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      in Security

      System tracks movement of food through global humanitarian supply chain

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      Although more than enough food is produced to feed everyone in the world, as many as 828 million people face hunger today. Poverty, social inequity, climate change, natural disasters, and political conflicts all contribute to inhibiting access to food. For decades, the U.S. Agency for International Development (USAID) Bureau for Humanitarian Assistance (BHA) has been a leader in global food assistance, supplying millions of metric tons of food to recipients worldwide. Alleviating hunger — and the conflict and instability hunger causes — is critical to U.S. national security.

      But BHA is only one player within a large, complex supply chain in which food gets handed off between more than 100 partner organizations before reaching its final destination. Traditionally, the movement of food through the supply chain has been a black-box operation, with stakeholders largely out of the loop about what happens to the food once it leaves their custody. This lack of direct visibility into operations is due to siloed data repositories, insufficient data sharing among stakeholders, and different data formats that operators must manually sort through and standardize. As a result, accurate, real-time information — such as where food shipments are at any given time, which shipments are affected by delays or food recalls, and when shipments have arrived at their final destination — is lacking. A centralized system capable of tracing food along its entire journey, from manufacture through delivery, would enable a more effective humanitarian response to food-aid needs.

      In 2020, a team from MIT Lincoln Laboratory began engaging with BHA to create an intelligent dashboard for their supply-chain operations. This dashboard brings together the expansive food-aid datasets from BHA’s existing systems into a single platform, with tools for visualizing and analyzing the data. When the team started developing the dashboard, they quickly realized the need for considerably more data than BHA had access to.

      “That’s where traceability comes in, with each handoff partner contributing key pieces of information as food moves through the supply chain,” explains Megan Richardson, a researcher in the laboratory’s Humanitarian Assistance and Disaster Relief Systems Group.

      Richardson and the rest of the team have been working with BHA and their partners to scope, build, and implement such an end-to-end traceability system. This system consists of serialized, unique identifiers (IDs) — akin to fingerprints — that are assigned to individual food items at the time they are produced. These individual IDs remain linked to items as they are aggregated along the supply chain, first domestically and then internationally. For example, individually tagged cans of vegetable oil get packaged into cartons; cartons are placed onto pallets and transported via railway and truck to warehouses; pallets are loaded onto shipping containers at U.S. ports; and pallets are unloaded and cartons are unpackaged overseas.

      With a trace

      Today, visibility at the single-item level doesn’t exist. Most suppliers mark pallets with a lot number (a lot is a batch of items produced in the same run), but this is for internal purposes (i.e., to track issues stemming back to their production supply, like over-enriched ingredients or machinery malfunction), not data sharing. So, organizations know which supplier lot a pallet and carton are associated with, but they can’t track the unique history of an individual carton or item within that pallet. As the lots move further downstream toward their final destination, they are often mixed with lots from other productions, and possibly other commodity types altogether, because of space constraints. On the international side, such mixing and the lack of granularity make it difficult to quickly pull commodities out of the supply chain if food safety concerns arise. Current response times can span several months.

      “Commodities are grouped differently at different stages of the supply chain, so it is logical to track them in those groupings where needed,” Richardson says. “Our item-level granularity serves as a form of Rosetta Stone to enable stakeholders to efficiently communicate throughout these stages. We’re trying to enable a way to track not only the movement of commodities, including through their lot information, but also any problems arising independent of lot, like exposure to high humidity levels in a warehouse. Right now, we have no way to associate commodities with histories that may have resulted in an issue.”

      “You can now track your checked luggage across the world and the fish on your dinner plate,” adds Brice MacLaren, also a researcher in the laboratory’s Humanitarian Assistance and Disaster Relief Systems Group. “So, this technology isn’t new, but it’s new to BHA as they evolve their methodology for commodity tracing. The traceability system needs to be versatile, working across a wide variety of operators who take custody of the commodity along the supply chain and fitting into their existing best practices.”

      As food products make their way through the supply chain, operators at each receiving point would be able to scan these IDs via a Lincoln Laboratory-developed mobile application (app) to indicate a product’s current location and transaction status — for example, that it is en route on a particular shipping container or stored in a certain warehouse. This information would get uploaded to a secure traceability server. By scanning a product, operators would also see its history up until that point.   

      Hitting the mark

      At the laboratory, the team tested the feasibility of their traceability technology, exploring different ways to mark and scan items. In their testing, they considered barcodes and radio-frequency identification (RFID) tags and handheld and fixed scanners. Their analysis revealed 2D barcodes (specifically data matrices) and smartphone-based scanners were the most feasible options in terms of how the technology works and how it fits into existing operations and infrastructure.

      “We needed to come up with a solution that would be practical and sustainable in the field,” MacLaren says. “While scanners can automatically read any RFID tags in close proximity as someone is walking by, they can’t discriminate exactly where the tags are coming from. RFID is expensive, and it’s hard to read commodities in bulk. On the other hand, a phone can scan a barcode on a particular box and tell you that code goes with that box. The challenge then becomes figuring out how to present the codes for people to easily scan without significantly interrupting their usual processes for handling and moving commodities.” 

      As the team learned from partner representatives in Kenya and Djibouti, offloading at the ports is a chaotic, fast operation. At manual warehouses, porters fling bags over their shoulders or stack cartons atop their heads any which way they can and run them to a drop point; at bagging terminals, commodities come down a conveyor belt and land this way or that way. With this variability comes several questions: How many barcodes do you need on an item? Where should they be placed? What size should they be? What will they cost? The laboratory team is considering these questions, keeping in mind that the answers will vary depending on the type of commodity; vegetable oil cartons will have different specifications than, say, 50-kilogram bags of wheat or peas.

      Leaving a mark

      Leveraging results from their testing and insights from international partners, the team has been running a traceability pilot evaluating how their proposed system meshes with real-world domestic and international operations. The current pilot features a domestic component in Houston, Texas, and an international component in Ethiopia, and focuses on tracking individual cartons of vegetable oil and identifying damaged cans. The Ethiopian team with Catholic Relief Services recently received a container filled with pallets of uniquely barcoded cartons of vegetable oil cans (in the next pilot, the cans will be barcoded, too). They are now scanning items and collecting data on product damage by using smartphones with the laboratory-developed mobile traceability app on which they were trained. 

      “The partners in Ethiopia are comparing a couple lid types to determine whether some are more resilient than others,” Richardson says. “With the app — which is designed to scan commodities, collect transaction data, and keep history — the partners can take pictures of damaged cans and see if a trend with the lid type emerges.”

      Next, the team will run a series of pilots with the World Food Program (WFP), the world’s largest humanitarian organization. The first pilot will focus on data connectivity and interoperability, and the team will engage with suppliers to directly print barcodes on individual commodities instead of applying barcode labels to packaging, as they did in the initial feasibility testing. The WFP will provide input on which of their operations are best suited for testing the traceability system, considering factors like the network bandwidth of WFP staff and local partners, the commodity types being distributed, and the country context for scanning. The BHA will likely also prioritize locations for system testing.

