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

    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

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    Q&A: Randolph Kirchain on how cool pavements can mitigate climate change

    As cities search for climate change solutions, many have turned to one burgeoning technology: cool pavements. By reflecting a greater proportion of solar radiation, cool pavements can offer an array of climate change mitigation benefits, from direct radiative forcing to reduced building energy demand.

    Yet, scientists from the MIT Concrete Sustainability Hub (CSHub) have found that cool pavements are not just a summertime solution. Here, Randolph Kirchain, a principal research scientist at CSHub, discusses how implementing cool pavements can offer myriad greenhouse gas reductions in cities — some of which occur even in the winter.

    Q: What exactly are cool pavements? 

    A: There are two ways to make a cool pavement: changing the pavement formulation to make the pavement porous like a sponge (a so-called “pervious pavement”), or paving with reflective materials. The latter method has been applied extensively because it can be easily adopted on the current road network with different traffic volumes while sustaining — and sometimes improving — the road longevity. To the average observer, surface reflectivity usually corresponds to the color of a pavement — the lighter, the more reflective. 

    We can quantify this surface reflectivity through a measurement called albedo, which refers to the percentage of light a surface reflects. Typically, a reflective pavement has an albedo of 0.3 or higher, meaning that it reflects 30 percent of the light it receives.

    To attain this reflectivity, there are a number of techniques at our disposal. The most common approach is to simply paint a brighter coating atop existing pavements. But it’s also possible to pave with materials that possess naturally greater reflectivity, such as concrete or lighter-colored binders and aggregates.

    Q: How can cool pavements mitigate climate change?

    A: Cool pavements generate several, often unexpected, effects. The most widely known is a reduction in surface and local air temperatures. This occurs because cool pavements absorb less radiation and, consequently, emit less of that radiation as heat. In the summer, this means they can lower urban air temperatures by several degrees Fahrenheit.

    By changing air temperatures or reflecting light into adjacent structures, cool pavements can also alter the need for heating and cooling in those structures, which can change their energy demand and, therefore, mitigate the climate change impacts associated with building energy demand.

    However, depending on how dense the neighborhood is built, a proportion of the radiation cool pavements reflect doesn’t strike buildings; instead, it travels back into the atmosphere and out into space. This process, called a radiative forcing, shifts the Earth’s energy balance and effectively offsets some of the radiation trapped by greenhouse gases (GHGs).

    Perhaps the least-known impact of cool pavements is on vehicle fuel consumption. Certain cool pavements, namely concrete, possess a combination of structural properties and longevity that can minimize the excess fuel consumption of vehicles caused by road quality. Over the lifetime of a pavement, these fuel savings can add up — often offsetting the higher initial footprint of paving with more durable materials.

    Q: With these impacts in mind, how do the effects of cool pavements vary seasonally and by location?

    A: Many view cool pavements as a solution to summer heat. But research has shown that they can offer climate change benefits throughout the year.

    In high-volume traffic roads, the most prominent climate change benefit of cool pavements is not their reflectivity but their impact on vehicle fuel consumption. As such, cool pavement alternatives that minimize fuel consumption can continue to cut GHG emissions in winter, assuming traffic is constant.

    Even in winter, pavement reflectivity still contributes greatly to the climate change mitigation benefits of cool pavements. We found that roughly a third of the annual CO2-equivalent emissions reductions from the radiative forcing effects of cool pavements occurred in the fall and winter.

    It’s important to note, too, that the direction — not just the magnitude — of cool pavement impacts also vary seasonally. The most prominent seasonal variation is the changes to building energy demand. As they lower air temperatures, cool pavements can lessen the demand for cooling in buildings in the summer, while, conversely, they can cause buildings to consume more energy and generate more emissions due to heating in the winter.

    Interestingly, the radiation reflected by cool pavements can also strike adjacent buildings, heating them up. In the summer, this can increase building energy demand significantly, yet in the winter it can also warm structures and reduce their need for heating. In that sense, cool pavements can warm — as well as cool — their surroundings, depending on the building insolation [solar exposure] systems and neighborhood density.

    Q: How can cities manage these many impacts?

    A: As you can imagine, such different and often competing impacts can complicate the implementation of cool pavements. In some contexts, for instance, a cool pavement might even generate more emissions over its life than a conventional pavement — despite lowering air temperatures.

    To ensure that the lowest-emitting pavement is selected, then, cities should use a life-cycle perspective that considers all potential impacts. When they do, research has shown that they can reap sizeable benefits. The city of Phoenix, for instance, could see its projected emissions fall by as much as 6 percent, while Boston would experience a reduction of up to 3 percent.

    These benefits don’t just demonstrate the potential of cool pavements: they also reflect the outsized impact of pavements on our built environment and, moreover, our climate. As cities move to fight climate change, they should know that one of their most extensive assets also presents an opportunity for greater sustainability.

