor and department head in the Department of Architecture
      “CP4All: Fast and local climate projections with scientific machine learning — towards accessibility for all of humanity,” led by Chris Hill, principal research scientist in the Department of Earth, Atmospheric and Planetary Sciences and Dava Newman, director of the MIT Media Lab and the Apollo Program Professor in the Department of Aeronautics and Astronautics
      “Emissions reductions and productivity in U.S. manufacturing,” led by Mert Demirer, assistant professor of applied economics at the MIT Sloan School of Management and Jing Li, assistant professor and William Barton Rogers Career Development Chair of Energy Economics in the MIT Sloan School of Management
      “Logistics electrification through scalable and inter-operable charging infrastructure: operations, planning, and policy,” led by Alex Jacquillat, the 1942 Career Development Professor and assistant professor of operations research and statistics in the MIT Sloan School of Management
      “Powertrain and system design for LOHC-powered long-haul trucking,” led by William Green, the Hoyt Hottel Professor in Chemical Engineering in the Department of Chemical Engineering and postdoctoral officer, and Wai K. Cheng, professor in the Department of Mechanical Engineering and director of the Sloan Automotive Laboratory
      “Sustainable Separation and Purification of Biochemicals and Biofuels using Membranes,” led by John Lienhard, the Abdul Latif Jameel Professor of Water in the Department of Mechanical Engineering, director of the Abdul Latif Jameel Water and Food Systems Lab, and director of the Rohsenow Kendall Heat Transfer Laboratory; and Nicolas Hadjiconstantinou, professor in the Department of Mechanical Engineering, co-director of the Center for Computational Science and Engineering, associate director of the Center for Exascale Simulation of Materials in Extreme Environments, and graduate officer
      “Toolkit for assessing the vulnerability of industry infrastructure siting to climate change,” led by Michael Howland, assistant professor in the Department of Civil and Environmental Engineering

      Circularity and Materials

      “Colorimetric Sulfidation for Aluminum Recycling,” led by Antoine Allanore, associate professor of metallurgy in the Department of Materials Science and Engineering
      “Double Loop Circularity in Materials Design Demonstrated on Polyurethanes,” led by Brad Olsen, the Alexander and I. Michael Kasser (1960) Professor and graduate admissions co-chair in the Department of Chemical Engineering, and Kristala Prather, the Arthur Dehon Little Professor and department executive officer in the Department of Chemical Engineering
      “Engineering of a microbial consortium to degrade and valorize plastic waste,” led by Otto Cordero, associate professor in the Department of Civil and Environmental Engineering, and Desiree Plata, the Gilbert W. Winslow (1937) Career Development Professor in Civil Engineering and associate professor in the Department of Civil and Environmental Engineering
      “Fruit-peel-inspired, biodegradable packaging platform with multifunctional barrier properties,” led by Kripa Varanasi, professor in the Department of Mechanical Engineering
      “High Throughput Screening of Sustainable Polyesters for Fibers,” led by Gregory Rutledge, the Lammot du Pont Professor in the Department of Chemical Engineering, and Brad Olsen, Alexander and I. Michael Kasser (1960) Professor and graduate admissions co-chair in the Department of Chemical Engineering
      “Short-term and long-term efficiency gains in reverse supply chains,” led by Yossi Sheffi, the Elisha Gray II Professor of Engineering Systems, professor in the Department of Civil and Environmental Engineering, and director of the Center for Transportation and Logistics
      The costs and benefits of circularity in building construction, led by Siqi Zheng, the STL Champion Professor of Urban and Real Estate Sustainability at the MIT Center for Real Estate and Department of Urban Studies and Planning, faculty director of the MIT Center for Real Estate, and faculty director for the MIT Sustainable Urbanization Lab; and Randolph Kirchain, principal research scientist and co-director of MIT Concrete Sustainability Hub

