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

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

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

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

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

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

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

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

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

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    Study: Shutting down nuclear power could increase air pollution

    Nearly 20 percent of today’s electricity in the United States comes from nuclear power. The U.S. has the largest nuclear fleet in the world, with 92 reactors scattered around the country. Many of these power plants have run for more than half a century and are approaching the end of their expected lifetimes.

    Policymakers are debating whether to retire the aging reactors or reinforce their structures to continue producing nuclear energy, which many consider a low-carbon alternative to climate-warming coal, oil, and natural gas.

    Now, MIT researchers say there’s another factor to consider in weighing the future of nuclear power: air quality. In addition to being a low carbon-emitting source, nuclear power is relatively clean in terms of the air pollution it generates. Without nuclear power, how would the pattern of air pollution shift, and who would feel its effects?

    The MIT team took on these questions in a new study appearing today in Nature Energy. They lay out a scenario in which every nuclear power plant in the country has shut down, and consider how other sources such as coal, natural gas, and renewable energy would fill the resulting energy needs throughout an entire year.

    Their analysis reveals that indeed, air pollution would increase, as coal, gas, and oil sources ramp up to compensate for nuclear power’s absence. This in itself may not be surprising, but the team has put numbers to the prediction, estimating that the increase in air pollution would have serious health effects, resulting in an additional 5,200 pollution-related deaths over a single year.

    If, however, more renewable energy sources become available to supply the energy grid, as they are expected to by the year 2030, air pollution would be curtailed, though not entirely. The team found that even under this heartier renewable scenario, there is still a slight increase in air pollution in some parts of the country, resulting in a total of 260 pollution-related deaths over one year.

    When they looked at the populations directly affected by the increased pollution, they found that Black or African American communities — a disproportionate number of whom live near fossil-fuel plants — experienced the greatest exposure.

    “This adds one more layer to the environmental health and social impacts equation when you’re thinking about nuclear shutdowns, where the conversation often focuses on local risks due to accidents and mining or long-term climate impacts,” says lead author Lyssa Freese, a graduate student in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS).

    “In the debate over keeping nuclear power plants open, air quality has not been a focus of that discussion,” adds study author Noelle Selin, a professor in MIT’s Institute for Data, Systems, and Society (IDSS) and EAPS. “What we found was that air pollution from fossil fuel plants is so damaging, that anything that increases it, such as a nuclear shutdown, is going to have substantial impacts, and for some people more than others.”

    The study’s MIT-affiliated co-authors also include Principal Research Scientist Sebastian Eastham and Guillaume Chossière SM ’17, PhD ’20, along with Alan Jenn of the University of California at Davis.

    Future phase-outs

    When nuclear power plants have closed in the past, fossil fuel use increased in response. In 1985, the closure of reactors in Tennessee Valley prompted a spike in coal use, while the 2012 shutdown of a plant in California led to an increase in natural gas. In Germany, where nuclear power has almost completely been phased out, coal-fired power increased initially to fill the gap.

    Noting these trends, the MIT team wondered how the U.S. energy grid would respond if nuclear power were completely phased out.

    “We wanted to think about what future changes were expected in the energy grid,” Freese says. “We knew that coal use was declining, and there was a lot of work already looking at the impact of what that would have on air quality. But no one had looked at air quality and nuclear power, which we also noticed was on the decline.”

    In the new study, the team used an energy grid dispatch model developed by Jenn to assess how the U.S. energy system would respond to a shutdown of nuclear power. The model simulates the production of every power plant in the country and runs continuously to estimate, hour by hour, the energy demands in 64 regions across the country.

    Much like the way the actual energy market operates, the model chooses to turn a plant’s production up or down based on cost: Plants producing the cheapest energy at any given time are given priority to supply the grid over more costly energy sources.

