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      in Environment

      Bringing the environment to the forefront of engineering

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      In a recent podcast interview with MIT President Sally Kornbluth, Associate Professor Desirée Plata described her childhood pastime of roaming the backyards and businesses of her grandmother’s hometown of Gray, Maine. Through her wanderings, Plata noticed a disturbing pattern.

      “I was 7 or 8 when I caught wind of all the illness,” Plata recalls. “It seemed like in every other house there was somebody who had a neurological disorder or a cancer of some sort.”

      While driving home one night with her mom, Plata made her first environmental hypothesis from the back seat. “I told my mom, ‘I think there’s something in the water or air where these people live.’”

      The conversation happened in the late 1980s. Plata was a little older when she learned her intuition was correct: The Environmental Protection Agency determined that a waste disposal facility had contaminated drinking water in the area while processing more than 1 million gallons of waste between 1965 and 1978.

      “There was a New York Times article on it, but it was sort of buried in a Sunday paper and a lot of folks up in Maine didn’t hear about it,” Plata says.

      What most struck Plata was that Gray was a tight-knit community, and the people who owned the waste disposal facility were friends with everybody. Eventually, some of the owner’s children even got sick.

      “People don’t poison their neighbors on purpose,” Plata says. “A lot of industrial contamination happens either by accident or because the engineers don’t know better. As an environmental scientist and engineer, it’s part of my job to help industrial engineers of any variety design their systems and processes such that they are thinking about what’s going into the environment from the start.”

      The insight led Plata to MIT, first as a PhD student, then as a visiting professor, and today as the newly tenured associate professor of civil and environmental engineering.

      These days Plata’s work is a bit more complex than her early backseat musings. In fact, her efforts extend far beyond research and include mentoring students, entrepreneurship, coalition-building, and coordination across industry, academia, and government. But the work can still be traced back to the childhood insight that environmental optimization needs to be a more tangible and important part of everyone’s thinking.

      “People think sustainability is this nebulous thing they can’t get their hands around,” Plata says. “But there are actually a set of rigorous principles you can use, and each one of those has a metric or a thing you can measure to go with it. MIT is such an innovative place. If we can incorporate environmental objectives into design at a place like MIT, the hope is the world can engage as well.”

      Taking the plunge

      Plata was first introduced to environmental research in high school, but it wasn’t until she attended Union College and got to work in a research lab that she knew it was what she’d do for the rest of her life.

      After graduating from Union, Plata decided to skip a master’s degree and “take the plunge” into the MIT-Woods Hole Oceanographic Institution (WHOI) joint doctoral program.

      “Talk about drinking from a firehose,” Plata says. “Everybody you bump into knows something that can help you solve the very hard problem you’re working on.”

      Plata began the program studying oil spills, and a paper she co-authored helped spur a law that changed the way oil is transported off the coast of Massachusetts. But developments in her personal life made her want to prevent environmental disasters before they happen.

      In her last year at Union, Plata’s aunt was diagnosed with breast cancer — a disease that’s been linked to one of the chemicals dumped in Gray, Maine. While Plata was at MIT, her aunt was receiving treatment at Massachusetts General Hospital down the road, so Plata would work at the lab at night, stay with her aunt during treatments all day, and go home with her on the weekends.

      “As I’m sampling oil, I’m recognizing that nothing I’m doing is going to help women like her escape the illness,” Plata recalls.

      In her third year of the MIT-WHOI program, Plata shifted her research to explore how industrial emissions generated during the creation of materials known as carbon nanotubes could inform how those valuable new materials were forming. The work led to a dramatically more sustainable way to make the materials, which are needed for important environmental applications themselves.

      After earning her PhD, Plata served as a visiting professor at MIT for two years before working in faculty positions at Duke University and Yale University, where she studied green chemistry and green optimization. She returned to MIT as an assistant professor in civil and environmental engineering in 2018.

      Working beyond academia

      While at Yale, Plata started a company, Nth Cycle, which uses electric currents to extract critical minerals like cobalt and nickel from lithium-ion batteries and other electronic waste. The company began commercial production last year.

      Plata also works extensively with government and industry, serving on a Massachusetts committee that published a roadmap to decarbonizing the state by 2050 and advising companies both formally and informally. (She estimates she gets a call every two weeks from a new company working on a sustainability problem.)

      “It’s undeniable that industry has an enormous impact on the environment,” Plata says. “Some like to think the government can wave a magic wand and make some regulation and we won’t be in this situation, but that’s not the case. There are technical challenges that need to be solved and businesses play an incredibly important role as agents of change.”

      Plata’s research at MIT, meanwhile, is focused increasingly on methane. Last year she helped create the MIT Methane Network, which she directs.

      Plata’s research has explored ways to convert methane into less harmful carbon dioxide and other fuels in places like dairy farms and coal plants. This past summer she took a team of students to dairy barns to conduct field tests.

      “If you could take methane from coal mining out of the air globally, it’s equivalent to taking all of the combustion engine vehicles off the road, even accounting for the small generation of CO2 that we have [as the result of our process],” Plata says. “If you can fix the problem at dairy farms, it’s like all the combustion engine vehicle emissions times three. It’s a hugely impactful number.”

      Taking action

      When Plata was in fourth grade, her teacher had students pick up trash around a nearby bay. She’s since done the exercise with other fourth graders.

      “You ask them what they think they’ll find, and they say, ‘Nothing. I didn’t see any trash on the way to school today,’ but when you ask them to look, everybody fills their bag by the end of the trip, and you start to realize how much fugitive emissions of waste exists, and then you start to start thinking about all of the chemical contamination that you can’t see,” Plata says.

      One of Plata’s chief research goals can be summed up with that exercise: getting people to appreciate the importance of environmental criteria and motivating them to take action.

      “Today, I see people looking for these silver bullet solutions to solve environmental problems,” Plata says. “That’s not how we got into this mess, and it’s not how we’re going to get out of it. The problem is really distributed, so what we really need is the sum of a lot of small actions to change the system.” More

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      in Energy

      Supporting sustainability, digital health, and the future of work

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      The MIT and Accenture Convergence Initiative for Industry and Technology has selected three new research projects that will receive support from the initiative. The research projects aim to accelerate progress in meeting complex societal needs through new business convergence insights in technology and innovation.

      Established in MIT’s School of Engineering and now in its third year, the MIT and Accenture Convergence Initiative is furthering its mission to bring together technological experts from across business and academia to share insights and learn from one another. Recently, Thomas W. Malone, the Patrick J. McGovern (1959) Professor of Management, joined the initiative as its first-ever faculty lead. The research projects relate to three of the initiative’s key focus areas: sustainability, digital health, and the future of work.

      “The solutions these research teams are developing have the potential to have tremendous impact,” says Anantha Chandrakasan, dean of the School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “They embody the initiative’s focus on advancing data-driven research that addresses technology and industry convergence.”

