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      Forging climate connections across the Institute

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      Climate change is the ultimate cross-cutting issue: Not limited to any one discipline, it ranges across science, technology, policy, culture, human behavior, and well beyond. The response to it likewise requires an all-of-MIT effort.

      Now, to strengthen such an effort, a new grant program spearheaded by the Climate Nucleus, the faculty committee charged with the oversight and implementation of Fast Forward: MIT’s Climate Action Plan for the Decade, aims to build up MIT’s climate leadership capacity while also supporting innovative scholarship on diverse climate-related topics and forging new connections across the Institute.

      Called the Fast Forward Faculty Fund (F^4 for short), the program has named its first cohort of six faculty members after issuing its inaugural call for proposals in April 2023. The cohort will come together throughout the year for climate leadership development programming and networking. The program provides financial support for graduate students who will work with the faculty members on the projects — the students will also participate in leadership-building activities — as well as $50,000 in flexible, discretionary funding to be used to support related activities. 

      “Climate change is a crisis that truly touches every single person on the planet,” says Noelle Selin, co-chair of the nucleus and interim director of the Institute for Data, Systems, and Society. “It’s therefore essential that we build capacity for every member of the MIT community to make sense of the problem and help address it. Through the Fast Forward Faculty Fund, our aim is to have a cohort of climate ambassadors who can embed climate everywhere at the Institute.”

      F^4 supports both faculty who would like to begin doing climate-related work, as well as faculty members who are interested in deepening their work on climate. The program has the core goal of developing cohorts of F^4 faculty and graduate students who, in addition to conducting their own research, will become climate leaders at MIT, proactively looking for ways to forge new climate connections across schools, departments, and disciplines.

      One of the projects, “Climate Crisis and Real Estate: Science-based Mitigation and Adaptation Strategies,” led by Professor Siqi Zheng of the MIT Center for Real Estate in collaboration with colleagues from the MIT Sloan School of Management, focuses on the roughly 40 percent of carbon dioxide emissions that come from the buildings and real estate sector. Zheng notes that this sector has been slow to respond to climate change, but says that is starting to change, thanks in part to the rising awareness of climate risks and new local regulations aimed at reducing emissions from buildings.

      Using a data-driven approach, the project seeks to understand the efficient and equitable market incentives, technology solutions, and public policies that are most effective at transforming the real estate industry. Johnattan Ontiveros, a graduate student in the Technology and Policy Program, is working with Zheng on the project.

      “We were thrilled at the incredible response we received from the MIT faculty to our call for proposals, which speaks volumes about the depth and breadth of interest in climate at MIT,” says Anne White, nucleus co-chair and vice provost and associate vice president for research. “This program makes good on key commitments of the Fast Forward plan, supporting cutting-edge new work by faculty and graduate students while helping to deepen the bench of climate leaders at MIT.”

      During the 2023-24 academic year, the F^4 faculty and graduate student cohorts will come together to discuss their projects, explore opportunities for collaboration, participate in climate leadership development, and think proactively about how to deepen interdisciplinary connections among MIT community members interested in climate change.

      The six inaugural F^4 awardees are:

      Professor Tristan Brown, History Section: Humanistic Approaches to the Climate Crisis  

      With this project, Brown aims to create a new community of practice around narrative-centric approaches to environmental and climate issues. Part of a broader humanities initiative at MIT, it brings together a global working group of interdisciplinary scholars, including Serguei Saavedra (Department of Civil and Environmental Engineering) and Or Porath (Tel Aviv University; Religion), collectively focused on examining the historical and present links between sacred places and biodiversity for the purposes of helping governments and nongovernmental organizations formulate better sustainability goals. Boyd Ruamcharoen, a PhD student in the History, Anthropology, and Science, Technology, and Society (HASTS) program, will work with Brown on this project.

      Professor Kerri Cahoy, departments of Aeronautics and Astronautics and Earth, Atmospheric, and Planetary Sciences (AeroAstro): Onboard Autonomous AI-driven Satellite Sensor Fusion for Coastal Region Monitoring

      The motivation for this project is the need for much better data collection from satellites, where technology can be “20 years behind,” says Cahoy. As part of this project, Cahoy will pursue research in the area of autonomous artificial intelligence-enabled rapid sensor fusion (which combines data from different sensors, such as radar and cameras) onboard satellites to improve understanding of the impacts of climate change, specifically sea-level rise and hurricanes and flooding in coastal regions. Graduate students Madeline Anderson, a PhD student in electrical engineering and computer science (EECS), and Mary Dahl, a PhD student in AeroAstro, will work with Cahoy on this project.

      Professor Priya Donti, Department of Electrical Engineering and Computer Science: Robust Reinforcement Learning for High-Renewables Power Grids 

      With renewables like wind and solar making up a growing share of electricity generation on power grids, Donti’s project focuses on improving control methods for these distributed sources of electricity. The research will aim to create a realistic representation of the characteristics of power grid operations, and eventually inform scalable operational improvements in power systems. It will “give power systems operators faith that, OK, this conceptually is good, but it also actually works on this grid,” says Donti. PhD candidate Ana Rivera from EECS is the F^4 graduate student on the project.