      “Our goal is to provide an infrastructure to enable as close to real-time data exchange as possible between all parties, given intermittent power and connectivity in these environments,” MacLaren says.

      In subsequent pilots, the team will try to integrate their approach with existing systems that partners rely on for tracking procurements, inventory, and movement of commodities under their custody so that this information is automatically pushed to the traceability server. The team also hopes to add a capability for real-time alerting of statuses, like the departure and arrival of commodities at a port or the exposure of unclaimed commodities to the elements. Real-time alerts would enable stakeholders to more efficiently respond to food-safety events. Currently, partners are forced to take a conservative approach, pulling out more commodities from the supply chain than are actually suspect, to reduce risk of harm. Both BHA and WHP are interested in testing out a food-safety event during one of the pilots to see how the traceability system works in enabling rapid communication response.

      To implement this technology at scale will require some standardization for marking different commodity types as well as give and take among the partners on best practices for handling commodities. It will also require an understanding of country regulations and partner interactions with subcontractors, government entities, and other stakeholders.

      “Within several years, I think it’s possible for BHA to use our system to mark and trace all their food procured in the United States and sent internationally,” MacLaren says.

      Once collected, the trove of traceability data could be harnessed for other purposes, among them analyzing historical trends, predicting future demand, and assessing the carbon footprint of commodity transport. In the future, a similar traceability system could scale for nonfood items, including medical supplies distributed to disaster victims, resources like generators and water trucks localized in emergency-response scenarios, and vaccines administered during pandemics. Several groups at the laboratory are also interested in such a system to track items such as tools deployed in space or equipment people carry through different operational environments.

      “When we first started this program, colleagues were asking why the laboratory was involved in simple tasks like making a dashboard, marking items with barcodes, and using hand scanners,” MacLaren says. “Our impact here isn’t about the technology; it’s about providing a strategy for coordinated food-aid response and successfully implementing that strategy. Most importantly, it’s about people getting fed.” More

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      in Environment

      J-WAFS announces 2023 seed grant recipients

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      Today, the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) announced its ninth round of seed grants to support innovative research projects at MIT. The grants are designed to fund research efforts that tackle challenges related to water and food for human use, with the ultimate goal of creating meaningful impact as the world population continues to grow and the planet undergoes significant climate and environmental changes.Ten new projects led by 15 researchers from seven different departments will be supported this year. The projects address a range of challenges by employing advanced materials, technology innovations, and new approaches to resource management. The new projects aim to remove harmful chemicals from water sources, develop monitoring and other systems to help manage various aquaculture industries, optimize water purification materials, and more.“The seed grant program is J-WAFS’ flagship grant initiative,” says J-WAFS executive director Renee J. Robins. “The funding is intended to spur groundbreaking MIT research addressing complex issues that are challenging our water and food systems. The 10 projects selected this year show great promise, and we look forward to the progress and accomplishments these talented researchers will make,” she adds.The 2023 J-WAFS seed grant researchers and their projects are:Sara Beery, an assistant professor in the Department of Electrical Engineering and Computer Science (EECS), is building the first completely automated system to estimate the size of salmon populations in the Pacific Northwest (PNW).Salmon are a keystone species in the PNW, feeding human populations for the last 7,500 years at least. However, overfishing, habitat loss, and climate change threaten extinction of salmon populations across the region. Accurate salmon counts during their seasonal migration to their natal river to spawn are essential for fisheries’ regulation and management but are limited by human capacity. Fish population monitoring is a widespread challenge in the United States and worldwide. Beery and her team are working to build a system that will provide a detailed picture of the state of salmon populations in unprecedented, spatial, and temporal resolution by combining sonar sensors and computer vision and machine learning (CVML) techniques. The sonar will capture individual fish as they swim upstream and CVML will train accurate algorithms to interpret the sonar video for detecting, tracking, and counting fish automatically while adapting to changing river conditions and fish densities.Another aquaculture project is being led by Michael Triantafyllou, the Henry L. and Grace Doherty Professor in Ocean Science and Engineering in the Department of Mechanical Engineering, and Robert Vincent, the assistant director at MIT’s Sea Grant Program. They are working with Otto Cordero, an associate professor in the Department of Civil and Environmental Engineering, to control harmful bacteria blooms in aquaculture algae feed production.

      Aquaculture in the United States represents a $1.5 billion industry annually and helps support 1.7 million jobs, yet many American hatcheries are not able to keep up with demand. One barrier to aquaculture production is the high degree of variability in survival rates, most likely caused by a poorly controlled microbiome that leads to bacterial infections and sub-optimal feed efficiency. Triantafyllou, Vincent, and Cordero plan to monitor the microbiome composition of a shellfish hatchery in order to identify possible causing agents of mortality, as well as beneficial microbes. They hope to pair microbe data with detail phenotypic information about the animal population to generate rapid diagnostic tests and explore the potential for microbiome therapies to protect larvae and prevent future outbreaks. The researchers plan to transfer their findings and technology to the local and regional aquaculture community to ensure healthy aquaculture production that will support the expansion of the U.S. aquaculture industry.

