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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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    Professor Emeritus Richard “Dick” Eckaus, who specialized in development economics, dies at 96

    Richard “Dick” Eckaus, Ford Foundation International Professor of Economics, emeritus, in the Department of Economics, died on Sept. 11 in Boston. He was 96 years old.

    Eckaus was born in Kansas City, Missouri on April 30, 1926, the youngest of three children to parents who had emigrated from Lithuania. His father, Julius Eckaus, was a tailor, and his mother, Bessie (Finkelstein) Eckaus helped run the business. The family struggled to make ends meet financially but academic success offered Eckaus a way forward.

    He graduated from Westport High School, joined the United States Navy, and was awarded a college scholarship via the V-12 Navy College Training Program during World War II to study electrical engineering at Iowa State University. After graduating in 1944, Eckaus served on a base in New York State until he was discharged in 1946 as lieutenant junior grade.

    He attended Washington University in St. Louis, Missouri, on the GI Bill, graduating in 1948 with a master’s degree in economics, before relocating to Boston and serving as instructor of economics at Babson Institute, and then assistant and associate professor of economics at Brandeis University from 1951 to 1962. He concurrently earned a PhD in economics from MIT in 1954.

    The following year, the American Economic Review published “The Factor Proportions Problem in Economic Development,” a paper written by Eckaus that remained part of the macroeconomics canon for decades. He returned to MIT in 1962 and went on to teach development economics to generations of MIT students, serving as head of the department from 1986 to 1990 and continuing to work there for the remainder of his career.

    The development economist Paul Rosenstein-Rodan (1902-85), Eckaus’ mentor at MIT, took him to live and work first in Italy in 1954 and then in India in 1961. These stints helping governments abroad solidified Eckaus’ commitment to not only excelling in the field, but also creating opportunities for colleagues and students to contribute as well — occasionally in conjunction with the World Bank.

    Longtime colleague Abhijit Banerjee, a Nobel laureate, Ford Foundation International Professor of Economics, and director of the Abdul Latif Jameel Poverty Action Lab at MIT, recalls reading a reprint of Eckaus’ 1955 paper as an undergraduate in India. When he subsequently arrived at MIT as a doctoral candidate, he remembers “trying to tread lightly and not to take up too much space,” around the senior economist. “In fact, he made me feel so welcome,” Banerjee says. “He was both an outstanding scholar and someone who had the modesty and generosity to make younger scholars feel valued and heard.”

    The field of development economics provided Eckaus with a broad, powerful platform to work with governments in developing countries — including India, Egypt, Bhutan, Mexico, and Portugal — to set up economic systems. His development planning models helped governments to forecast where their economies were headed and how public policies could be implemented to shift or accelerate the direction.

    The Government of Portugal awarded Eckaus the Great-Cross of the Order of Prince Henry the Navigator after he brought teams from MIT to assist the country in its peaceful transition to democracy following the 1974 Carnation Revolution. Initiated at the request of the Portuguese Central Bank, these graduate students became some of the most prominent economists of their generation in America. They include Paul Krugman, Andrew Abel, Jeremy I. Bulow, and Kenneth Rogoff.

    His colleague for five decades, Paul Joskow, the Elizabeth and James Killian Professor of Economics at MIT, says that’s no surprise. “He was a real rock of the economics department. He deeply cared about the graduate students and younger faculty. He was a very supportive person.”

    Eckaus was also deeply interested in economic aspects of energy and environment, and in 1991 was instrumental in the formation of the MIT Joint Program on the Science and Policy of Global Change, a program that integrates the natural and social sciences in analysis of global climate threat. As Joint Program co-founder Henry Jacoby observes, “Dick provided crucial ideas as to how that kind of interdisciplinary work might be done at MIT. He was already 65 at the time, and continued for three decades to be active in guiding the research and analysis.”

    Although Eckaus retired officially in 1996, he continued to attend weekly faculty lunches, conduct research, mentor colleagues, and write papers related to climate change and the energy crisis. He leaves behind a trove of more than 100 published papers and eight authored and co-authored books.