      Professor Jason Jackson, Department of Urban Studies and Planning (DUSP): Political Economy of the Climate Crisis: Institutions, Power and Global Governance

      This project takes a political economy approach to the climate crisis, offering a distinct lens to examine, first, the political governance challenge of mobilizing climate action and designing new institutional mechanisms to address the global and intergenerational distributional aspects of climate change; second, the economic challenge of devising new institutional approaches to equitably finance climate action; and third, the cultural challenge — and opportunity — of empowering an adaptive socio-cultural ecology through traditional knowledge and local-level social networks to achieve environmental resilience. Graduate students Chen Chu and Mrinalini Penumaka, both PhD students in DUSP, are working with Jackson on the project.

      Professor Haruko Wainwright, departments of Nuclear Science and Engineering (NSE) and Civil and Environmental Engineering: Low-cost Environmental Monitoring Network Technologies in Rural Communities for Addressing Climate Justice 

      This project will establish a community-based climate and environmental monitoring network in addition to a data visualization and analysis infrastructure in rural marginalized communities to better understand and address climate justice issues. The project team plans to work with rural communities in Alaska to install low-cost air and water quality, weather, and soil sensors. Graduate students Kay Whiteaker, an MS candidate in NSE, and Amandeep Singh, and MS candidate in System Design and Management at Sloan, are working with Wainwright on the project, as is David McGee, professor in earth, atmospheric, and planetary sciences.

      Professor Siqi Zheng, MIT Center for Real Estate and DUSP: Climate Crisis and Real Estate: Science-based Mitigation and Adaptation Strategies 

      See the text above for the details on this project. More

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      Improving US air quality, equitably

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      Decarbonization of national economies will be key to achieving global net-zero emissions by 2050, a major stepping stone to the Paris Agreement’s long-term goal of keeping global warming well below 2 degrees Celsius (and ideally 1.5 C), and thereby averting the worst consequences of climate change. Toward that end, the United States has pledged to reduce its greenhouse gas emissions by 50-52 percent from 2005 levels by 2030, backed by its implementation of the 2022 Inflation Reduction Act. This strategy is consistent with a 50-percent reduction in carbon dioxide (CO2) by the end of the decade.

      If U.S. federal carbon policy is successful, the nation’s overall air quality will also improve. Cutting CO2 emissions reduces atmospheric concentrations of air pollutants that lead to the formation of fine particulate matter (PM2.5), which causes more than 200,000 premature deaths in the United States each year. But an average nationwide improvement in air quality will not be felt equally; air pollution exposure disproportionately harms people of color and lower-income populations.

      How effective are current federal decarbonization policies in reducing U.S. racial and economic disparities in PM2.5 exposure, and what changes will be needed to improve their performance? To answer that question, researchers at MIT and Stanford University recently evaluated a range of policies which, like current U.S. federal carbon policies, reduce economy-wide CO2 emissions by 40-60 percent from 2005 levels by 2030. Their findings appear in an open-access article in the journal Nature Communications.

      First, they show that a carbon-pricing policy, while effective in reducing PM2.5 exposure for all racial/ethnic groups, does not significantly mitigate relative disparities in exposure. On average, the white population undergoes far less exposure than Black, Hispanic, and Asian populations. This policy does little to reduce exposure disparities because the CO2 emissions reductions that it achieves primarily occur in the coal-fired electricity sector. Other sectors, such as industry and heavy-duty diesel transportation, contribute far more PM2.5-related emissions.

      The researchers then examine thousands of different reduction options through an optimization approach to identify whether any possible combination of carbon dioxide reductions in the range of 40-60 percent can mitigate disparities. They find that that no policy scenario aligned with current U.S. carbon dioxide emissions targets is likely to significantly reduce current PM2.5 exposure disparities.

      “Policies that address only about 50 percent of CO2 emissions leave many polluting sources in place, and those that prioritize reductions for minorities tend to benefit the entire population,” says Noelle Selin, supervising author of the study and a professor at MIT’s Institute for Data, Systems and Society and Department of Earth, Atmospheric and Planetary Sciences. “This means that a large range of policies that reduce CO2 can improve air quality overall, but can’t address long-standing inequities in air pollution exposure.”

      So if climate policy alone cannot adequately achieve equitable air quality results, what viable options remain? The researchers suggest that more ambitious carbon policies could narrow racial and economic PM2.5 exposure disparities in the long term, but not within the next decade. To make a near-term difference, they recommend interventions designed to reduce PM2.5 emissions resulting from non-CO2 sources, ideally at the economic sector or community level.

      “Achieving improved PM2.5 exposure for populations that are disproportionately exposed across the United States will require thinking that goes beyond current CO2 policy strategies, most likely involving large-scale structural changes,” says Selin. “This could involve changes in local and regional transportation and housing planning, together with accelerated efforts towards decarbonization.” More

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      New clean air and water labs to bring together researchers, policymakers to find climate solutions

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      MIT’s Abdul Latif Jameel Poverty Action Lab (J-PAL) is launching the Clean Air and Water Labs, with support from Community Jameel, to generate evidence-based solutions aimed at increasing access to clean air and water.

      Led by J-PAL’s Africa, Middle East and North Africa (MENA), and South Asia regional offices, the labs will partner with government agencies to bring together researchers and policymakers in areas where impactful clean air and water solutions are most urgently needed.

      Together, the labs aim to improve clean air and water access by informing the scaling of evidence-based policies and decisions of city, state, and national governments that serve nearly 260 million people combined.

