News J-WAFS awards seed grants to seven MIT projects in water and food 

The 2024 grantees will address challenges in water and food systems using biology, engineering, social science, and other disciplines

Carolyn Blais June 3, 2024

A grid collage of 14 MIT researcher headshots with the J-WAFS logo in the top right

MIT’s Abdul Latif Jameel Water and Food Systems Lab, or J-WAFS, is solving important problems in water and food systems, including problems associated with what might be the most pressing issue facing humanity today—climate change. Envisioning a world where every person on Earth has access to clean, safe water and plentiful food, necessitates multi-faceted solutions that span across different disciplines and take climate change into serious consideration. Luckily, the MIT faculty, research staff, and students that J-WAFS supports have a broad range of expertise that enables them to take on some of the most pressing water and food challenges of our time.

The 2024 J-WAFS seed grant recipients will pursue research on topics as diverse as novel techniques to improve atmospheric water harvesting for arid regions and collaborative planning frameworks to address climate-driven water and food shortages for Indigenous and migrant communities.

“We received many excellent proposals from faculty across MIT, resulting in a competitive selection process. The seven projects that were awarded funding stood out for their technical and team strength, and likelihood of having a meaningful impact,” said J-WAFS associate director Rohit Karnik. “The awarded projects reflect the drive and ability of MIT researchers to tackle fundamental research, create new technologies, work with communities, and propose innovative solutions, all with the goal of addressing humanity’s need for water and food,” he added.

This year’s grants include many collaborative projects involving two or more principal investigators (PIs), often from different departments and schools. The seven seed grant projects will be conducted by fourteen MIT PIs from ten different departments, labs, and centers. Read more about the 2024 seed grant researchers and their projects below.

Fortifying water and food systems against climate change

Empowering Indigenous Communities: A Framework for Climate Resilience and Migration Planning in La Guajira, Colombia

Indigenous groups and migrants worldwide have faced multiple climate and socio-political shocks.  Living in densely populated settlements in peri-urban areas (regions that are neither completely urban nor rural), these communities often lack adequate water and sanitation, access to food, and healthcare. Addressing the multifaceted challenges of Indigenous and migrant communities requires a comprehensive approach, bringing together the techniques of convergence science, integrated systems thinking, transdisciplinary frameworks, and community engagement. Yet, there have been few attempts to integrate and apply these methods in peri-urban areas. 

Associate Professors Sarah Williams and Gabriella Carolini and Professors Janelle Knox-Hayes and Eran Ben-Joseph, all of the Department of Urban Studies and Planning, will develop a framework that considers the cultural, technical, and social dynamics of Indigenous and migrant communities while ensuring long-term sustainability. Specifically, the researchers will tackle the pressing issue of water and food shortages in Maicao, a region in Northern Colombia severely affected by drought due to climate change. The area is home to both the Indigenous Wayúu people and Venezuelan migrants who face significant challenges in accessing basic necessities. The team will collaborate with the Wayúu, Venezuelan peoples, and the United Nations World Food Programme (WFP) to co-design social, ecological, technical, and infrastructural solutions tailored to the social-political dynamics associated with climate change in Maicao. By engaging the community through a series of workshops on traditional ecological management practices, the researchers will ensure that the developed interventions are effective, culturally appropriate, and supported by those they are meant to help.

National crop type maps of India using deep learning and street view imagery

Accurate crop maps are an essential source of information for monitoring yield progress, projecting global crop production, and planning effective policies. However, only a handful of countries—mostly high-income—have the large-scale ground data necessary to harness satellite images and machine learning for crop type mapping. India, which is home to 150M smallholder farmers, currently has no crop type map for public use, with a lack of “ground truthing” being the main bottleneck.

Sherrie Wang, an assistant professor in the Department of Mechanical Engineering and the Institute of Data, Systems, and Society, created a cost-effective, automated, deep learning pipeline to map crop types with minimal manual labeling by using roadside imagery to generate ground references. With this method, Wang and her team will create, and make publicly available, a large dataset of geolocated crop type ground references for crop type maps of all of India.

Food Security in Africa under a Changing Climate – Navigating the Energy and Agricultural Transition to Net Zero

As Africa pursues sustainable development, several challenges emerge, such as improving living standards for the continent’s poor populations; increasing food security; developing renewable energy sources for a green energy transition; and reducing emissions toward net zero, all while facing the uncertainty of future climate impacts. African leaders have called for addressing these challenges by utilizing Africa’s land and water resources, but there are competing uses for those resources. What’s more, using resources for food versus energy versus carbon dioxide removal has important implications for sustainable development goals and economic and climate outcomes, as well as investment needed for infrastructure. Integrated modeling can provide important guidance to African policymakers for sustainable development paths to food security and green energy. Creating an integrated modeling framework that captures global dynamics while also representing detailed spatial and sectoral scales that provide regional- and national-level guidance can shed light on infrastructure needs and tradeoffs.

This project aims to build a framework that links highly resolved sectoral models for agriculture and water with the MIT Integrated Global System Model (IGSM), which represents global economic and climate systems. This novel global framework will assess food-energy-water-land interactions, as well as biophysical and economic impacts of climate change. The project team includes researchers from the MIT Joint Program on the Science and Policy of Global Change: Jennifer Morris, principal research scientist at the Joint Program and the MIT Energy Initiative; Adam Schlosser, senior research scientist and deputy director for the Joint Program; and Kenneth Strzepek, research scientist at the Joint Program and climate, water, and food specialist at J-WAFS.