      “The convergence of science and technology driven by advancements in generative AI, digital twins, quantum computing, and other technologies makes this an especially exciting time for Accenture and MIT to be undertaking this joint research,” says Kenneth Munie, senior managing director at Accenture Strategy, Life Sciences. “Our three new research projects focusing on sustainability, digital health, and the future of work have the potential to help guide and shape future innovations that will benefit the way we work and live.”

      The MIT and Accenture Convergence Initiative charter project researchers are described below.

      Accelerating the journey to net zero with industrial clusters

      Jessika Trancik is a professor at the Institute for Data, Systems, and Society (IDSS). Trancik’s research examines the dynamic costs, performance, and environmental impacts of energy systems to inform climate policy and accelerate beneficial and equitable technology innovation. Trancik’s project aims to identify how industrial clusters can enable companies to derive greater value from decarbonization, potentially making companies more willing to invest in the clean energy transition.

      To meet the ambitious climate goals that have been set by countries around the world, rising greenhouse gas emissions trends must be rapidly reversed. Industrial clusters — geographically co-located or otherwise-aligned groups of companies representing one or more industries — account for a significant portion of greenhouse gas emissions globally. With major energy consumers “clustered” in proximity, industrial clusters provide a potential platform to scale low-carbon solutions by enabling the aggregation of demand and the coordinated investment in physical energy supply infrastructure.

      In addition to Trancik, the research team working on this project will include Aliza Khurram, a postdoc in IDSS; Micah Ziegler, an IDSS research scientist; Melissa Stark, global energy transition services lead at Accenture; Laura Sanderfer, strategy consulting manager at Accenture; and Maria De Miguel, strategy senior analyst at Accenture.

      Eliminating childhood obesity

      Anette “Peko” Hosoi is the Neil and Jane Pappalardo Professor of Mechanical Engineering. A common theme in her work is the fundamental study of shape, kinematic, and rheological optimization of biological systems with applications to the emergent field of soft robotics. Her project will use both data from existing studies and synthetic data to create a return-on-investment (ROI) calculator for childhood obesity interventions so that companies can identify earlier returns on their investment beyond reduced health-care costs.

      Childhood obesity is too prevalent to be solved by a single company, industry, drug, application, or program. In addition to the physical and emotional impact on children, society bears a cost through excess health care spending, lost workforce productivity, poor school performance, and increased family trauma. Meaningful solutions require multiple organizations, representing different parts of society, working together with a common understanding of the problem, the economic benefits, and the return on investment. ROI is particularly difficult to defend for any single organization because investment and return can be separated by many years and involve asymmetric investments, returns, and allocation of risk. Hosoi’s project will consider the incentives for a particular entity to invest in programs in order to reduce childhood obesity.

      Hosoi will be joined by graduate students Pragya Neupane and Rachael Kha, both of IDSS, as well a team from Accenture that includes Kenneth Munie, senior managing director at Accenture Strategy, Life Sciences; Kaveh Safavi, senior managing director in Accenture Health Industry; and Elizabeth Naik, global health and public service research lead.

      Generating innovative organizational configurations and algorithms for dealing with the problem of post-pandemic employment

      Thomas Malone is the Patrick J. McGovern (1959) Professor of Management at the MIT Sloan School of Management and the founding director of the MIT Center for Collective Intelligence. His research focuses on how new organizations can be designed to take advantage of the possibilities provided by information technology. Malone will be joined in this project by John Horton, the Richard S. Leghorn (1939) Career Development Professor at the MIT Sloan School of Management, whose research focuses on the intersection of labor economics, market design, and information systems. Malone and Horton’s project will look to reshape the future of work with the help of lessons learned in the wake of the pandemic.

      The Covid-19 pandemic has been a major disrupter of work and employment, and it is not at all obvious how governments, businesses, and other organizations should manage the transition to a desirable state of employment as the pandemic recedes. Using natural language processing algorithms such as GPT-4, this project will look to identify new ways that companies can use AI to better match applicants to necessary jobs, create new types of jobs, assess skill training needed, and identify interventions to help include women and other groups whose employment was disproportionately affected by the pandemic.

      In addition to Malone and Horton, the research team will include Rob Laubacher, associate director and research scientist at the MIT Center for Collective Intelligence, and Kathleen Kennedy, executive director at the MIT Center for Collective Intelligence and senior director at MIT Horizon. The team will also include Nitu Nivedita, managing director of artificial intelligence at Accenture, and Thomas Hancock, data science senior manager at Accenture. More

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      in Environment

      The curse of variety in transportation systems

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      Cathy Wu has always delighted in systems that run smoothly. In high school, she designed a project to optimize the best route for getting to class on time. Her research interests and career track are evidence of a propensity for organizing and optimizing, coupled with a strong sense of responsibility to contribute to society instilled by her parents at a young age.

      As an undergraduate at MIT, Wu explored domains like agriculture, energy, and education, eventually homing in on transportation. “Transportation touches each of our lives,” she says. “Every day, we experience the inefficiencies and safety issues as well as the environmental harms associated with our transportation systems. I believe we can and should do better.”

      But doing so is complicated. Consider the long-standing issue of traffic systems control. Wu explains that it is not one problem, but more accurately a family of control problems impacted by variables like time of day, weather, and vehicle type — not to mention the types of sensing and communication technologies used to measure roadway information. Every differentiating factor introduces an exponentially larger set of control problems. There are thousands of control-problem variations and hundreds, if not thousands, of studies and papers dedicated to each problem. Wu refers to the sheer number of variations as the curse of variety — and it is hindering innovation.

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      “To prove that a new control strategy can be safely deployed on our streets can take years. As time lags, we lose opportunities to improve safety and equity while mitigating environmental impacts. Accelerating this process has huge potential,” says Wu.  

      Which is why she and her group in the MIT Laboratory for Information and Decision Systems are devising machine learning-based methods to solve not just a single control problem or a single optimization problem, but families of control and optimization problems at scale. “In our case, we’re examining emerging transportation problems that people have spent decades trying to solve with classical approaches. It seems to me that we need a different approach.”

      Optimizing intersections

      Currently, Wu’s largest research endeavor is called Project Greenwave. There are many sectors that directly contribute to climate change, but transportation is responsible for the largest share of greenhouse gas emissions — 29 percent, of which 81 percent is due to land transportation. And while much of the conversation around mitigating environmental impacts related to mobility is focused on electric vehicles (EVs), electrification has its drawbacks. EV fleet turnover is time-consuming (“on the order of decades,” says Wu), and limited global access to the technology presents a significant barrier to widespread adoption.

      Wu’s research, on the other hand, addresses traffic control problems by leveraging deep reinforcement learning. Specifically, she is looking at traffic intersections — and for good reason. In the United States alone, there are more than 300,000 signalized intersections where vehicles must stop or slow down before re-accelerating. And every re-acceleration burns fossil fuels and contributes to greenhouse gas emissions.