    The MIT Concrete Sustainability Hub is a team of researchers from several departments across MIT working on concrete and infrastructure science, engineering, and economics. Its research is supported by the Portland Cement Association and the Ready Mixed Concrete Research and Education Foundation. More

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    3 Questions: The future of international education

    Evan Lieberman is the Total Professor of Political Science and Contemporary Africa in the MIT Department of Political Science. He conducts research in the field of comparative politics, with a focus on development and ethnic conflict in sub-Saharan Africa. He directs the Global Diversity Lab (GDL) and was recently named faculty director of the MIT International Science and Technology Initiatives (MISTI), MIT’s global experiential learning program. Here, Lieberman describes international education and its import for solving global problems.

    Q: Why is now an especially important time for international education?

    A: The major challenges we currently face — climate change, the pandemic, supply chain management — are all global problems that require global solutions. We will need to collaborate across borders to a greater extent than ever before. There is no time more pressing for students to gain an international outlook on these challenges; the ideas, thinking, and perspectives from other parts of the world; and to build global networks. And yet, most of us have stayed very close to home for the past couple of years. While remote internships and communications have offered temporary solutions when travel was limited, these have been decidedly inferior to the opportunities for learning and making connections through in-person cultural and collaborative experiences at the heart of MISTI. It is important for students and faculty to be able to thrive in an interconnected world as they navigate their research/careers during this unusual time. The changing landscape of the past few years has left all of us somewhat anxious. Nonetheless, I am buoyed by important examples of global collaboration in problem-solving, with scientists, governments and other organizations working together on the things that unite us all.

    Q: How is MIT uniquely positioned to provide global opportunities for students and faculty?

    A: MISTI is a unique program with a long history of building robust partnerships with industry, universities, and other sectors in countries around the world, establishing opportunities that complement MIT students’ unique skill sets. MIT is fortunate to be the home of some of the top students and faculty in the world, and this is a benefit to partners seeking collaborators. The broad range of disciplines across the entire institute provides opportunities to match in nearly every sector. MISTI’s rigorous, country-specific preparation ensures that students build durable cultural connections while abroad and empowers them to play a role in addressing critical global challenges. The combination of technical and humanistic training that MIT students receive are exactly the profiles necessary to take advantage of opportunities abroad, hopefully with a long-term impact. Student participants have a depth of knowledge in their subject areas as well as MIT’s one-of-a-kind education model that is exceptionally valuable. The diversity of our community offers a wide variety of perspectives and life experiences, on top of academic expertise. Also, MISTI’s donor-funded programs provide the unique ability for all students to be able to participate in international programs, regardless of financial situation. This is a direct contrast with internship programs that often skew toward participants with little-to-no financial need.

    Q: How do these kinds of collaborations help tackle global problems?

    A: Of course, we don’t expect that even intensive internships of a few months are going to generate the global solutions we need. It is our hope that our students — who we anticipate being leaders in a range of sectors — will opt for global careers, and/or bring a global perspective to their work and in their lives. We believe that by building on their MISTI experiences and training, they will be able to forge the types of collaborations that lead to equity-enhancing solutions to universal problems — the climate emergency, ongoing threats to global public health, the liabilities associated with the computing revolution — and are able to improve human development more generally.

    More than anything, at MISTI we are planting the seeds for longer-term collaborations. We literally grant several millions of dollars in seed funds to establish faculty-led collaborations with student involvement in addition to supporting hundreds of internships around the world. The MISTI Global Seed Funds (GSF) program compounds the Institute’s impact by supporting partnerships abroad that often turn into long-standing research relationships addressing the critical challenges that require international solutions. GSF projects often have an impact far beyond their original scope. For example, a number of MISTI GSF projects have utilized their results to jump-start research efforts to combat the pandemic. More

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    3 Questions: What a single car can say about traffic

    Vehicle traffic has long defied description. Once measured roughly through visual inspection and traffic cameras, new smartphone crowdsourcing tools are now quantifying traffic far more precisely. This popular method, however, also presents a problem: Accurate measurements require a lot of data and users.

    Meshkat Botshekan, an MIT PhD student in civil and environmental engineering and research assistant at the MIT Concrete Sustainability Hub, has sought to expand on crowdsourcing methods by looking into the physics of traffic. During his time as a doctoral candidate, he has helped develop Carbin, a smartphone-based roadway crowdsourcing tool created by MIT CSHub and the University of Massachusetts Dartmouth, and used its data to offer more insight into the physics of traffic — from the formation of traffic jams to the inference of traffic phase and driving behavior. Here, he explains how recent findings can allow smartphones to infer traffic properties from the measurements of a single vehicle.  

    Q: Numerous navigation apps already measure traffic. Why do we need alternatives?

    A: Traffic characteristics have always been tough to measure. In the past, visual inspection and cameras were used to produce traffic metrics. So, there’s no denying that today’s navigation tools apps offer a superior alternative. Yet even these modern tools have gaps.