      David Des Marais is the Cecil and Ida Green Career Development Professor in the Department of Civil and Environmental Engineering. His 2023 J-WAFS project seeks to understand plant growth responses to elevated carbon dioxide (CO2) in the atmosphere, in the hopes of identifying breeding strategies that maximize crop yield under future CO2 scenarios.Today’s crop plants experience higher atmospheric CO2 than 20 or 30 years ago. Crops such as wheat, oat, barley, and rice typically increase their growth rate and biomass when grown at experimentally elevated atmospheric CO2. This is known as the so-called “CO2 fertilization effect.” However, not all plant species respond to rising atmospheric CO2 with increased growth, and for the ones that do, increased growth doesn’t necessarily correspond to increased crop yield. Using specially built plant growth chambers that can control the concentration of CO2, Des Marais will explore how CO2 availability impacts the development of tillers (branches) in the grass species Brachypodium. He will study how gene expression controls tiller development, and whether this is affected by the growing environment. The tillering response refers to how many branches a plant produces, which sets a limit on how much grain it can yield. Therefore, optimizing the tillering response to elevated CO2 could greatly increase yield. Des Marais will also look at the complete genome sequence of Brachypodium, wheat, oat, and barley to help identify genes relevant for branch growth.Darcy McRose, an assistant professor in the Department of Civil and Environmental Engineering, is researching whether a combination of plant metabolites and soil bacteria can be used to make mineral-associated phosphorus more bioavailable.The nutrient phosphorus is essential for agricultural plant growth, but when added as a fertilizer, phosphorus sticks to the surface of soil minerals, decreasing bioavailability, limiting plant growth, and accumulating residual phosphorus. Heavily fertilized agricultural soils often harbor large reservoirs of this type of mineral-associated “legacy” phosphorus. Redox transformations are one chemical process that can liberate mineral-associated phosphorus. However, this needs to be carefully controlled, as overly mobile phosphorus can lead to runoff and pollution of natural waters. Ideally, phosphorus would be made bioavailable when plants need it and immobile when they don’t. Many plants make small metabolites called coumarins that might be able to solubilize mineral-adsorbed phosphorus and be activated and inactivated under different conditions. McRose will use laboratory experiments to determine whether a combination of plant metabolites and soil bacteria can be used as a highly efficient and tunable system for phosphorus solubilization. She also aims to develop an imaging platform to investigate exchanges of phosphorus between plants and soil microbes.Many of the 2023 seed grants will support innovative technologies to monitor, quantify, and remediate various kinds of pollutants found in water. Two of the new projects address the problem of per- and polyfluoroalkyl substances (PFAS), human-made chemicals that have recently emerged as a global health threat. Known as “forever chemicals,” PFAS are used in many manufacturing processes. These chemicals are known to cause significant health issues including cancer, and they have become pervasive in soil, dust, air, groundwater, and drinking water. Unfortunately, the physical and chemical properties of PFAS render them difficult to detect and remove.Aristide Gumyusenge, the Merton C. Assistant Professor of Materials Science and Engineering, is using metal-organic frameworks for low-cost sensing and capture of PFAS. Most metal-organic frameworks (MOFs) are synthesized as particles, which complicates their high accuracy sensing performance due to defects such as intergranular boundaries. Thin, film-based electronic devices could enable the use of MOFs for many applications, especially chemical sensing. Gumyusenge’s project aims to design test kits based on two-dimensional conductive MOF films for detecting PFAS in drinking water. In early demonstrations, Gumyusenge and his team showed that these MOF films can sense PFAS at low concentrations. They will continue to iterate using a computation-guided approach to tune sensitivity and selectivity of the kits with the goal of deploying them in real-world scenarios.Carlos Portela, the Brit (1961) and Alex (1949) d’Arbeloff Career Development Professor in the Department of Mechanical Engineering, and Ariel Furst, the Cook Career Development Professor in the Department of Chemical Engineering, are building novel architected materials to act as filters for the removal of PFAS from water. Portela and Furst will design and fabricate nanoscale materials that use activated carbon and porous polymers to create a physical adsorption system. They will engineer the materials to have tunable porosities and morphologies that can maximize interactions between contaminated water and functionalized surfaces, while providing a mechanically robust system.Rohit Karnik is a Tata Professor and interim co-department head of the Department of Mechanical Engineering. He is working on another technology, his based on microbead sensors, to rapidly measure and monitor trace contaminants in water.Water pollution from both biological and chemical contaminants contributes to an estimated 1.36 million deaths annually. Chemical contaminants include pesticides and herbicides, heavy metals like lead, and compounds used in manufacturing. These emerging contaminants can be found throughout the environment, including in water supplies. The Environmental Protection Agency (EPA) in the United States sets recommended water quality standards, but states are responsible for developing their own monitoring criteria and systems, which must be approved by the EPA every three years. However, the availability of data on regulated chemicals and on candidate pollutants is limited by current testing methods that are either insensitive or expensive and laboratory-based, requiring trained scientists and technicians. Karnik’s project proposes a simple, self-contained, portable system for monitoring trace and emerging pollutants in water, making it suitable for field studies. The concept is based on multiplexed microbead-based sensors that use thermal or gravitational actuation to generate a signal. His proposed sandwich assay, a testing format that is appealing for environmental sensing, will enable both single-use and continuous monitoring. The hope is that the bead-based assays will increase the ease and reach of detecting and quantifying trace contaminants in water for both personal and industrial scale applications.Alexander Radosevich, a professor in the Department of Chemistry, and Timothy Swager, the John D. MacArthur Professor of Chemistry, are teaming up to create rapid, cost-effective, and reliable techniques for on-site arsenic detection in water.Arsenic contamination of groundwater is a problem that affects as many as 500 million people worldwide. Arsenic poisoning can lead to a range of severe health problems from cancer to cardiovascular and neurological impacts. Both the EPA and the World Health Organization have established that 10 parts per billion is a practical threshold for arsenic in drinking water, but measuring arsenic in water at such low levels is challenging, especially in resource-limited environments where access to sensitive laboratory equipment may not be readily accessible. Radosevich and Swager plan to develop reaction-based chemical sensors that bind and extract electrons from aqueous arsenic. In this way, they will exploit the inherent reactivity of aqueous arsenic to selectively detect and quantify it. This work will establish the chemical basis for a new method of detecting trace arsenic in drinking water.Rajeev Ram is a professor in the Department of Electrical Engineering and Computer Science. His J-WAFS research will advance a robust technology for monitoring nitrogen-containing pollutants, which threaten over 15,000 bodies of water in the United States alone.Nitrogen in the form of nitrate, nitrite, ammonia, and urea can run off from agricultural fertilizer and lead to harmful algal blooms that jeopardize human health. Unfortunately, monitoring these contaminants in the environment is challenging, as sensors are difficult to maintain and expensive to deploy. Ram and his students will work to establish limits of detection for nitrate, nitrite, ammonia, and urea in environmental, industrial, and agricultural samples using swept-source Raman spectroscopy. Swept-source Raman spectroscopy is a method of detecting the presence of a chemical by using a tunable, single mode laser that illuminates a sample. This method does not require costly, high-power lasers or a spectrometer. Ram will then develop and demonstrate a portable system that is capable of achieving chemical specificity in complex, natural environments. Data generated by such a system should help regulate polluters and guide remediation.Kripa Varanasi, a professor in the Department of Mechanical Engineering, and Angela Belcher, the James Mason Crafts Professor and head of the Department of Biological Engineering, will join forces to develop an affordable water disinfection technology that selectively identifies, adsorbs, and kills “superbugs” in domestic and industrial wastewater.Recent research predicts that antibiotic-resistance bacteria (superbugs) will result in $100 trillion in health care expenses and 10 million deaths annually by 2050. The prevalence of superbugs in our water systems has increased due to corroded pipes, contamination, and climate change. Current drinking water disinfection technologies are designed to kill all types of bacteria before human consumption. However, for certain domestic and industrial applications there is a need to protect the good bacteria required for ecological processes that contribute to soil and plant health. Varanasi and Belcher will combine material, biological, process, and system engineering principles to design a sponge-based water disinfection technology that can identify and destroy harmful bacteria while leaving the good bacteria unharmed. By modifying the sponge surface with specialized nanomaterials, their approach will be able to kill superbugs faster and more efficiently. The sponge filters can be deployed under very low pressure, making them an affordable technology, especially in resource-constrained communities.In addition to the 10 seed grant projects, J-WAFS will also fund a research initiative led by Greg Sixt. Sixt is the research manager for climate and food systems at J-WAFS, and the director of the J-WAFS-led Food and Climate Systems Transformation (FACT) Alliance. His project focuses on the Lake Victoria Basin (LVB) of East Africa. The second-largest freshwater lake in the world, Lake Victoria straddles three countries (Uganda, Tanzania, and Kenya) and has a catchment area that encompasses two more (Rwanda and Burundi). Sixt will collaborate with Michael Hauser of the University of Natural Resources and Life Sciences, Vienna, and Paul Kariuki, of the Lake Victoria Basin Commission.The group will study how to adapt food systems to climate change in the Lake Victoria Basin. The basin is facing a range of climate threats that could significantly impact livelihoods and food systems in the expansive region. For example, extreme weather events like droughts and floods are negatively affecting agricultural production and freshwater resources. Across the LVB, current approaches to land and water management are unsustainable and threaten future food and water security. The Lake Victoria Basin Commission (LVBC), a specialized institution of the East African Community, wants to play a more vital role in coordinating transboundary land and water management to support transitions toward more resilient, sustainable, and equitable food systems. The primary goal of this research will be to support the LVBC’s transboundary land and water management efforts, specifically as they relate to sustainability and climate change adaptation in food systems. The research team will work with key stakeholders in Kenya, Uganda, and Tanzania to identify specific capacity needs to facilitate land and water management transitions. The two-year project will produce actionable recommendations to the LVBC. More