    The team fed the model available data on each plant’s changing emissions and energy costs throughout an entire year. They then ran the model under different scenarios, including: an energy grid with no nuclear power, a baseline grid similar to today’s that includes nuclear power, and a grid with no nuclear power that also incorporates the additional renewable sources that are expected to be added by 2030.

    They combined each simulation with an atmospheric chemistry model to simulate how each plant’s various emissions travel around the country and to overlay these tracks onto maps of population density. For populations in the path of pollution, they calculated the risk of premature death based on their degree of exposure.

    System response

    Play video

    Courtesy of the researchers, edited by MIT News

    Their analysis showed a clear pattern: Without nuclear power, air pollution worsened in general, mainly affecting regions in the East Coast, where nuclear power plants are mostly concentrated. Without those plants, the team observed an uptick in production from coal and gas plants, resulting in 5,200 pollution-related deaths across the country, compared to the baseline scenario.

    They also calculated that more people are also likely to die prematurely due to climate impacts from the increase in carbon dioxide emissions, as the grid compensates for nuclear power’s absence. The climate-related effects from this additional influx of carbon dioxide could lead to 160,000 additional deaths over the next century.

    “We need to be thoughtful about how we’re retiring nuclear power plants if we are trying to think about them as part of an energy system,” Freese says. “Shutting down something that doesn’t have direct emissions itself can still lead to increases in emissions, because the grid system will respond.”

    “This might mean that we need to deploy even more renewables, in order to fill the hole left by nuclear, which is essentially a zero-emissions energy source,” Selin adds. “Otherwise we will have a reduction in air quality that we weren’t necessarily counting on.”

    This study was supported, in part, by the U.S. Environmental Protection Agency. More

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    Helping the cause of environmental resilience

    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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    New MIT internships expand research opportunities in Africa

    With new support from the Office of the Associate Provost for International Activities, MIT International Science and Technology Initiatives (MISTI) and the MIT-Africa program are expanding internship opportunities for MIT students at universities and leading academic research centers in Africa. This past summer, MISTI supported 10 MIT student interns at African universities, significantly more than in any previous year.

    “These internships are an opportunity to better merge the research ecosystem of MIT with academia-based research systems in Africa,” says Evan Lieberman, the Total Professor of Political Science and Contemporary Africa and faculty director for MISTI.

    For decades, MISTI has helped MIT students to learn and explore through international experiential learning opportunities and internships in industries like health care, education, agriculture, and energy. MISTI’s MIT-Africa Seed Fund supports collaborative research between MIT faculty and Africa-based researchers, and the new student research internship opportunities are part of a broader vision for deeper engagement between MIT and research institutions across the African continent.

    While Africa is home to 12.5 percent of the world’s population, it generates less than 1 percent of scientific research output in the form of academic journal publications, according to the African Academy of Sciences. Research internships are one way that MIT can build mutually beneficial partnerships across Africa’s research ecosystem, to advance knowledge and spawn innovation in fields important to MIT and its African counterparts, including health care, biotechnology, urban planning, sustainable energy, and education.

    Ari Jacobovits, managing director of MIT-Africa, notes that the new internships provide additional funding to the lab hosting the MIT intern, enabling them to hire a counterpart student research intern from the local university. This support can make the internships more financially feasible for host institutions and helps to grow the research pipeline.

    With the support of MIT, State University of Zanzibar (SUZA) lecturers Raya Ahmada and Abubakar Bakar were able to hire local students to work alongside MIT graduate students Mel Isidor and Rajan Hoyle. Together the students collaborated over a summer on a mapping project designed to plan and protect Zanzibar’s coastal economy.

    “It’s been really exciting to work with research peers in a setting where we can all learn alongside one another and develop this project together,” says Hoyle.

    Using low-cost drone technology, the students and their local counterparts worked to create detailed maps of Zanzibar to support community planning around resilience projects designed to combat coastal flooding and deforestation and assess climate-related impacts to seaweed farming activities. 