    “He was continuously retooling himself and creating new interests. I was impressed by his agility of mind and his willingness to shift to new areas,” says his oldest living friend and peer, Jagdish Bhagwati, Columbia University professor of economics, law, and international relations, emeritus, and director of the Raj Center on Indian Economic Policies. “In their early career, economists usually write short theoretical articles that make large points, and Dick did that with two seminal articles in the leading professional journals of the time, the Quarterly Journal of Economics and the American Economic Review. Then, he shifted his focus to building large computable models. He also diversified by working in an advisory capacity in countries as diverse as Portugal and India. He was a ‘complete’ economist who straddled all styles of economics with distinction.” 

    Eckaus is survived by his beloved wife of 32 years Patricia Leahy Meaney of Brookline, Massachusetts. The two traveled the world, hiked the Alps, and collected pre-Columbian and contemporary art. He is lovingly remembered by his daughter Susan Miller; his step-son James Meaney (Bruna); step-daughter Caitlin Meaney Burrows (Lee); and four grandchildren, Chloe Burrows, Finley Burrows, Brandon Meaney, and Maria Sophia Meaney.

    In lieu of flowers, please consider a donation in Eckaus’ name to MIT Economics (77 Massachusetts Ave., Building E52-300, Cambridge, MA 02139). A memorial in his honor will be held later this year. More

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    Stranded assets could exact steep costs on fossil energy producers and investors

    A 2021 study in the journal Nature found that in order to avert the worst impacts of climate change, most of the world’s known fossil fuel reserves must remain untapped. According to the study, 90 percent of coal and nearly 60 percent of oil and natural gas must be kept in the ground in order to maintain a 50 percent chance that global warming will not exceed 1.5 degrees Celsius above preindustrial levels.

    As the world transitions away from greenhouse-gas-emitting activities to keep global warming well below 2 C (and ideally 1.5 C) in alignment with the Paris Agreement on climate change, fossil fuel companies and their investors face growing financial risks (known as transition risks), including the prospect of ending up with massive stranded assets. This ongoing transition is likely to significantly scale back fossil fuel extraction and coal-fired power plant operations, exacting steep costs — most notably asset value losses — on fossil-energy producers and shareholders.

    Now, a new study in the journal Climate Change Economics led by researchers at the MIT Joint Program on the Science and Policy of Global Change estimates the current global asset value of untapped fossil fuels through 2050 under four increasingly ambitious climate-policy scenarios. The least-ambitious scenario (“Paris Forever”) assumes that initial Paris Agreement greenhouse gas emissions-reduction pledges are upheld in perpetuity; the most stringent scenario (“Net Zero 2050”) adds coordinated international policy instruments aimed at achieving global net-zero emissions by 2050.

    Powered by the MIT Joint Program’s model of the world economy with detailed representation of the energy sector and energy industry assets over time, the study finds that the global net present value of untapped fossil fuel output through 2050 relative to a reference “No Policy” scenario ranges from $21.5 trillion (Paris Forever) to $30.6 trillion (Net Zero 2050). The estimated global net present value of stranded assets in coal power generation through 2050 ranges from $1.3 to $2.3 trillion.

    “The more stringent the climate policy, the greater the volume of untapped fossil fuels, and hence the higher the potential asset value loss for fossil-fuel owners and investors,” says Henry Chen, a research scientist at the MIT Joint Program and the study’s lead author.

    The global economy-wide analysis presented in the study provides a more fine-grained assessment of stranded assets than those performed in previous studies. Firms and financial institutions may combine the MIT analysis with details on their own investment portfolios to assess their exposure to climate-related transition risk. More

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    Getting the carbon out of India’s heavy industries

    The world’s third largest carbon emitter after China and the United States, India ranks seventh in a major climate risk index. Unless India, along with the nearly 200 other signatory nations of the Paris Agreement, takes aggressive action to keep global warming well below 2 degrees Celsius relative to preindustrial levels, physical and financial losses from floods, droughts, and cyclones could become more severe than they are today. So, too, could health impacts associated with the hazardous air pollution levels now affecting more than 90 percent of its population.  

