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

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      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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      in Environment

      3 Questions: What a single car can say about traffic

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      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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      in Environment

      Q&A: More-sustainable concrete with machine learning

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      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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      in Environment

      Making roadway spending more sustainable

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      The share of federal spending on infrastructure has reached an all-time low, falling from 30 percent in 1960 to just 12 percent in 2018.

      While the nation’s ailing infrastructure will require more funding to reach its full potential, recent MIT research finds that more sustainable and higher performing roads are still possible even with today’s limited budgets.

      The research, conducted by a team of current and former MIT Concrete Sustainability Hub (MIT CSHub) scientists and published in Transportation Research D, finds that a set of innovative planning strategies could improve pavement network environmental and performance outcomes even if budgets don’t increase.

      The paper presents a novel budget allocation tool and pairs it with three innovative strategies for managing pavement networks: a mix of paving materials, a mix of short- and long-term paving actions, and a long evaluation period for those actions.

      This novel approach offers numerous benefits. When applied to a 30-year case study of the Iowa U.S. Route network, the MIT CSHub model and management strategies cut emissions by 20 percent while sustaining current levels of road quality. Achieving this with a conventional planning approach would require the state to spend 32 percent more than it does today. The key to its success is the consideration of a fundamental — but fraught — aspect of pavement asset management: uncertainty.

      Predicting unpredictability

      The average road must last many years and support the traffic of thousands — if not millions — of vehicles. Over that time, a lot can change. Material prices may fluctuate, budgets may tighten, and traffic levels may intensify. Climate (and climate change), too, can hasten unexpected repairs.

      Managing these uncertainties effectively means looking long into the future and anticipating possible changes.

      “Capturing the impacts of uncertainty is essential for making effective paving decisions,” explains Fengdi Guo, the paper’s lead author and a departing CSHub research assistant.

      “Yet, measuring and relating these uncertainties to outcomes is also computationally intensive and expensive. Consequently, many DOTs [departments of transportation] are forced to simplify their analysis to plan maintenance — often resulting in suboptimal spending and outcomes.”

      To give DOTs accessible tools to factor uncertainties into their planning, CSHub researchers have developed a streamlined planning approach. It offers greater specificity and is paired with several new pavement management strategies.

      The planning approach, known as Probabilistic Treatment Path Dependence (PTPD), is based on machine learning and was devised by Guo.

      “Our PTPD model is composed of four steps,” he explains. “These steps are, in order, pavement damage prediction; treatment cost prediction; budget allocation; and pavement network condition evaluation.”

      The model begins by investigating every segment in an entire pavement network and predicting future possibilities for pavement deterioration, cost, and traffic.

      “We [then] run thousands of simulations for each segment in the network to determine the likely cost and performance outcomes for each initial and subsequent sequence, or ‘path,’ of treatment actions,” says Guo. “The treatment paths with the best cost and performance outcomes are selected for each segment, and then across the network.”

      The PTPD model not only seeks to minimize costs to agencies but also to users — in this case, drivers. These user costs can come primarily in the form of excess fuel consumption due to poor road quality.

      “One improvement in our analysis is the incorporation of electric vehicle uptake into our cost and environmental impact predictions,” Randolph Kirchain, a principal research scientist at MIT CSHub and MIT Materials Research Laboratory (MRL) and one of the paper’s co-authors. “Since the vehicle fleet will change over the next several decades due to electric vehicle adoption, we made sure to consider how these changes might impact our predictions of excess energy consumption.”

      After developing the PTPD model, Guo wanted to see how the efficacy of various pavement management strategies might differ. To do this, he developed a sophisticated deterioration prediction model.

      A novel aspect of this deterioration model is its treatment of multiple deterioration metrics simultaneously. Using a multi-output neural network, a tool of artificial intelligence, the model can predict several forms of pavement deterioration simultaneously, thereby, accounting for their correlations among one another.