    “I really appreciated learning about how engagement happens in this particular context and how community members understand local environmental challenges and conditions based on research and lived experience,” says Isidor. “This is beneficial for us whether we’re working in an international context or in the United States.”

    For biology major Shaida Nishat, her internship at the University of Cape Town allowed her to work in a vital sphere of public health and provided her with the chance to work with a diverse, international team headed by Associate Professor Salome Maswine, head of the global surgery division and a widely-renowned expert in global surgery, a multidisciplinary field in the sphere of global health focused on improved and equitable surgical outcomes.

    “It broadened my perspective as to how an effort like global surgery ties so many nations together through a common goal that would benefit them all,” says Nishat, who plans to pursue a career in public health.

    For computer science sophomore Antonio L. Ortiz Bigio, the MISTI research internship in Africa was an incomparable experience, culturally and professionally. Bigio interned at the Robotics Autonomous Intelligence and Learning Laboratory at the University of Witwatersrand in Johannesburg, led by Professor Benjamin Rosman, where he developed software to enable a robot to play chess. The experience has inspired Bigio to continue to pursue robotics and machine learning.

    Participating faculty at the host institutions welcomed their MIT interns, and were impressed by their capabilities. Both Rosman and Maswime described their MIT interns as hard-working and valued team members, who had helped to advance their own work.  

    Building strong global partnerships, whether through faculty research, student internships, or other initiatives, takes time and cultivation, explains Jacobovits. Each successful collaboration helps to seed future exchanges and builds interest at MIT and peer institutions in creative partnerships. As MIT continues to deepen its connections to institutions and researchers across Africa, says Jacobovits, “students like Shaida, Rajan, Mel, and Antonio are really effective ambassadors in building those networks.” More

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    A healthy wind

    Nearly 10 percent of today’s electricity in the United States comes from wind power. The renewable energy source benefits climate, air quality, and public health by displacing emissions of greenhouse gases and air pollutants that would otherwise be produced by fossil-fuel-based power plants.

    A new MIT study finds that the health benefits associated with wind power could more than quadruple if operators prioritized turning down output from the most polluting fossil-fuel-based power plants when energy from wind is available.

    In the study, published today in Science Advances, researchers analyzed the hourly activity of wind turbines, as well as the reported emissions from every fossil-fuel-based power plant in the country, between the years 2011 and 2017. They traced emissions across the country and mapped the pollutants to affected demographic populations. They then calculated the regional air quality and associated health costs to each community.

    The researchers found that in 2014, wind power that was associated with state-level policies improved air quality overall, resulting in $2 billion in health benefits across the country. However, only roughly 30 percent of these health benefits reached disadvantaged communities.

    The team further found that if the electricity industry were to reduce the output of the most polluting fossil-fuel-based power plants, rather than the most cost-saving plants, in times of wind-generated power, the overall health benefits could quadruple to $8.4 billion nationwide. However, the results would have a similar demographic breakdown.

    “We found that prioritizing health is a great way to maximize benefits in a widespread way across the U.S., which is a very positive thing. But it suggests it’s not going to address disparities,” says study co-author Noelle Selin, a professor in the Institute for Data, Systems, and Society and the Department of Earth, Atmospheric and Planetary Sciences at MIT. “In order to address air pollution disparities, you can’t just focus on the electricity sector or renewables and count on the overall air pollution benefits addressing these real and persistent racial and ethnic disparities. You’ll need to look at other air pollution sources, as well as the underlying systemic factors that determine where plants are sited and where people live.”

    Selin’s co-authors are lead author and former MIT graduate student Minghao Qiu PhD ’21, now at Stanford University, and Corwin Zigler at the University of Texas at Austin.

    Turn-down service

    In their new study, the team looked for patterns between periods of wind power generation and the activity of fossil-fuel-based power plants, to see how regional electricity markets adjusted the output of power plants in response to influxes of renewable energy.

    “One of the technical challenges, and the contribution of this work, is trying to identify which are the power plants that respond to this increasing wind power,” Qiu notes.