    Chief among them is their dependence on spatially distributed user counts: Essentially, these apps tally up their users on road segments to estimate the density of traffic. While this approach may seem adequate, it is both vulnerable to manipulation, as demonstrated in some viral videos, and requires immense quantities of data for reliable estimates. Processing these data is so time- and resource-intensive that, despite their availability, they can’t be used to quantify traffic effectively across a whole road network. As a result, this immense quantity of traffic data isn’t actually optimal for traffic management.

    Q: How could new technologies improve how we measure traffic?

    A: New alternatives have the potential to offer two improvements over existing methods: First, they can extrapolate far more about traffic with far fewer data. Second, they can cost a fraction of the price while offering a far simpler method of data collection. Just like Waze and Google Maps, they rely on crowdsourcing data from users. Yet, they are grounded in the incorporation of high-level statistical physics into data analysis.

    For instance, the Carbin app, which we are developing in collaboration with UMass Dartmouth, applies principles of statistical physics to existing traffic models to entirely forgo the need for user counts. Instead, it can infer traffic density and driver behavior using the input of a smartphone mounted in single vehicle.

    The method at the heart of the app, which was published last fall in Physical Review E, treats vehicles like particles in a many-body system. Just as the behavior of a closed many-body system can be understood through observing the behavior of an individual particle relying on the ergodic theorem of statistical physics, we can characterize traffic through the fluctuations in speed and position of a single vehicle across a road. As a result, we can infer the behavior and density of traffic on a segment of a road.

    As far less data is required, this method is more rapid and makes data management more manageable. But most importantly, it also has the potential to make traffic data less expensive and accessible to those that need it.

    Q: Who are some of the parties that would benefit from new technologies?

    A: More accessible and sophisticated traffic data would benefit more than just drivers seeking smoother, faster routes. It would also enable state and city departments of transportation (DOTs) to make local and collective interventions that advance the critical transportation objectives of equity, safety, and sustainability.

    As a safety solution, new data collection technologies could pinpoint dangerous driving conditions on a much finer scale to inform improved traffic calming measures. And since socially vulnerable communities experience traffic violence disproportionately, these interventions would have the added benefit of addressing pressing equity concerns. 

    There would also be an environmental benefit. DOTs could mitigate vehicle emissions by identifying minute deviations in traffic flow. This would present them with more opportunities to mitigate the idling and congestion that generate excess fuel consumption.  

    As we’ve seen, these three challenges have become increasingly acute, especially in urban areas. Yet, the data needed to address them exists already — and is being gathered by smartphones and telematics devices all over the world. So, to ensure a safer, more sustainable road network, it will be crucial to incorporate these data collection methods into our decision-making. More

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    3 Questions: Anuradha Annaswamy on building smart infrastructures

    Much of Anuradha Annaswamy’s research hinges on uncertainty. How does cloudy weather affect a grid powered by solar energy? How do we ensure that electricity is delivered to the consumer if a grid is powered by wind and the wind does not blow? What’s the best course of action if a bird hits a plane engine on takeoff? How can you predict the behavior of a cyber attacker?

    A senior research scientist in MIT’s Department of Mechanical Engineering, Annaswamy spends most of her research time dealing with decision-making under uncertainty. Designing smart infrastructures that are resilient to uncertainty can lead to safer, more reliable systems, she says.

    Annaswamy serves as the director of MIT’s Active Adaptive Control Laboratory. A world-leading expert in adaptive control theory, she was named president of the Institute of Electrical and Electronics Engineers Control Systems Society for 2020. Her team uses adaptive control and optimization to account for various uncertainties and anomalies in autonomous systems. In particular, they are developing smart infrastructures in the energy and transportation sectors.

    Using a combination of control theory, cognitive science, economic modeling, and cyber-physical systems, Annaswamy and her team have designed intelligent systems that could someday transform the way we travel and consume energy. Their research includes a diverse range of topics such as safer autopilot systems on airplanes, the efficient dispatch of resources in electrical grids, better ride-sharing services, and price-responsive railway systems.

    In a recent interview, Annaswamy spoke about how these smart systems could help support a safer and more sustainable future.

    Q: How is your team using adaptive control to make air travel safer?

    A: We want to develop an advanced autopilot system that can safely recover the airplane in the event of a severe anomaly — such as the wing becoming damaged mid-flight, or a bird flying into the engine. In the airplane, you have a pilot and autopilot to make decisions. We’re asking: How do you combine those two decision-makers?

    The answer we landed on was developing a shared pilot-autopilot control architecture. We collaborated with David Woods, an expert in cognitive engineering at The Ohio State University, to develop an intelligent system that takes the pilot’s behavior into account. For example, all humans have something known as “capacity for maneuver” and “graceful command degradation” that inform how we react in the face of adversity. Using mathematical models of pilot behavior, we proposed a shared control architecture where the pilot and the autopilot work together to make an intelligent decision on how to react in the face of uncertainties. In this system, the pilot reports the anomaly to an adaptive autopilot system that ensures resilient flight control.