      The MIT team selected two key metrics to compare the effectiveness of various treatment paths: pavement quality and greenhouse gas emissions. These metrics were then calculated for all pavement segments in the Iowa network.

      Improvement through variation

       The MIT model can help DOTs make better decisions, but that decision-making is ultimately constrained by the potential options considered.

      Guo and his colleagues, therefore, sought to expand current decision-making paradigms by exploring a broad set of network management strategies and evaluating them with their PTPD approach. Based on that evaluation, the team discovered that networks had the best outcomes when the management strategy includes using a mix of paving materials, a variety of long- and short-term paving repair actions (treatments), and longer time periods on which to base paving decisions.

      They then compared this proposed approach with a baseline management approach that reflects current, widespread practices: the use of solely asphalt materials, short-term treatments, and a five-year period for evaluating the outcomes of paving actions.

      With these two approaches established, the team used them to plan 30 years of maintenance across the Iowa U.S. Route network. They then measured the subsequent road quality and emissions.

      Their case study found that the MIT approach offered substantial benefits. Pavement-related greenhouse gas emissions would fall by around 20 percent across the network over the whole period. Pavement performance improved as well. To achieve the same level of road quality as the MIT approach, the baseline approach would need a 32 percent greater budget.

      “It’s worth noting,” says Guo, “that since conventional practices employ less effective allocation tools, the difference between them and the CSHub approach should be even larger in practice.”

      Much of the improvement derived from the precision of the CSHub planning model. But the three treatment strategies also play a key role.

      “We’ve found that a mix of asphalt and concrete paving materials allows DOTs to not only find materials best-suited to certain projects, but also mitigates the risk of material price volatility over time,” says Kirchain.

      It’s a similar story with a mix of paving actions. Employing a mix of short- and long-term fixes gives DOTs the flexibility to choose the right action for the right project.

      The final strategy, a long-term evaluation period, enables DOTs to see the entire scope of their choices. If the ramifications of a decision are predicted over only five years, many long-term implications won’t be considered. Expanding the window for planning, then, can introduce beneficial, long-term options.

      It’s not surprising that paving decisions are daunting to make; their impacts on the environment, driver safety, and budget levels are long-lasting. But rather than simplify this fraught process, the CSHub method aims to reflect its complexity. The result is an approach that provides DOTs with the tools to do more with less.

      This research was supported through the MIT Concrete Sustainability Hub by the Portland Cement Association and the Ready Mixed Concrete Research and Education Foundation. More

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      in Energy

      Predicting building emissions across the US

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      The United States is entering a building boom. Between 2017 and 2050, it will build the equivalent of New York City 20 times over. Yet, to meet climate targets, the nation must also significantly reduce the greenhouse gas (GHG) emissions of its buildings, which comprise 27 percent of the nation’s total emissions.

      A team of current and former MIT Concrete Sustainability Hub (CSHub) researchers is addressing these conflicting demands with the aim of giving policymakers the tools and information to act. They have detailed the results of their collaboration in a recent paper in the journal Applied Energy that projects emissions for all buildings across the United States under two GHG reduction scenarios.

      Their paper found that “embodied” emissions — those from materials production and construction — would represent around a quarter of emissions between 2016 and 2050 despite extensive construction.

      Further, many regions would have varying priorities for GHG reductions; some, like the West, would benefit most from reductions to embodied emissions, while others, like parts of the Midwest, would see the greatest payoff from interventions to emissions from energy consumption. If these regional priorities were addressed aggressively, building sector emissions could be reduced by around 30 percent between 2016 and 2050.

      Quantifying contradictions

      Modern buildings are far more complex — and efficient — than their predecessors. Due to new technologies and more stringent building codes, they can offer lower energy consumption and operational emissions. And yet, more-efficient materials and improved construction standards can also generate greater embodied emissions.

      Concrete, in many ways, epitomizes this tradeoff. Though its durability can minimize energy-intensive repairs over a building’s operational life, the scale of its production means that it contributes to a large proportion of the embodied impacts in the building sector.