      Natural carbon sinks

      “Carbon sequestration through sustainable practices by smallholder farmers,” led by Joann de Zegher, the Maurice F. Strong Career Development Professor and assistant professor of operations management in the MIT Sloan School of Management, and Karen Zheng the George M. Bunker Professor and associate professor of operations management in the MIT Sloan School of Management
      “Coatings to protect and enhance diverse microbes for improved soil health and crop yields,” led by Ariel Furst, the Raymond A. (1921) And Helen E. St. Laurent Career Development Professor of Chemical Engineering in the Department of Chemical Engineering, and Mary Gehring, associate professor of biology in the Department of Biology, core member of the Whitehead Institute for Biomedical Research, and graduate officer
      “ECO-LENS: Mainstreaming biodiversity data through AI,” led by John Fernández, professor of building technology in the Department of Architecture and director of MIT Environmental Solutions Initiative
      “Growing season length, productivity, and carbon balance of global ecosystems under climate change,” led by Charles Harvey, professor in the Department of Civil and Environmental Engineering, and César Terrer, assistant professor in the Department of Civil and Environmental Engineering

      Social dimensions and adaptation

      “Anthro-engineering decarbonization at the million-person scale,” led by Manduhai Buyandelger, professor in the Anthropology Section, and Michael Short, the Class of ’42 Associate Professor of Nuclear Science and Engineering in the Department of Nuclear Science and Engineering
      “Sustainable solutions for climate change adaptation: weaving traditional ecological knowledge and STEAM,” led by Janelle Knox-Hayes, the Lister Brothers Associate Professor of Economic Geography and Planning and head of the Environmental Policy and Planning Group in the Department of Urban Studies and Planning, and Miho Mazereeuw, associate professor of architecture and urbanism in the Department of Architecture and director of the Urban Risk Lab (a research lead on a Climate Grand Challenges flagship project) More

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      in Energy

      What choices does the world need to make to keep global warming below 2 C?

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      When the 2015 Paris Agreement set a long-term goal of keeping global warming “well below 2 degrees Celsius, compared to pre-industrial levels” to avoid the worst impacts of climate change, it did not specify how its nearly 200 signatory nations could collectively achieve that goal. Each nation was left to its own devices to reduce greenhouse gas emissions in alignment with the 2 C target. Now a new modeling strategy developed at the MIT Joint Program on the Science and Policy of Global Change that explores hundreds of potential future development pathways provides new insights on the energy and technology choices needed for the world to meet that target.

      Described in a study appearing in the journal Earth’s Future, the new strategy combines two well-known computer modeling techniques to scope out the energy and technology choices needed over the coming decades to reduce emissions sufficiently to achieve the Paris goal.

      The first technique, Monte Carlo analysis, quantifies uncertainty levels for dozens of energy and economic indicators including fossil fuel availability, advanced energy technology costs, and population and economic growth; feeds that information into a multi-region, multi-economic-sector model of the world economy that captures the cross-sectoral impacts of energy transitions; and runs that model hundreds of times to estimate the likelihood of different outcomes. The MIT study focuses on projections through the year 2100 of economic growth and emissions for different sectors of the global economy, as well as energy and technology use.

      The second technique, scenario discovery, uses machine learning tools to screen databases of model simulations in order to identify outcomes of interest and their conditions for occurring. The MIT study applies these tools in a unique way by combining them with the Monte Carlo analysis to explore how different outcomes are related to one another (e.g., do low-emission outcomes necessarily involve large shares of renewable electricity?). This approach can also identify individual scenarios, out of the hundreds explored, that result in specific combinations of outcomes of interest (e.g., scenarios with low emissions, high GDP growth, and limited impact on electricity prices), and also provide insight into the conditions needed for that combination of outcomes.

      Using this unique approach, the MIT Joint Program researchers find several possible patterns of energy and technology development under a specified long-term climate target or economic outcome.

      “This approach shows that there are many pathways to a successful energy transition that can be a win-win for the environment and economy,” says Jennifer Morris, an MIT Joint Program research scientist and the study’s lead author. “Toward that end, it can be used to guide decision-makers in government and industry to make sound energy and technology choices and avoid biases in perceptions of what ’needs’ to happen to achieve certain outcomes.”