      Highlighting the magnitude of the issue, Wu says, “We have done preliminary analysis indicating that up to 15 percent of land transportation CO2 is wasted through energy spent idling and re-accelerating at intersections.”

      To date, she and her group have modeled 30,000 different intersections across 10 major metropolitan areas in the United States. That is 30,000 different configurations, roadway topologies (e.g., grade of road or elevation), different weather conditions, and variations in travel demand and fuel mix. Each intersection and its corresponding scenarios represents a unique multi-agent control problem.

      Wu and her team are devising techniques that can solve not just one, but a whole family of problems comprised of tens of thousands of scenarios. Put simply, the idea is to coordinate the timing of vehicles so they arrive at intersections when traffic lights are green, thereby eliminating the start, stop, re-accelerate conundrum. Along the way, they are building an ecosystem of tools, datasets, and methods to enable roadway interventions and impact assessments of strategies to significantly reduce carbon-intense urban driving.

      Play video

      Their collaborator on the project is the Utah Department of Transportation, which Wu says has played an essential role, in part by sharing data and practical knowledge that she and her group otherwise would not have been able to access publicly.

      “I appreciate industry and public sector collaborations,” says Wu. “When it comes to important societal problems, one really needs grounding with practitioners. One needs to be able to hear the perspectives in the field. My interactions with practitioners expand my horizons and help ground my research. You never know when you’ll hear the perspective that is the key to the solution, or perhaps the key to understanding the problem.”

      Finding the best routes

      In a similar vein, she and her research group are tackling large coordination problems. For example, vehicle routing. “Every day, delivery trucks route more than a hundred thousand packages for the city of Boston alone,” says Wu. Accomplishing the task requires, among other things, figuring out which trucks to use, which packages to deliver, and the order in which to deliver them as efficiently as possible. If and when the trucks are electrified, they will need to be charged, adding another wrinkle to the process and further complicating route optimization.

      The vehicle routing problem, and therefore the scope of Wu’s work, extends beyond truck routing for package delivery. Ride-hailing cars may need to pick up objects as well as drop them off; and what if delivery is done by bicycle or drone? In partnership with Amazon, for example, Wu and her team addressed routing and path planning for hundreds of robots (up to 800) in their warehouses.

      Every variation requires custom heuristics that are expensive and time-consuming to develop. Again, this is really a family of problems — each one complicated, time-consuming, and currently unsolved by classical techniques — and they are all variations of a central routing problem. The curse of variety meets operations and logistics.

      By combining classical approaches with modern deep-learning methods, Wu is looking for a way to automatically identify heuristics that can effectively solve all of these vehicle routing problems. So far, her approach has proved successful.

      “We’ve contributed hybrid learning approaches that take existing solution methods for small problems and incorporate them into our learning framework to scale and accelerate that existing solver for large problems. And we’re able to do this in a way that can automatically identify heuristics for specialized variations of the vehicle routing problem.” The next step, says Wu, is applying a similar approach to multi-agent robotics problems in automated warehouses.

      Wu and her group are making big strides, in part due to their dedication to use-inspired basic research. Rather than applying known methods or science to a problem, they develop new methods, new science, to address problems. The methods she and her team employ are necessitated by societal problems with practical implications. The inspiration for the approach? None other than Louis Pasteur, who described his research style in a now-famous article titled “Pasteur’s Quadrant.” Anthrax was decimating the sheep population, and Pasteur wanted to better understand why and what could be done about it. The tools of the time could not solve the problem, so he invented a new field, microbiology, not out of curiosity but out of necessity. More

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      in Energy

      Cutting urban carbon emissions by retrofitting buildings

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      To support the worldwide struggle to reduce carbon emissions, many cities have made public pledges to cut their carbon emissions in half by 2030, and some have promised to be carbon neutral by 2050. Buildings can be responsible for more than half a municipality’s carbon emissions. Today, new buildings are typically designed in ways that minimize energy use and carbon emissions. So attention focuses on cleaning up existing buildings.

      A decade ago, leaders in some cities took the first step in that process: They quantified their problem. Based on data from their utilities on natural gas and electricity consumption and standard pollutant-emission rates, they calculated how much carbon came from their buildings. They then adopted policies to encourage retrofits, such as adding insulation, switching to double-glazed windows, or installing rooftop solar panels. But will those steps be enough to meet their pledges?

      “In nearly all cases, cities have no clear plan for how they’re going to reach their goal,” says Christoph Reinhart, a professor in the Department of Architecture and director of the Building Technology Program. “That’s where our work comes in. We aim to help them perform analyses so they can say, ‘If we, as a community, do A, B, and C to buildings of a certain type within our jurisdiction, then we are going to get there.’”

      To support those analyses, Reinhart and a team in the MIT Sustainable Design Lab (SDL) — PhD candidate Zachary M. Berzolla SM ’21; former doctoral student Yu Qian Ang PhD ’22, now a research collaborator at the SDL; and former postdoc Samuel Letellier-Duchesne, now a senior building performance analyst at the international building engineering and consulting firm Introba — launched a publicly accessible website providing a series of simulation tools and a process for using them to determine the impacts of planned steps on a specific building stock. Says Reinhart: “The takeaway can be a clear technology pathway — a combination of building upgrades, renewable energy deployments, and other measures that will enable a community to reach its carbon-reduction goals for their built environment.”

      Analyses performed in collaboration with policymakers from selected cities around the world yielded insights demonstrating that reaching current goals will require more effort than city representatives and — in a few cases — even the research team had anticipated.

      Exploring carbon-reduction pathways

      The researchers’ approach builds on a physics-based “building energy model,” or BEM, akin to those that architects use to design high-performance green buildings. In 2013, Reinhart and his team developed a method of extending that concept to analyze a cluster of buildings. Based on publicly available geographic information system (GIS) data, including each building’s type, footprint, and year of construction, the method defines the neighborhood — including trees, parks, and so on — and then, using meteorological data, how the buildings will interact, the airflows among them, and their energy use. The result is an “urban building energy model,” or UBEM, for a neighborhood or a whole city.

      The website developed by the MIT team enables neighborhoods and cities to develop their own UBEM and to use it to calculate their current building energy use and resulting carbon emissions, and then how those outcomes would change assuming different retrofit programs or other measures being implemented or considered. “The website — UBEM.io — provides step-by-step instructions and all the simulation tools that a team will need to perform an analysis,” says Reinhart.

      The website starts by describing three roles required to perform an analysis: a local sustainability champion who is familiar with the municipality’s carbon-reduction efforts; a GIS manager who has access to the municipality’s urban datasets and maintains a digital model of the built environment; and an energy modeler — typically a hired consultant — who has a background in green building consulting and individual building energy modeling.