      As such, the team centered GHG reductions for concrete in its analysis.

      “We took a bottom-up approach, developing reference designs based on a set of residential and commercial building models,” explains Ehsan Vahidi, an assistant professor at the University of Nevada at Reno and a former CSHub postdoc. “These designs were differentiated by roof and slab insulation, HVAC efficiency, and construction materials — chiefly concrete and wood.”

      After measuring the operational and embodied GHG emissions for each reference design, the team scaled up their results to the county level and then national level based on building stock forecasts. This allowed them to estimate the emissions of the entire building sector between 2016 and 2050.

      To understand how various interventions could cut GHG emissions, researchers ran two different scenarios — a “projected” and an “ambitious” scenario — through their framework.

      The projected scenario corresponded to current trends. It assumed grid decarbonization would follow Energy Information Administration predictions; the widespread adoption of new energy codes; efficiency improvement of lighting and appliances; and, for concrete, the implementation of 50 percent low-carbon cements and binders in all new concrete construction and the adoption of full carbon capture, storage, and utilization (CCUS) of all cement and concrete emissions.

      “Our ambitious scenario was intended to reflect a future where more aggressive actions are taken to reduce GHG emissions and achieve the targets,” says Vahidi. “Therefore, the ambitious scenario took these same strategies [of the projected scenario] but featured more aggressive targets for their implementation.”

      For instance, it assumed a 33 percent reduction in grid emissions by 2050 and moved the projected deadlines for lighting and appliances and thermal insulation forward by five and 10 years, respectively. Concrete decarbonization occurred far more quickly as well.

      Reductions and variations

      The extensive growth forecast for the U.S. building sector will inevitably generate a sizable number of emissions. But how much can this figure be minimized?

      Without the implementation of any GHG reduction strategies, the team found that the building sector would emit 62 gigatons CO2 equivalent between 2016 and 2050. That’s comparable to the emissions generated from 156 trillion passenger vehicle miles traveled.

      But both GHG reduction scenarios could cut the emissions from this unmitigated, business-as-usual scenario significantly.

      Under the projected scenario, emissions would fall to 45 gigatons CO2 equivalent — a 27 percent decrease over the analysis period. The ambitious scenario would offer a further 6 percent reduction over the projected scenario, reaching 40 gigatons CO2 equivalent — like removing around 55 trillion passenger vehicle miles from the road over the period.

      “In both scenarios, the largest contributor to reductions was the greening of the energy grid,” notes Vahidi. “Other notable opportunities for reductions were from increasing the efficiency of lighting, HVAC, and appliances. Combined, these four attributes contributed to 85 percent of the emissions over the analysis period. Improvements to them offered the greatest potential emissions reductions.”

      The remaining attributes, such as thermal insulation and low-carbon concrete, had a smaller impact on emissions and, consequently, offered smaller reduction opportunities. That’s because these two attributes were only applied to new construction in the analysis, which was outnumbered by existing structures throughout the period.

      The disparities in impact between strategies aimed at new and existing structures underscore a broader finding: Despite extensive construction over the period, embodied emissions would comprise just 23 percent of cumulative emissions between 2016 and 2050, with the remainder coming primarily from operation.  

      “This is a consequence of existing structures far outnumbering new structures,” explains Jasmina Burek, a CSHub postdoc and an incoming assistant professor at the University of Massachusetts Lowell. “The operational emissions generated by all new and existing structures between 2016 and 2050 will always greatly exceed the embodied emissions of new structures at any given time, even as buildings become more efficient and the grid gets greener.”

      Yet the emissions reductions from both scenarios were not distributed evenly across the entire country. The team identified several regional variations that could have implications for how policymakers must act to reduce building sector emissions.

      “We found that western regions in the United States would see the greatest reduction opportunities from interventions to residential emissions, which would constitute 90 percent of the region’s total emissions over the analysis period,” says Vahidi.