    To do so, the researchers compared two historical datasets from the period between 2011 and 2017: an hour-by-hour record of energy output of wind turbines across the country, and a detailed record of emissions measurements from every fossil-fuel-based power plant in the U.S. The datasets covered each of seven major regional electricity markets, each market providing energy to one or multiple states.

    “California and New York are each their own market, whereas the New England market covers around seven states, and the Midwest covers more,” Qiu explains. “We also cover about 95 percent of all the wind power in the U.S.”

    In general, they observed that, in times when wind power was available, markets adjusted by essentially scaling back the power output of natural gas and sub-bituminous coal-fired power plants. They noted that the plants that were turned down were likely chosen for cost-saving reasons, as certain plants were less costly to turn down than others.

    The team then used a sophisticated atmospheric chemistry model to simulate the wind patterns and chemical transport of emissions across the country, and determined where and at what concentrations the emissions generated fine particulates and ozone — two pollutants that are known to damage air quality and human health. Finally, the researchers mapped the general demographic populations across the country, based on U.S. census data, and applied a standard epidemiological approach to calculate a population’s health cost as a result of their pollution exposure.

    This analysis revealed that, in the year 2014, a general cost-saving approach to displacing fossil-fuel-based energy in times of wind energy resulted in $2 billion in health benefits, or savings, across the country. A smaller share of these benefits went to disadvantaged populations, such as communities of color and low-income communities, though this disparity varied by state.

    “It’s a more complex story than we initially thought,” Qiu says. “Certain population groups are exposed to a higher level of air pollution, and those would be low-income people and racial minority groups. What we see is, developing wind power could reduce this gap in certain states but further increase it in other states, depending on which fossil-fuel plants are displaced.”

    Tweaking power

    The researchers then examined how the pattern of emissions and the associated health benefits would change if they prioritized turning down different fossil-fuel-based plants in times of wind-generated power. They tweaked the emissions data to reflect several alternative scenarios: one in which the most health-damaging, polluting power plants are turned down first; and two other scenarios in which plants producing the most sulfur dioxide and carbon dioxide respectively, are first to reduce their output.

    They found that while each scenario increased health benefits overall, and the first scenario in particular could quadruple health benefits, the original disparity persisted: Communities of color and low-income communities still experienced smaller health benefits than more well-off communities.

    “We got to the end of the road and said, there’s no way we can address this disparity by being smarter in deciding which plants to displace,” Selin says.

    Nevertheless, the study can help identify ways to improve the health of the general population, says Julian Marshall, a professor of environmental engineering at the University of Washington.

    “The detailed information provided by the scenarios in this paper can offer a roadmap to electricity-grid operators and to state air-quality regulators regarding which power plants are highly damaging to human health and also are likely to noticeably reduce emissions if wind-generated electricity increases,” says Marshall, who was not involved in the study.

    “One of the things that makes me optimistic about this area is, there’s a lot more attention to environmental justice and equity issues,” Selin concludes. “Our role is to figure out the strategies that are most impactful in addressing those challenges.”

    This work was supported, in part, by the U.S. Environmental Protection Agency, and by the National Institutes of Health. More

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    Coordinating climate and air-quality policies to improve public health

    As America’s largest investment to fight climate change, the Inflation Reduction Act positions the country to reduce its greenhouse gas emissions by an estimated 40 percent below 2005 levels by 2030. But as it edges the United States closer to achieving its international climate commitment, the legislation is also expected to yield significant — and more immediate — improvements in the nation’s health. If successful in accelerating the transition from fossil fuels to clean energy alternatives, the IRA will sharply reduce atmospheric concentrations of fine particulates known to exacerbate respiratory and cardiovascular disease and cause premature deaths, along with other air pollutants that degrade human health. One recent study shows that eliminating air pollution from fossil fuels in the contiguous United States would prevent more than 50,000 premature deaths and avoid more than $600 billion in health costs each year.

