More stories

  • in

    Sustainable supply chains put the customer first

    When we consider the supply chain, we typically think of factories, ships, trucks, and warehouses. Yet, the customer side is equally important, especially in efforts to make our distribution networks more sustainable. Customers are an untapped resource in building sustainability, says Josué C. Velázquez Martínez, a research scientist at MIT Center for Transportation and Logistics. 

    Velázquez Martínez, who is director of MIT’s Sustainable Supply Chain Lab, investigates how customer-facing supply chains can be made more environmentally and socially sustainable. One way is a Green Button project that explores how to optimize e-commerce delivery schedules to reduce carbon emissions and persuade customers to use less carbon-intensive four- or five-day shipping options instead of one or two days. Velázquez Martínez has also launched the MIT Low Income Firms Transformation (LIFT) Lab that is researching ways to improve micro-retailer supply chains in the developing world to provide owners with the necessary tools for survival.  

    “The definition of sustainable supply chain keeps evolving because things that were sustainable 20 to 30 years ago are not as sustainable now,” says Velázquez Martínez. “Today, there are more companies that are capturing information to build strategies for environmental, economic, and social sustainability. They are investing in alternative energy and other solutions to make the supply chain more environmentally friendly and are tracking their suppliers and identifying key vulnerabilities. A big part of this is an attempt to create fairer conditions for people who work in supply chains or are dependent on them.”

    Play video

    The move toward sustainable supply chain is being driven as much by people as by companies, whether they are playing the role of selective consumer or voting citizens. The consumer aspect is often overlooked, says Velázquez Martínez. “Consumers are the ones who move the supply chain. We are looking at how companies can provide transparency to involve customers in their sustainability strategy.” 

    Proposed solutions for sustainability are not always as effective as promised. Some fashion rental schemes fall into this category, says Velázquez Martínez. “There are many new rental companies that are trying to get more use out of clothes to offset the emissions associated with production. We recently researched the environmental impact of monthly subscription models where consumers pay a fee to receive clothes for a month before returning them, as well as peer-to-peer sharing models.” 

    The researchers found that while rental services generally have a lower carbon footprint than retail sales, hidden emissions from logistics played a surprisingly large role. “First, you need to deliver the clothes and pick them up, and there are high return rates,” says Velázquez Martínez. “When you factor in dry cleaning and packaging emissions, the rental models in some cases have a worse carbon footprint than buying new clothes.” Peer-to-peer sharing could be better, he adds, but that depends on how far the consumers travel to meet-up points. 

    Typically, says Velázquez Martínez, garment types that are frequently used are not well suited to rental models. “But for specialty clothes such as wedding dresses or prom dresses, it is better to rent.” 

    Waiting a few days to save the planet 

    Even before the pandemic, online retailing gained a second wind due to low-cost same- and next-day delivery options. While e-commerce may have its drawbacks as a contributor to social isolation and reduced competition, it has proven itself to be far more eco-friendly than brick-and-mortar shopping, not to mention a lot more convenient. Yet rapid deliveries are cutting into online-shopping’s carbon-cutting advantage.

    In 2019, MIT’s Sustainable Supply Chain Lab launched a Green Bottle project to study the rapid delivery phenomenon. The project has been “testing whether consumers would be willing to delay their e-commerce deliveries to reduce the environmental impact of fast shipping,” says Velázquez Martínez. “Many companies such as Walmart and Target have followed Amazon’s 2019 strategy of moving from two-day to same-day delivery. Instead of sending a fully loaded truck to a neighborhood every few days, they now send multiple trucks to that neighborhood every day, and there are more days when trucks are targeting each neighborhood. All this increases carbon emissions and makes it hard for shippers to consolidate. ”  

    Working with Coppel, one of Mexico’s largest retailers, the Green Button project inspired a related Consolidation Ecommerce Project that built a large-scale mathematical model to provide a strategy for consolidation. The model determined what delivery time window each neighborhood demands and then calculated the best day to deliver to each neighborhood to meet the desired window while minimizing carbon emissions. 

    No matter what mixture of delivery times was used, the consolidation model helped retailers schedule deliveries more efficiently. Yet, the biggest cuts in emissions emerged when customers were willing to wait several days.

    Play video

    “When we ran a month-long simulation comparing our model for four-to-five-day delivery with Coppel’s existing model for one- or two-day delivery, we saw savings in fuel consumption of over 50 percent on certain routes” says Velázquez Martínez. “This is huge compared to other strategies for squeezing more efficiency from the last-mile supply chain, such as routing optimization, where savings are close to 5 percent. The optimal solution depends on factors such as the capacity for consolidation, the frequency of delivery, the store capacity, and the impact on inbound operations.” 

    The researchers next set out to determine if customers could be persuaded to wait longer for deliveries. Considering that the price differential is low or nonexistent, this was a considerable challenge. Yet, the same day habit is only a few years old, and some consumers have come to realize they don’t always need rapid deliveries. “Some consumers who order by rapid delivery find they are too busy to open the packages right away,” says Velázquez Martínez.  