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      in Energy

      Helping the cause of environmental resilience

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      Haruko Wainwright, the Norman C. Rasmussen Career Development Professor in Nuclear Science and Engineering (NSE) and assistant professor in civil and environmental engineering at MIT, grew up in rural Japan, where many nuclear facilities are located. She remembers worrying about the facilities as a child. Wainwright was only 6 at the time of the Chernobyl accident in 1986, but still recollects it vividly.

      Those early memories have contributed to Wainwright’s determination to research how technologies can mold environmental resilience — the capability of mitigating the consequences of accidents and recovering from contamination.

      Wainwright believes that environmental monitoring can help improve resilience. She co-leads the U.S. Department of Energy (DOE)’s Advanced Long-term Environmental Monitoring Systems (ALTEMIS) project, which integrates technologies such as in situ sensors, geophysics, remote sensing, simulations, and artificial intelligence to establish new paradigms for monitoring. The project focuses on soil and groundwater contamination at more than 100 U.S. sites that were used for nuclear weapons production.

      As part of this research, which was featured last year in Environmental Science & Technology Journal, Wainwright is working on a machine learning framework for improving environmental monitoring strategies. She hopes the ALTEMIS project will enable the rapid detection of anomalies while ensuring the stability of residual contamination and waste disposal facilities.

      Childhood in rural Japan

      Even as a child, Wainwright was interested in physics, history, and a variety of other subjects.

      But growing up in a rural area was not ideal for someone interested in STEM. There were no engineers or scientists in the community and no science museums, either. “It was not so cool to be interested in science, and I never talked about my interest with anyone,” Wainwright recalls.

      Television and books were the only door to the world of science. “I did not study English until middle school and I had never been on a plane until college. I sometimes find it miraculous that I am now working in the U.S. and teaching at MIT,” she says.

      As she grew a little older, Wainwright heard a lot of discussions about nuclear facilities in the region and many stories about Hiroshima and Nagasaki.

      At the same time, giants like Marie Curie inspired her to pursue science. Nuclear physics was particularly fascinating. “At some point during high school, I started wondering ‘what are radiations, what is radioactivity, what is light,’” she recalls. Reading Richard Feynman’s books and trying to understand quantum mechanics made her want to study physics in college.

      Pursuing research in the United States

      Wainwright pursued an undergraduate degree in engineering physics at Kyoto University. After two research internships in the United States, Wainwright was impressed by the dynamic and fast-paced research environment in the country.

      And compared to Japan, there were “more women in science and engineering,” Wainwright says. She enrolled at the University of California at Berkeley in 2005, where she completed her doctorate in nuclear engineering with minors in statistics and civil and environmental engineering.

      Before moving to MIT NSE in 2022, Wainwright was a staff scientist in the Earth and Environmental Area at Lawrence Berkeley National Laboratory (LBNL). She worked on a variety of topics, including radioactive contamination, climate science, CO2 sequestration, precision agriculture, and watershed science. Her time at LBNL helped Wainwright build a solid foundation about a variety of environmental sensors and monitoring and simulation methods across different earth science disciplines.   

      Empowering communities through monitoring

      One of the most compelling takeaways from Wainwright’s early research: People trust actual measurements and data as facts, even though they are skeptical about models and predictions. “I talked with many people living in Fukushima prefecture. Many of them have dosimeters and measure radiation levels on their own. They might not trust the government, but they trust their own data and are then convinced that it is safe to live there and to eat local food,” Wainwright says.

      She has been impressed that area citizens have gained significant knowledge about radiation and radioactivity through these efforts. “But they are often frustrated that people living far away, in cities like Tokyo, still avoid agricultural products from Fukushima,” Wainwright says.

      Wainwright thinks that data derived from environmental monitoring — through proper visualization and communication — can address misconceptions and fake news that often hurt people near contaminated sites.

      Wainwright is now interested in how these technologies — tested with real data at contaminated sites — can be proactively used for existing and future nuclear facilities “before contamination happens,” as she explored for Nuclear News. “I don’t think it is a good idea to simply dismiss someone’s concern as irrational. Showing credible data has been much more effective to provide assurance. Or a proper monitoring network would enable us to minimize contamination or support emergency responses when accidents happen,” she says.

      Educating communities and students

      Part of empowering communities involves improving their ability to process science-based information. “Potentially hazardous facilities always end up in rural regions; minorities’ concerns are often ignored. The problem is that these regions don’t produce so many scientists or policymakers; they don’t have a voice,” Wainwright says, “I am determined to dedicate my time to improve STEM education in rural regions and to increase the voice in these regions.”

      In a project funded by DOE, she collaborates with the team of researchers at the University of Alaska — the Alaska Center for Energy and Power and Teaching Through Technology program — aiming to improve STEM education for rural and indigenous communities. “Alaska is an important place for energy transition and environmental justice,” Wainwright says. Micro-nuclear reactors can potentially improve the life of rural communities who bear the brunt of the high cost of fuel and transportation. However, there is a distrust of nuclear technologies, stemming from past nuclear weapon testing. At the same time, Alaska has vast metal mining resources for renewable energy and batteries. And there are concerns about environmental contamination from mining and various sources. The teams’ vision is much broader, she points out. “The focus is on broader environmental monitoring technologies and relevant STEM education, addressing general water and air qualities,” Wainwright says.