      The predominance of residential emissions stems from the region’s ongoing population surge and its subsequent growth in housing stock. Proposed solutions would include CCUS and low-carbon binders for concrete production, and improvements to energy codes aimed at residential buildings.

      As with the West, ideal solutions for the Southeast would include CCUS, low-carbon binders, and improved energy codes.

      “In the case of Southeastern regions, interventions should equally target commercial and residential buildings, which we found were split more evenly among the building stock,” explains Burek. “Due to the stringent energy codes in both regions, interventions to operational emissions were less impactful than those to embodied emissions.”

      Much of the Midwest saw the inverse outcome. Its energy mix remains one of the most carbon-intensive in the nation and improvements to energy efficiency and the grid would have a large payoff — particularly in Missouri, Kansas, and Colorado.

      New England and California would see the smallest reductions. As their already-strict energy codes would limit further operational reductions, opportunities to reduce embodied emissions would be the most impactful.

      This tremendous regional variation uncovered by the MIT team is in many ways a reflection of the great demographic and geographic diversity of the nation as a whole. And there are still further variables to consider.

      In addition to GHG emissions, future research could consider other environmental impacts, like water consumption and air quality. Other mitigation strategies to consider include longer building lifespans, retrofitting, rooftop solar, and recycling and reuse.

      In this sense, their findings represent the lower bounds of what is possible in the building sector. And even if further improvements are ultimately possible, they’ve shown that regional variation will invariably inform those environmental impact reductions.

      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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      in Environment

      Concrete’s role in reducing building and pavement emissions

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      Encountering concrete is a common, even routine, occurrence. And that’s exactly what makes concrete exceptional.

      As the most consumed material after water, concrete is indispensable to the many essential systems — from roads to buildings — in which it is used.

      But due to its extensive use, concrete production also contributes to around 1 percent of emissions in the United States and remains one of several carbon-intensive industries globally. Tackling climate change, then, will mean reducing the environmental impacts of concrete, even as its use continues to increase.

      In a new paper in the Proceedings of the National Academy of Sciences, a team of current and former researchers at the MIT Concrete Sustainability Hub (CSHub) outlines how this can be achieved.

      They present an extensive life-cycle assessment of the building and pavements sectors that estimates how greenhouse gas (GHG) reduction strategies — including those for concrete and cement — could minimize the cumulative emissions of each sector and how those reductions would compare to national GHG reduction targets. 

      The team found that, if reduction strategies were implemented, the emissions for pavements and buildings between 2016 and 2050 could fall by up to 65 percent and 57 percent, respectively, even if concrete use accelerated greatly over that period. These are close to U.S. reduction targets set as part of the Paris Climate Accords. The solutions considered would also enable concrete production for both sectors to attain carbon neutrality by 2050.

      Despite continued grid decarbonization and increases in fuel efficiency, they found that the vast majority of the GHG emissions from new buildings and pavements during this period would derive from operational energy consumption rather than so-called embodied emissions — emissions from materials production and construction.

      Sources and solutions

      The consumption of concrete, due to its versatility, durability, constructability, and role in economic development, has been projected to increase around the world.

      While it is essential to consider the embodied impacts of ongoing concrete production, it is equally essential to place these initial impacts in the context of the material’s life cycle.

      Due to concrete’s unique attributes, it can influence the long-term sustainability performance of the systems in which it is used. Concrete pavements, for instance, can reduce vehicle fuel consumption, while concrete structures can endure hazards without needing energy- and materials-intensive repairs.

      Concrete’s impacts, then, are as complex as the material itself — a carefully proportioned mixture of cement powder, water, sand, and aggregates. Untangling concrete’s contribution to the operational and embodied impacts of buildings and pavements is essential for planning GHG reductions in both sectors.

      Set of scenarios

      In their paper, CSHub researchers forecast the potential greenhouse gas emissions from the building and pavements sectors as numerous emissions reduction strategies were introduced between 2016 and 2050.