      The team begins by defining “shallow” and “deep” building retrofit scenarios. To explain, Reinhart offers some examples: “‘Shallow’ refers to things that just happen, like when you replace your old, failing appliances with new, energy-efficient ones, or you install LED light bulbs and weatherstripping everywhere,” he says. “‘Deep’ adds to that list things you might do only every 20 years, such as ripping out walls and putting in insulation or replacing your gas furnace with an electric heat pump.”

      Once those scenarios are defined, the GIS manager uploads to UBEM.io a dataset of information about the city’s buildings, including their locations and attributes such as geometry, height, age, and use (e.g., commercial, retail, residential). The energy modeler then builds a UBEM to calculate the energy use and carbon emissions of the existing building stock. Once that baseline is established, the energy modeler can calculate how specific retrofit measures will change the outcomes.

      Workshop to test-drive the method

      Two years ago, the MIT team set up a three-day workshop to test the website with sample users. Participants included policymakers from eight cities and municipalities around the world: namely, Braga (Portugal), Cairo (Egypt), Dublin (Ireland), Florianopolis (Brazil), Kiel (Germany), Middlebury (Vermont, United States), Montreal (Canada), and Singapore. Taken together, the cities represent a wide range of climates, socioeconomic demographics, cultures, governing structures, and sizes.

      Working with the MIT team, the participants presented their goals, defined shallow- and deep-retrofit scenarios for their city, and selected a limited but representative area for analysis — an approach that would speed up analyses of different options while also generating results valid for the city as a whole.

      They then performed analyses to quantify the impacts of their retrofit scenarios. Finally, they learned how best to present their findings — a critical part of the exercise. “When you do this analysis and bring it back to the people, you can say, ‘This is our homework over the next 30 years. If we do this, we’re going to get there,’” says Reinhart. “That makes you part of the community, so it’s a joint goal.”

      Sample results

      After the close of the workshop, Reinhart and his team confirmed their findings for each city and then added one more factor to the analyses: the state of the city’s electric grid. Several cities in the study had pledged to make their grid carbon-neutral by 2050. Including the grid in the analysis was therefore critical: If a building becomes all-electric and purchases its electricity from a carbon-free grid, then that building will be carbon neutral — even with no on-site energy-saving retrofits.

      The final analysis for each city therefore calculated the total kilograms of carbon dioxide equivalent emitted per square meter of floor space assuming the following scenarios: the baseline; shallow retrofit only; shallow retrofit plus a clean electricity grid; deep retrofit only; deep retrofit plus rooftop photovoltaic solar panels; and deep retrofit plus a clean electricity grid. (Note that “clean electricity grid” is based on the area’s most ambitious decarbonization target for their power grid.)

      The following paragraphs provide highlights of the analyses for three of the eight cities. Included are the city’s setting, emission-reduction goals, current and proposed measures, and calculations of how implementation of those measures would affect their energy use and carbon emissions.

      Singapore

      Singapore is generally hot and humid, and its building energy use is largely in the form of electricity for cooling. The city is dominated by high-rise buildings, so there’s not much space for rooftop solar installations to generate the needed electricity. Therefore, plans for decarbonizing the current building stock must involve retrofits. The shallow-retrofit scenario focuses on installing energy-efficient lighting and appliances. To those steps, the deep-retrofit scenario adds adopting a district cooling system. Singapore’s stated goals are to cut the baseline carbon emissions by about a third by 2030 and to cut it in half by 2050.

      The analysis shows that, with just the shallow retrofits, Singapore won’t achieve its 2030 goal. But with the deep retrofits, it should come close. Notably, decarbonizing the electric grid would enable Singapore to meet and substantially exceed its 2050 target assuming either retrofit scenario.

      Dublin

      Dublin has a mild climate with relatively comfortable summers but cold, humid winters. As a result, the city’s energy use is dominated by fossil fuels, in particular, natural gas for space heating and domestic hot water. The city presented just one target — a 40 percent reduction by 2030.

      Dublin has many neighborhoods made up of Georgian row houses, and, at the time of the workshop, the city already had a program in place encouraging groups of owners to insulate their walls. The shallow-retrofit scenario therefore focuses on weatherization upgrades (adding weatherstripping to windows and doors, insulating crawlspaces, and so on). To that list, the deep-retrofit scenario adds insulating walls and installing upgraded windows. The participants didn’t include electric heat pumps, as the city was then assessing the feasibility of expanding the existing district heating system.

      Results of the analyses show that implementing the shallow-retrofit scenario won’t enable Dublin to meet its 2030 target. But the deep-retrofit scenario will. However, like Singapore, Dublin could make major gains by decarbonizing its electric grid. The analysis shows that a decarbonized grid — with or without the addition of rooftop solar panels where possible — could more than halve the carbon emissions that remain in the deep-retrofit scenario. Indeed, a decarbonized grid plus electrification of the heating system by incorporating heat pumps could enable Dublin to meet a future net-zero target.

      Middlebury

      Middlebury, Vermont, has warm, wet summers and frigid winters. Like Dublin, its energy demand is dominated by natural gas for heating. But unlike Dublin, it already has a largely decarbonized electric grid with a high penetration of renewables.

      For the analysis, the Middlebury team chose to focus on an aging residential neighborhood similar to many that surround the city core. The shallow-retrofit scenario calls for installing heat pumps for space heating, and the deep-retrofit scenario adds improvements in building envelopes (the façade, roof, and windows). The town’s targets are a 40 percent reduction from the baseline by 2030 and net-zero carbon by 2050.

      Results of the analyses showed that implementing the shallow-retrofit scenario won’t achieve the 2030 target. The deep-retrofit scenario would get the city to the 2030 target but not to the 2050 target. Indeed, even with the deep retrofits, fossil fuel use remains high. The explanation? While both retrofit scenarios call for installing heat pumps for space heating, the city would continue to use natural gas to heat its hot water.

      Lessons learned

      For several policymakers, seeing the results of their analyses was a wake-up call. They learned that the strategies they had planned might not be sufficient to meet their stated goals — an outcome that could prove publicly embarrassing for them in the future.

      Like the policymakers, the researchers learned from the experience. Reinhart notes three main takeaways.

      First, he and his team were surprised to find how much of a building’s energy use and carbon emissions can be traced to domestic hot water. With Middlebury, for example, even switching from natural gas to heat pumps for space heating didn’t yield the expected effect: On the bar graphs generated by their analyses, the gray bars indicating carbon from fossil fuel use remained. As Reinhart recalls, “I kept saying, ‘What’s all this gray?’” While the policymakers talked about using heat pumps, they were still going to use natural gas to heat their hot water. “It’s just stunning that hot water is such a big-ticket item. It’s huge,” says Reinhart.

      Second, the results demonstrate the importance of including the state of the local electric grid in this type of analysis. “Looking at the results, it’s clear that if we want to have a successful energy transition, the building sector and the electric grid sector both have to do their homework,” notes Reinhart. Moreover, in many cases, reaching carbon neutrality by 2050 would require not only a carbon-free grid but also all-electric buildings.