    To address both climate and air pollution risks and meet its population’s escalating demand for energy, India will need to dramatically decarbonize its energy system in the coming decades. To that end, its initial Paris Agreement climate policy pledge calls for a reduction in carbon dioxide intensity of GDP by 33-35 percent by 2030 from 2005 levels, and an increase in non-fossil-fuel-based power to about 40 percent of cumulative installed capacity in 2030. At the COP26 international climate change conference, India announced more aggressive targets, including the goal of achieving net-zero emissions by 2070.

    Meeting its climate targets will require emissions reductions in every economic sector, including those where emissions are particularly difficult to abate. In such sectors, which involve energy-intensive industrial processes (production of iron and steel; nonferrous metals such as copper, aluminum, and zinc; cement; and chemicals), decarbonization options are limited and more expensive than in other sectors. Whereas replacing coal and natural gas with solar and wind could lower carbon dioxide emissions in electric power generation and transportation, no easy substitutes can be deployed in many heavy industrial processes that release CO2 into the air as a byproduct.

    However, other methods could be used to lower the emissions associated with these processes, which draw upon roughly 50 percent of India’s natural gas, 25 percent of its coal, and 20 percent of its oil. Evaluating the potential effectiveness of such methods in the next 30 years, a new study in the journal Energy Economics led by researchers at the MIT Joint Program on the Science and Policy of Global Change is the first to explicitly explore emissions-reduction pathways for India’s hard-to-abate sectors.

    Using an enhanced version of the MIT Economic Projection and Policy Analysis (EPPA) model, the study assesses existing emissions levels in these sectors and projects how much they can be reduced by 2030 and 2050 under different policy scenarios. Aimed at decarbonizing industrial processes, the scenarios include the use of subsidies to increase electricity use, incentives to replace coal with natural gas, measures to improve industrial resource efficiency, policies to put a price on carbon, carbon capture and storage (CCS) technology, and hydrogen in steel production.

    The researchers find that India’s 2030 Paris Agreement pledge may still drive up fossil fuel use and associated greenhouse gas emissions, with projected carbon dioxide emissions from hard-to-abate sectors rising by about 2.6 times from 2020 to 2050. But scenarios that also promote electrification, natural gas support, and resource efficiency in hard-to-abate sectors can lower their CO2 emissions by 15-20 percent.

    While appearing to move the needle in the right direction, those reductions are ultimately canceled out by increased demand for the products that emerge from these sectors. So what’s the best path forward?

    The researchers conclude that only the incentive of carbon pricing or the advance of disruptive technology can move hard-to-abate sector emissions below their current levels. To achieve significant emissions reductions, they maintain, the price of carbon must be high enough to make CCS economically viable. In that case, reductions of 80 percent below current levels could be achieved by 2050.

    “Absent major support from the government, India will be unable to reduce carbon emissions in its hard-to-abate sectors in alignment with its climate targets,” says MIT Joint Program deputy director Sergey Paltsev, the study’s lead author. “A comprehensive government policy could provide robust incentives for the private sector in India and generate favorable conditions for foreign investments and technology advances. We encourage decision-makers to use our findings to design efficient pathways to reduce emissions in those sectors, and thereby help lower India’s climate and air pollution-related health risks.” More

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    Absent legislative victory, the president can still meet US climate goals

    The most recent United Nations climate change report indicates that without significant action to mitigate global warming, the extent and magnitude of climate impacts — from floods to droughts to the spread of disease — could outpace the world’s ability to adapt to them. The latest effort to introduce meaningful climate legislation in the United States Congress, the Build Back Better bill, has stalled. The climate package in that bill — $555 billion in funding for climate resilience and clean energy — aims to reduce U.S. greenhouse gas emissions by about 50 percent below 2005 levels by 2030, the nation’s current Paris Agreement pledge. With prospects of passing a standalone climate package in the Senate far from assured, is there another pathway to fulfilling that pledge?