      The issues also weave into the courses Wainwright teaches at MIT. “I think it is important for engineering students to be aware of environmental justice related to energy waste and mining as well as past contamination events and their recovery,” she says. “It is not OK just to send waste to, or develop mines in, rural regions, which could be a special place for some people. We need to make sure that these developments will not harm the environment and health of local communities.” Wainwright also hopes that this knowledge will ultimately encourage students to think creatively about engineering designs that minimize waste or recycle material.

      The last question of the final quiz of one of her recent courses was: Assume that you store high-level radioactive waste in your “backyard.” What technical strategies would make you and your family feel safe? “All students thought about this question seriously and many suggested excellent points, including those addressing environmental monitoring,” Wainwright says, “that made me hopeful about the future.” More

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      in Energy

      Minimizing electric vehicles’ impact on the grid

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      National and global plans to combat climate change include increasing the electrification of vehicles and the percentage of electricity generated from renewable sources. But some projections show that these trends might require costly new power plants to meet peak loads in the evening when cars are plugged in after the workday. What’s more, overproduction of power from solar farms during the daytime can waste valuable electricity-generation capacity.

      In a new study, MIT researchers have found that it’s possible to mitigate or eliminate both these problems without the need for advanced technological systems of connected devices and real-time communications, which could add to costs and energy consumption. Instead, encouraging the placing of charging stations for electric vehicles (EVs) in strategic ways, rather than letting them spring up anywhere, and setting up systems to initiate car charging at delayed times could potentially make all the difference.

      The study, published today in the journal Cell Reports Physical Science, is by Zachary Needell PhD ’22, postdoc Wei Wei, and Professor Jessika Trancik of MIT’s Institute for Data, Systems, and Society.

      In their analysis, the researchers used data collected in two sample cities: New York and Dallas. The data were gathered from, among other sources, anonymized records collected via onboard devices in vehicles, and surveys that carefully sampled populations to cover variable travel behaviors. They showed the times of day cars are used and for how long, and how much time the vehicles spend at different kinds of locations — residential, workplace, shopping, entertainment, and so on.

      The findings, Trancik says, “round out the picture on the question of where to strategically locate chargers to support EV adoption and also support the power grid.”

      Better availability of charging stations at workplaces, for example, could help to soak up peak power being produced at midday from solar power installations, which might otherwise go to waste because it is not economical to build enough battery or other storage capacity to save all of it for later in the day. Thus, workplace chargers can provide a double benefit, helping to reduce the evening peak load from EV charging and also making use of the solar electricity output.

      These effects on the electric power system are considerable, especially if the system must meet charging demands for a fully electrified personal vehicle fleet alongside the peaks in other demand for electricity, for example on the hottest days of the year. If unmitigated, the evening peaks in EV charging demand could require installing upwards of 20 percent more power-generation capacity, the researchers say.

      “Slow workplace charging can be more preferable than faster charging technologies for enabling a higher utilization of midday solar resources,” Wei says.

      Meanwhile, with delayed home charging, each EV charger could be accompanied by a simple app to estimate the time to begin its charging cycle so that it charges just before it is needed the next day. Unlike other proposals that require a centralized control of the charging cycle, such a system needs no interdevice communication of information and can be preprogrammed — and can accomplish a major shift in the demand on the grid caused by increasing EV penetration. The reason it works so well, Trancik says, is because of the natural variability in driving behaviors across individuals in a population.

      By “home charging,” the researchers aren’t only referring to charging equipment in individual garages or parking areas. They say it’s essential to make charging stations available in on-street parking locations and in apartment building parking areas as well.

      Trancik says the findings highlight the value of combining the two measures — workplace charging and delayed home charging — to reduce peak electricity demand, store solar energy, and conveniently meet drivers’ charging needs on all days. As the team showed in earlier research, home charging can be a particularly effective component of a strategic package of charging locations; workplace charging, they have found, is not a good substitute for home charging for meeting drivers’ needs on all days.

      “Given that there’s a lot of public money going into expanding charging infrastructure,” Trancik says, “how do you incentivize the location such that this is going to be efficiently and effectively integrated into the power grid without requiring a lot of additional capacity expansion?” This research offers some guidance to policymakers on where to focus rules and incentives.

      “I think one of the fascinating things about these findings is that by being strategic you can avoid a lot of physical infrastructure that you would otherwise need,” she adds. “Your electric vehicles can displace some of the need for stationary energy storage, and you can also avoid the need to expand the capacity of power plants, by thinking about the location of chargers as a tool for managing demands — where they occur and when they occur.”

      Delayed home charging could make a surprising amount of difference, the team found. “It’s basically incentivizing people to begin charging later. This can be something that is preprogrammed into your chargers. You incentivize people to delay the onset of charging by a bit, so that not everyone is charging at the same time, and that smooths out the peak.”

      Such a program would require some advance commitment on the part of participants. “You would need to have enough people committing to this program in advance to avoid the investment in physical infrastructure,” Trancik says. “So, if you have enough people signing up, then you essentially don’t have to build those extra power plants.”

      It’s not a given that all of this would line up just right, and putting in place the right mix of incentives would be crucial. “If you want electric vehicles to act as an effective storage technology for solar energy, then the [EV] market needs to grow fast enough in order to be able to do that,” Trancik says.

      To best use public funds to help make that happen, she says, “you can incentivize charging installations, which would go through ideally a competitive process — in the private sector, you would have companies bidding for different projects, but you can incentivize installing charging at workplaces, for example, to tap into both of these benefits.” Chargers people can access when they are parked near their residences are also important, Trancik adds, but for other reasons. Home charging is one of the ways to meet charging needs while avoiding inconvenient disruptions to people’s travel activities.

      The study was supported by the European Regional Development Fund Operational Program for Competitiveness and Internationalization, the Lisbon Portugal Regional Operation Program, and the Portuguese Foundation for Science and Technology. More

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      in Environment

      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

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      in Environment

      MIT Policy Hackathon produces new solutions for technology policy challenges

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      Almost three years ago, the Covid-19 pandemic changed the world. Many are still looking to uncover a “new normal.”

      “Instead of going back to normal, [there’s a new generation that] wants to build back something different, something better,” says Jorge Sandoval, a second-year graduate student in MIT’s Technology and Policy Program (TPP) at the Institute for Data, Systems and Society (IDSS). “How do we communicate this mindset to others, that the world cannot be the same as before?”

      This was the inspiration behind “A New (Re)generation,” this year’s theme for the IDSS-student-run MIT Policy Hackathon, which Sandoval helped to organize as the event chair. The Policy Hackathon is a weekend-long, interdisciplinary competition that brings together participants from around the globe to explore potential solutions to some of society’s greatest challenges. 