    Trees beat kilograms of CO2

    The researchers set out to find if consumers would be willing to sacrifice a bit of convenience if they knew they were helping to reduce climate change. The Green Button project tested different public outreach strategies. For one test group, they reported the carbon impact of delivery times in kilograms of carbon dioxide (CO2). Another group received the information expressed in terms of the energy required to recycle a certain amount of garbage. A third group learned about emissions in terms of the number of trees required to trap the carbon. “Explaining the impact in terms of trees led to almost 90 percent willing to wait another day or two,” says Velázquez Martínez. “This is compared to less than 40 percent for the group that received the data in kilograms of CO2.” 

    Another surprise was that there was no difference in response based on income, gender, or age. “Most studies of green consumers suggest they are predominantly high income, female, highly educated, or younger,” says Velázquez Martínez. “However, our results show that the differences were the same between low and high income, women and men, and younger and older people. We have shown that disclosing emissions transparently and making the consumer a part of the strategy can be a new opportunity for more consumer-driven logistics sustainability.” 

    The researchers are now developing similar models for business-to-business (B2B) e-commerce. “We found that B2B supply chain emissions are often high because many shipping companies require strict delivery windows,” says Velázquez Martínez.  

    The B2B models drill down to examine the Corporate Value Chain (Scope 3) emissions of suppliers. “Although some shipping companies are now asking their suppliers to review emissions, it is a challenge to create a transparent supply chain,” says Velázquez Martínez.  “Technological innovations have made it easier, starting with RFID [radio frequency identification], and then real-time GPS mapping and blockchain. But these technologies need to be more accessible and affordable, and we need more companies willing to use them.” 

    Some companies have been hesitant to dig too deeply into their supply chain, fearing they might uncover a scandal that might risk their reputation, says Velázquez Martínez. Other organizations are forced to look at the issue when nongovernmental organizations research sustainability issues such as social injustice in sweat shops and conflict mineral mines. 

    One challenge to building a transparent supply chain is that “in many companies, the sustainability teams are separate from the rest of the company,” says Velázquez Martínez. “Even if the CEOs receive information on sustainability issues, it often doesn’t filter down because the information does not belong to the planners or managers. We are pushing companies to not only account for sustainability factors in supply chain network design but also examine daily operations that affect sustainability. This is a big topic now: How can we translate sustainability information into something that everybody can understand and use?” 

    LIFT Lab lifts micro-retailers  

    In 2016, Velázquez Martínez launched the MIT GeneSys project to gain insights into micro and small enterprises (MSEs) in developing countries. The project released a GeneSys mobile app, which was used by more than 500 students throughout Latin America to collect data on more than 800 microfirms. In 2022, he launched the LIFT Lab, which focuses more specifically on studying and improving the supply chain for MSEs.  

    Worldwide, some 90 percent of companies have fewer than 10 employees. In Latin America and the Caribbean, companies with fewer than 50 employees represent 99 percent of all companies and 47 percent of employment. 

    Although MSEs represent much of the world’s economy, they are poorly understood, notes Velázquez Martínez. “Those tiny businesses are driving a lot of the economy and serve as important customers for the large companies working in developing countries. They range from small businesses down to people trying to get some money to eat by selling cakes or tacos through their windows.”  

    The MIT LIFT Lab researchers investigated whether MSE supply chain issues could help shed light on why many Latin American countries have been limited to marginal increases in gross domestic product. “Large companies from the developed world that are operating in Latin America, such as Unilever, Walmart, and Coca-Cola, have huge growth there, in some cases higher than they have in the developed world,” says Velázquez Martínez. “Yet, the countries are not developing as fast as we would expect.” 

    The LIFT Lab data showed that while the multinationals are thriving in Latin America, the local MSEs are decreasing in productivity. The study also found the trend has worsened with Covid-19.  

    The LIFT Lab’s first big project, which is sponsored by Mexican beverage and retail company FEMSA, is studying supply chains in Mexico. The study spans 200,000 micro-retailers and 300,000 consumers. In a collaboration with Tecnológico de Monterrey, hundreds of students are helping with a field study.  

    “We are looking at supply chain management and business capabilities and identifying the challenges to adoption of technology and digitalization,” says Velázquez Martínez. “We want to find the best ways for micro-firms to work with suppliers and consumers by identifying the consumers who access this market, as well as the products and services that can best help the micro-firms drive growth.” 

    Based on the earlier research by GeneSys, Velázquez Martínez has developed some hypotheses for potential improvements for micro-retailer supply chain, starting with payment terms. “We found that the micro-firms often get the worst purchasing deals. Owners without credit cards and with limited cash often buy in smaller amounts at much higher prices than retailers like Walmart. The big suppliers are squeezing them.” 