    While national climate policies such as those advanced by the IRA can simultaneously help mitigate climate change and improve air quality, their results may vary widely when it comes to improving public health. That’s because the potential health benefits associated with air quality improvements are much greater in some regions and economic sectors than in others. Those benefits can be maximized, however, through a prudent combination of climate and air-quality policies.

    Several past studies have evaluated the likely health impacts of various policy combinations, but their usefulness has been limited due to a reliance on a small set of standard policy scenarios. More versatile tools are needed to model a wide range of climate and air-quality policy combinations and assess their collective effects on air quality and human health. Now researchers at the MIT Joint Program on the Science and Policy of Global Change and MIT Institute for Data, Systems and Society (IDSS) have developed a publicly available, flexible scenario tool that does just that.

    In a study published in the journal Geoscientific Model Development, the MIT team introduces its Tool for Air Pollution Scenarios (TAPS), which can be used to estimate the likely air-quality and health outcomes of a wide range of climate and air-quality policies at the regional, sectoral, and fuel-based level. 

    “This tool can help integrate the siloed sustainability issues of air pollution and climate action,” says the study’s lead author William Atkinson, who recently served as a Biogen Graduate Fellow and research assistant at the IDSS Technology and Policy Program’s (TPP) Research to Policy Engagement Initiative. “Climate action does not guarantee a clean air future, and vice versa — but the issues have similar sources that imply shared solutions if done right.”

    The study’s initial application of TAPS shows that with current air-quality policies and near-term Paris Agreement climate pledges alone, short-term pollution reductions give way to long-term increases — given the expected growth of emissions-intensive industrial and agricultural processes in developing regions. More ambitious climate and air-quality policies could be complementary, each reducing different pollutants substantially to give tremendous near- and long-term health benefits worldwide.

    “The significance of this work is that we can more confidently identify the long-term emission reduction strategies that also support air quality improvements,” says MIT Joint Program Deputy Director C. Adam Schlosser, a co-author of the study. “This is a win-win for setting climate targets that are also healthy targets.”

    TAPS projects air quality and health outcomes based on three integrated components: a recent global inventory of detailed emissions resulting from human activities (e.g., fossil fuel combustion, land-use change, industrial processes); multiple scenarios of emissions-generating human activities between now and the year 2100, produced by the MIT Economic Projection and Policy Analysis model; and emissions intensity (emissions per unit of activity) scenarios based on recent data from the Greenhouse Gas and Air Pollution Interactions and Synergies model.

    “We see the climate crisis as a health crisis, and believe that evidence-based approaches are key to making the most of this historic investment in the future, particularly for vulnerable communities,” says Johanna Jobin, global head of corporate reputation and responsibility at Biogen. “The scientific community has spoken with unanimity and alarm that not all climate-related actions deliver equal health benefits. We’re proud of our collaboration with the MIT Joint Program to develop this tool that can be used to bridge research-to-policy gaps, support policy decisions to promote health among vulnerable communities, and train the next generation of scientists and leaders for far-reaching impact.”

    The tool can inform decision-makers about a wide range of climate and air-quality policies. Policy scenarios can be applied to specific regions, sectors, or fuels to investigate policy combinations at a more granular level, or to target short-term actions with high-impact benefits.

    TAPS could be further developed to account for additional emissions sources and trends.

    “Our new tool could be used to examine a large range of both climate and air quality scenarios. As the framework is expanded, we can add detail for specific regions, as well as additional pollutants such as air toxics,” says study supervising co-author Noelle Selin, professor at IDSS and the MIT Department of Earth, Atmospheric and Planetary Sciences, and director of TPP.    