      Since both of these sectors are immense and rapidly evolving, modeling them required an intricate framework.

      “We don’t have details on every building and pavement in the United States,” explains Randolph Kirchain, a research scientist at the Materials Research Laboratory and co-director of CSHub.

      “As such, we began by developing reference designs, which are intended to be representative of current and future buildings and pavements. These were adapted to be appropriate for 14 different climate zones in the United States and then distributed across the U.S. based on data from the U.S. Census and the Federal Highway Administration”

      To reflect the complexity of these systems, their models had to have the highest resolutions possible.

      “In the pavements sector, we collected the current stock of the U.S. network based on high-precision 10-mile segments, along with the surface conditions, traffic, thickness, lane width, and number of lanes for each segment,” says Hessam AzariJafari, a postdoc at CSHub and a co-author on the paper.

      “To model future paving actions over the analysis period, we assumed four climate conditions; four road types; asphalt, concrete, and composite pavement structures; as well as major, minor, and reconstruction paving actions specified for each climate condition.”

      Using this framework, they analyzed a “projected” and an “ambitious” scenario of reduction strategies and system attributes for buildings and pavements over the 34-year analysis period. The scenarios were defined by the timing and intensity of GHG reduction strategies.

      As its name might suggest, the projected scenario reflected current trends. For the building sector, solutions encompassed expected grid decarbonization and improvements to building codes and energy efficiency that are currently being implemented across the country. For pavements, the sole projected solution was improvements to vehicle fuel economy. That’s because as vehicle efficiency continues to increase, excess vehicle emissions due to poor road quality will also decrease.

      Both the projected scenarios for buildings and pavements featured the gradual introduction of low-carbon concrete strategies, such as recycled content, carbon capture in cement production, and the use of captured carbon to produce aggregates and cure concrete.

      “In the ambitious scenario,” explains Kirchain, “we went beyond projected trends and explored reasonable changes that exceed current policies and [industry] commitments.”

      Here, the building sector strategies were the same, but implemented more aggressively. The pavements sector also abided by more aggressive targets and incorporated several novel strategies, including investing more to yield smoother roads, selectively applying concrete overlays to produce stiffer pavements, and introducing more reflective pavements — which can change the Earth’s energy balance by sending more energy out of the atmosphere.

      Results

      As the grid becomes greener and new homes and buildings become more efficient, many experts have predicted the operational impacts of new construction projects to shrink in comparison to their embodied emissions.

      “What our life-cycle assessment found,” says Jeremy Gregory, the executive director of the MIT Climate Consortium and the lead author on the paper, “is that [this prediction] isn’t necessarily the case.”

      “Instead, we found that more than 80 percent of the total emissions from new buildings and pavements between 2016 and 2050 would derive from their operation.”

      In fact, the study found that operations will create the majority of emissions through 2050 unless all energy sources — electrical and thermal — are carbon-neutral by 2040. This suggests that ambitious interventions to the electricity grid and other sources of operational emissions can have the greatest impact.

      Their predictions for emissions reductions generated additional insights.  

      For the building sector, they found that the projected scenario would lead to a reduction of 49 percent compared to 2016 levels, and that the ambitious scenario provided a 57 percent reduction.

      As most buildings during the analysis period were existing rather than new, energy consumption dominated emissions in both scenarios. Consequently, decarbonizing the electricity grid and improving the efficiency of appliances and lighting led to the greatest improvements for buildings, they found.

      In contrast to the building sector, the pavements scenarios had a sizeable gulf between outcomes: the projected scenario led to only a 14 percent reduction while the ambitious scenario had a 65 percent reduction — enough to meet U.S. Paris Accord targets for that sector. This gulf derives from the lack of GHG reduction strategies being pursued under current projections.

      “The gap between the pavement scenarios shows that we need to be more proactive in managing the GHG impacts from pavements,” explains Kirchain. “There is tremendous potential, but seeing those gains requires action now.”