    While large retailers usually get 60 to 120 days to pay, micro-retailers “either pay at the moment of the transaction or in advance,” says Velázquez Martínez. “In a study of 500 micro-retailers in five countries in Latin America, we found the average payment time was minus seven days payment in advance. These terms reduce cash availability and often lead to bankruptcy.” 

    LIFT Lab is working with suppliers to persuade them to offer a minimum payment time of two weeks. “We can show the suppliers that the change in terms will let them move more product and increase sales,” says Velázquez Martínez. “Meanwhile, the micro-retailers gain higher profits and become more stable, even if they may pay a bit more.” 

    LIFT Lab is also looking at ways that micro-retailers can leverage smartphones for digitalization and planning. “Some of these companies are keeping records on napkins,” says Velázquez Martínez. “By using a cellphone, they can charge orders to suppliers and communicate with consumers. We are testing different dashboards for mobile apps to help with planning and financial performance. We are also recommending services the stores can provide, such as paying electricity or water bills. The idea is to build more capabilities and knowledge and increase business competencies for the supply chain that are tailored for micro-retailers.” 

    From a financial perspective, micro-retailers are not always the most efficient way to move products. Yet they also play an important role in building social cohesion within neighborhoods. By offering more services, the corner bodega can bring people together in ways that are impossible with e-commerce and big-box stores.  

    Whether the consumers are micro-firms buying from suppliers or e-commerce customers waiting for packages, “transparency is key to building a sustainable supply chain,” says Velázquez Martínez. “To change consumer habits, consumers need to be better educated on the impacts of their behaviors. With consumer-facing logistics, ‘The last shall be first, and the first last.’” More

  • in

    Q&A: Climate Grand Challenges finalists on new pathways to decarbonizing industry

    Note: This is the third article in a four-part interview series highlighting the work of the 27 MIT Climate Grand Challenges finalist teams, which received a total of $2.7 million in startup funding to advance their projects. In April, the Institute will name a subset of the finalists as multiyear flagship projects.

    The industrial sector is the backbone of today’s global economy, yet its activities are among the most energy-intensive and the toughest to decarbonize. Efforts to reach net-zero targets and avert runaway climate change will not succeed without new solutions for replacing sources of carbon emissions with low-carbon alternatives and developing scalable nonemitting applications of hydrocarbons.

    In conversations prepared for MIT News, faculty from three of the teams with projects in the competition’s “Decarbonizing complex industries and processes” category discuss strategies for achieving impact in hard-to-abate sectors, from long-distance transportation and building construction to textile manufacturing and chemical refining. The other Climate Grand Challenges research themes include using data and science to forecast climate-related risk, building equity and fairness into climate solutions, and removing, managing, and storing greenhouse gases. The following responses have been edited for length and clarity.

    Moving toward an all-carbon material approach to building

    Faced with the prospect of building stock doubling globally by 2050, there is a great need for sustainable alternatives to conventional mineral- and metal-based construction materials. Mark Goulthorpe, associate professor in the Department of Architecture, explains the methods behind Carbon >Building, an initiative to develop energy-efficient building materials by reorienting hydrocarbons from current use as fuels to environmentally benign products, creating an entirely new genre of lightweight, all-carbon buildings that could actually drive decarbonization.

    Q: What are all-carbon buildings and how can they help mitigate climate change?

    A: Instead of burning hydrocarbons as fuel, which releases carbon dioxide and other greenhouse gases that contribute to atmospheric pollution, we seek to pioneer a process that uses carbon materially to build at macro scale. New forms of carbon — carbon nanotube, carbon foam, etc. — offer salient properties for building that might effectively displace the current material paradigm. Only hydrocarbons offer sufficient scale to beat out the billion-ton mineral and metal markets, and their perilous impact. Carbon nanotube from methane pyrolysis is of special interest, as it offers hydrogen as a byproduct.

    Q: How will society benefit from the widespread use of all-carbon buildings?

    A: We anticipate reducing costs and timelines in carbon composite buildings, while increasing quality, longevity, and performance, and diminishing environmental impact. Affordability of buildings is a growing problem in all global markets as the cost of labor and logistics in multimaterial assemblies creates a burden that is very detrimental to economic growth and results in overcrowding and urban blight.

    Alleviating these challenges would have huge societal benefits, especially for those in lower income brackets who cannot afford housing, but the biggest benefit would be in drastically reducing the environmental footprint of typical buildings, which account for nearly 40 percent of global energy consumption.

    An all-carbon building sector will not only reduce hydrocarbon extraction, but can produce higher value materials for building. We are looking to rethink the building industry by greatly streamlining global production and learning from the low-labor methods pioneered by composite manufacturing such as wind turbine blades, which are quick and cheap to produce. This technology can improve the sustainability and affordability of buildings — and holds the promise of faster, cheaper, greener, and more resilient modes of dwelling.