    This research was supported by the U.S. Environmental Protection Agency and its Science to Achieve Results (STAR) program; Biogen; TPP’s Leading Technology and Policy Initiative; and TPP’s Research to Policy Engagement Initiative. More

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    J-WAFS awards $150K Solutions grant to Patrick Doyle and team for rapid removal of micropollutants from water

    The Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) has awarded a 2022 J-WAFS Solutions grant to Patrick S. Doyle, the Robert T. Haslam Professor of Chemical Engineering at MIT, for his innovative system to tackle water pollution. Doyle will be working with co-Principal Investigator Rafael Gomez-Bombarelli, assistant professor in materials processing in the Department of Materials Science, as well as PhD students Devashish Gokhale and Tynan Perez. Building off of findings from a 2019 J-WAFS seed grant, Doyle and the research team will create cost-effective industry-scale processes to remove micropollutants from water. Project work will commence this month.

    The J-WAFS Solutions program provides one-year, renewable, commercialization grants to help move MIT technology from the laboratory to market. Grants of up to $150,000 are awarded to researchers with breakthrough technologies and inventions in water or food. Since its launch in 2015, J-WAFS Solutions grants have led to seven spinout companies and helped commercialize two products as open-source technologies. The grant program is supported by Community Jameel.

    A widespread problem 

    Micropollutants are contaminants that occur in low concentrations in the environment, yet continuous exposure and bioaccumulation of micropollutants make them a cause for concern. According to the U.S. Environmental Protection Agency, the plastics derivative Bisphenol A (BPA), the “forever chemicals” per-and polyfluoroalkyl substances (PFAS), and heavy metals like lead are common micropollutants known to be found in more than 85 percent of rivers, ponds, and lakes in the United States. Many of these bodies of water are sources of drinking water. Over long periods of time, exposure to micropollutants through drinking water can cause physiological damage in humans, increasing the risk of cancer, developmental disorders, and reproductive failure.

    Since micropollutants occur in low concentrations, it is difficult to detect and monitor their presence, and the chemical diversity of micropollutants makes it difficult to inexpensively remove them from water. Currently, activated carbon is the industry standard for micropollutant elimination, but this method cannot efficiently remove contaminants at parts-per-billion and parts-per-trillion concentrations. There are also strong sustainability concerns associated with activated carbon production, which is energy-intensive and releases large volumes of carbon dioxide.

    A solution with societal and economic benefits

    Doyle and his team are developing a technology that uses sustainable hydrogel microparticles to remove micropollutants from water. The polymeric hydrogel microparticles use chemically anchored structures including micelles and other chelating agents that act like a sponge by absorbing organic micropollutants and heavy metal ions. The microparticles are large enough to separate from water using simple gravitational settling. The system is sustainable because the microparticles can be recycled for continuous use. In testing, the long-lasting, reusable microparticles show quicker removal of contaminants than commercial activated carbon. The researchers plan to utilize machine learning to find optimal microparticle compositions that maximize performance on complex combinations of micropollutants in simulated and real wastewater samples.

    Economically, the technology is a new offering that has applications in numerous large markets where micropollutant elimination is vital, including municipal and industrial water treatment equipment, as well as household water purification systems. The J-WAFS Solutions grant will allow the team to build and test prototypes of the water treatment system, identify the best use cases and customers, and perform technoeconomic analyses and market research to formulate a preliminary business plan. With J-WAFS commercialization support, the project could eventually lead to a startup company.

    “Emerging micropollutants are a growing threat to drinking water supplies worldwide,” says J-WAFS Director John H. Lienhard, the Abdul Latif Jameel Professor of Water at MIT. “Cost-effective and scalable technologies for micropollutant removal are urgently needed. This project will develop and commercialize a promising new tool for water treatment, with the goal of improving water quality for millions of people.” More

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    Assay determines the percentage of Omicron, other variants in Covid wastewater

    Wastewater monitoring emerged amid the Covid-19 pandemic as an effective and noninvasive way to track a viral outbreak, and advances in the technology have enabled researchers to not only identify but also quantify the presence of particular variants of concern (VOCs) in wastewater samples.