      Third, Reinhart was struck by how different the bar graphs presenting results for the eight cities look. “This really celebrates the uniqueness of different parts of the world,” he says. “The physics used in the analysis is the same everywhere, but differences in the climate, the building stock, construction practices, electric grids, and other factors make the consequences of making the same change vary widely.”

      In addition, says Reinhart, “there are sometimes deeply ingrained conflicts of interest and cultural norms, which is why you cannot just say everybody should do this and do this.” For instance, in one case, the city owned both the utility and the natural gas it burned. As a result, the policymakers didn’t consider putting in heat pumps because “the natural gas was a significant source of municipal income, and they didn’t want to give that up,” explains Reinhart.

      Finally, the analyses quantified two other important measures: energy use and “peak load,” which is the maximum electricity demanded from the grid over a specific time period. Reinhart says that energy use “is probably mostly a plausibility check. Does this make sense?” And peak load is important because the utilities need to keep a stable grid.

      Middlebury’s analysis provides an interesting look at how certain measures could influence peak electricity demand. There, the introduction of electric heat pumps for space heating more than doubles the peak demand from buildings, suggesting that substantial additional capacity would have to be added to the grid in that region. But when heat pumps are combined with other retrofitting measures, the peak demand drops to levels lower than the starting baseline.

      The aftermath: An update

      Reinhart stresses that the specific results from the workshop provide just a snapshot in time; that is, where the cities were at the time of the workshop. “This is not the fate of the city,” he says. “If we were to do the same exercise today, we’d no doubt see a change in thinking, and the outcomes would be different.”

      For example, heat pumps are now familiar technology and have demonstrated their ability to handle even bitterly cold climates. And in some regions, they’ve become economically attractive, as the war in Ukraine has made natural gas both scarce and expensive. Also, there’s now awareness of the need to deal with hot water production.

      Reinhart notes that performing the analyses at the workshop did have the intended impact: It brought about change. Two years after the project had ended, most of the cities reported that they had implemented new policy measures or had expanded their analysis across their entire building stock. “That’s exactly what we want,” comments Reinhart. “This is not an academic exercise. It’s meant to change what people focus on and what they do.”

      Designing policies with socioeconomics in mind

      Reinhart notes a key limitation of the UBEM.io approach: It looks only at technical feasibility. But will the building owners be willing and able to make the energy-saving retrofits? Data show that — even with today’s incentive programs and subsidies — current adoption rates are only about 1 percent. “That’s way too low to enable a city to achieve its emission-reduction goals in 30 years,” says Reinhart. “We need to take into account the socioeconomic realities of the residents to design policies that are both effective and equitable.”

      To that end, the MIT team extended their UBEM.io approach to create a socio-techno-economic analysis framework that can predict the rate of retrofit adoption throughout a city. Based on census data, the framework creates a UBEM that includes demographics for the specific types of buildings in a city. Accounting for the cost of making a specific retrofit plus financial benefits from policy incentives and future energy savings, the model determines the economic viability of the retrofit package for representative households.

      Sample analyses for two Boston neighborhoods suggest that high-income households are largely ineligible for need-based incentives or the incentives are insufficient to prompt action. Lower-income households are eligible and could benefit financially over time, but they don’t act, perhaps due to limited access to information, a lack of time or capital, or a variety of other reasons.

      Reinhart notes that their work thus far “is mainly looking at technical feasibility. Next steps are to better understand occupants’ willingness to pay, and then to determine what set of federal and local incentive programs will trigger households across the demographic spectrum to retrofit their apartments and houses, helping the worldwide effort to reduce carbon emissions.”

      This work was supported by Shell through the MIT Energy Initiative. Zachary Berzolla was supported by the U.S. National Science Foundation Graduate Research Fellowship. Samuel Letellier-Duchesne was supported by the postdoctoral fellowship of the Natural Sciences and Engineering Research Council of Canada.

      This article appears in the Spring 2023 issue of Energy Futures, the magazine of the MIT Energy Initiative. More

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      in Energy

      Tackling the MIT campus’s top energy consumers, building by building

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      When staff in MIT’s Department of Facilities would visualize energy use and carbon-associated emissions by campus buildings, Building 46 always stood out — attributed to its energy intensity, which accounted for 8 percent of MIT’s total campus energy use. This high energy draw was not surprising, as the building is home of the Brain and Cognitive Sciences Complex and a large amount of lab space, but it also made the building a perfect candidate for an energy performance audit to seek out potential energy saving opportunities.

      This audit revealed that several energy efficiency updates to the building mechanical systems infrastructure, including optimization of the room-by-room ventilation rates, could result in an estimated 35 percent reduction of energy use, which would in turn lower MIT’s total greenhouse gas emissions by an estimated 2 percent — driving toward the Institute’s 2026 goal of net-zero and 2050 goal of elimination of direct campus emissions.

      Building energy efficiency projects are not new for MIT. Since 2010, MIT has been engaged in a partnership agreement with utility company Eversource establishing the Efficiency Forward program, empowering MIT to invest in more than 300 energy conservation projects to date and lowering energy consumption on campus for a total calculated savings of approximately 70 million kilowatt hours and 4.2 million therms. But at 418,000 gross square feet, Building 46 is the first energy efficiency project of its size on the campus.

      “We’ve never tackled a whole building like this — it’s the first capital project that is technically an energy project,” explains Siobhan Carr, energy efficiency program manager, who was part of the team overseeing the energy audit and lab ventilation performance assessment in the building. “That gives you an idea of the magnitude and complexity of this.”

      The project started with the full building energy assessment and lab ventilation risk audit. “We had a team go through every corner of the building and look at every possible opportunity to save energy,” explains Jessica Parks, senior project manager for systems performance and turnover in campus construction. “One of the biggest issues we saw was that there’s a lot of dry lab spaces which are basically offices, but they’re all getting the same ventilation as if they were a high-intensity lab.” Higher ventilation and more frequent air exchange rates draw more energy. By optimizing for the required ventilation rates, there was an opportunity to save energy in nearly every space in the building.

      In addition to the optimized ventilation, the project team will convert fume hoods from constant volume to variable volume and install equipment to help the building systems run more efficiently. The team also identified opportunities to work with labs to implement programs such as fume hood hibernation and unoccupied setbacks for temperature and ventilation. As different spaces in the building have varying needs, the energy retrofit will touch all 1,254 spaces in the building — one by one — to implement the different energy measures to reach that estimated 35 percent reduction in energy use.

      Although time-consuming and complex, this room-by-room approach has a big benefit in that it has allowed research to continue in the space largely uninterrupted. With a few exceptions, the occupants of Building 46, which include the Department of Brain and Cognitive Sciences, The McGovern Institute for Brain Research, and The Picower Institute for Learning and Memory, have remained in place for the duration of the project. Partners in the MIT Environment, Health and Safety Office are instrumental to this balance of renovations and keeping the building operational during the optimization efforts and are one of several teams across MIT contributing to building efficiency efforts.