    Q: How does your research on adaptive control fit into the concept of smart cities?

    A: Smart cities are an interesting way we can use intelligent systems to promote sustainability. Our team is looking at ride-sharing services in particular. Services like Uber and Lyft have provided new transportation options, but their impact on the carbon footprint has to be considered. We’re looking at developing a system where the number of passenger-miles per unit of energy is maximized through something called “shared mobility on demand services.” Using the alternating minimization approach, we’ve developed an algorithm that can determine the optimal route for multiple passengers traveling to various destinations.

    As with the pilot-autopilot dynamic, human behavior is at play here. In sociology there is an interesting concept of behavioral dynamics known as Prospect Theory. If we give passengers options with regards to which route their shared ride service will take, we are empowering them with free will to accept or reject a route. Prospect Theory shows that if you can use pricing as an incentive, people are much more loss-averse so they would be willing to walk a bit extra or wait a few minutes longer to join a low-cost ride with an optimized route. If everyone utilized a system like this, the carbon footprint of ride-sharing services could decrease substantially.

    Q: What other ways are you using intelligent systems to promote sustainability?

    A: Renewable energy and sustainability are huge drivers for our research. To enable a world where all of our energy is coming from renewable sources like solar or wind, we need to develop a smart grid that can account for the fact that the sun isn’t always shining and wind isn’t always blowing. These uncertainties are the biggest hurdles to achieving an all-renewable grid. Of course, there are many technologies being developed for batteries that can help store renewable energy, but we are taking a different approach.

    We have created algorithms that can optimally schedule distributed energy resources within the grid — this includes making decisions on when to use onsite generators, how to operate storage devices, and when to call upon demand response technologies, all in response to the economics of using such resources and their physical constraints. If we can develop an interconnected smart grid where, for example, the air conditioning setting in a house is set to 72 degrees instead of 69 degrees automatically when demand is high, there could be a substantial savings in energy usage without impacting human comfort. In one of our studies, we applied a distributed proximal atomic coordination algorithm to the grid in Tokyo to demonstrate how this intelligent system could account for the uncertainties present in a grid powered by renewable resources. More

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    Q&A: Can the world change course on climate?

    In this ongoing series on climate issues, MIT faculty, students, and alumni in the humanistic fields share perspectives that are significant for solving climate change and mitigating its myriad social and ecological impacts. Nazli Choucri is a professor of political science and an expert on climate issues, who also focuses on international relations and cyberpolitics. She is the architect and director of the Global System for Sustainable Development, an evolving knowledge networking system centered on sustainability problems and solution strategies. The author and/or editor of 12 books, she is also the founding editor of the MIT Press book series “Global Environmental Accord: Strategies for Sustainability and Institutional Innovation.” Q: The impacts of climate change — including storms, floods, wildfires, and droughts — have the potential to destabilize nations, yet they are not constrained by borders. What international developments most concern you in terms of addressing climate change and its myriad ecological and social impacts?