      For example, while achieving the 2 C goal, the global level of combined wind and solar electricity generation by 2050 could be less than three times or more than 12 times the current level (which is just over 2,000 terawatt hours). These are very different energy pathways, but both can be consistent with the 2 C goal. Similarly, there are many different energy mixes that can be consistent with maintaining high GDP growth in the United States while also achieving the 2 C goal, with different possible roles for renewables, natural gas, carbon capture and storage, and bioenergy. The study finds renewables to be the most robust electricity investment option, with sizable growth projected under each of the long-term temperature targets explored.

      The researchers also find that long-term climate targets have little impact on economic output for most economic sectors through 2050, but do require each sector to significantly accelerate reduction of its greenhouse gas emissions intensity (emissions per unit of economic output) so as to reach near-zero levels by midcentury.

      “Given the range of development pathways that can be consistent with meeting a 2 degrees C goal, policies that target only specific sectors or technologies can unnecessarily narrow the solution space, leading to higher costs,” says former MIT Joint Program Co-Director John Reilly, a co-author of the study. “Our findings suggest that policies designed to encourage a portfolio of technologies and sectoral actions can be a wise strategy that hedges against risks.”

      The research was supported by the U.S. Department of Energy Office of Science. More

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      in Environment

      Empowering people to adapt on the frontlines of climate change

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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 fifth in a five-part series highlighting the most promising concepts to emerge from the competition and the interdisciplinary research teams behind them.

      In the coastal south of Bangladesh, rice paddies that farmers could once harvest three times a year lie barren. Sea-level rise brings saltwater to the soil, ruining the staple crop. It’s one of many impacts, and inequities, of climate change. Despite producing less than 1 percent of global carbon emissions, Bangladesh is suffering more than most countries. Rising seas, heat waves, flooding, and cyclones threaten 90 million people.

      A platform being developed in a collaboration between MIT and BRAC, a Bangladesh-based global development organization, aims to inform and empower climate-threatened communities to proactively adapt to a changing future. Selected as one of five MIT Climate Grand Challenges flagship projects, the Climate Resilience Early Warning System (CREWSnet) will forecast the local impacts of climate change on people’s lives, homes, and livelihoods. These forecasts will guide BRAC’s development of climate-resiliency programs to help residents prepare for and adapt to life-altering conditions.

      “The communities that CREWSnet will focus on have done little to contribute to the problem of climate change in the first place. However, because of socioeconomic situations, they may be among the most vulnerable. We hope that by providing state-of-the-art projections and sharing them broadly with communities, and working through partners like BRAC, we can help improve the capacity of local communities to adapt to climate change, significantly,” says Elfatih Eltahir, the H.M. King Bhumibol Professor in the Department of Civil and Environmental Engineering.

      Eltahir leads the project with John Aldridge and Deborah Campbell in the Humanitarian Assistance and Disaster Relief Systems Group at Lincoln Laboratory. Additional partners across MIT include the Center for Global Change Science; the Department of Earth, Atmospheric and Planetary Sciences; the Joint Program on the Science and Policy of Global Change; and the Abdul Latif Jameel Poverty Action Lab. 

      Predicting local risks

      CREWSnet’s forecasts rely upon a sophisticated model, developed in Eltahir’s research group over the past 25 years, called the MIT Regional Climate Model. This model zooms in on climate processes at local scales, at a resolution as granular as 6 miles. In Bangladesh’s population-dense cities, a 6-mile area could encompass tens, or even hundreds, of thousands of people. The model takes into account the details of a region’s topography, land use, and coastline to predict changes in local conditions.

      When applying this model over Bangladesh, researchers found that heat waves will get more severe and more frequent over the next 30 years. In particular, wet-bulb temperatures, which indicate the ability for humans to cool down by sweating, will rise to dangerous levels rarely observed today, particularly in western, inland cities.

      Such hot spots exacerbate other challenges predicted to worsen near Bangladesh’s coast. Rising sea levels and powerful cyclones are eroding and flooding coastal communities, causing saltwater to surge into land and freshwater. This salinity intrusion is detrimental to human health, ruins drinking water supplies, and harms crops, livestock, and aquatic life that farmers and fishermen depend on for food and income.