    Recent detailed legal analysis shows that there is at least one viable option for the United States to achieve the 2030 target without legislative action. Under Section 115 on International Air Pollution of the Clean Air Act, the U.S. Environmental Protection Agency (EPA) could assign emissions targets to the states that collectively meet the national goal. The president could simply issue an executive order to empower the EPA to do just that. But would that be prudent?

    A new study led by researchers at the MIT Joint Program on the Science and Policy of Global Change explores how, under a federally coordinated carbon dioxide emissions cap-and-trade program aligned with the U.S. Paris Agreement pledge and implemented through Section 115 of the Clean Air Act, the EPA might allocate emissions cuts among states. Recognizing that the Biden or any future administration considering this strategy would need to carefully weigh its benefits against its potential political risks, the study highlights the policy’s net economic benefits to the nation.

    The researchers calculate those net benefits by combining the estimated total cost of carbon dioxide emissions reduction under the policy with the corresponding estimated expenditures that would be avoided as a result of the policy’s implementation — expenditures on health care due to particulate air pollution, and on society at large due to climate impacts.

    Assessing three carbon dioxide emissions allocation strategies (each with legal precedent) for implementing Section 115 to return cap-and-trade program revenue to the states and distribute it to state residents on an equal per-capita basis, the study finds that at the national level, the economic net benefits are substantial, ranging from $70 to $150 billion in 2030. The results appear in the journal Environmental Research Letters.

    “Our findings not only show significant net gains to the U.S. economy under a national emissions policy implemented through the Clean Air Act’s Section 115,” says Mei Yuan, a research scientist at the MIT Joint Program and lead author of the study. “They also show the policy impact on consumer costs may differ across states depending on the choice of allocation strategy.”

    The national price on carbon needed to achieve the policy’s emissions target, as well as the policy’s ultimate cost to consumers, are substantially lower than those found in studies a decade earlier, although in line with other recent studies. The researchers speculate that this is largely due to ongoing expansion of ambitious state policies in the electricity sector and declining renewable energy costs. The policy is also progressive, consistent with earlier studies, in that equal lump-sum distribution of allowance revenue to state residents generally leads to net benefits to lower-income households. Regional disparities in consumer costs can be moderated by the allocation of allowances among states.

    State-by-state emissions estimates for the study are derived from MIT’s U.S. Regional Energy Policy model, with electricity sector detail of the Renewable Energy Development System model developed by the U.S. National Renewable Energy Laboratory; air quality benefits are estimated using U.S. EPA and other models; and the climate benefits estimate is based on the social cost of carbon, the U.S. federal government’s assessment of the economic damages that would result from emitting one additional ton of carbon dioxide into the atmosphere (currently $51/ton, adjusted for inflation). 

    “In addition to illustrating the economic, health, and climate benefits of a Section 115 implementation, our study underscores the advantages of a policy that imposes a uniform carbon price across all economic sectors,” says John Reilly, former co-director of the MIT Joint Program and a study co-author. “A national carbon price would serve as a major incentive for all sectors to decarbonize.” More

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    What choices does the world need to make to keep global warming below 2 C?

    When the 2015 Paris Agreement set a long-term goal of keeping global warming “well below 2 degrees Celsius, compared to pre-industrial levels” to avoid the worst impacts of climate change, it did not specify how its nearly 200 signatory nations could collectively achieve that goal. Each nation was left to its own devices to reduce greenhouse gas emissions in alignment with the 2 C target. Now a new modeling strategy developed at the MIT Joint Program on the Science and Policy of Global Change that explores hundreds of potential future development pathways provides new insights on the energy and technology choices needed for the world to meet that target.

    Described in a study appearing in the journal Earth’s Future, the new strategy combines two well-known computer modeling techniques to scope out the energy and technology choices needed over the coming decades to reduce emissions sufficiently to achieve the Paris goal.

    The first technique, Monte Carlo analysis, quantifies uncertainty levels for dozens of energy and economic indicators including fossil fuel availability, advanced energy technology costs, and population and economic growth; feeds that information into a multi-region, multi-economic-sector model of the world economy that captures the cross-sectoral impacts of energy transitions; and runs that model hundreds of times to estimate the likelihood of different outcomes. The MIT study focuses on projections through the year 2100 of economic growth and emissions for different sectors of the global economy, as well as energy and technology use.