    Last year, researchers with the Singapore-MIT Alliance for Research and Technology (SMART) made the news for developing a quantitative assay for the Alpha variant of SARS-CoV-2 in wastewater, while also working on a similar assay for the Delta variant. Previously, conventional wastewater detection methods could only detect the presence of SARS-CoV-2 viral material in a sample, without identifying the variant of the virus.

    Now, a team at SMART has developed a quantitative RT-qPCR assay that can detect the Omicron variant of SARS-CoV-2. This type of assay enables wastewater surveillance to accurately trace variant dynamics in any given community or population, and support and inform the implementation of appropriate public health measures tailored according to the specific traits of a particular viral pathogen.

    The capacity to count and assess particular VOCs is unique to SMART’s open-source assay, and allows researchers to accurately determine displacement trends in a community. Hence, the new assay can reveal what proportion of SARS-CoV-2 virus circulating in a community belongs to a particular variant. This is particularly significant, as different SARS-CoV-2 VOCs — Alpha, Delta, Omicron, and their offshoots — have emerged at various points throughout the pandemic, each causing a new wave of infections to which the population was more susceptible.

    The team’s new allele-specific RT-qPCR assay is described in a paper, “Rapid displacement of SARS-CoV-2 variant Delta by Omicron revealed by allele-specific PCR in wastewater,” published this month in Water Research. Senior author on the work is Eric Alm, professor of biological engineering at MIT and a principal investigator in the Antimicrobial Resistance (AMR) interdisciplinary research group within SMART, MIT’s research enterprise in Singapore. Co-authors include researchers from Nanyang Technological University (NTU), Singapore National University (NUS), MIT, Singapore Centre for Environmental Life Sciences Engineering (SCELSE), and Istituto Zooprofilattico Sperimentale della Lombardia e dell’Emilia Romagna (IZSLER) in Italy.

    Omicron overtakes delta within three weeks in Italy study

    In their study, SMART researchers found that the increase in booster vaccine population coverage in Italy concurred with the complete displacement of the Delta variant by the Omicron variant in wastewater samples obtained from the Torbole Casaglia wastewater treatment plant, with a catchment size of 62,722 people. Taking less than three weeks, the rapid pace of this displacement can be attributed to Omicron’s infection advantage over the previously dominant Delta in vaccinated individuals, which may stem from Omicron’s more efficient evasion of vaccination-induced immunity.

    “In a world where Covid-19 is endemic, the monitoring of VOCs through wastewater surveillance will be an effective tool for the tracking of variants circulating in the community and will play an increasingly important role in guiding public health response,” says paper co-author Federica Armas, a senior postdoc at SMART AMR. “This work has demonstrated that wastewater surveillance can be used to quickly and quantitatively trace VOCs present in a community.”

    Wastewater surveillance vital for future pandemic responses

    As the global population becomes increasingly vaccinated and exposed to prior infections, nations have begun transitioning toward the classification of SARS-CoV-2 as an endemic disease, rolling back active clinical surveillance toward decentralized antigen rapid tests, and consequently reducing sequencing of patient samples. However, SARS-CoV-2 has been shown to produce novel VOCs that can swiftly emerge and spread rapidly across populations, displacing previously dominant variants of the virus. This was observed when Delta displaced Alpha across the globe after the former’s emergence in India in December 2020, and again when Omicron displaced Delta at an even faster rate following its discovery in South Africa in November 2021. The continuing emergence of novel VOCs therefore necessitates continued vigilance on the monitoring of circulating SARS-CoV-2 variants in communities.

    In a separate review paper on wastewater surveillance titled “Making Waves: Wastewater Surveillance of SARS-CoV-2 in an Endemic Future,” published in the journal Water Research, SMART researchers and collaborators found that the utility of wastewater surveillance in the near future could include 1) monitoring the trend of viral loads in wastewater for quantified viral estimates circulating in a community; 2) sampling of wastewater at the source — e.g., taking samples from particular neighborhoods or buildings — for pinpointing infections in neighborhoods and at the building level; 3) integrating wastewater and clinical surveillance for cost-efficient population surveillance; and 4) genome sequencing wastewater samples to track circulating and emerging variants in the population.