      The Clean Air and Water Labs expand the work of J-PAL’s King Climate Action Initiative, building on the foundational support of King Philanthropies, which significantly expanded J-PAL’s work at the nexus of climate change and poverty alleviation worldwide. 

      Air pollution, water scarcity and the need for evidence 

      Africa, MENA, and South Asia are on the front lines of global air and water crises. 

      “There is no time to waste investing in solutions that do not achieve their desired effects,” says Iqbal Dhaliwal, global executive director of J-PAL. “By co-generating rigorous real-world evidence with researchers, policymakers can have the information they need to dedicate resources to scaling up solutions that have been shown to be effective.”

      In India, about 75 percent of households did not have drinking water on premises in 2018. In MENA, nearly 90 percent of children live in areas facing high or extreme water stress. Across Africa, almost 400 million people lack access to safe drinking water. 

      Simultaneously, air pollution is one of the greatest threats to human health globally. In India, extraordinary levels of air pollution are shortening the average life expectancy by five years. In Africa, rising indoor and ambient air pollution contributed to 1.1 million premature deaths in 2019. 

      There is increasing urgency to find high-impact and cost-effective solutions to the worsening threats to human health and resources caused by climate change. However, data and evidence on potential solutions are limited.

      Fostering collaboration to generate policy-relevant evidence 

      The Clean Air and Water Labs will foster deep collaboration between government stakeholders, J-PAL regional offices, and researchers in the J-PAL network. 

      Through the labs, J-PAL will work with policymakers to:

      co-diagnose the most pressing air and water challenges and opportunities for policy innovation;
      expand policymakers’ access to and use of high-quality air and water data;
      co-design potential solutions informed by existing evidence;
      co-generate evidence on promising solutions through rigorous evaluation, leveraging existing and new data sources; and
      support scaling of air and water policies and programs that are found to be effective through evaluation. 
      A research and scaling fund for each lab will prioritize resources for co-generated pilot studies, randomized evaluations, and scaling projects. 

      The labs will also collaborate with C40 Cities, a global network of mayors of the world’s leading cities that are united in action to confront the climate crisis, to share policy-relevant evidence and identify opportunities for potential new connections and research opportunities within India and across Africa.

      This model aims to strengthen the use of evidence in decision-making to ensure solutions are highly effective and to guide research to answer policymakers’ most urgent questions. J-PAL Africa, MENA, and South Asia’s strong on-the-ground presence will further bridge research and policy work by anchoring activities within local contexts. 

      “Communities across the world continue to face challenges in accessing clean air and water, a threat to human safety that has only been exacerbated by the climate crisis, along with rising temperatures and other hazards,” says George Richards, director of Community Jameel. “Through our collaboration with J-PAL and C40 in creating climate policy labs embedded in city, state, and national governments in Africa and South Asia, we are committed to innovative and science-based approaches that can help hundreds of millions of people enjoy healthier lives.”

      J-PAL Africa, MENA, and South Asia will formally launch Clean Air and Water Labs with government partners over the coming months. J-PAL is housed in the MIT Department of Economics, within the School of Humanities, Arts, and Social Sciences. More

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      MIT at the 2023 Venice Biennale

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      The Venice Architecture Biennale, the world’s largest and most visited exhibition focusing on architecture, is once again featuring work by many MIT faculty, students, and alumni. On view through Nov. 26, the 2023 biennale, curated by Ghanaian-Scottish architect, academic, and novelist Lesley Lokko, is showcasing projects responding to the theme of “The Laboratory of Change.”

      Architecture and Planning and curator of the previous Venice Biennale. “Our students, faculty, and alumni have responded to the speculative theme with innovative projects at a range of scales and in varied media.”

      Below are descriptions of MIT-related projects and activities.

      MIT faculty participants

      Xavi Laida Aguirre, assistant professor of architecture

      Project: Everlasting Plastics

      Project description: SPACES, a nonprofit alternative art organization based in Cleveland, Ohio, and the U.S. Department of State’s Bureau of Educational and Cultural Affairs are behind the U.S. Pavilion’s exhibition at this year’s biennale. The theme, Everlasting Plastics, provides a platform for artists and designers to engage audiences in reframing the overabundance of plastic detritus in our waterways, landfills, and streets as a rich resource. Aguirre’s installation covers two rooms and holds a series of partial scenographies examining indoor proofing materials such as coatings, rubbers, gaskets, bent aluminum, silicone, foam, cement board, and beveled edges.

      Yolande Daniels, associate professor of architecture

      Project: The BLACK City Astrolabe: A Constellation of African Diasporic Women

      Project description: From the multiple displacements of race and gender, enter “The BLACK City Astrolabe,” a space-time field comprised of a 3D map and a 24-hour cycle of narratives that reorder the forces of subjugation, devaluation, and displacement through the spaces and events of African diasporic women. The diaspora map traces the flows of descendants of Africa (whether voluntary or forced) atop the visible tension between the mathematical regularity of meridians of longitude and the biases of international date lines.

      In this moment we are running out of time. The meridians and timeline decades are indexed to an infinite conical projection metered in decades. It structures both the diaspora map and timeline and serves as a threshold to project future structures and events. “The BLACK City Astrolabe” is a vehicle to proactively contemplate things that have happened, that are happening, and that will happen. Yesterday, a “Black” woman went to the future, and here she is.