    The second technique, scenario discovery, uses machine learning tools to screen databases of model simulations in order to identify outcomes of interest and their conditions for occurring. The MIT study applies these tools in a unique way by combining them with the Monte Carlo analysis to explore how different outcomes are related to one another (e.g., do low-emission outcomes necessarily involve large shares of renewable electricity?). This approach can also identify individual scenarios, out of the hundreds explored, that result in specific combinations of outcomes of interest (e.g., scenarios with low emissions, high GDP growth, and limited impact on electricity prices), and also provide insight into the conditions needed for that combination of outcomes.

    Using this unique approach, the MIT Joint Program researchers find several possible patterns of energy and technology development under a specified long-term climate target or economic outcome.

    “This approach shows that there are many pathways to a successful energy transition that can be a win-win for the environment and economy,” says Jennifer Morris, an MIT Joint Program research scientist and the study’s lead author. “Toward that end, it can be used to guide decision-makers in government and industry to make sound energy and technology choices and avoid biases in perceptions of what ’needs’ to happen to achieve certain outcomes.”

    For example, while achieving the 2 C goal, the global level of combined wind and solar electricity generation by 2050 could be less than three times or more than 12 times the current level (which is just over 2,000 terawatt hours). These are very different energy pathways, but both can be consistent with the 2 C goal. Similarly, there are many different energy mixes that can be consistent with maintaining high GDP growth in the United States while also achieving the 2 C goal, with different possible roles for renewables, natural gas, carbon capture and storage, and bioenergy. The study finds renewables to be the most robust electricity investment option, with sizable growth projected under each of the long-term temperature targets explored.

    The researchers also find that long-term climate targets have little impact on economic output for most economic sectors through 2050, but do require each sector to significantly accelerate reduction of its greenhouse gas emissions intensity (emissions per unit of economic output) so as to reach near-zero levels by midcentury.

    “Given the range of development pathways that can be consistent with meeting a 2 degrees C goal, policies that target only specific sectors or technologies can unnecessarily narrow the solution space, leading to higher costs,” says former MIT Joint Program Co-Director John Reilly, a co-author of the study. “Our findings suggest that policies designed to encourage a portfolio of technologies and sectoral actions can be a wise strategy that hedges against risks.”

    The research was supported by the U.S. Department of Energy Office of Science. More

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    Empowering people to adapt on the frontlines of climate change

    On April 11, MIT announced five multiyear flagship projects in the first-ever Climate Grand Challenges, a new initiative to tackle complex climate problems and deliver breakthrough solutions to the world as quickly as possible. This article is the fifth in a five-part series highlighting the most promising concepts to emerge from the competition and the interdisciplinary research teams behind them.

    In the coastal south of Bangladesh, rice paddies that farmers could once harvest three times a year lie barren. Sea-level rise brings saltwater to the soil, ruining the staple crop. It’s one of many impacts, and inequities, of climate change. Despite producing less than 1 percent of global carbon emissions, Bangladesh is suffering more than most countries. Rising seas, heat waves, flooding, and cyclones threaten 90 million people.

    A platform being developed in a collaboration between MIT and BRAC, a Bangladesh-based global development organization, aims to inform and empower climate-threatened communities to proactively adapt to a changing future. Selected as one of five MIT Climate Grand Challenges flagship projects, the Climate Resilience Early Warning System (CREWSnet) will forecast the local impacts of climate change on people’s lives, homes, and livelihoods. These forecasts will guide BRAC’s development of climate-resiliency programs to help residents prepare for and adapt to life-altering conditions.

    “The communities that CREWSnet will focus on have done little to contribute to the problem of climate change in the first place. However, because of socioeconomic situations, they may be among the most vulnerable. We hope that by providing state-of-the-art projections and sharing them broadly with communities, and working through partners like BRAC, we can help improve the capacity of local communities to adapt to climate change, significantly,” says Elfatih Eltahir, the H.M. King Bhumibol Professor in the Department of Civil and Environmental Engineering.