    A: Climate change is a global issue. By definition, and a long history of practice, countries focus on their own priorities and challenges. Over time, we have seen the gradual development of norms reflecting shared interests, and the institutional arrangements to support and pursue the global good. What concerns me most is that general responses to the climate crisis are being framed in broad terms; the overall pace of change remains perilously slow; and uncertainty remains about operational action and implementation of stated intent. We have just seen the completion of the 26th meeting of states devoted to climate change, the United Nations Climate Change Conference (COP26). In some ways this is positive. Yet, past commitments remain unfulfilled, creating added stress in an already stressful political situation. Industrial countries are uneven in their recognition of, and responses to, climate change. This may signal uncertainty about whether climate matters are sufficiently compelling to call for immediate action. Alternatively, the push for changing course may seem too costly at a time when other imperatives — such as employment, economic growth, or protecting borders — inevitably dominate discourse and decisions. Whatever the cause, the result has been an unwillingness to take strong action. Unfortunately, climate change remains within the domain of “low politics,” although there are signs the issue is making a slow but steady shift to “high politics” — those issues deemed vital to the existence of the state. This means that short-term priorities, such as those noted above, continue to shape national politics and international positions and, by extension, to obscure the existential threat revealed by scientific evidence. As for developing countries, these are overwhelmed by internal challenges, and managing the difficulties of daily life always takes priority over other challenges, however compelling. Long-term thinking is a luxury, but daily bread is a necessity. Non-state actors — including registered nongovernmental organizations, climate organizations, sustainability support groups, activists of various sorts, and in some cases much of civil society — have been left with a large share of the responsibility for educating and convincing diverse constituencies of the consequences of inaction on climate change. But many of these institutions carry their own burdens and struggle to manage current pressures. The international community, through its formal and informal institutions, continues to articulate the perils of climate change and to search for a powerful consensus that can prove effective both in form and in function. The general contours are agreed upon — more or less. But leadership of, for, and by the global collective is elusive and difficult to shape. Most concerning of all is the clear reluctance to address head-on the challenge of planning for changes that we know will occur. The reality that we are all being affected — in different ways and to different degrees — has yet to be sufficiently appreciated by everyone, everywhere. Yet, in many parts of the world, major shifts in climate will create pressures on human settlements, spur forced migrations, or generate social dislocations. Some small island states, for example, may not survive a sea-level surge. Everywhere there is a need to cut emissions, and this means adaptation and/or major changes in economic activity and in lifestyle.The discourse and debate at COP26 reflect all of such persistent features in the international system. So far, the largest achievements center on the common consensus that more must be done to prevent the rise in temperature from creating a global catastrophe. This is not enough, however. Differences remain, and countries have yet to specify what cuts in emissions they are willing to make.Echoes of who is responsible for what remains strong. The thorny matter of the unfulfilled pledge of $100 billion once promised by rich countries to help countries to reduce their emissions remained unresolved. At the same time, however, some important agreements were reached. The United States and China announced they would make greater efforts to cut methane, a powerful greenhouse gas. More than 100 countries agreed to end deforestation. India joined the countries committed to attain zero emissions by 2070. And on matters of finance, countries agreed to a two-year plan to determine how to meet the needs of the most-vulnerable countries. Q: In what ways do you think the tools and insights from political science can advance efforts to address climate change and its impacts?A: I prefer to take a multidisciplinary view of the issues at hand, rather than focus on the tools of political science alone. Disciplinary perspectives can create siloed views and positions that undermine any overall drive toward consensus. The scientific evidence is pointing to, even anticipating, pervasive changes that transcend known and established parameters of social order all across the globe.That said, political science provides important insight, even guidance, for addressing the impacts of climate change in some notable ways. One is understanding the extent to which our formal institutions enable discussion, debate, and decisions about the directions we can take collectively to adapt, adjust, or even depart from the established practices of managing social order.If we consider politics as the allocation of values in terms of who gets what, when, and how, then it becomes clear that the current allocation requires a change in course. Coordination and cooperation across the jurisdictions of sovereign states is foundational for any response to climate change impacts.We have already recognized, and to some extent, developed targets for reducing carbon emissions — a central impact from traditional forms of energy use — and are making notable efforts to shift toward alternatives. This move is an easy one compared to all the work that needs to be done to address climate change. But, in taking this step we have learned quite a bit that might help in creating a necessary consensus for cross-jurisdiction coordination and response.Respecting individuals and protecting life is increasingly recognized as a global value — at least in principle. As we work to change course, new norms will be developed, and political science provides important perspectives on how to establish such norms. We will be faced with demands for institutional design, and these will need to embody our guiding values. For example, having learned to recognize the burdens of inequity, we can establish the value of equity as foundational for our social order both now and as we recognize and address the impacts of climate change.

    Q: You teach a class on “Sustainability Development: Theory and Practice.” Broadly speaking, what are goals of this class? What lessons do you hope students will carry with them into the future?A: The goal of 17.181, my class on sustainability, is to frame as clearly as possible the concept of sustainable development (sustainability) with attention to conceptual, empirical, institutional, and policy issues.The course centers on human activities. Individuals are embedded in complex interactive systems: the social system, the natural environment, and the constructed cyber domain — each with distinct temporal, special, and dynamic features. Sustainability issues intersect with, but cannot be folded into, the impacts of climate change. Sustainability places human beings in social systems at the core of what must be done to respect the imperatives of a highly complex natural environment.We consider sustainability an evolving knowledge domain with attendant policy implications. It is driven by events on the ground, not by revolution in academic or theoretical concerns per se. Overall, sustainable development refers to the process of meeting the needs of current and future generations, without undermining the resilience of the life-supporting properties, the integrity of social systems, or the supports of the human-constructed cyberspace.More specifically, we differentiate among four fundamental dimensions and their necessary conditions:

    (a) ecological systems — exhibiting balance and resilience;(b) economic production and consumption — with equity and efficiency;(c) governance and politics — with participation and responsiveness; and(d) institutional performance — demonstrating adaptation and incorporating feedback.The core proposition is this: If all conditions hold, then the system is (or can be) sustainable. Then, we must examine the critical drivers — people, resources, technology, and their interactions — followed by a review and assessment of evolving policy responses. Then we ask: What are new opportunities?I would like students to carry forward these ideas and issues: what has been deemed “normal” in modern Western societies and in developing societies seeking to emulate the Western model is damaging humans in many ways — all well-known. Yet only recently have alternatives begun to be considered to the traditional economic growth model based on industrialization and high levels of energy use. To make changes, we must first understand the underlying incentives, realities, and choices that shape a whole set of dysfunctional behaviors and outcomes. We then need to delve deep into the driving sources and consequences, and to consider the many ways in which our known “normal” can be adjusted — in theory and in practice. Q: In confronting an issue as formidable as global climate change, what gives you hope?  A: I see a few hopeful signs; among them:The scientific evidence is clear and compelling. We are no longer discussing whether there is climate change, or if we will face major challenges of unprecedented proportions, or even how to bring about an international consensus on the salience of such threats.Climate change has been recognized as a global phenomenon. Imperatives for cooperation are necessary. No one can go it alone. Major efforts have and are being made in world politics to forge action agendas with specific targets.The issue appears to be on the verge of becoming one of “high politics” in the United States.Younger generations are more sensitive to the reality that we are altering the life-supporting properties of our planet. They are generally more educated, skilled, and open to addressing such challenges than their elders.However disappointing the results of COP26 might seem, the global community is moving in the right direction.None of the above points, individually or jointly, translates into an effective response to the known impacts of climate change — let alone the unknown. But, this is what gives me hope.