      Mark Jarzombek, professor of architecture

      Project: Kishkindha NY

      Project description: “Kishkindha NY (Office of (Un)Certainty Research: Mark Jarzombek and Vikramaditya Parakash)” is inspired by an imagined forest-city as described in the ancient Indian text the Ramayana. It comes into being not through the limitations of human agency, but through a multi-species creature that destroys and rebuilds. It is exhibited as a video (Space, Time, Existence) and as a special dance performance.

      Ana Miljački, professor of architecture

      Team: Ana Miljački, professor of architecture and director of Critical Broadcasting Lab, MIT; Ous Abou Ras, MArch candidate; Julian Geltman, MArch; Recording and Design, faculty of Dramatic Arts, Belgrade; Calvin Zhong, MArch candidate. Sound design and production: Pavle Dinulović, assistant professor, Department of Sound Recording and Design, University of Arts in Belgrade.

      Collaborators: Melika Konjičanin, researcher, faculty of architecture, Sarajevo; Ana Martina Bakić, assistant professor, head of department of drawing and visual design, faculty of architecture, Zagreb; Jelica Jovanović, Grupa Arhitekata, Belgrade; Andrew Lawler, Belgrade; Sandro Đukić, CCN Images, Zagreb; Other Tomorrows, Boston.

      Project: The Pilgrimage/Pionirsko hodočašće

      Project description:  The artifacts that constitute Yugoslavia’s socialist architectural heritage, and especially those instrumental in the ideological wiring of several postwar generations for anti-fascism and inclusive living, have been subject to many forms of local and global political investment in forgetting their meaning, as well as to vandalism. The “Pilgrimage” synthesizes “memories” from Yugoslavian childhood visits to myriad postwar anti-fascist memorial monuments and offers them in a shifting and spatial multi-channel video presentation accompanied by a nonlinear documentary soundscape, presenting thus anti-fascism and unity as political and activist positions available (and necessary) today, for the sake of the future. Supported by: MIT Center for Art, Science, and Technology (CAST) Mellon Faculty Grant.

      Adèle Naudé Santos, professor of architecture, planning, and urban design; and Mohamad Nahleh, lecturer in architecture and urbanism; in collaboration with the Beirut Urban Lab at the American University of Beirut

      MIT research team: Ghida El Bsat, Joude Mabsout, Sarin Gacia Vosgerichian, Lasse Rau

      Project: Housing as Infrastructure

      Project description: On Aug. 4, 2020, an estimated 2,750 tons of ammonium nitrate stored at the Port of Beirut exploded, resulting in the deaths of more than 200 people and the devastation of port-adjacent neighborhoods. With over 200,000 housing units in disrepair, exploitative real estate ventures, and the lack of equitable housing policies, we viewed the port blast as a potential escalation of the mechanisms that have produced the ongoing affordable housing crisis across the city. 

      The Dar Group requested proposals to rethink the affected part of the city, through MIT’s Norman B. Leventhal Center for Advanced Urbanism. To best ground our design proposal, we invited the Beirut Urban Lab at the American University of Beirut to join us. We chose to work on the heavily impacted low-rise and high-density neighborhood of Mar Mikhael. Our resultant urban strategy anchors housing within a corridor of shared open spaces. Housing is inscribed within this network and sustained through an adaptive system defined by energy-efficiency and climate responsiveness. Cross-ventilation sweeps through the project on all sides, with solar panel lined roofs integrated to always provide adequate levels of electricity for habitation. These strategies are coupled with an array of modular units designed to echo the neighborhood’s intimate quality — all accessible through shared ramps and staircases. Within this context, housing itself becomes the infrastructure, guiding circulation, managing slopes, integrating green spaces, and providing solar energy across the community. 

      Rafi Segal, associate professor of architecture and urbanism, director of the Future Urban Collectives Lab, director of the SMArchS program; and Susannah Drake.

      Contributors: Olivia Serra, William Minghao Du

      Project:  From Redlining to Blue Zoning: Equity and Environmental Risk, Miami 2100 (2021)

      Project description: As part of Susannah Drake and Rafi Segal’s ongoing work on “Coastal Urbanism,” this project examines the legacy of racial segregation in South Florida and the existential threat that climate change poses to communities in Miami. Through models of coops and community-owned urban blocks, this project seeks to empower formerly disenfranchised communities with new methods of equity capture, allowing residents whose parents and grandparents suffered from racial discrimination to build wealth and benefit from increased real estate value and development.

      Nomeda Urbonas, Art, Culture, and Technology research affiliate; and Gediminas Urbonas, ACT associate professor

      Project: The Swamp Observatory

      Project description: “The Swamp Observatory” augmented reality app is a result of two-year collaboration with a school in Gotland Island in the Baltic Sea, arguably the most polluted sea in the world. Developed as a conceptual playground and a digital tool to augment reality with imaginaries for new climate commons, the app offers new perspective to the planning process, suggesting eco-monsters as emergent ecology for the planned stormwater ponds in the new sustainable city. 

      Sarah Williams, associate professor, technology and urban planning

      Team members: listed here.

      Project: DISTANCE UNKNOWN: RISKS AND OPPORTUNITIES OF MIGRATION IN THE AMERICAS 

      Project description: On view are visualizations made by the MIT Civic Data Design Lab and the United Nations World Food Program that helped to shape U.S. migration policy. The exhibition is built from a unique dataset collected from 4,998 households surveyed in El Salvador, Guatemala, and Honduras. A tapestry woven out of money and constructed by the hands of Central America migrants illustrates that migrants spent $2.2 billion to migrate from Central America in 2021.