    Eltahir leads the project with John Aldridge and Deborah Campbell in the Humanitarian Assistance and Disaster Relief Systems Group at Lincoln Laboratory. Additional partners across MIT include the Center for Global Change Science; the Department of Earth, Atmospheric and Planetary Sciences; the Joint Program on the Science and Policy of Global Change; and the Abdul Latif Jameel Poverty Action Lab. 

    Predicting local risks

    CREWSnet’s forecasts rely upon a sophisticated model, developed in Eltahir’s research group over the past 25 years, called the MIT Regional Climate Model. This model zooms in on climate processes at local scales, at a resolution as granular as 6 miles. In Bangladesh’s population-dense cities, a 6-mile area could encompass tens, or even hundreds, of thousands of people. The model takes into account the details of a region’s topography, land use, and coastline to predict changes in local conditions.

    When applying this model over Bangladesh, researchers found that heat waves will get more severe and more frequent over the next 30 years. In particular, wet-bulb temperatures, which indicate the ability for humans to cool down by sweating, will rise to dangerous levels rarely observed today, particularly in western, inland cities.

    Such hot spots exacerbate other challenges predicted to worsen near Bangladesh’s coast. Rising sea levels and powerful cyclones are eroding and flooding coastal communities, causing saltwater to surge into land and freshwater. This salinity intrusion is detrimental to human health, ruins drinking water supplies, and harms crops, livestock, and aquatic life that farmers and fishermen depend on for food and income.

    CREWSnet will fuse climate science with forecasting tools that predict the social and economic impacts to villages and cities. These forecasts — such as how often a crop season may fail, or how far floodwaters will reach — can steer decision-making.

    “What people need to know, whether they’re a governor or head of a household, is ‘What is going to happen in my area, and what decisions should I make for the people I’m responsible for?’ Our role is to integrate this science and technology together into a decision support system,” says Aldridge, whose group at Lincoln Laboratory specializes in this area. Most recently, they transitioned a hurricane-evacuation planning system to the U.S. government. “We know that making decisions based on climate change requires a deep level of trust. That’s why having a powerful partner like BRAC is so important,” he says.

    Testing interventions

    Established 50 years ago, just after Bangladesh’s independence, BRAC works in every district of the nation to provide social services that help people rise from extreme poverty. Today, it is one of the world’s largest nongovernmental organizations, serving 110 million people across 11 countries in Asia and Africa, but its success is cultivated locally.

    “BRAC is thrilled to partner with leading researchers at MIT to increase climate resilience in Bangladesh and provide a model that can be scaled around the globe,” says Donella Rapier, president and CEO of BRAC USA. “Locally led climate adaptation solutions that are developed in partnership with communities are urgently needed, particularly in the most vulnerable regions that are on the frontlines of climate change.”

    CREWSnet will help BRAC identify communities most vulnerable to forecasted impacts. In these areas, they will share knowledge and innovate or bolster programs to improve households’ capacity to adapt.

    Many climate initiatives are already underway. One program equips homes to filter and store rainwater, as salinity intrusion makes safe drinking water hard to access. Another program is building resilient housing, able to withstand 120-mile-per-hour winds, that can double as local shelters during cyclones and flooding. Other services are helping farmers switch to different livestock or crops better suited for wetter or saltier conditions (e.g., ducks instead of chickens, or salt-tolerant rice), providing interest-free loans to enable this change.

    But adapting in place will not always be possible, for example in areas predicted to be submerged or unbearably hot by midcentury. “Bangladesh is working on identifying and developing climate-resilient cities and towns across the country, as closer-by alternative destinations as compared to moving to Dhaka, the overcrowded capital of Bangladesh,” says Campbell. “CREWSnet can help identify regions better suited for migration, and climate-resilient adaptation strategies for those regions.” At the same time, BRAC’s Climate Bridge Fund is helping to prepare cities for climate-induced migration, building up infrastructure and financial services for people who have been displaced.