    Emissions reduction through innovation in the textile industry

    Collectively, the textile industry is responsible for over 4 billion metric tons of carbon dioxide equivalent per year, or 5 to 10 percent of global greenhouse gas emissions — more than aviation and maritime shipping combined. And the problem is only getting worse with the industry’s rapid growth. Under the current trajectory, consumption is projected to increase 30 percent by 2030, reaching 102 million tons. A diverse group of faculty and researchers led by Gregory Rutledge, the Lammot du Pont Professor in the Department of Chemical Engineering, and Yuly Fuentes-Medel, project manager for fiber technologies and research advisor to the MIT Innovation Initiative, is developing groundbreaking innovations to reshape how textiles are selected, sourced, designed, manufactured, and used, and to create the structural changes required for sustained reductions in emissions by this industry.

    Q: Why has the textile industry been difficult to decarbonize?

    A: The industry currently operates under a linear model that relies heavily on virgin feedstock, at roughly 97 percent, yet recycles or downcycles less than 15 percent. Furthermore, recent trends in “fast fashion” have led to massive underutilization of apparel, such that products are discarded on average after only seven to 10 uses. In an industry with high volume and low margins, replacement technologies must achieve emissions reduction at scale while maintaining performance and economic efficiency.

    There are also technical barriers to adopting circular business models, from the challenge of dealing with products comprising fiber blends and chemical additives to the low maturity of recycling technologies. The environmental impacts of textiles and apparel have been estimated using life cycle analysis, and industry-standard indexes are under development to assess sustainability throughout the life cycle of a product, but information and tools are needed to model how new solutions will alter those impacts and include the consumer as an active player to keep our planet safe. This project seeks to deliver both the new solutions and the tools to evaluate their potential for impact.

    Q: Describe the five components of your program. What is the anticipated timeline for implementing these solutions?

    A: Our plan comprises five programmatic sections, which include (1) enabling a paradigm shift to sustainable materials using nontraditional, carbon-negative polymers derived from biomass and additives that facilitate recycling; (2) rethinking manufacturing with processes to structure fibers and fabrics for performance, waste reduction, and increased material efficiency; (3) designing textiles for value by developing products that are customized, adaptable, and multifunctional, and that interact with their environment to reduce energy consumption; (4) exploring consumer behavior change through human interventions that reduce emissions by encouraging the adoption of new technologies, increased utilization of products, and circularity; and (5) establishing carbon transparency with systems-level analyses that measure the impact of these strategies and guide decision making.

    We have proposed a five-year timeline with annual targets for each project. Conservatively, we estimate our program could reduce greenhouse gas emissions in the industry by 25 percent by 2030, with further significant reductions to follow.

    Tough-to-decarbonize transportation

    Airplanes, transoceanic ships, and freight trucks are critical to transporting people and delivering goods, and the cornerstone of global commerce, manufacturing, and tourism. But these vehicles also emit 3.7 billion tons of carbon dioxide annually and, left unchecked, they could take up a quarter of the remaining carbon budget by 2050. William Green, the Hoyt C. Hottel Professor in the Department Chemical Engineering, co-leads a multidisciplinary team with Steven Barrett, professor of aeronautics and astronautics and director of the MIT Laboratory for Aviation and the Environment, that is working to identify and advance economically viable technologies and policies for decarbonizing heavy duty trucking, shipping, and aviation. The Tough to Decarbonize Transportation research program aims to design and optimize fuel chemistry and production, vehicles, operations, and policies to chart the course to net-zero emissions by midcentury.

    Q: What are the highest priority focus areas of your research program?

    A: Hydrocarbon fuels made from biomass are the least expensive option, but it seems impractical, and probably damaging to the environment, to harvest the huge amount of biomass that would be needed to meet the massive and growing energy demands from these sectors using today’s biomass-to-fuel technology. We are exploring strategies to increase the amount of useful fuel made per ton of biomass harvested, other methods to make low-climate-impact hydrocarbon fuels, such as from carbon dioxide, and ways to make fuels that do not contain carbon at all, such as with hydrogen, ammonia, and other hydrogen carriers.

    These latter zero-carbon options free us from the need for biomass or to capture gigatons of carbon dioxide, so they could be a very good long-term solution, but they would require changing the vehicles significantly, and the construction of new refueling infrastructure, with high capital costs.

    Q: What are the scientific, technological, and regulatory barriers to scaling and implementing potential solutions?

    A: Reimagining an aviation, trucking, and shipping sector that connects the world and increases equity without creating more environmental damage is challenging because these vehicles must operate disconnected from the electrical grid and have energy requirements that cannot be met by batteries alone. Some of the concepts do not even exist in prototype yet, and none of the appealing options have been implemented at anywhere near the scale required.