      CREWSnet will fuse climate science with forecasting tools that predict the social and economic impacts to villages and cities. These forecasts — such as how often a crop season may fail, or how far floodwaters will reach — can steer decision-making.

      “What people need to know, whether they’re a governor or head of a household, is ‘What is going to happen in my area, and what decisions should I make for the people I’m responsible for?’ Our role is to integrate this science and technology together into a decision support system,” says Aldridge, whose group at Lincoln Laboratory specializes in this area. Most recently, they transitioned a hurricane-evacuation planning system to the U.S. government. “We know that making decisions based on climate change requires a deep level of trust. That’s why having a powerful partner like BRAC is so important,” he says.

      Testing interventions

      Established 50 years ago, just after Bangladesh’s independence, BRAC works in every district of the nation to provide social services that help people rise from extreme poverty. Today, it is one of the world’s largest nongovernmental organizations, serving 110 million people across 11 countries in Asia and Africa, but its success is cultivated locally.

      “BRAC is thrilled to partner with leading researchers at MIT to increase climate resilience in Bangladesh and provide a model that can be scaled around the globe,” says Donella Rapier, president and CEO of BRAC USA. “Locally led climate adaptation solutions that are developed in partnership with communities are urgently needed, particularly in the most vulnerable regions that are on the frontlines of climate change.”

      CREWSnet will help BRAC identify communities most vulnerable to forecasted impacts. In these areas, they will share knowledge and innovate or bolster programs to improve households’ capacity to adapt.

      Many climate initiatives are already underway. One program equips homes to filter and store rainwater, as salinity intrusion makes safe drinking water hard to access. Another program is building resilient housing, able to withstand 120-mile-per-hour winds, that can double as local shelters during cyclones and flooding. Other services are helping farmers switch to different livestock or crops better suited for wetter or saltier conditions (e.g., ducks instead of chickens, or salt-tolerant rice), providing interest-free loans to enable this change.

      But adapting in place will not always be possible, for example in areas predicted to be submerged or unbearably hot by midcentury. “Bangladesh is working on identifying and developing climate-resilient cities and towns across the country, as closer-by alternative destinations as compared to moving to Dhaka, the overcrowded capital of Bangladesh,” says Campbell. “CREWSnet can help identify regions better suited for migration, and climate-resilient adaptation strategies for those regions.” At the same time, BRAC’s Climate Bridge Fund is helping to prepare cities for climate-induced migration, building up infrastructure and financial services for people who have been displaced.

      Evaluating impact

      While CREWSnet’s goal is to enable action, it can’t quite measure the impact of those actions. The Abdul Latif Jameel Poverty Action Lab (J-PAL), a development economics program in the MIT School of Humanities, Arts, and Social Sciences, will help evaluate the effectiveness of the climate-adaptation programs.

      “We conduct randomized controlled trials, similar to medical trials, that help us understand if a program improved people’s lives,” says Claire Walsh, the project director of the King Climate Action Initiative at J-PAL. “Once CREWSnet helps BRAC implement adaptation programs, we will generate scientific evidence on their impacts, so that BRAC and CREWSnet can make a case to funders and governments to expand effective programs.”

      The team aspires to bring CREWSnet to other nations disproportionately impacted by climate change. “Our vision is to have this be a globally extensible capability,” says Campbell. CREWSnet’s name evokes another early-warning decision-support system, FEWSnet, that helped organizations address famine in eastern Africa in the 1980s. Today it is a pillar of food-security planning around the world.

      CREWSnet hopes for a similar impact in climate change planning. Its selection as an MIT Climate Grand Challenges flagship project will inject the project with more funding and resources, momentum that will also help BRAC’s fundraising. The team plans to deploy CREWSnet to southwestern Bangladesh within five years.

      “The communities that we are aspiring to reach with CREWSnet are deeply aware that their lives are changing — they have been looking climate change in the eye for many years. They are incredibly resilient, creative, and talented,” says Ashley Toombs, the external affairs director for BRAC USA. “As a team, we are excited to bring this system to Bangladesh. And what we learn together, we will apply at potentially even larger scales.” More

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      in Environment

      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