    Evaluating impact

    While CREWSnet’s goal is to enable action, it can’t quite measure the impact of those actions. The Abdul Latif Jameel Poverty Action Lab (J-PAL), a development economics program in the MIT School of Humanities, Arts, and Social Sciences, will help evaluate the effectiveness of the climate-adaptation programs.

    “We conduct randomized controlled trials, similar to medical trials, that help us understand if a program improved people’s lives,” says Claire Walsh, the project director of the King Climate Action Initiative at J-PAL. “Once CREWSnet helps BRAC implement adaptation programs, we will generate scientific evidence on their impacts, so that BRAC and CREWSnet can make a case to funders and governments to expand effective programs.”

    The team aspires to bring CREWSnet to other nations disproportionately impacted by climate change. “Our vision is to have this be a globally extensible capability,” says Campbell. CREWSnet’s name evokes another early-warning decision-support system, FEWSnet, that helped organizations address famine in eastern Africa in the 1980s. Today it is a pillar of food-security planning around the world.

    CREWSnet hopes for a similar impact in climate change planning. Its selection as an MIT Climate Grand Challenges flagship project will inject the project with more funding and resources, momentum that will also help BRAC’s fundraising. The team plans to deploy CREWSnet to southwestern Bangladesh within five years.

    “The communities that we are aspiring to reach with CREWSnet are deeply aware that their lives are changing — they have been looking climate change in the eye for many years. They are incredibly resilient, creative, and talented,” says Ashley Toombs, the external affairs director for BRAC USA. “As a team, we are excited to bring this system to Bangladesh. And what we learn together, we will apply at potentially even larger scales.” More

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    Computing our climate future

    On Monday, MIT announced five multiyear flagship projects in the first-ever Climate Grand Challenges, a new initiative to tackle complex climate problems and deliver breakthrough solutions to the world as quickly as possible. This article is the first in a five-part series highlighting the most promising concepts to emerge from the competition, and the interdisciplinary research teams behind them.

    With improvements to computer processing power and an increased understanding of the physical equations governing the Earth’s climate, scientists are continually working to refine climate models and improve their predictive power. But the tools they’re refining were originally conceived decades ago with only scientists in mind. When it comes to developing tangible climate action plans, these models remain inscrutable to the policymakers, public safety officials, civil engineers, and community organizers who need their predictive insight most.

    “What you end up having is a gap between what’s typically used in practice, and the real cutting-edge science,” says Noelle Selin, a professor in the Institute for Data, Systems and Society and the Department of Earth, Atmospheric and Planetary Sciences (EAPS), and co-lead with Professor Raffaele Ferrari on the MIT Climate Grand Challenges flagship project “Bringing Computation to the Climate Crisis.” “How can we use new computational techniques, new understandings, new ways of thinking about modeling, to really bridge that gap between state-of-the-art scientific advances and modeling, and people who are actually needing to use these models?”

    Using this as a driving question, the team won’t just be trying to refine current climate models, they’re building a new one from the ground up.

    This kind of game-changing advancement is exactly what the MIT Climate Grand Challenges is looking for, which is why the proposal has been named one of the five flagship projects in the ambitious Institute-wide program aimed at tackling the climate crisis. The proposal, which was selected from 100 submissions and was among 27 finalists, will receive additional funding and support to further their goal of reimagining the climate modeling system. It also brings together contributors from across the Institute, including the MIT Schwarzman College of Computing, the School of Engineering, and the Sloan School of Management.

    When it comes to pursuing high-impact climate solutions that communities around the world can use, “it’s great to do it at MIT,” says Ferrari, EAPS Cecil and Ida Green Professor of Oceanography. “You’re not going to find many places in the world where you have the cutting-edge climate science, the cutting-edge computer science, and the cutting-edge policy science experts that we need to work together.”