      The completion date of the building efficiency project is set for 2024, but Carr says that some of the impact of this ongoing work may soon be seen. “We should start to see savings as we move through the building, and we expect to fully realize all of our projected savings a year after completion,” she says, noting that the length of time is required for a year-over-year perspective to see the full reduction in energy use.

      The impact of the project goes far beyond the footprint of Building 46 as it offers insights and spurred actions for future projects — including buildings 76 and 68, the number two and three top energy users on campus. Both buildings recently underwent their own energy audits and lab ventilation performance assessments. The energy efficiency team is now crafting a plan for full-building approaches, much like Building 46. “To date, 46 has presented many learning opportunities, such as how to touch every space in a building while research continues, as well as how to overcome challenges encountered when working on existing systems,” explains Parks. “The good news is that we have developed solutions for those challenges and the teams have been proactively implementing those lessons in our other projects.”

      Communication has proven to be another key for these large projects where occupants see the work happening and often play a role in answering questions about their unique space. “People are really engaged, they ask questions about the work, and we ask them about the space they’re in every day,” says Parks. “The Building 46 occupants have been wonderful partners as we worked in all of their spaces, which is paving the way for a successful project.”

      The release of Fast Forward in 2021 has also made communications easier, notes Carr, who says the plan helps to frame these projects as part of the big picture — not just a construction interruption. “Fast Forward has brought a visibility into what we’re doing within [MIT] Facilities on these buildings,” she says. “It brings more eyes and ears, and people understand that these projects are happening throughout campus and not just in their own space — we’re all working to reduce energy and to reduce greenhouse gas across campus.”

      The Energy Efficiency team will continue to apply that big-picture approach as ongoing building efficiency projects on campus are assessed to reach toward a 10 to 15 percent reduction in energy use and corresponding emissions over the next several years. More

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      in Energy

      Finding “hot spots” where compounding environmental and economic risks converge

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      A computational tool developed by researchers at the MIT Joint Program on the Science and Policy of Global Change pinpoints specific counties within the United States that are particularly vulnerable to economic distress resulting from a transition from fossil fuels to low-carbon energy sources. By combining county-level data on employment in fossil fuel (oil, natural gas, and coal) industries with data on populations below the poverty level, the tool identifies locations with high risks for transition-driven economic hardship. It turns out that many of these high-risk counties are in the south-central U.S., with a heavy concentration in the lower portions of the Mississippi River.

      The computational tool, which the researchers call the System for the Triage of Risks from Environmental and Socio-economic Stressors (STRESS) platform, almost instantly displays these risk combinations on an easy-to-read visual map, revealing those counties that stand to gain the most from targeted green jobs retraining programs.  

      Drawing on data that characterize land, water, and energy systems; biodiversity; demographics; environmental equity; and transportation networks, the STRESS platform enables users to assess multiple, co-evolving, compounding hazards within a U.S. geographical region from the national to the county level. Because of its comprehensiveness and precision, this screening-level visualization tool can pinpoint risk “hot spots” that can be subsequently investigated in greater detail. Decision-makers can then plan targeted interventions to boost resilience to location-specific physical and economic risks.

      The platform and its applications are highlighted in a new study in the journal Frontiers in Climate.

      “As risks to natural and managed resources — and to the economies that depend upon them — become more complex, interdependent, and compounding amid rapid environmental and societal changes, they require more and more human and computational resources to understand and act upon,” says MIT Joint Program Deputy Director C. Adam Schlosser, the lead author of the study. “The STRESS platform provides decision-makers with an efficient way to combine and analyze data on those risks that matter most to them, identify ‘hot spots’ of compounding risk, and design interventions to minimize that risk.”

      In one demonstration of the STRESS platform’s capabilities, the study shows that national and global actions to reduce greenhouse gas emissions could simultaneously reduce risks to land, water, and air quality in the upper Mississippi River basin while increasing economic risks in the lower basin, where poverty and unemployment are already disproportionate. In another demonstration, the platform finds concerning “hot spots” where flood risk, poverty, and nonwhite populations coincide.

      The risk triage platform is based on an emerging discipline called multi-sector dynamics (MSD), which seeks to understand and model compounding risks and potential tipping points across interconnected natural and human systems. Tipping points occur when these systems can no longer sustain multiple, co-evolving stresses, such as extreme events, population growth, land degradation, drinkable water shortages, air pollution, aging infrastructure, and increased human demands. MSD researchers use observations and computer models to identify key precursory indicators of such tipping points, providing decision-makers with critical information that can be applied to mitigate risks and boost resilience in natural and managed resources. With funding from the U.S. Department of Energy, the MIT Joint Program has since 2018 been developing MSD expertise and modeling tools and using them to explore compounding risks and potential tipping points in selected regions of the United States.

      Current STRESS platform data includes more than 100 risk metrics at the county-level scale, but data collection is ongoing. MIT Joint Program researchers are continuing to develop the STRESS platform as an “open-science tool” that welcomes input from academics, researchers, industry and the general public. More

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      in Environment

      Inaugural J-WAFS Grand Challenge aims to develop enhanced crop variants and move them from lab to land

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      According to MIT’s charter, established in 1861, part of the Institute’s mission is to advance the “development and practical application of science in connection with arts, agriculture, manufactures, and commerce.” Today, the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) is one of the driving forces behind water and food-related research on campus, much of which relates to agriculture. In 2022, J-WAFS established the Water and Food Grand Challenge Grant to inspire MIT researchers to work toward a water-secure and food-secure future for our changing planet. Not unlike MIT’s Climate Grand Challenges, the J-WAFS Grand Challenge seeks to leverage multiple areas of expertise, programs, and Institute resources. The initial call for statements of interests returned 23 letters from MIT researchers spanning 18 departments, labs, and centers. J-WAFS hosted workshops for the proposers to present and discuss their initial ideas. These were winnowed down to a smaller set of invited concept papers, followed by the final proposal stage. 

      Today, J-WAFS is delighted to report that the inaugural J-WAFS Grand Challenge Grant has been awarded to a team of researchers led by Professor Matt Shoulders and research scientist Robert Wilson of the Department of Chemistry. A panel of expert, external reviewers highly endorsed their proposal, which tackles a longstanding problem in crop biology — how to make photosynthesis more efficient. The team will receive $1.5 million over three years to facilitate a multistage research project that combines cutting-edge innovations in synthetic and computational biology. If successful, this project could create major benefits for agriculture and food systems worldwide.

      “Food systems are a major source of global greenhouse gas emissions, and they are also increasingly vulnerable to the impacts of climate change. That’s why when we talk about climate change, we have to talk about food systems, and vice versa,” says Maria T. Zuber, MIT’s vice president for research. “J-WAFS is central to MIT’s efforts to address the interlocking challenges of climate, water, and food. This new grant program aims to catalyze innovative projects that will have real and meaningful impacts on water and food. I congratulate Professor Shoulders and the rest of the research team on being the inaugural recipients of this grant.”