      MIT student curators

      Carmelo Ignaccolo, PhD candidate, Department of Urban Studies and Planning (DUSP)

      Curator: Carmelo Ignaccolo; advisor: Sarah Williams; researchers: Emily Levenson (DUSP), Melody Phu (MIT), Leo Saenger (Harvard University), Yuke Zheng (Harvard); digital animation designer: Ting Zhang

      Exhibition Design Assistant: Dila Ozberkman (architecture and DUSP)

      Project: The Consumed City 

      Project description: “The Consumed City” narrates a spatial investigation of “overtourism” in the historic city of Venice by harnessing granular data on lodging, dining, and shopping. The exhibition presents two large maps and digital animations to showcase the complexity of urban tourism and to reveal the spatial interplay between urban tourism and urban features, such as landmarks, bridges, and street patterns. By leveraging by-product geospatial datasets and advancing visualization techniques, “The Consumed City” acts as a prototype to call for novel policymaking tools in cities “consumed” by “overtourism.”

      MIT-affiliated auxiliary events

      Rania Ghosn, associate professor of architecture and urbanism, El Hadi Jazairy, Anhong Li, and Emma Jurczynski, with initial contributions from Marco Nieto and Zhifei Xu. Graphic design: Office of Luke Bulman.

      Project: Climate Inheritance

      Project description: “Climate Inheritance” is a speculative design research publication that reckons with the complexity of “heritage” and “world” in the Anthropocene Epoch. The impacts of climate change on heritage sites — from Venice flooding to extinction in the Galapagos Islands — have garnered empathetic attention in a media landscape that has otherwise mostly failed to communicate the urgency of the climate crisis. In a strategic subversion of the media aura of heritage, the project casts World Heritage sites as narrative figures to visualize pervasive climate risks all while situating the present emergency within the wreckage of other ends of worlds, replete with the salvages of extractivism, racism, and settler colonialism.   

      Rebuilding Beirut: Using Data to Co-Design a New Future

      SA+P faculty, researchers, and students are participating in the sixth biennial architecture exhibition “Time Space Existence,” presented by the European Cultural Center. The exhibit showcases three collaborative research and design proposals that support the rebuilding efforts in Beirut following the catastrophic explosion at the Port of Beirut in August 2020.

      “Living Heritage Atlas” captures the significance and vulnerability of Beirut’s cultural heritage. 

      “City Scanner” tracks the environmental impacts of the explosion and the subsequent rebuilding efforts. “Community Streets” supports the redesign of streets and public space. 

      The work is supported by the Dar Group Urban Seed Grant Fund at MIT’s Norman B. Leventhal Center for Advanced Urbanism.

      Team members:Living Heritage AtlasCivic Data Design Lab and Future Heritage Lab at MITAssociate Professor Sarah Williams, co-principal investigator (PI)Associate Professor Azra Aksamija, co-PICity Scanner Senseable City Lab at MIT with the American University of Beirut and FAE Technology Professor Carlo Ratti, co-PIFábio Duarte, co-PISimone Mora, research and project leadCommunity Streets City Form Lab at MIT with the American University of BeirutAssociate Professor Andres Sevtsuk, co-PIProfessor Maya Abou-Zeid, co-PISchool of Architecture and Planning alumni participants   Rodrigo Escandón Cesarman SMArchS Design ’20 (co-curator, Mexican Pavilion)Felecia Davis PhD ’17 Design and Computation, SOFTLAB@PSU (Penn State University)Jaekyung Jung SM ’10, (with the team for the Korean pavilion)Vijay Rajkumar MArch ’22 (with the team for the Bahrain Pavilion)

      Other MIT alumni participants

      Basis with GKZ

      Team: Emily Mackevicius PhD ’18, brain and cognitive sciences, with Zenna Tavares, Kibwe Tavares, Gaika Tavares, and Eli Bingham

      Project description: The nonprofit research group works on rethinking AI as a “reasoning machine.” Their two goals are to develop advanced technological models and to make society able to tackle “intractable problems.” Their approach to technology is founded less on pattern elaboration than on the Bayes’ hypothesis, the ability of machines to work on abductive reasoning, which is the same used by the human mind. Two city-making projects model cities after interaction between experts and stakeholders, and representation is at the heart of the dialogue. More

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      To improve solar and other clean energy tech, look beyond hardware

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      To continue reducing the costs of solar energy and other clean energy technologies, scientists and engineers will likely need to focus, at least in part, on improving technology features that are not based on hardware, according to MIT researchers. They describe this finding and the mechanisms behind it today in Nature Energy.

      While the cost of installing a solar energy system has dropped by more than 99 percent since 1980, this new analysis shows that “soft technology” features, such as the codified permitting practices, supply chain management techniques, and system design processes that go into deploying a solar energy plant, contributed only 10 to 15 percent of total cost declines. Improvements to hardware features were responsible for the lion’s share.

      But because soft technology is increasingly dominating the total costs of installing solar energy systems, this trend threatens to slow future cost savings and hamper the global transition to clean energy, says the study’s senior author, Jessika Trancik, a professor in MIT’s Institute for Data, Systems, and Society (IDSS).