    In most cases, we do not know the best way to make the fuel, and for new fuels the vehicles and refueling systems all need to be developed. Also, new fuels, or large-scale use of biomass, will introduce new environmental problems that need to be carefully considered, to ensure that decarbonization solutions do not introduce big new problems.

    Perhaps most difficult are the policy, economic, and equity issues. A new long-haul transportation system will be expensive, and everyone will be affected by the increased cost of shipping freight. To have the desired climate impact, the transport system must change in almost every country. During the transition period, we will need both the existing vehicle and fuel system to keep running smoothly, even as a new low-greenhouse system is introduced. We will also examine what policies could make that work and how we can get countries around the world to agree to implement them. More

  • in

    New maps show airplane contrails over the U.S. dropped steeply in 2020

    As Covid-19’s initial wave crested around the world, travel restrictions and a drop in passengers led to a record number of grounded flights in 2020. The air travel reduction cleared the skies of not just jets but also the fluffy white contrails they produce high in the atmosphere.

    MIT engineers have mapped the contrails that were generated over the United States in 2020, and compared the results to prepandemic years. They found that on any given day in 2018, and again in 2019, contrails covered a total area equal to Massachusetts and Connecticut combined. In 2020, this contrail coverage shrank by about 20 percent, mirroring a similar drop in U.S. flights.  

    While 2020’s contrail dip may not be surprising, the findings are proof that the team’s mapping technique works. Their study marks the first time researchers have captured the fine and ephemeral details of contrails over a large continental scale.

    Now, the researchers are applying the technique to predict where in the atmosphere contrails are likely to form. The cloud-like formations are known to play a significant role in aviation-related global warming. The team is working with major airlines to forecast regions in the atmosphere where contrails may form, and to reroute planes around these regions to minimize contrail production.

    “This kind of technology can help divert planes to prevent contrails, in real time,” says Steven Barrett, professor and associate head of MIT’s Department of Aeronautics and Astronautics. “There’s an unusual opportunity to halve aviation’s climate impact by eliminating most of the contrails produced today.”

    Barrett and his colleagues have published their results today in the journal Environmental Research Letters. His co-authors at MIT include graduate student Vincent Meijer, former graduate student Luke Kulik, research scientists Sebastian Eastham, Florian Allroggen, and Raymond Speth, and LIDS Director and professor Sertac Karaman.

    Trail training

    About half of the aviation industry’s contribution to global warming comes directly from planes’ carbon dioxide emissions. The other half is thought to be a consequence of their contrails. The signature white tails are produced when a plane’s hot, humid exhaust mixes with cool humid air high in the atmosphere. Emitted in thin lines, contrails quickly spread out and can act as blankets that trap the Earth’s outgoing heat.

    While a single contrail may not have much of a warming effect, taken together contrails have a significant impact. But the estimates of this effect are uncertain and based on computer modeling as well as limited satellite data. What’s more, traditional computer vision algorithms that analyze contrail data have a hard time discerning the wispy tails from natural clouds.

    To precisely pick out and track contrails over a large scale, the MIT team looked to images taken by NASA’s GOES-16, a geostationary satellite that hovers over the same swath of the Earth, including the United States, taking continuous, high-resolution images.

    The team first obtained about 100 images taken by the satellite, and trained a set of people to interpret remote sensing data and label each image’s pixel as either part of a contrail or not. They used this labeled dataset to train a computer-vision algorithm to discern a contrail from a cloud or other image feature.

    The researchers then ran the algorithm on about 100,000 satellite images, amounting to nearly 6 trillion pixels, each pixel representing an area of about 2 square kilometers. The images covered the contiguous U.S., along with parts of Canada and Mexico, and were taken about every 15 minutes, between Jan. 1, 2018, and Dec. 31, 2020.

    The algorithm automatically classified each pixel as either a contrail or not a contrail, and generated daily maps of contrails over the United States. These maps mirrored the major flight paths of most U.S. airlines, with some notable differences. For instance, contrail “holes” appeared around major airports, which reflects the fact that planes landing and taking off around airports are generally not high enough in the atmosphere for contrails to form.

    “The algorithm knows nothing about where planes fly, and yet when processing the satellite imagery, it resulted in recognizable flight routes,” Barrett says. “That’s one piece of evidence that says this method really does capture contrails over a large scale.”

    Cloudy patterns

    Based on the algorithm’s maps, the researchers calculated the total area covered each day by contrails in the US. On an average day in 2018 and in 2019, U.S. contrails took up about 43,000 square kilometers. This coverage dropped by 20 percent in March of 2020 as the pandemic set in. From then on, contrails slowly reappeared as air travel resumed through the year.

    The team also observed daily and seasonal patterns. In general, contrails appeared to peak in the morning and decline in the afternoon. This may be a training artifact: As natural cirrus clouds are more likely to form in the afternoon, the algorithm may have trouble discerning contrails amid the clouds later in the day. But it might also be an important indication about when contrails form most. Contrails also peaked in late winter and early spring, when more of the air is naturally colder and more conducive for contrail formation.