      Unlike other competitions of its kind, Sandoval says MIT’s event emphasizes a humanistic approach. “The idea of our hackathon is to promote applications of technology that are humanistic or human-centered,” he says. “We take the opportunity to examine aspects of technology in the spaces where they tend to interact with society and people, an opportunity most technical competitions don’t offer because their primary focus is on the technology.”

      The competition started with 50 teams spread across four challenge categories. This year’s categories included Internet and Cybersecurity, Environmental Justice, Logistics, and Housing and City Planning. While some people come into the challenge with friends, Sandoval said most teams form organically during an online networking meeting hosted by MIT.

      “We encourage people to pair up with others outside of their country and to form teams of different diverse backgrounds and ages,” Sandoval says. “We try to give people who are often not invited to the decision-making table the opportunity to be a policymaker, bringing in those with backgrounds in not only law, policy, or politics, but also medicine, and people who have careers in engineering or experience working in nonprofits.”

      Once an in-person event, the Policy Hackathon has gone through its own regeneration process these past three years, according to Sandoval. After going entirely online during the pandemic’s height, last year they successfully hosted the first hybrid version of the event, which served as their model again this year.

      “The hybrid version of the event gives us the opportunity to allow people to connect in a way that is lost if it is only online, while also keeping the wide range of accessibility, allowing people to join from anywhere in the world, regardless of nationality or income, to provide their input,” Sandoval says.

      For Swetha Tadisina, an undergraduate computer science major at Lafayette College and participant in the internet and cybersecurity category, the hackathon was a unique opportunity to meet and work with people much more advanced in their careers. “I was surprised how such a diverse team that had never met before was able to work so efficiently and creatively,” Tadisina says.

      Erika Spangler, a public high school teacher from Massachusetts and member of the environmental justice category’s winning team, says that while each member of “Team Slime Mold” came to the table with a different set of skills, they managed to be in sync from the start — even working across the nine-and-a-half-hour time difference the four-person team faced when working with policy advocate Shruti Nandy from Calcutta, India.

      “We divided the project into data, policy, and research and trusted each other’s expertise,” Spangler says, “Despite having separate areas of focus, we made sure to have regular check-ins to problem-solve and cross-pollinate ideas.”

      During the 48-hour period, her team proposed the creation of an algorithm to identify high-quality brownfields that could be cleaned up and used as sites for building renewable energy. Their corresponding policy sought to mandate additional requirements for renewable energy businesses seeking tax credits from the Inflation Reduction Act.

      “Their policy memo had the most in-depth technical assessment, including deep dives in a few key cities to show the impact of their proposed approach for site selection at a very granular level,” says Amanda Levin, director of policy analysis for the Natural Resources Defense Council (NRDC). Levin acted as both a judge and challenge provider for the environmental justice category.

      “They also presented their policy recommendations in the memo in a well-thought-out way, clearly noting the relevant actor,” she adds. This clarity around what can be done, and who would be responsible for those actions, is highly valuable for those in policy.”

      Levin says the NRDC, one of the largest environmental nonprofits in the United States, provided five “challenge questions,” making it clear that teams did not need to address all of them. She notes that this gave teams significant leeway, bringing a wide variety of recommendations to the table. 

      “As a challenge partner, the work put together by all the teams is already being used to help inform discussions about the implementation of the Inflation Reduction Act,” Levin says. “Being able to tap into the collective intelligence of the hackathon helped uncover new perspectives and policy solutions that can help make an impact in addressing the important policy challenges we face today.”

      While having partners with experience in data science and policy definitely helped, fellow Team Slime Mold member Sara Sheffels, a PhD candidate in MIT’s biomaterials program, says she was surprised how much her experiences outside of science and policy were relevant to the challenge: “My experience organizing MIT’s Graduate Student Union shaped my ideas about more meaningful community involvement in renewables projects on brownfields. It is not meaningful to merely educate people about the importance of renewables or ask them to sign off on a pre-planned project without addressing their other needs.”

      “I wanted to test my limits, gain exposure, and expand my world,” Tadisina adds. “The exposure, friendships, and experiences you gain in such a short period of time are incredible.”

      For Willy R. Vasquez, an electrical and computer engineering PhD student at the University of Texas, the hackathon is not to be missed. “If you’re interested in the intersection of tech, society, and policy, then this is a must-do experience.” More

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      in Environment

      Methane research takes on new urgency at MIT

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      One of the most notable climate change provisions in the 2022 Inflation Reduction Act is the first U.S. federal tax on a greenhouse gas (GHG). That the fee targets methane (CH4), rather than carbon dioxide (CO2), emissions is indicative of the urgency the scientific community has placed on reducing this short-lived but powerful gas. Methane persists in the air about 12 years — compared to more than 1,000 years for CO2 — yet it immediately causes about 120 times more warming upon release. The gas is responsible for at least a quarter of today’s gross warming. 

      “Methane has a disproportionate effect on near-term warming,” says Desiree Plata, the director of MIT Methane Network. “CH4 does more damage than CO2 no matter how long you run the clock. By removing methane, we could potentially avoid critical climate tipping points.” 

      Because GHGs have a runaway effect on climate, reductions made now will have a far greater impact than the same reductions made in the future. Cutting methane emissions will slow the thawing of permafrost, which could otherwise lead to massive methane releases, as well as reduce increasing emissions from wetlands.  

      “The goal of MIT Methane Network is to reduce methane emissions by 45 percent by 2030, which would save up to 0.5 degree C of warming by 2100,” says Plata, an associate professor of civil and environmental engineering at MIT and director of the Plata Lab. “When you consider that governments are trying for a 1.5-degree reduction of all GHGs by 2100, this is a big deal.” 

      Under normal concentrations, methane, like CO2, poses no health risks. Yet methane assists in the creation of high levels of ozone. In the lower atmosphere, ozone is a key component of air pollution, which leads to “higher rates of asthma and increased emergency room visits,” says Plata. 

      Methane-related projects at the Plata Lab include a filter made of zeolite — the same clay-like material used in cat litter — designed to convert methane into CO2 at dairy farms and coal mines. At first glance, the technology would appear to be a bit of a hard sell, since it converts one GHG into another. Yet the zeolite filter’s low carbon and dollar costs, combined with the disproportionate warming impact of methane, make it a potential game-changer.

      The sense of urgency about methane has been amplified by recent studies that show humans are generating far more methane emissions than previously estimated, and that the rates are rising rapidly. Exactly how much methane is in the air is uncertain. Current methods for measuring atmospheric methane, such as ground, drone, and satellite sensors, “are not readily abundant and do not always agree with each other,” says Plata.  