    “Our experience with SARS-CoV-2 has shown that clinical testing can often only paint a limited picture of the true extent of an outbreak or pandemic. With Covid-19 becoming prevalent and with the anticipated emergence of further variants of concern, qualitative and quantitative data from wastewater surveillance will be an integral component of a cost- and resource-efficient public health surveillance program, empowering authorities to make more informed policy decisions,” adds corresponding author Janelle Thompson, associate professor at SCELSE and NTU. “Our review provides a roadmap for the wider deployment of wastewater surveillance, with opportunities and challenges that, if addressed, will enable us to not only better manage Covid-19, but also future-proof societies for other viral pathogens and future pandemics.”

    In addition, the review suggests that future wastewater research should comply with a set of standardized wastewater processing methods to reduce inconsistencies in wastewater data toward improving epidemiological inference. Methods developed in the context of SARS-CoV-2 and its analyses could be of invaluable benefit for future wastewater monitoring work on discovering emerging zoonotic pathogens — pathogens that can be transmitted from animals to humans — and for early detection of future pandemics.

    Furthermore, far from being confined to SARS-CoV-2, wastewater surveillance has already been adapted for use in combating other viral pathogens. Another paper from September 2021 described an advance in the development of effective wastewater surveillance for dengue, Zika, and yellow fever viruses, with SMART researchers successfully measuring decay rates of these medically significant arboviruses in wastewater. This was followed by another review paper by SMART published in July 2022 that explored current progress and future challenges and opportunities in wastewater surveillance for arboviruses. These developments represent an important first step toward establishing arbovirus wastewater surveillance, which would help policymakers in Singapore and beyond make better informed and more targeted public health measures in controlling arbovirus outbreaks such as dengue, which is a significant public health concern in Singapore.

    “Our learnings from using wastewater surveillance as a key tool over the course of Covid-19 will be crucial in helping researchers develop similar methods to monitor and tackle other viral pathogens and future pandemics,” says Lee Wei Lin, first author of the latest SMART paper and research scientist at SMART AMR. “Wastewater surveillance has already shown promising utility in helping to fight other viral pathogens, including some of the world’s most prevalent mosquito-borne diseases, and there is significant potential for the technology to be adapted for use against other infectious viral diseases.”

    The research is carried out by SMART and its collaborators at SCELSE, NTU, and NUS, co-led by Professor Eric Alm (SMART and MIT) and Associate Professor Janelle Thompson (SCELSE and NTU), and is supported by Singapore’sNational Research Foundation (NRF) under its Campus for Research Excellence And Technological Enterprise (CREATE) program. The research is part of an initiative funded by the NRF to develop sewage-based surveillance for rapid outbreak detection and intervention in Singapore.

    SMART was established by MIT in partnership with the NRF in 2007. SMART is the first entity in CREATE developed by NRF and serves as an intellectual and innovation hub for research interactions between MIT and Singapore, undertaking cutting-edge research projects in areas of interest to both Singapore and MIT. SMART currently comprises an Innovation Centre and five interdisciplinary research groups: AMR, Critical Analytics for Manufacturing Personalized-Medicine, Disruptive & Sustainable Technologies for Agricultural Precision, Future Urban Mobility, and Low Energy Electronic Systems.

    The AMR IRG is a translational research and entrepreneurship program that tackles the growing threat of antimicrobial resistance. By leveraging talent and convergent technologies across Singapore and MIT, they tackle AMR head-on by developing multiple innovative and disruptive approaches to identify, respond to, and treat drug-resistant microbial infections. Through strong scientific and clinical collaborations, our goal is to provide transformative, holistic solutions for Singapore and the world. More