    The team has now adapted the technique to predict where contrails are likely to form in real time. Avoiding these regions, Barrett says, could take a significant, almost immediate chunk out of aviation’s global warming contribution.  

    “Most measures to make aviation sustainable take a long time,” Barrett says. “(Contrail avoidance) could be accomplished in a few years, because it requires small changes to how aircraft are flown, with existing airplanes and observational technology. It’s a near-term way of reducing aviation’s warming by about half.”

    The team is now working towards this objective of large-scale contrail avoidance using realtime satellite observations.

    This research was supported in part by NASA and the MIT Environmental Solutions Initiative. More

  • in

    3 Questions: What a single car can say about traffic

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  • in

    3 Questions: Anuradha Annaswamy on building smart infrastructures

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  • in

    MIT Energy Initiative launches the Future Energy Systems Center

    The MIT Energy Initiative (MITEI) has launched a new research consortium — the Future Energy Systems Center — to address the climate crisis and the role energy systems can play in solving it. This integrated effort engages researchers from across all of MIT to help the global community reach its goal of net-zero carbon emissions. The center examines the accelerating energy transition and collaborates with industrial leaders to reform the world’s energy systems. The center is part of “Fast Forward: MIT’s Climate Action Plan for the Decade,” MIT’s multi-pronged effort announced last year to address the climate crisis.

    The Future Energy Systems Center investigates the emerging technology, policy, demographics, and economics reshaping the landscape of energy supply and demand. The center conducts integrative analysis of the entire energy system — a holistic approach essential to understanding the cross-sectorial impact of the energy transition.

    “We must act quickly to get to net-zero greenhouse gas emissions. At the same time, we have a billion people around the world with inadequate access, or no access, to electricity — and we need to deliver it to them,” says MITEI Director Robert C. Armstrong, the Chevron Professor of Chemical Engineering. “The Future Energy Systems Center combines MIT’s deep knowledge of energy science and technology with advanced tools for systems analysis to examine how advances in technology and system economics may respond to various policy scenarios.”  

    The overarching focus of the center is integrative analysis of the entire energy system, providing insights into the complex multi-sectorial transformations needed to alter the three major energy-consuming sectors of the economy — transportation, industry, and buildings — in conjunction with three major decarbonization-enabling technologies — electricity, energy storage and low-carbon fuels, and carbon management. “Deep decarbonization of our energy system requires an economy-wide perspective on the technology options, energy flows, materials flows, life-cycle emissions, costs, policies, and socioeconomics consequences,” says Randall Field, the center’s executive director. “A systems approach is essential in enabling cross-disciplinary teams to work collaboratively together to address the existential crisis of climate change.”

    Through techno-economic and systems-oriented research, the center analyzes these important interactions. For example:

    •  Increased reliance on variable renewable energy, such as wind and solar, and greater electrification of transportation, industry, and buildings will require expansion of demand management and other solutions for balancing of electricity supply and demand across these areas.

    •  Likewise, balancing supply and demand will require deploying grid-scale energy storage and converting the electricity to low-carbon fuels (hydrogen and liquid fuels), which can in turn play a vital role in the energy transition for hard-to-decarbonize segments of transportation, industry, and buildings.

    •  Carbon management (carbon dioxide capture from industry point sources and from air and oceans; utilization/conversion to valuable products; transport; storage) will also play a critical role in decarbonizing industry, electricity, and fuels — both as carbon-mitigation and negative-carbon solutions.

    As a member-supported research consortium, the center collaborates with industrial experts and leaders — from both energy’s consumer and supplier sides — to gain insights to help researchers anticipate challenges and opportunities of deploying technology at the scale needed to achieve decarbonization. “The Future Energy Systems Center gives us a powerful way to engage with industry to accelerate the energy transition,” says Armstrong. “Working together, we can better understand how our current technology toolbox can be more effectively put to use now to reduce emissions, and what new technologies and policies will ultimately be needed to reach net-zero.”

    A steering committee, made up of 11 MIT professors and led by Armstrong, selects projects to create a research program with high impact on decarbonization, while leveraging MIT strengths and addressing interests of center members in pragmatic and scalable solutions. “MIT — through our recently released climate action plan — is committed to moving with urgency and speed to help wring carbon dioxide emissions out the global economy to resolve the growing climate crisis,” says Armstrong. “We have no time to waste.”

    The center members to date are: AECI, Analog Devices, Chevron, ConocoPhillips, Copec, Dominion, Duke Energy, Enerjisa, Eneva, Eni, Equinor, Eversource, Exelon, ExxonMobil, Ferrovial, Iberdrola, IHI, National Grid, Raizen, Repsol, Rio Tinto, Shell, Tata Power, Toyota Research Institute, and Washington Gas. More

  • in

    New visions for better transportation

    We typically experience transportation problems from the ground up. Waiting for a delayed bus, packing ourselves into a subway car, or crawling along in traffic, it is common to see such systems struggling at close range.