      The Plata Lab is collaborating with Tim Swager in the MIT Department of Chemistry to develop low-cost methane sensors. “We are developing chemiresisitive sensors that cost about a dollar that you could place near energy infrastructure to back-calculate where leaks are coming from,” says Plata.  

      The researchers are working on improving the accuracy of the sensors using machine learning techniques and are planning to integrate internet-of-things technology to transmit alerts. Plata and Swager are not alone in focusing on data collection: the Inflation Reduction Act adds significant funding for methane sensor research. 

      Other research at the Plata Lab includes the development of nanomaterials and heterogeneous catalysis techniques for environmental applications. The lab also explores mitigation solutions for industrial waste, particularly those related to the energy transition. Plata is the co-founder of an lithium-ion battery recycling startup called Nth Cycle. 

      On a more fundamental level, the Plata Lab is exploring how to develop products with environmental and social sustainability in mind. “Our overarching mission is to change the way that we invent materials and processes so that environmental objectives are incorporated along with traditional performance and cost metrics,” says Plata. “It is important to do that rigorous assessment early in the design process.”

      Play video

      MIT amps up methane research 

      The MIT Methane Network brings together 26 researchers from MIT along with representatives of other institutions “that are dedicated to the idea that we can reduce methane levels in our lifetime,” says Plata. The organization supports research such as Plata’s zeolite and sensor projects, as well as designing pipeline-fixing robots, developing methane-based fuels for clean hydrogen, and researching the capture and conversion of methane into liquid chemical precursors for pharmaceuticals and plastics. Other members are researching policies to encourage more sustainable agriculture and land use, as well as methane-related social justice initiatives. 

      “Methane is an especially difficult problem because it comes from all over the place,” says Plata. A recent Global Carbon Project study estimated that half of methane emissions are caused by humans. This is led by waste and agriculture (28 percent), including cow and sheep belching, rice paddies, and landfills.  

      Fossil fuels represent 18 percent of the total budget. Of this, about 63 percent is derived from oil and gas production and pipelines, 33 percent from coal mining activities, and 5 percent from industry and transportation. Human-caused biomass burning, primarily from slash-and-burn agriculture, emits about 4 percent of the global total.  

      The other half of the methane budget includes natural methane emissions from wetlands (20 percent) and other natural sources (30 percent). The latter includes permafrost melting and natural biomass burning, such as forest fires started by lightning.  

      With increases in global warming and population, the line between anthropogenic and natural causes is getting fuzzier. “Human activities are accelerating natural emissions,” says Plata. “Climate change increases the release of methane from wetlands and permafrost and leads to larger forest and peat fires.”  

      The calculations can get complicated. For example, wetlands provide benefits from CO2 capture, biological diversity, and sea level rise resiliency that more than compensate for methane releases. Meanwhile, draining swamps for development increases emissions. 

      Over 100 nations have signed onto the U.N.’s Global Methane Pledge to reduce at least 30 percent of anthropogenic emissions within the next 10 years. The U.N. report estimates that this goal can be achieved using proven technologies and that about 60 percent of these reductions can be accomplished at low cost. 

      Much of the savings would come from greater efficiencies in fossil fuel extraction, processing, and delivery. The methane fees in the Inflation Reduction Act are primarily focused on encouraging fossil fuel companies to accelerate ongoing efforts to cap old wells, flare off excess emissions, and tighten pipeline connections.  

      Fossil fuel companies have already made far greater pledges to reduce methane than they have with CO2, which is central to their business. This is due, in part, to the potential savings, as well as in preparation for methane regulations expected from the Environmental Protection Agency in late 2022. The regulations build upon existing EPA oversight of drilling operations, and will likely be exempt from the U.S. Supreme Court’s ruling that limits the federal government’s ability to regulate GHGs. 

      Zeolite filter targets methane in dairy and coal 

      The “low-hanging fruit” of gas stream mitigation addresses most of the 20 percent of total methane emissions in which the gas is released in sufficiently high concentrations for flaring. Plata’s zeolite filter aims to address the thornier challenge of reducing the 80 percent of non-flammable dilute emissions. 

      Plata found inspiration in decades-old catalysis research for turning methane into methanol. One strategy has been to use an abundant, low-cost aluminosilicate clay called zeolite.  

      “The methanol creation process is challenging because you need to separate a liquid, and it has very low efficiency,” says Plata. “Yet zeolite can be very efficient at converting methane into CO2, and it is much easier because it does not require liquid separation. Converting methane to CO2 sounds like a bad thing, but there is a major anti-warming benefit. And because methane is much more dilute than CO2, the relative CO2 contribution is minuscule.”  

      Using zeolite to create methanol requires highly concentrated methane, high temperatures and pressures, and industrial processing conditions. Yet Plata’s process, which dopes the zeolite with copper, operates in the presence of oxygen at much lower temperatures under typical pressures. “We let the methane proceed the way it wants from a thermodynamic perspective from methane to methanol down to CO2,” says Plata. 

      Researchers around the world are working on other dilute methane removal technologies. Projects include spraying iron salt aerosols into sea air where they react with natural chlorine or bromine radicals, thereby capturing methane. Most of these geoengineering solutions, however, are difficult to measure and would require massive scale to make a difference.  

      Plata is focusing her zeolite filters on environments where concentrations are high, but not so high as to be flammable. “We are trying to scale zeolite into filters that you could snap onto the side of a cross-ventilation fan in a dairy barn or in a ventilation air shaft in a coal mine,” says Plata. “For every packet of air we bring in, we take a lot of methane out, so we get more bang for our buck.”  

      The major challenge is creating a filter that can handle high flow rates without getting clogged or falling apart. Dairy barn air handlers can push air at up to 5,000 cubic feet per minute and coal mine handlers can approach 500,000 CFM. 

      Plata is exploring engineering options including fluidized bed reactors with floating catalyst particles. Another filter solution, based in part on catalytic converters, features “higher-order geometric structures where you have a porous material with a long path length where the gas can interact with the catalyst,” says Plata. “This avoids the challenge with fluidized beds of containing catalyst particles in the reactor. Instead, they are fixed within a structured material.”  

      Competing technologies for removing methane from mine shafts “operate at temperatures of 1,000 to 1,200 degrees C, requiring a lot of energy and risking explosion,” says Plata. “Our technology avoids safety concerns by operating at 300 to 400 degrees C. It reduces energy use and provides more tractable deployment costs.” 

      Potentially, energy and dollar costs could be further reduced in coal mines by capturing the heat generated by the conversion process. “In coal mines, you have enrichments above a half-percent methane, but below the 4 percent flammability threshold,” says Plata. “The excess heat from the process could be used to generate electricity using off-the-shelf converters.” 