    Interview prepared by MIT SHASS CommunicationsEditorial, design, and series director: Emily HiestandSenior writer: Kathryn O’Neill More

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    Q&A: More-sustainable concrete with machine learning

    As a building material, concrete withstands the test of time. Its use dates back to early civilizations, and today it is the most popular composite choice in the world. However, it’s not without its faults. Production of its key ingredient, cement, contributes 8-9 percent of the global anthropogenic CO2 emissions and 2-3 percent of energy consumption, which is only projected to increase in the coming years. With aging United States infrastructure, the federal government recently passed a milestone bill to revitalize and upgrade it, along with a push to reduce greenhouse gas emissions where possible, putting concrete in the crosshairs for modernization, too.

    Elsa Olivetti, the Esther and Harold E. Edgerton Associate Professor in the MIT Department of Materials Science and Engineering, and Jie Chen, MIT-IBM Watson AI Lab research scientist and manager, think artificial intelligence can help meet this need by designing and formulating new, more sustainable concrete mixtures, with lower costs and carbon dioxide emissions, while improving material performance and reusing manufacturing byproducts in the material itself. Olivetti’s research improves environmental and economic sustainability of materials, and Chen develops and optimizes machine learning and computational techniques, which he can apply to materials reformulation. Olivetti and Chen, along with their collaborators, have recently teamed up for an MIT-IBM Watson AI Lab project to make concrete more sustainable for the benefit of society, the climate, and the economy.

    Q: What applications does concrete have, and what properties make it a preferred building material?

    Olivetti: Concrete is the dominant building material globally with an annual consumption of 30 billion metric tons. That is over 20 times the next most produced material, steel, and the scale of its use leads to considerable environmental impact, approximately 5-8 percent of global greenhouse gas (GHG) emissions. It can be made locally, has a broad range of structural applications, and is cost-effective. Concrete is a mixture of fine and coarse aggregate, water, cement binder (the glue), and other additives.

    Q: Why isn’t it sustainable, and what research problems are you trying to tackle with this project?

    Olivetti: The community is working on several ways to reduce the impact of this material, including alternative fuels use for heating the cement mixture, increasing energy and materials efficiency and carbon sequestration at production facilities, but one important opportunity is to develop an alternative to the cement binder.

    While cement is 10 percent of the concrete mass, it accounts for 80 percent of the GHG footprint. This impact is derived from the fuel burned to heat and run the chemical reaction required in manufacturing, but also the chemical reaction itself releases CO2 from the calcination of limestone. Therefore, partially replacing the input ingredients to cement (traditionally ordinary Portland cement or OPC) with alternative materials from waste and byproducts can reduce the GHG footprint. But use of these alternatives is not inherently more sustainable because wastes might have to travel long distances, which adds to fuel emissions and cost, or might require pretreatment processes. The optimal way to make use of these alternate materials will be situation-dependent. But because of the vast scale, we also need solutions that account for the huge volumes of concrete needed. This project is trying to develop novel concrete mixtures that will decrease the GHG impact of the cement and concrete, moving away from the trial-and-error processes towards those that are more predictive.

    Chen: If we want to fight climate change and make our environment better, are there alternative ingredients or a reformulation we could use so that less greenhouse gas is emitted? We hope that through this project using machine learning we’ll be able to find a good answer.

    Q: Why is this problem important to address now, at this point in history?

    Olivetti: There is urgent need to address greenhouse gas emissions as aggressively as possible, and the road to doing so isn’t necessarily straightforward for all areas of industry. For transportation and electricity generation, there are paths that have been identified to decarbonize those sectors. We need to move much more aggressively to achieve those in the time needed; further, the technological approaches to achieve that are more clear. However, for tough-to-decarbonize sectors, such as industrial materials production, the pathways to decarbonization are not as mapped out.

    Q: How are you planning to address this problem to produce better concrete?