    Yet sometimes transportation solutions come from a high-level, top-down approach. That was the theme of the final talk in MIT’s Mobility Forum series, delivered on Friday by MIT Professor Thomas Magnanti, which centered on applying to transportation the same overarching analytical framework used in other domains, such as bioengineering.

    Magnanti’s remarks focused on a structured approach to problem-solving known as the 4M method — which stands for measuring, mining, modeling, and manipulating. In urban transportation planning, for instance, measuring and mining might involve understanding traffic flows. Modeling might simulate those traffic flows, and manipulating would mean engineering interventions: tolls, one-way streets, or other changes.

    “These are four things that interact quite a bit with each other,” said Magnanti, who is an Institute Professor — MIT’s highest faculty distinction — and a professor of operations research at the MIT Sloan School of Management. “And they provide us with a sense of how you can gather data and understand a system, but also how you can improve it.”

    Magnanti, a leading expert in operations research, pointed out that the 4M method can be applied to systems from physics to biomedical research. He outlined how it might be used to analyze transportations-related systems such as supply chains and warehouse movements.

    In all cases, he noted, applying the 4M concept to a system is an iterative process: Making changes to a system will likely produce new flows — of traffic and goods — and thus be subject to a new set of measurements.

    “One thing to notice here, once you manipulate the system, it changes the data,” Magnanti observed. “You’re doing this so you can hopefully improve operations, but it creates new data. So, you want to measure that new data again, you want to mine it, you want to model it again, and then manipulate it. … This is a continuing loop that we use in these systems.”

    Magnanti’s talk, “Understanding and Improving Transportation Systems,” was delivered online to a public audience of about 175 people. It was the 12th and final event of the MIT Mobility Forum in the fall 2021 semester. The event series is organized by the MIT Mobility Initiative, an Institute-wide effort to research and accelerate the evolution of transportation, at a time when decarbonization in the sector is critical.

    Other MIT Mobility Forum talks have focused on topics such as zero-environmental-impact aviation, measuring pedestrian flows in cities, autonomous vehicles, the impact of high-speed rail and subways on cities, values and equity in mobility design, and more.

    Overall, the forum “offers an opportunity to showcase the groundbreaking transportation research occurring across the Institute,” says Jinhua Zhao, an associate professor of transportation and city planning in MIT’s Department of Urban Studies and Planning, and director of the MIT Mobility Initiative.

    The initiative has held 39 such talks since it launched in 2020, and the series will continue again in the spring semester of 2022.

    One of the principal features of the forum, like the MIT Mobility Initiative in general, is that it “facilitates cross-disciplinary exchanges both within MIT and without,” Zhao says. Faculty and students from every school at MIT have participated in the forum, lending intellectual and methodological diversity to a broad field.

    For his part, Magnanti, who is both an engineer and operations researcher by training, embraced that interdisciplinary approach in his remarks, fielding a variety of audience questions after his talk, about research methods and other issues. Magnanti, who served from 2009 to 2017 as the founding president of the Singapore University of Technology and Design (with which MIT has had research collaborations), noted that the setting can heavily influence transportation research and progress.

    In Singapore, he noted, “They measure everything. They measure how people access the subway … and they use their data.” Of course, Singapore’s status as a city-state of modest size, among other factors, makes comprehensive transportation planning more feasible there. Still, Magnanti also noted that the infrastructure bill recently passed by the U.S. federal government is “going to provide lots of opportunities” for transportation improvements.

    And in general, Magnanti added, one of the best things academic leaders and research communities can do is to “continue to create a sense of excitement. Even when things are tough, the problems are going to be interesting.” More

  • in

    New “risk triage” platform pinpoints compounding threats to US infrastructure

    Over a 36-hour period in August, Hurricane Henri delivered record rainfall in New York City, where an aging storm-sewer system was not built to handle the deluge, resulting in street flooding. Meanwhile, an ongoing drought in California continued to overburden aquifers and extend statewide water restrictions. As climate change amplifies the frequency and intensity of extreme events in the United States and around the world, and the populations and economies they threaten grow and change, there is a critical need to make infrastructure more resilient. But how can this be done in a timely, cost-effective way?

    An emerging discipline called multi-sector dynamics (MSD) offers a promising solution. MSD homes in on compounding risks and potential tipping points across interconnected natural and human systems. Tipping points occur when these systems can no longer sustain multiple, co-evolving stresses, such as extreme events, population growth, land degradation, drinkable water shortages, air pollution, aging infrastructure, and increased human demands. MSD researchers use observations and computer models to identify key precursory indicators of such tipping points, providing decision-makers with critical information that can be applied to mitigate risks and boost resilience in infrastructure and managed resources.