      These gains from both ambitious scenarios could occur even as concrete use tripled over the analysis period in comparison to the projected scenarios — a reflection of not only concrete’s growing demand but its potential role in decarbonizing both sectors.

      Though only one of their reduction scenarios (the ambitious pavement scenario) met the Paris Accord targets, that doesn’t preclude the achievement of those targets: many other opportunities exist.

      “In this study, we focused on mainly embodied reductions for concrete,” explains Gregory. “But other construction materials could receive similar treatment.

      “Further reductions could also come from retrofitting existing buildings and by designing structures with durability, hazard resilience, and adaptability in mind in order to minimize the need for reconstruction.”

      This study answers a paradox in the field of sustainability. For the world to become more equitable, more development is necessary. And yet, that very same development may portend greater emissions.

      The MIT team found that isn’t necessarily the case. Even as America continues to use more concrete, the benefits of the material itself and the interventions made to it can make climate targets more achievable.

      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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      in Environment

      Mitigating hazards with vulnerability in mind

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      From tropical storms to landslides, the form and frequency of natural hazards vary widely. But the feelings of vulnerability they can provoke are universal.

      Growing up in hazard-prone cities, Ipek Bensu Manav, a civil and environmental engineering PhD candidate with the MIT Concrete Sustainability Hub (CSHub), noticed that this vulnerability was always at the periphery. Today, she’s studying vulnerability, in both its engineering and social dimensions, with the aim of promoting more hazard-resilient communities.

      Her research at CSHub has taken her across the country to attend impactful conferences and allowed her to engage with prominent experts and decision-makers in the realm of resilience. But more fundamentally, it has also taken her beyond the conventional bounds of engineering, reshaping her understanding of the practice.

      From her time in Miami, Florida, and Istanbul, Turkey, Manav is no stranger to natural hazards. Istanbul, which suffered a devastating earthquake in 1999, is predicted to experience an equally violent tremor in the near future, while Miami ranks among the top cities in the U.S. in terms of natural disaster risk due to its vulnerability to hurricanes.

      “Growing up in Miami, I’d always hear about hurricane season on the news,” recounts Manav, “While in Istanbul there was a constant fear about the next big earthquake. Losing people and [witnessing] those kinds of events instilled in me a desire to tame nature.”

      It was this desire to “push the bounds of what is possible” — and to protect lives in the process — that motivated Manav to study civil engineering at Boğaziçi University. Her studies there affirmed her belief in the formidable power of engineering to “outsmart nature.”

      This, in part, led her to continue her studies at MIT CSHub — a team of interdisciplinary researchers who study how to achieve resilient and sustainable infrastructure. Her role at CSHub has given her the opportunity to study resilience in depth. It has also challenged her understanding of natural disasters — and whether they are “natural” at all.

      “Over the past few decades, some policy choices have increased the risk of experiencing disasters,” explains Manav. “An increasingly popular sentiment among resilience researchers is that natural disasters are not ‘natural,’ but are actually man-made. At CSHub we believe there is an opportunity to do better with the growing knowledge and engineering and policy research.”

      As a part of the CSHub portfolio, Manav’s research looks not just at resilient engineering, but the engineering of resilient communities.

      Her work draws on a metric developed at CSHub known as city texture, which is a measurement of the rectilinearity of a city’s layout. City texture, Manav and her colleagues have found, is a versatile and informative measurement. By capturing a city’s order or disorder, it can predict variations in wind flow — variations currently too computationally intensive for most cities to easily render.  

      Manav has derived this metric for her native South Florida. A city texture analysis she conducted there found that numerous census tracts could experience wind speeds 50 percent greater than currently predicted. Mitigating these wind variations could lead to some $697 million in savings annually.

      Such enormous hazard losses and the growing threat of climate change have presented her with a new understanding of engineering.