      Plata’s dairy barn research is funded by the Gerstner Family Foundation and the coal mining project by the U.S. Department of Energy. “The DOE would like us to spin out the technology for scale-up within three years,” says Plata. “We cannot guarantee we will hit that goal, but we are trying to develop this as quickly as possible. Our society needs to start reducing methane emissions now.”  More

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      in Energy

      Taking a magnifying glass to data center operations

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      When the MIT Lincoln Laboratory Supercomputing Center (LLSC) unveiled its TX-GAIA supercomputer in 2019, it provided the MIT community a powerful new resource for applying artificial intelligence to their research. Anyone at MIT can submit a job to the system, which churns through trillions of operations per second to train models for diverse applications, such as spotting tumors in medical images, discovering new drugs, or modeling climate effects. But with this great power comes the great responsibility of managing and operating it in a sustainable manner — and the team is looking for ways to improve.

      “We have these powerful computational tools that let researchers build intricate models to solve problems, but they can essentially be used as black boxes. What gets lost in there is whether we are actually using the hardware as effectively as we can,” says Siddharth Samsi, a research scientist in the LLSC. 

      To gain insight into this challenge, the LLSC has been collecting detailed data on TX-GAIA usage over the past year. More than a million user jobs later, the team has released the dataset open source to the computing community.

      Their goal is to empower computer scientists and data center operators to better understand avenues for data center optimization — an important task as processing needs continue to grow. They also see potential for leveraging AI in the data center itself, by using the data to develop models for predicting failure points, optimizing job scheduling, and improving energy efficiency. While cloud providers are actively working on optimizing their data centers, they do not often make their data or models available for the broader high-performance computing (HPC) community to leverage. The release of this dataset and associated code seeks to fill this space.

      “Data centers are changing. We have an explosion of hardware platforms, the types of workloads are evolving, and the types of people who are using data centers is changing,” says Vijay Gadepally, a senior researcher at the LLSC. “Until now, there hasn’t been a great way to analyze the impact to data centers. We see this research and dataset as a big step toward coming up with a principled approach to understanding how these variables interact with each other and then applying AI for insights and improvements.”

      Papers describing the dataset and potential applications have been accepted to a number of venues, including the IEEE International Symposium on High-Performance Computer Architecture, the IEEE International Parallel and Distributed Processing Symposium, the Annual Conference of the North American Chapter of the Association for Computational Linguistics, the IEEE High-Performance and Embedded Computing Conference, and International Conference for High Performance Computing, Networking, Storage and Analysis. 

      Workload classification

      Among the world’s TOP500 supercomputers, TX-GAIA combines traditional computing hardware (central processing units, or CPUs) with nearly 900 graphics processing unit (GPU) accelerators. These NVIDIA GPUs are specialized for deep learning, the class of AI that has given rise to speech recognition and computer vision.

      The dataset covers CPU, GPU, and memory usage by job; scheduling logs; and physical monitoring data. Compared to similar datasets, such as those from Google and Microsoft, the LLSC dataset offers “labeled data, a variety of known AI workloads, and more detailed time series data compared with prior datasets. To our knowledge, it’s one of the most comprehensive and fine-grained datasets available,” Gadepally says. 

      Notably, the team collected time-series data at an unprecedented level of detail: 100-millisecond intervals on every GPU and 10-second intervals on every CPU, as the machines processed more than 3,000 known deep-learning jobs. One of the first goals is to use this labeled dataset to characterize the workloads that different types of deep-learning jobs place on the system. This process would extract features that reveal differences in how the hardware processes natural language models versus image classification or materials design models, for example.   

      The team has now launched the MIT Datacenter Challenge to mobilize this research. The challenge invites researchers to use AI techniques to identify with 95 percent accuracy the type of job that was run, using their labeled time-series data as ground truth.

      Such insights could enable data centers to better match a user’s job request with the hardware best suited for it, potentially conserving energy and improving system performance. Classifying workloads could also allow operators to quickly notice discrepancies resulting from hardware failures, inefficient data access patterns, or unauthorized usage.

      Too many choices

      Today, the LLSC offers tools that let users submit their job and select the processors they want to use, “but it’s a lot of guesswork on the part of users,” Samsi says. “Somebody might want to use the latest GPU, but maybe their computation doesn’t actually need it and they could get just as impressive results on CPUs, or lower-powered machines.”

      Professor Devesh Tiwari at Northeastern University is working with the LLSC team to develop techniques that can help users match their workloads to appropriate hardware. Tiwari explains that the emergence of different types of AI accelerators, GPUs, and CPUs has left users suffering from too many choices. Without the right tools to take advantage of this heterogeneity, they are missing out on the benefits: better performance, lower costs, and greater productivity.

      “We are fixing this very capability gap — making users more productive and helping users do science better and faster without worrying about managing heterogeneous hardware,” says Tiwari. “My PhD student, Baolin Li, is building new capabilities and tools to help HPC users leverage heterogeneity near-optimally without user intervention, using techniques grounded in Bayesian optimization and other learning-based optimization methods. But, this is just the beginning. We are looking into ways to introduce heterogeneity in our data centers in a principled approach to help our users achieve the maximum advantage of heterogeneity autonomously and cost-effectively.”

      Workload classification is the first of many problems to be posed through the Datacenter Challenge. Others include developing AI techniques to predict job failures, conserve energy, or create job scheduling approaches that improve data center cooling efficiencies.

      Energy conservation 

      To mobilize research into greener computing, the team is also planning to release an environmental dataset of TX-GAIA operations, containing rack temperature, power consumption, and other relevant data.

      According to the researchers, huge opportunities exist to improve the power efficiency of HPC systems being used for AI processing. As one example, recent work in the LLSC determined that simple hardware tuning, such as limiting the amount of power an individual GPU can draw, could reduce the energy cost of training an AI model by 20 percent, with only modest increases in computing time. “This reduction translates to approximately an entire week’s worth of household energy for a mere three-hour time increase,” Gadepally says.

      They have also been developing techniques to predict model accuracy, so that users can quickly terminate experiments that are unlikely to yield meaningful results, saving energy. The Datacenter Challenge will share relevant data to enable researchers to explore other opportunities to conserve energy.

      The team expects that lessons learned from this research can be applied to the thousands of data centers operated by the U.S. Department of Defense. The U.S. Air Force is a sponsor of this work, which is being conducted under the USAF-MIT AI Accelerator.

      Other collaborators include researchers at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). Professor Charles Leiserson’s Supertech Research Group is investigating performance-enhancing techniques for parallel computing, and research scientist Neil Thompson is designing studies on ways to nudge data center users toward climate-friendly behavior.

      Samsi presented this work at the inaugural AI for Datacenter Optimization (ADOPT’22) workshop last spring as part of the IEEE International Parallel and Distributed Processing Symposium. The workshop officially introduced their Datacenter Challenge to the HPC community.

      “We hope this research will allow us and others who run supercomputing centers to be more responsive to user needs while also reducing the energy consumption at the center level,” Samsi says. More