    Olivetti: The goal is to predict mixtures that will both meet performance criteria, such as strength and durability, with those that also balance economic and environmental impact. A key to this is to use industrial wastes in blended cements and concretes. To do this, we need to understand the glass and mineral reactivity of constituent materials. This reactivity not only determines the limit of the possible use in cement systems but also controls concrete processing, and the development of strength and pore structure, which ultimately control concrete durability and life-cycle CO2 emissions.

    Chen: We investigate using waste materials to replace part of the cement component. This is something that we’ve hypothesized would be more sustainable and economic — actually waste materials are common, and they cost less. Because of the reduction in the use of cement, the final concrete product would be responsible for much less carbon dioxide production. Figuring out the right concrete mixture proportion that makes endurable concretes while achieving other goals is a very challenging problem. Machine learning is giving us an opportunity to explore the advancement of predictive modeling, uncertainty quantification, and optimization to solve the issue. What we are doing is exploring options using deep learning as well as multi-objective optimization techniques to find an answer. These efforts are now more feasible to carry out, and they will produce results with reliability estimates that we need to understand what makes a good concrete.

    Q: What kinds of AI and computational techniques are you employing for this?

    Olivetti: We use AI techniques to collect data on individual concrete ingredients, mix proportions, and concrete performance from the literature through natural language processing. We also add data obtained from industry and/or high throughput atomistic modeling and experiments to optimize the design of concrete mixtures. Then we use this information to develop insight into the reactivity of possible waste and byproduct materials as alternatives to cement materials for low-CO2 concrete. By incorporating generic information on concrete ingredients, the resulting concrete performance predictors are expected to be more reliable and transformative than existing AI models.

    Chen: The final objective is to figure out what constituents, and how much of each, to put into the recipe for producing the concrete that optimizes the various factors: strength, cost, environmental impact, performance, etc. For each of the objectives, we need certain models: We need a model to predict the performance of the concrete (like, how long does it last and how much weight does it sustain?), a model to estimate the cost, and a model to estimate how much carbon dioxide is generated. We will need to build these models by using data from literature, from industry, and from lab experiments.

    We are exploring Gaussian process models to predict the concrete strength, going forward into days and weeks. This model can give us an uncertainty estimate of the prediction as well. Such a model needs specification of parameters, for which we will use another model to calculate. At the same time, we also explore neural network models because we can inject domain knowledge from human experience into them. Some models are as simple as multi-layer perceptions, while some are more complex, like graph neural networks. The goal here is that we want to have a model that is not only accurate but also robust — the input data is noisy, and the model must embrace the noise, so that its prediction is still accurate and reliable for the multi-objective optimization.

    Once we have built models that we are confident with, we will inject their predictions and uncertainty estimates into the optimization of multiple objectives, under constraints and under uncertainties.

    Q: How do you balance cost-benefit trade-offs?

    Chen: The multiple objectives we consider are not necessarily consistent, and sometimes they are at odds with each other. The goal is to identify scenarios where the values for our objectives cannot be further pushed simultaneously without compromising one or a few. For example, if you want to further reduce the cost, you probably have to suffer the performance or suffer the environmental impact. Eventually, we will give the results to policymakers and they will look into the results and weigh the options. For example, they may be able to tolerate a slightly higher cost under a significant reduction in greenhouse gas. Alternatively, if the cost varies little but the concrete performance changes drastically, say, doubles or triples, then this is definitely a favorable outcome.

    Q: What kinds of challenges do you face in this work?

    Chen: The data we get either from industry or from literature are very noisy; the concrete measurements can vary a lot, depending on where and when they are taken. There are also substantial missing data when we integrate them from different sources, so, we need to spend a lot of effort to organize and make the data usable for building and training machine learning models. We also explore imputation techniques that substitute missing features, as well as models that tolerate missing features, in our predictive modeling and uncertainty estimate.

    Q: What do you hope to achieve through this work?

    Chen: In the end, we are suggesting either one or a few concrete recipes, or a continuum of recipes, to manufacturers and policymakers. We hope that this will provide invaluable information for both the construction industry and for the effort of protecting our beloved Earth.

    Olivetti: We’d like to develop a robust way to design cements that make use of waste materials to lower their CO2 footprint. Nobody is trying to make waste, so we can’t rely on one stream as a feedstock if we want this to be massively scalable. We have to be flexible and robust to shift with feedstocks changes, and for that we need improved understanding. Our approach to develop local, dynamic, and flexible alternatives is to learn what makes these wastes reactive, so we know how to optimize their use and do so as broadly as possible. We do that through predictive model development through software we have developed in my group to automatically extract data from literature on over 5 million texts and patents on various topics. We link this to the creative capabilities of our IBM collaborators to design methods that predict the final impact of new cements. If we are successful, we can lower the emissions of this ubiquitous material and play our part in achieving carbon emissions mitigation goals.