      Shoulders will work with Bryan Bryson, associate professor of biological engineering, as well as Bin Zhang, associate professor of chemistry, and Mary Gehring, a professor in the Department of Biology and the Whitehead Institute for Biomedical Research. Robert Wilson from the Shoulders lab will be coordinating the research effort. The team at MIT will work with outside collaborators Spencer Whitney, a professor from the Australian National University, and Ahmed Badran, an assistant professor at the Scripps Research Institute. A milestone-based collaboration will also take place with Stephen Long, a professor from the University of Illinois at Urbana-Champaign. The group consists of experts in continuous directed evolution, machine learning, molecular dynamics simulations, translational plant biochemistry, and field trials.

      “This project seeks to fundamentally improve the RuBisCO enzyme that plants use to convert carbon dioxide into the energy-rich molecules that constitute our food,” says J-WAFS Director John H. Lienhard V. “This difficult problem is a true grand challenge, calling for extensive resources. With J-WAFS’ support, this long-sought goal may finally be achieved through MIT’s leading-edge research,” he adds.

      RuBisCO: No, it’s not a new breakfast cereal; it just might be the key to an agricultural revolution

      A growing global population, the effects of climate change, and social and political conflicts like the war in Ukraine are all threatening food supplies, particularly grain crops. Current projections estimate that crop production must increase by at least 50 percent over the next 30 years to meet food demands. One key barrier to increased crop yields is a photosynthetic enzyme called Ribulose-1,5-Bisphosphate Carboxylase/Oxygenase (RuBisCO). During photosynthesis, crops use energy gathered from light to draw carbon dioxide (CO2) from the atmosphere and transform it into sugars and cellulose for growth, a process known as carbon fixation. RuBisCO is essential for capturing the CO2 from the air to initiate conversion of CO2 into energy-rich molecules like glucose. This reaction occurs during the second stage of photosynthesis, also known as the Calvin cycle. Without RuBisCO, the chemical reactions that account for virtually all carbon acquisition in life could not occur.

      Unfortunately, RuBisCO has biochemical shortcomings. Notably, the enzyme acts slowly. Many other enzymes can process a thousand molecules per second, but RuBisCO in chloroplasts fixes less than six carbon dioxide molecules per second, often limiting the rate of plant photosynthesis. Another problem is that oxygen (O2) molecules and carbon dioxide molecules are relatively similar in shape and chemical properties, and RuBisCO is unable to fully discriminate between the two. The inadvertent fixation of oxygen by RuBisCO leads to energy and carbon loss. What’s more, at higher temperatures RuBisCO reacts even more frequently with oxygen, which will contribute to decreased photosynthetic efficiency in many staple crops as our climate warms.

      The scientific consensus is that genetic engineering and synthetic biology approaches could revolutionize photosynthesis and offer protection against crop losses. To date, crop RuBisCO engineering has been impaired by technological obstacles that have limited any success in significantly enhancing crop production. Excitingly, genetic engineering and synthetic biology tools are now at a point where they can be applied and tested with the aim of creating crops with new or improved biological pathways for producing more food for the growing population.

      An epic plan for fighting food insecurity

      The 2023 J-WAFS Grand Challenge project will use state-of-the-art, transformative protein engineering techniques drawn from biomedicine to improve the biochemistry of photosynthesis, specifically focusing on RuBisCO. Shoulders and his team are planning to build what they call the Enhanced Photosynthesis in Crops (EPiC) platform. The project will evolve and design better crop RuBisCO in the laboratory, followed by validation of the improved enzymes in plants, ultimately resulting in the deployment of enhanced RuBisCO in field trials to evaluate the impact on crop yield. 

      Several recent developments make high-throughput engineering of crop RuBisCO possible. RuBisCO requires a complex chaperone network for proper assembly and function in plants. Chaperones are like helpers that guide proteins during their maturation process, shielding them from aggregation while coordinating their correct assembly. Wilson and his collaborators previously unlocked the ability to recombinantly produce plant RuBisCO outside of plant chloroplasts by reconstructing this chaperone network in Escherichia coli (E. coli). Whitney has now established that the RuBisCO enzymes from a range of agriculturally relevant crops, including potato, carrot, strawberry, and tobacco, can also be expressed using this technology. Whitney and Wilson have further developed a range of RuBisCO-dependent E. coli screens that can identify improved RuBisCO from complex gene libraries. Moreover, Shoulders and his lab have developed sophisticated in vivo mutagenesis technologies that enable efficient continuous directed evolution campaigns. Continuous directed evolution refers to a protein engineering process that can accelerate the steps of natural evolution simultaneously in an uninterrupted cycle in the lab, allowing for rapid testing of protein sequences. While Shoulders and Badran both have prior experience with cutting-edge directed evolution platforms, this will be the first time directed evolution is applied to RuBisCO from plants.

      Artificial intelligence is changing the way enzyme engineering is undertaken by researchers. Principal investigators Zhang and Bryson will leverage modern computational methods to simulate the dynamics of RuBisCO structure and explore its evolutionary landscape. Specifically, Zhang will use molecular dynamics simulations to simulate and monitor the conformational dynamics of the atoms in a protein and its programmed environment over time. This approach will help the team evaluate the effect of mutations and new chemical functionalities on the properties of RuBisCO. Bryson will employ artificial intelligence and machine learning to search the RuBisCO activity landscape for optimal sequences. The computational and biological arms of the EPiC platform will work together to both validate and inform each other’s approaches to accelerate the overall engineering effort.

      Shoulders and the group will deploy their designed enzymes in tobacco plants to evaluate their effects on growth and yield relative to natural RuBisCO. Gehring, a plant biologist, will assist with screening improved RuBisCO variants using the tobacco variety Nicotiana benthamianaI, where transient expression can be deployed. Transient expression is a speedy approach to test whether novel engineered RuBisCO variants can be correctly synthesized in leaf chloroplasts. Variants that pass this quality-control checkpoint at MIT will be passed to the Whitney Lab at the Australian National University for stable transformation into Nicotiana tabacum (tobacco), enabling robust measurements of photosynthetic improvement. In a final step, Professor Long at the University of Illinois at Urbana-Champaign will perform field trials of the most promising variants.

      Even small improvements could have a big impact

      A common criticism of efforts to improve RuBisCO is that natural evolution has not already identified a better enzyme, possibly implying that none will be found. Traditional views have speculated a catalytic trade-off between RuBisCO’s specificity factor for CO2 / O2 versus its CO2 fixation efficiency, leading to the belief that specificity factor improvements might be offset by even slower carbon fixation or vice versa. This trade-off has been suggested to explain why natural evolution has been slow to achieve a better RuBisCO. But Shoulders and the team are convinced that the EPiC platform can unlock significant overall improvements to plant RuBisCO. This view is supported by the fact that Wilson and Whitney have previously used directed evolution to improve CO2 fixation efficiency by 50 percent in RuBisCO from cyanobacteria (the ancient progenitors of plant chloroplasts) while simultaneously increasing the specificity factor. 