    The climate model of the future

    The proposal builds on work that Ferrari began three years ago as part of a joint project with Caltech, the Naval Postgraduate School, and NASA’s Jet Propulsion Lab. Called the Climate Modeling Alliance (CliMA), the consortium of scientists, engineers, and applied mathematicians is constructing a climate model capable of more accurately projecting future changes in critical variables, such as clouds in the atmosphere and turbulence in the ocean, with uncertainties at least half the size of those in existing models.

    To do this, however, requires a new approach. For one thing, current models are too coarse in resolution — at the 100-to-200-kilometer scale — to resolve small-scale processes like cloud cover, rainfall, and sea ice extent. But also, explains Ferrari, part of this limitation in resolution is due to the fundamental architecture of the models themselves. The languages most global climate models are coded in were first created back in the 1960s and ’70s, largely by scientists for scientists. Since then, advances in computing driven by the corporate world and computer gaming have given rise to dynamic new computer languages, powerful graphics processing units, and machine learning.

    For climate models to take full advantage of these advancements, there’s only one option: starting over with a modern, more flexible language. Written in Julia, a part of Julialab’s Scientific Machine Learning technology, and spearheaded by Alan Edelman, a professor of applied mathematics in MIT’s Department of Mathematics, CliMA will be able to harness far more data than the current models can handle.

    “It’s been real fun finally working with people in computer science here at MIT,” Ferrari says. “Before it was impossible, because traditional climate models are in a language their students can’t even read.”

    The result is what’s being called the “Earth digital twin,” a climate model that can simulate global conditions on a large scale. This on its own is an impressive feat, but the team wants to take this a step further with their proposal.

    “We want to take this large-scale model and create what we call an ‘emulator’ that is only predicting a set of variables of interest, but it’s been trained on the large-scale model,” Ferrari explains. Emulators are not new technology, but what is new is that these emulators, being referred to as the “Earth digital cousins,” will take advantage of machine learning.

    “Now we know how to train a model if we have enough data to train them on,” says Ferrari. Machine learning for projects like this has only become possible in recent years as more observational data become available, along with improved computer processing power. The goal is to create smaller, more localized models by training them using the Earth digital twin. Doing so will save time and money, which is key if the digital cousins are going to be usable for stakeholders, like local governments and private-sector developers.

    Adaptable predictions for average stakeholders

    When it comes to setting climate-informed policy, stakeholders need to understand the probability of an outcome within their own regions — in the same way that you would prepare for a hike differently if there’s a 10 percent chance of rain versus a 90 percent chance. The smaller Earth digital cousin models will be able to do things the larger model can’t do, like simulate local regions in real time and provide a wider range of probabilistic scenarios.

    “Right now, if you wanted to use output from a global climate model, you usually would have to use output that’s designed for general use,” says Selin, who is also the director of the MIT Technology and Policy Program. With the project, the team can take end-user needs into account from the very beginning while also incorporating their feedback and suggestions into the models, helping to “democratize the idea of running these climate models,” as she puts it. Doing so means building an interactive interface that eventually will give users the ability to change input values and run the new simulations in real time. The team hopes that, eventually, the Earth digital cousins could run on something as ubiquitous as a smartphone, although developments like that are currently beyond the scope of the project.

    The next thing the team will work on is building connections with stakeholders. Through participation of other MIT groups, such as the Joint Program on the Science and Policy of Global Change and the Climate and Sustainability Consortium, they hope to work closely with policymakers, public safety officials, and urban planners to give them predictive tools tailored to their needs that can provide actionable outputs important for planning. Faced with rising sea levels, for example, coastal cities could better visualize the threat and make informed decisions about infrastructure development and disaster preparedness; communities in drought-prone regions could develop long-term civil planning with an emphasis on water conservation and wildfire resistance.

    “We want to make the modeling and analysis process faster so people can get more direct and useful feedback for near-term decisions,” she says.

    The final piece of the challenge is to incentivize students now so that they can join the project and make a difference. Ferrari has already had luck garnering student interest after co-teaching a class with Edelman and seeing the enthusiasm students have about computer science and climate solutions.

    “We’re intending in this project to build a climate model of the future,” says Selin. “So it seems really appropriate that we would also train the builders of that climate model.” More