    At MIT, the Joint Program on the Science and Policy of Global Change has since 2018 been developing MSD expertise and modeling tools and using them to explore compounding risks and potential tipping points in selected regions of the United States. In a two-hour webinar on Sept. 15, MIT Joint Program researchers presented an overview of the program’s MSD research tool set and its applications.  

    MSD and the risk triage platform

    “Multi-sector dynamics explores interactions and interdependencies among human and natural systems, and how these systems may adapt, interact, and co-evolve in response to short-term shocks and long-term influences and stresses,” says MIT Joint Program Deputy Director C. Adam Schlosser, noting that such analysis can reveal and quantify potential risks that would likely evade detection in siloed investigations. “These systems can experience cascading effects or failures after crossing tipping points. The real question is not just where these tipping points are in each system, but how they manifest and interact across all systems.”

    To address that question, the program’s MSD researchers have developed the MIT Socio-Environmental Triage (MST) platform, now publicly available for the first time. Focused on the continental United States, the first version of the platform analyzes present-day risks related to water, land, climate, the economy, energy, demographics, health, and infrastructure, and where these compound to create risk hot spots. It’s essentially a screening-level visualization tool that allows users to examine risks, identify hot spots when combining risks, and make decisions about how to deploy more in-depth analysis to solve complex problems at regional and local levels. For example, MST can identify hot spots for combined flood and poverty risks in the lower Mississippi River basin, and thereby alert decision-makers as to where more concentrated flood-control resources are needed.

    Successive versions of the platform will incorporate projections based on the MIT Joint Program’s Integrated Global System Modeling (IGSM) framework of how different systems and stressors may co-evolve into the future and thereby change the risk landscape. This enhanced capability could help uncover cost-effective pathways for mitigating and adapting to a wide range of environmental and economic risks.  

    MSD applications

    Five webinar presentations explored how MIT Joint Program researchers are applying the program’s risk triage platform and other MSD modeling tools to identify potential tipping points and risks in five key domains: water quality, land use, economics and energy, health, and infrastructure. 

    Joint Program Principal Research Scientist Xiang Gao described her efforts to apply a high-resolution U.S. water-quality model to calculate a location-specific, water-quality index over more than 2,000 river basins in the country. By accounting for interactions among climate, agriculture, and socioeconomic systems, various water-quality measures can be obtained ranging from nitrate and phosphate levels to phytoplankton concentrations. This modeling approach advances a unique capability to identify potential water-quality risk hot spots for freshwater resources.

    Joint Program Research Scientist Angelo Gurgel discussed his MSD-based analysis of how climate change, population growth, changing diets, crop-yield improvements and other forces that drive land-use change at the global level may ultimately impact how land is used in the United States. Drawing upon national observational data and the IGSM framework, the analysis shows that while current U.S. land-use trends are projected to persist or intensify between now and 2050, there is no evidence of any concerning tipping points arising throughout this period.  

    MIT Joint Program Research Scientist Jennifer Morris presented several examples of how the risk triage platform can be used to combine existing U.S. datasets and the IGSM framework to assess energy and economic risks at the regional level. For example, by aggregating separate data streams on fossil-fuel employment and poverty, one can target selected counties for clean energy job training programs as the nation moves toward a low-carbon future. 

    “Our modeling and risk triage frameworks can provide pictures of current and projected future economic and energy landscapes,” says Morris. “They can also highlight interactions among different human, built, and natural systems, including compounding risks that occur in the same location.”  

    MIT Joint Program research affiliate Sebastian Eastham, a research scientist at the MIT Laboratory for Aviation and the Environment, described an MSD approach to the study of air pollution and public health. Linking the IGSM with an atmospheric chemistry model, Eastham ultimately aims to better understand where the greatest health risks are in the United States and how they may compound throughout this century under different policy scenarios. Using the risk triage tool to combine current risk metrics for air quality and poverty in a selected county based on current population and air-quality data, he showed how one can rapidly identify cardiovascular and other air-pollution-induced disease risk hot spots.

    Finally, MIT Joint Program research affiliate Alyssa McCluskey, a lecturer at the University of Colorado at Boulder, showed how the risk triage tool can be used to pinpoint potential risks to roadways, waterways, and power distribution lines from flooding, extreme temperatures, population growth, and other stressors. In addition, McCluskey described how transportation and energy infrastructure development and expansion can threaten critical wildlife habitats.

    Enabling comprehensive, location-specific analyses of risks and hot spots within and among multiple domains, the Joint Program’s MSD modeling tools can be used to inform policymaking and investment from the municipal to the global level.

    “MSD takes on the challenge of linking human, natural, and infrastructure systems in order to inform risk analysis and decision-making,” says Schlosser. “Through our risk triage platform and other MSD models, we plan to assess important interactions and tipping points, and to provide foresight that supports action toward a sustainable, resilient, and prosperous world.”

    This research is funded by the U.S. Department of Energy’s Office of Science as an ongoing project. More