      Trancik’s co-authors include lead author Magdalena M. Klemun, a former IDSS graduate student and postdoc who is now an assistant professor at the Hong Kong University of Science and Technology; Goksin Kavlak, a former IDSS graduate student and postdoc who is now an associate at the Brattle Group; and James McNerney, a former IDSS postdoc and now senior research fellow at the Harvard Kennedy School.

      The team created a quantitative model to analyze the cost evolution of solar energy systems, which captures the contributions of both hardware technology features and soft technology features.

      The framework shows that soft technology hasn’t improved much over time — and that soft technology features contributed even less to overall cost declines than previously estimated.

      Their findings indicate that to reverse this trend and accelerate cost declines, engineers could look at making solar energy systems less reliant on soft technology to begin with, or they could tackle the problem directly by improving inefficient deployment processes.  

      “Really understanding where the efficiencies and inefficiencies are, and how to address those inefficiencies, is critical in supporting the clean energy transition. We are making huge investments of public dollars into this, and soft technology is going to be absolutely essential to making those funds count,” says Trancik.

      “However,” Klemun adds, “we haven’t been thinking about soft technology design as systematically as we have for hardware. That needs to change.”

      The hard truth about soft costs

      Researchers have observed that the so-called “soft costs” of building a solar power plant — the costs of designing and installing the plant — are becoming a much larger share of total costs. In fact, the share of soft costs now typically ranges from 35 to 64 percent.

      “We wanted to take a closer look at where these soft costs were coming from and why they weren’t coming down over time as quickly as the hardware costs,” Trancik says.

      In the past, scientists have modeled the change in solar energy costs by dividing total costs into additive components — hardware components and nonhardware components — and then tracking how these components changed over time.

      “But if you really want to understand where those rates of change are coming from, you need to go one level deeper to look at the technology features. Then things split out differently,” Trancik says.

      The researchers developed a quantitative approach that models the change in solar energy costs over time by assigning contributions to the individual technology features, including both hardware features and soft technology features.

      For instance, their framework would capture how much of the decline in system installation costs — a soft cost — is due to standardized practices of certified installers — a soft technology feature. It would also capture how that same soft cost is affected by increased photovoltaic module efficiency — a hardware technology feature.

      With this approach, the researchers saw that improvements in hardware had the greatest impacts on driving down soft costs in solar energy systems. For example, the efficiency of photovoltaic modules doubled between 1980 and 2017, reducing overall system costs by 17 percent. But about 40 percent of that overall decline could be attributed to reductions in soft costs tied to improved module efficiency.

      The framework shows that, while hardware technology features tend to improve many cost components, soft technology features affect only a few.

      “You can see this structural difference even before you collect data on how the technologies have changed over time. That’s why mapping out a technology’s network of cost dependencies is a useful first step to identify levers of change, for solar PV and for other technologies as well,” Klemun notes.  

      Static soft technology

      The researchers used their model to study several countries, since soft costs can vary widely around the world. For instance, solar energy soft costs in Germany are about 50 percent less than those in the U.S.

      The fact that hardware technology improvements are often shared globally led to dramatic declines in costs over the past few decades across locations, the analysis showed. Soft technology innovations typically aren’t shared across borders. Moreover, the team found that countries with better soft technology performance 20 years ago still have better performance today, while those with worse performance didn’t see much improvement.

      This country-by-country difference could be driven by regulation and permitting processes, cultural factors, or by market dynamics such as how firms interact with each other, Trancik says.

      “But not all soft technology variables are ones that you would want to change in a cost-reducing direction, like lower wages. So, there are other considerations, beyond just bringing the cost of the technology down, that we need to think about when interpreting these results,” she says.

      Their analysis points to two strategies for reducing soft costs. For one, scientists could focus on developing hardware improvements that make soft costs more dependent on hardware technology variables and less on soft technology variables, such as by creating simpler, more standardized equipment that could reduce on-site installation time.

      Or researchers could directly target soft technology features without changing hardware, perhaps by creating more efficient workflows for system installation or automated permitting platforms.

      “In practice, engineers will often pursue both approaches, but separating the two in a formal model makes it easier to target innovation efforts by leveraging specific relationships between technology characteristics and costs,” Klemun says.

      “Often, when we think about information processing, we are leaving out processes that still happen in a very low-tech way through people communicating with one another. But it is just as important to think about that as a technology as it is to design fancy software,” Trancik notes.

      In the future, she and her collaborators want to apply their quantitative model to study the soft costs related to other technologies, such as electrical vehicle charging and nuclear fission. They are also interested in better understanding the limits of soft technology improvement, and how one could design better soft technology from the outset.

      This research is funded by the U.S. Department of Energy Solar Energy Technologies Office. More

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      in Data Management & Statistics

      Embracing the future we need

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      When you picture MIT doctoral students taking small PhD courses together, you probably don’t imagine them going on class field trips. But it does happen, sometimes, and one of those trips changed Andy Sun’s career.

      Today, Sun is a faculty member at the MIT Sloan School of Management and a leading global expert on integrating renewable energy into the electric grid. Back in 2007, Sun was an operations research PhD candidate with a diversified academic background: He had studied electrical engineering, quantum computing, and analog computing but was still searching for a doctoral research subject involving energy. 