      The EPiC researchers anticipate that their initial variants could yield 20 percent increases in RuBisCO’s specificity factor without impairing other aspects of catalysis. More sophisticated variants could lift RuBisCO out of its evolutionary trap and display attributes not currently observed in nature. “If we achieve anywhere close to such an improvement and it translates to crops, the results could help transform agriculture,” Shoulders says. “If our accomplishments are more modest, it will still recruit massive new investments to this essential field.”

      Successful engineering of RuBisCO would be a scientific feat of its own and ignite renewed enthusiasm for improving plant CO2 fixation. Combined with other advances in photosynthetic engineering, such as improved light usage, a new green revolution in agriculture could be achieved. Long-term impacts of the technology’s success will be measured in improvements to crop yield and grain availability, as well as resilience against yield losses under higher field temperatures. Moreover, improved land productivity together with policy initiatives would assist in reducing the environmental footprint of agriculture. With more “crop per drop,” reductions in water consumption from agriculture would be a major boost to sustainable farming practices.

      “Our collaborative team of biochemists and synthetic biologists, computational biologists, and chemists is deeply integrated with plant biologists and field trial experts, yielding a robust feedback loop for enzyme engineering,” Shoulders adds. “Together, this team will be able to make a concerted effort using the most modern, state-of-the-art techniques to engineer crop RuBisCO with an eye to helping make meaningful gains in securing a stable crop supply, hopefully with accompanying improvements in both food and water security.” More

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      Study: Carbon-neutral pavements are possible by 2050, but rapid policy and industry action are needed

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      Almost 2.8 million lane-miles, or about 4.6 million lane-kilometers, of the United States are paved.

      Roads and streets form the backbone of our built environment. They take us to work or school, take goods to their destinations, and much more.

      However, a new study by MIT Concrete Sustainability Hub (CSHub) researchers shows that the annual greenhouse gas (GHG) emissions of all construction materials used in the U.S. pavement network are 11.9 to 13.3 megatons. This is equivalent to the emissions of a gasoline-powered passenger vehicle driving about 30 billion miles in a year.

      As roads are built, repaved, and expanded, new approaches and thoughtful material choices are necessary to dampen their carbon footprint. 

      The CSHub researchers found that, by 2050, mixtures for pavements can be made carbon-neutral if industry and governmental actors help to apply a range of solutions — like carbon capture — to reduce, avoid, and neutralize embodied impacts. (A neutralization solution is any compensation mechanism in the value chain of a product that permanently removes the global warming impact of the processes after avoiding and reducing the emissions.) Furthermore, nearly half of pavement-related greenhouse gas (GHG) savings can be achieved in the short term with a negative or nearly net-zero cost.

      The research team, led by Hessam AzariJafari, MIT CSHub’s deputy director, closed gaps in our understanding of the impacts of pavements decisions by developing a dynamic model quantifying the embodied impact of future pavements materials demand for the U.S. road network. 

      The team first split the U.S. road network into 10-mile (about 16 kilometer) segments, forecasting the condition and performance of each. They then developed a pavement management system model to create benchmarks helping to understand the current level of emissions and the efficacy of different decarbonization strategies. 

      This model considered factors such as annual traffic volume and surface conditions, budget constraints, regional variation in pavement treatment choices, and pavement deterioration. The researchers also used a life-cycle assessment to calculate annual state-level emissions from acquiring pavement construction materials, considering future energy supply and materials procurement.

      The team considered three scenarios for the U.S. pavement network: A business-as-usual scenario in which technology remains static, a projected improvement scenario aligned with stated industry and national goals, and an ambitious improvement scenario that intensifies or accelerates projected strategies to achieve carbon neutrality. 

      If no steps are taken to decarbonize pavement mixtures, the team projected that GHG emissions of construction materials used in the U.S. pavement network would increase by 19.5 percent by 2050. Under the projected scenario, there was an estimated 38 percent embodied impact reduction for concrete and 14 percent embodied impact reduction for asphalt by 2050.

      The keys to making the pavement network carbon neutral by 2050 lie in multiple places. Fully renewable energy sources should be used for pavement materials production, transportation, and other processes. The federal government must contribute to the development of these low-carbon energy sources and carbon capture technologies, as it would be nearly impossible to achieve carbon neutrality for pavements without them. 

      Additionally, increasing pavements’ recycled content and improving their design and production efficiency can lower GHG emissions to an extent. Still, neutralization is needed to achieve carbon neutrality.

      Making the right pavement construction and repair choices would also contribute to the carbon neutrality of the network. For instance, concrete pavements can offer GHG savings across the whole life cycle as they are stiffer and stay smoother for longer, meaning they require less maintenance and have a lesser impact on the fuel efficiency of vehicles. 

      Concrete pavements have other use-phase benefits including a cooling effect through an intrinsically high albedo, meaning they reflect more sunlight than regular pavements. Therefore, they can help combat extreme heat and positively affect the earth’s energy balance through positive radiative forcing, making albedo a potential neutralization mechanism.

      At the same time, a mix of fixes, including using concrete and asphalt in different contexts and proportions, could produce significant GHG savings for the pavement network; decision-makers must consider scenarios on a case-by-case basis to identify optimal solutions. 

      In addition, it may appear as though the GHG emissions of materials used in local roads are dwarfed by the emissions of interstate highway materials. However, the study found that the two road types have a similar impact. In fact, all road types contribute heavily to the total GHG emissions of pavement materials in general. Therefore, stakeholders at the federal, state, and local levels must be involved if our roads are to become carbon neutral. 

      The path to pavement network carbon-neutrality is, therefore, somewhat of a winding road. It demands regionally specific policies and widespread investment to help implement decarbonization solutions, just as renewable energy initiatives have been supported. Providing subsidies and covering the costs of premiums, too, are vital to avoid shifts in the market that would derail environmental savings.

      When planning for these shifts, we must recall that pavements have impacts not just in their production, but across their entire life cycle. As pavements are used, maintained, and eventually decommissioned, they have significant impacts on the surrounding environment.

      If we are to meet climate goals such as the Paris Agreement, which demands that we reach carbon-neutrality by 2050 to avoid the worst impacts of climate change, we — as well as industry and governmental stakeholders — must come together to take a hard look at the roads we use every day and work to reduce their life cycle emissions. 

      The study was published in the International Journal of Life Cycle Assessment. In addition to AzariJafari, the authors include Fengdi Guo of the MIT Department of Civil and Environmental Engineering; Jeremy Gregory, executive director of the MIT Climate and Sustainability Consortium; and Randolph Kirchain, director of the MIT CSHub. More