Developing and enhancing water treatment and harvesting technologies

Protecting Drinking Water From Widespread Organic Contaminants Using Engineered Soil Bacteria

Emerging organic contaminants (EOCs), which are known for their carcinogenic properties, toxicity to human organ systems, and endocrine disrupting effects, are increasingly prevalent in drinking water. Examples of EOCs include a chemical used in plastics called bisphenol A (BPA) and benzophenone-3 (BP-3), an organic compound found in sunscreens and other products. Much of the EOC pollution in drinking water stems from pollution of groundwater, which serves as a primary water source for over 2.5 billion people worldwide, from sources such as railroad tracks, industrial zones, factories, and landfills. Traditional wastewater treatment methods remain unable to address EOCs, as they form harmful disinfection byproducts when EOCs interact with chlorination processes.

A possible solution to EOC water pollution will be undertaken by Professor Christopher Voigt of the Department of Biological Engineering, who will work with Professor Kristala Prather of the Department of Chemical Engineering, and Professor Kate Brown of the Program in Science, Technology, and Society. Professor Brown initiated the collaboration after connecting with graduate students Victoria Chen and Yonatan Chemla from the Voigt lab. The group plans to develop, test, and evaluate a synthetic microbiological solution that will safeguard groundwater sources by deploying engineered bacteria in polluted areas to remediate EOCs at their point source, preventing them from reaching groundwater in the first place. The team will also research the historical context of an early use of human-engineered organisms in Soviet Estonia in 1988-89 through oral interviews with participants and witnesses and archival documents. The goal of this research is to lead to a scalable bioremediation technology capable of improving water quality for both drinking and agricultural use. Findings also aim to inform policymakers about biotechnologies involving the release of engineered bacteria to the environment to help drive much-needed regulatory reform.

Predictive Activity Coefficient and Diffusion Models for Transport in Multicomponent Brines

More than two-thirds of the global population currently face severe water scarcity for at least one month each year. Recycling agricultural and industrial wastewater is critical to alleviating water scarcity. Minimizing wastewater volumes and removing harmful pollutants such as heavy metals and eutrophication-causing minerals, also plays an important role in protecting freshwater resources from contamination. New, efficient treatment processes and materials that can recover water from highly polluted brines from industrial and agricultural water use are needed. But first, scientists and engineers need to better understand how emerging membrane-based and electrochemical processes can separate multicomponent brines. Existing thermodynamic and mass transport models require an extensive set of parameters which must be estimated from experimental data and cannot be applied to new mixtures and compositions.

Professor John H. Lienhard V of the Department of Mechanical Engineering, and the director of J-WAFS, is working to develop open-source computational tools to estimate unknown thermodynamic interaction parameters and diffusion coefficients in highly nonideal, multicomponent aqueous mixtures. Using a combination of scientific machine learning techniques and rigorous theoretical frameworks, Lienhard is working with MIT research scientist Akshay Deshmukh to build a generalizable computational framework to predict chemical potential in high-salinity brines containing a large number of salts. They will also develop models for diffusive flow in multicomponent brines, and analyze mass transfer in complex, nonideal brines. While focused on fundamentals, the models developed will be applicable across varied fields in the water space.

High-efficiency atmospheric water harvesting enabled by vibrational actuation

Populations living in arid climates can face harsh conditions and water security challenges. Atmospheric water harvesting (AWH) technology, which extracts moisture from ambient air to generate water, is a promising strategy for producing clean water in arid regions. Sorption-based AWH technologies collect moisture from the air through porous structures such as hydrogels and metal organic frameworks. However, most existing sorption-based AWH prototypes exhibit prohibitively high energy consumption associated with their high desorption heat.

Svetlana Boriskina, a principal research scientist in the Department of Mechanical Engineering, has shown that utilizing a vibrational mechanical actuation technique can accelerate extraction of the atmospheric moisture captured by AWH sorbent materials and bypass the energy-intensive evaporation process. She will investigate the fundamental physics underlying this efficiency enhancement and will co-engineer new sorbent materials that will be tested by collaborators in Mexico, Israel, and Ukraine—countries with large arid areas or territories at the risk of desertification. Boriskina will also use AI techniques to optimize the vibrational actuator configuration to maximize both AWH productivity and energy efficiency. The aim is to make the technology economically feasible for adoption on scale to decentralize water production.

Denitrifying capsules to clean water sources

Nitrogen is an essential nutrient for the growth of all biological organisms, but ecosystems must maintain a precarious balance: too little nitrogen restricts overall productivity, but too much leads to overgrowth of plants and harmful algal blooms. To feed ourselves, humans manufacture nitrogen-based fertilizers by fixing atmospheric nitrogen through the Haber-Bosch process. This has resulted in a doubling of the global rate of natural nitrogen fixation. Unfortunately, as much as two-thirds of the nitrogen fertilizers that we apply to croplands wash off into local waterways where they stimulate algal blooms that lead to hypoxia and fish kills, and can also be toxic for humans and pets.

Andrew Babbin, an associate professor in the Department of Earth, Atmospheric and Planetary Sciences, plans to construct capsules that will scrub local waterways of excess anthropogenic nitrogen to prevent algal blooms. The self-sustaining capsules, which will be designed to preferentially let specific non-toxic algae grow inside of them, will be paired with bacteria that use the live algal material to remove nitrogen from water. The goal is to prevent harmful algal blooms before they arise in rivers, streams, and coastal estuaries.