      One day, as part of a graduate energy class taught by visiting professor Ignacio J. Pérez Arriaga, the students visited the headquarters of ISO-New England, the organization that operates New England’s entire power grid and wholesale electricity market. Suddenly, it hit Sun. His understanding of engineering, used to design and optimize computing systems, could be applied to the grid as a whole, with all its connections, circuitry, and need for efficiency. 

      “The power grids in the U.S. continent are composed of two major interconnections, the Western Interconnection, the Eastern Interconnection, and one minor interconnection, the Texas grid,” Sun says. “Within each interconnection, the power grid is one big machine, essentially. It’s connected by tens of thousands of miles of transmission lines, thousands of generators, and consumers, and if anything is not synchronized, the system may collapse. It’s one of the most complicated engineering systems.”

      And just like that, Sun had a subject he was motivated to pursue. “That’s how I got into this field,” he says. “Taking a field trip.”Sun has barely looked back. He has published dozens of papers about optimizing the flow of intermittent renewable energy through the electricity grid, a major practical issue for grid operators, while also thinking broadly about the future form of the grid and the process of making almost all energy renewable. Sun, who in 2022 rejoined MIT as the Iberdrola-Avangrid Associate Professor in Electric Power Systems, and is also an associate professor of operations research, emphasizes the urgency of rapidly switching to renewables.

      “The decarbonization of our energy system is fundamental,” Sun says. “It will change a lot of things because it has to. We don’t have much time to get there. Two decades, three decades is the window in which we have to get a lot of things done. If you think about how much money will need to be invested, it’s not actually that much. We should embrace this future that we have to get to.”

      Successful operations

      Unexpected as it may have been, Sun’s journey toward being an electricity grid expert was informed by all the stages of his higher education. Sun grew up in China, and received his BA in electronic engineering from Tsinghua University in Beijing, in 2003. He then moved to MIT, joining the Media Lab as a graduate student. Sun intended to study quantum computing but instead began working on analog computer circuit design for Professor Neil Gershenfeld, another person whose worldview influenced Sun.  

      “He had this vision about how optimization is very important in things,” Sun says. “I had never heard of optimization before.” 

      To learn more about it, Sun started taking MIT courses in operations research. “I really enjoyed it, especially the nonlinear optimization course taught by Robert Freund in the Operations Research Center,” he recalls. 

      Sun enjoyed it so much that after a while, he joined MIT’s PhD program in operations research, thanks to the guidance of Freund. Later, he started working with MIT Sloan Professor Dimitri Bertsimas, a leading figure in the field. Still, Sun hadn’t quite nailed down what he wanted to focus on within operations research. Thinking of Sun’s engineering skills, Bertsimas suggested that Sun look for a research topic related to energy. 

      “He wasn’t an expert in energy at that time, but he knew that there are important problems there and encouraged me to go ahead and learn,” Sun says. 

      So it was that Sun found himself in ISO-New England headquarters one day in 2007, finally knowing what he wanted to study, and quickly finding opportunities to start learning from the organization’s experts on electricity markets. By 2011, Sun had finished his MIT PhD dissertation. Based in part on ISO-New England data, the thesis presented new modeling to more efficiently integrate renewable energy into the grid; built some new modeling tools grid operators could use; and developed a way to add fair short-term energy auctions to an efficient grid system.

      The core problem Sun deals with is that, unlike some other sources of electricity, renewables tend to be intermittent, generating power in an uneven pattern over time. That’s not an insurmountable problem for grid operators, but it does require some new approaches. Many of the papers Sun has written focus on precisely how to increasingly draw upon intermittent energy sources while ensuring that the grid’s current level of functionality remains intact. This is also the focus of his 2021 book, co-authored with Antonio J. Conejo, “Robust Optimiziation in Electric Energy Systems.”

      “A major theme of my research is how to achieve the integration of renewables and still operate the system reliably,” Sun says. “You have to keep the balance of supply and demand. This requires many time scales of operation from multidecade planning, to monthly or annual maintenance, to daily operations, down through second-by-second. I work on problems in all these timescales.”

      “I sit in the interface between power engineering and operations research,” Sun says. “I’m not a power engineer, but I sit in this boundary, and I keep the problems in optimization as my motivation.”

      Culture shift

      Sun’s presence on the MIT campus represents a homecoming of sorts. After receiving his doctorate from MIT, Sun spent a year as a postdoc at IBM’s Thomas J. Watson Research Center, then joined the faculty at Georgia Tech, where he remained for a decade. He returned to the Institute in January of 2022.

      “I’m just very excited about the opportunity of being back at MIT,” Sun says. “The MIT Energy Initiative is a such a vibrant place, where many people come together to work on energy. I sit in Sloan, but one very strong point of MIT is there are not many barriers, institutionally. I really look forward to working with colleagues from engineering, Sloan, everywhere, moving forward. We’re moving in the right direction, with a lot of people coming together to break the traditional academic boundaries.” 

      Still, Sun warns that some people may be underestimating the severity of the challenge ahead and the need to implement changes right now. The assets in power grids have long life time, lasting multiple decades. That means investment decisions made now could affect how much clean power is being used a generation from now. 

      “We’re talking about a short timeline, for changing something as huge as how a society fundamentally powers itself with energy,” Sun says. “A lot of that must come from the technology we have today. Renewables are becoming much better and cheaper, so their use has to go up.”