    Other researchers involved with this project include Stefanie Jegelka, the X-Window Consortium Career Development Associate Professor in the MIT Department of Electrical Engineering and Computer Science; Richard Goodwin, IBM principal researcher; Soumya Ghosh, MIT-IBM Watson AI Lab research staff member; and Kristen Severson, former research staff member. Collaborators included Nghia Hoang, former research staff member with MIT-IBM Watson AI Lab and IBM Research; and Jeremy Gregory, research scientist in the MIT Department of Civil and Environmental Engineering and executive director of the MIT Concrete Sustainability Hub.

    This research is supported by the MIT-IBM Watson AI Lab. More

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    3 Questions: Tolga Durak on building a safety culture at MIT

    Environment, Health, and Safety Managing Director Tolga Durak heads a team working to build a strong safety culture at the Institute and to implement systems that lead to successful lab and makerspace operations. EHS is also pursuing new opportunities in the areas of safe and sustainable labs and applied makerspace research. 

    Durak holds a BS in mechanical engineering, a MS in industrial and systems engineering, and a PhD in building construction/environmental design and planning. He has over 20 years of experience in engineering and EHS in higher education, having served in such roles as authority having jurisdiction, responsible official, fire marshal, risk manager, radiation safety officer, laser safety officer, safety engineer, project manager, and emergency manager for government agencies, as well as universities with extensive health-care and research facilities.

    Q: What “words of wisdom” regarding lab/shop health and safety would you like to share with the research community? 

    A: EHS staff always strive to help maintain the safety and well-being of the MIT community. When it comes to lab/shop safety or any areas with hazards, first and foremost, we encourage wearing the appropriate personal protective equipment (PPE) when handling potentially hazardous materials. While PPE needs depend on the hazards and the space, common PPE includes safety glasses, lab coats, gloves, clothes that cover your skin, and closed-toe shoes. Shorts and open-toe shoes have no place in the lab/shop setting when hazardous materials are stored or used. Accidents will and do happen. The severity of injuries due to accidental exposures can be minimized when researchers are wearing PPE. Remember, there is only one you!   

    Overall, be aware of your surroundings, be knowledgeable about the hazards of the materials and equipment you are using, and be prepared for the unexpected. Ask yourself, “What’s the worst thing that can happen during this experiment or procedure?” Prepare by doing a thorough risk assessment, ask others who may be knowledgeable for their ideas and help, and standardize procedures where possible. Be prepared to respond appropriately when an emergency arises. 

    Safety in our classrooms, labs, and makerspaces is paramount and requires a collaborative effort. 

    Q: What are the established programs within EHS that students and researchers should be aware of, and what opportunities and challenges do you face trying to advance a healthy safety culture at MIT? 

    A: The EHS program staff in Biosafety, Industrial Hygiene, Environmental Management, Occupational and Construction Safety, and Radiation Protection are ready to assist with risk assessments, chemical safety, physical hazards, hazard-specific training, materials management, and hazardous waste disposal and reuse/recycling. Locally, each department, laboratory, and center has an EHS coordinator, as well as an assigned EHS team, to assist in the implementation of required EHS programs. Each lab/shop also has a designated EHS representative — someone who has local knowledge of your lab/shop and can help you with safety requirements specific to your work area.  

    One of the biggest challenges we face is that due to the decentralized nature of the Institute, no one size fits all when it comes to implementing successful safety practices. We also view this as an opportunity to enhance our safety culture. A strong safety culture is reflected at MIT when all lab and makerspace members are willing to look out for each other, challenge the status quo when necessary, and do the right thing even when no one is looking. In labs/shops with a strong safety culture, faculty and researchers discuss safety topics at group meetings, group members remind each other to wear the appropriate PPE (lab coats, safety glasses, etc.), more experienced team members mentor the newcomers, and riskier operations are reviewed and assessed to make them as safe as possible.  

    Q: Can you describe the new Safe and Sustainable Laboratories (S2L) efforts and the makerspace operational research programs envisioned for the future? 

    A: The MIT EHS Office has a plan for renewing its dedication to sustainability and climate action. We are dedicated to doing our part to promote a research environment that assures the highest level of health and safety but also strives to reduce energy, water, and waste through educating and supporting faculty, students, and researchers. With the goal of integrating sustainability across the lab sector of campus and bridging that with the Institute’s climate action goals, EHS has partnered with the MIT Office of Sustainability, Department of Facilities, vice president for finance, and vice president for campus services and stewardship to relaunch the “green” labs sustainability efforts under a new Safe and Sustainable Labs program.

    Part of that plan is to implement a Sustainable Labs Certification program. The process is designed to be as easy as possible for the lab groups. We are starting with simple actions like promoting the use of equipment timers in certain locations to conserve energy, fume hood/ventilation management, preventative maintenance for ultra-low-temperature freezers, increasing recycling, and helping labs update their central chemical inventory system, which can help forecast MIT’s potential waste streams. 

    EHS has also partnered with Project Manus to build a test-bed lab to study potential health and environmental exposures present in makerspaces as a result of specialized equipment and processes with our new Applied Makerspace Research Initiative.   More