      “With resilience and climate change at the forefront of engineering, the focus has shifted,” she explains, “from defying limits and building impressive structures to making structures that adapt to the changing environment around us.”

      Witnessing this shift has reoriented her relationship with engineering. Rather than viewing it as a distinct science, she has begun to place it in its broader social and political context — and to recognize how those social and political dynamics often determine engineering outcomes.

      “When I started grad school, I often felt ‘Oh this is an engineering problem. I can engineer a solution’,” recounts Manav. “But as I’ve read more about resilience, I’ve realized that it’s just as much a concern of politics and policy as it is of engineering.”

      She attributes her awareness of policy to MIT CSHub’s collaboration with the Portland Cement Association and the Ready Mixed Concrete Research & Education Foundation. The commitment of the concrete and cement industries to resilient construction has exposed her to the myriad policies that dictate the resilience of communities.

      “Spending time with our partners made me realize how much of a policy issue [resilience] is,” she explains. “And working with them has provided me with a seat at the table with the people engaged in resilience.”

      Opportunities for engagement have been plentiful. She has attended numerous conferences and met with leaders in the realm of sustainability and resilience, including the International Code Council (ICC), Smart Home America, and Strengthen Alabama Homes.

      Some opportunities have proven particularly fortuitous. When attending a presentation hosted by the ICC and the National Association for the Advancement of Colored People (NAACP) that highlighted people of color working on building codes, Manav felt inspired to reach out to the presenters. Soon after, she found herself collaborating with them on a policy report on resilience in communities of color.

      “For me, it was a shifting point, going from prophesizing about what we could be doing, to observing what is being done. It was a very humbling experience,” she says. “Having worked in this lab made me feel more comfortable stepping outside of my comfort zone and reaching out.”

      Manav credits this growing confidence to her mentorship at CSHub. More than just providing support, CSHub Co-director Randy Kirchain has routinely challenged her and inspired further growth.

      “There have been countless times that I’ve reached out to him because I was feeling unsure of myself or my ideas,” says Manav. “And he’s offered clarity and assurance.”

      Before her first conference, she recalls Kirchain staying in the office well into the evening to help her practice and hone her presentation. He’s also advocated for her on research projects to ensure that her insight is included and that she receives the credit she deserves. But most of all, he’s been a great person to work with.

      “Randy is a lighthearted, funny, and honest person to be around,” recounts Manav. “He builds in me the confidence to dive straight into whatever task I’m tackling.”

      That current task is related to equity. Inspired by her conversations with members of the NAACP, Manav has introduced a new dimension to her research — social vulnerability.

      In contrast to place vulnerability, which captures the geographical susceptibility to hazards, social vulnerability captures the extent to which residents have the resources to respond to and recover from hazard events. Household income could act as a proxy for these resources, and the spread of household income across geographies and demographics can help derive metrics of place and social vulnerability. And these metrics matter.

      “Selecting different metrics favors different people when distributing hazard mitigation and recovery funds,” explains Manav. “If we’re looking at just the dollar value of losses, then wealthy households with more valuable properties disproportionally benefit. But, conversely, if we look at losses as a percentage of income, we’re going to prioritize low-income households that might not necessarily have the resources to recover.”

      Manav has incorporated metrics of social vulnerability into her city texture loss estimations. The resulting approach could predict unmitigated damage, estimate subsequent hazard losses, and measure the disparate impact of those losses on low-income and socially vulnerable communities.

      Her hope is that this streamlined approach could change how funds are disbursed and give communities the tools to solve the entwined challenges of climate change and equity.

      The city texture work Manav has adopted is quite different from the gravity-defying engineering that drew her to the field. But she’s found that it is often more pragmatic and impactful.

      Rather than mastering the elements, she’s learning how to adapt to them and help others do the same. Solutions to climate change, she’s discovered, demand the collaboration of numerous parties — as well as a willingness to confront one’s own vulnerabilities and make the decision to reach out.  More