      And that means more people need to work on issues of how to deploy and integrate renewables into everyday life, in the electric grid, transportation, and more. Sun hopes people will increasingly recognize energy as a huge growth area for research and applied work. For instance, when MIT President Sally Kornbluth gave her inaugural address on May 1 this year, she emphasized tackling the climate crisis as her highest priority, something Sun noticed and applauded. 

      “I think the most important thing is the culture,” Sun says. “Bring climate up to the front, and create the platform to encourage people to come together and work on this issue.” More

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      in Data Management & Statistics

      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.

      Play video

      “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 Data Management & Statistics

      A new dataset of Arctic images will spur artificial intelligence research

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      As the U.S. Coast Guard (USCG) icebreaker Healy takes part in a voyage across the North Pole this summer, it is capturing images of the Arctic to further the study of this rapidly changing region. Lincoln Laboratory researchers installed a camera system aboard the Healy while at port in Seattle before it embarked on a three-month science mission on July 11. The resulting dataset, which will be one of the first of its kind, will be used to develop artificial intelligence tools that can analyze Arctic imagery.

      “This dataset not only can help mariners navigate more safely and operate more efficiently, but also help protect our nation by providing critical maritime domain awareness and an improved understanding of how AI analysis can be brought to bear in this challenging and unique environment,” says Jo Kurucar, a researcher in Lincoln Laboratory’s AI Software Architectures and Algorithms Group, which led this project.

      As the planet warms and sea ice melts, Arctic passages are opening up to more traffic, both to military vessels and ships conducting illegal fishing. These movements may pose national security challenges to the United States. The opening Arctic also leaves questions about how its climate, wildlife, and geography are changing.

      Today, very few imagery datasets of the Arctic exist to study these changes. Overhead images from satellites or aircraft can only provide limited information about the environment. An outward-looking camera attached to a ship can capture more details of the setting and different angles of objects, such as other ships, in the scene. These types of images can then be used to train AI computer-vision tools, which can help the USCG plan naval missions and automate analysis. According to Kurucar, USCG assets in the Arctic are spread thin and can benefit greatly from AI tools, which can act as a force multiplier.

      The Healy is the USCG’s largest and most technologically advanced icebreaker. Given its current mission, it was a fitting candidate to be equipped with a new sensor to gather this dataset. The laboratory research team collaborated with the USCG Research and Development Center to determine the sensor requirements. Together, they developed the Cold Region Imaging and Surveillance Platform (CRISP).

      “Lincoln Laboratory has an excellent relationship with the Coast Guard, especially with the Research and Development Center. Over a decade, we’ve established ties that enabled the deployment of the CRISP system,” says Amna Greaves, the CRISP project lead and an assistant leader in the AI Software Architectures and Algorithms Group. “We have strong ties not only because of the USCG veterans working at the laboratory and in our group, but also because our technology missions are complementary. Today it was deploying infrared sensing in the Arctic; tomorrow it could be operating quadruped robot dogs on a fast-response cutter.”

      The CRISP system comprises a long-wave infrared camera, manufactured by Teledyne FLIR (for forward-looking infrared), that is designed for harsh maritime environments. The camera can stabilize itself during rough seas and image in complete darkness, fog, and glare. It is paired with a GPS-enabled time-synchronized clock and a network video recorder to record both video and still imagery along with GPS-positional data.  

      The camera is mounted at the front of the ship’s fly bridge, and the electronics are housed in a ruggedized rack on the bridge. The system can be operated manually from the bridge or be placed into an autonomous surveillance mode, in which it slowly pans back and forth, recording 15 minutes of video every three hours and a still image once every 15 seconds.

      “The installation of the equipment was a unique and fun experience. As with any good project, our expectations going into the install did not meet reality,” says Michael Emily, the project’s IT systems administrator who traveled to Seattle for the install. Working with the ship’s crew, the laboratory team had to quickly adjust their route for running cables from the camera to the observation station after they discovered that the expected access points weren’t in fact accessible. “We had 100-foot cables made for this project just in case of this type of scenario, which was a good thing because we only had a few inches to spare,” Emily says.

      The CRISP project team plans to publicly release the dataset, anticipated to be about 4 terabytes in size, once the USCG science mission concludes in the fall.

      The goal in releasing the dataset is to enable the wider research community to develop better tools for those operating in the Arctic, especially as this region becomes more navigable. “Collecting and publishing the data allows for faster and greater progress than what we could accomplish on our own,” Kurucar adds. “It also enables the laboratory to engage in more advanced AI applications while others make more incremental advances using the dataset.”

      On top of providing the dataset, the laboratory team plans to provide a baseline object-detection model, from which others can make progress on their own models. More advanced AI applications planned for development are classifiers for specific objects in the scene and the ability to identify and track objects across images.

      Beyond assisting with USCG missions, this project could create an influential dataset for researchers looking to apply AI to data from the Arctic to help combat climate change, says Paul Metzger, who leads the AI Software Architectures and Algorithms Group.

      Metzger adds that the group was honored to be a part of this project and is excited to see the advances that come from applying AI to novel challenges facing the United States: “I’m extremely proud of how our group applies AI to the highest-priority challenges in our nation, from predicting outbreaks of Covid-19 and assisting the U.S. European Command in their support of Ukraine to now employing AI in the Arctic for maritime awareness.”

      Once the dataset is available, it will be free to download on the Lincoln Laboratory dataset website. More