Skip to content ↓

2024 Seed Awards Projects

Saurabh Amin, professor of civil and environmental engineering and principal investigator at the MIT Laboratory of Information and Decision Systems (LIDS); Alexandre Jacquillat, associate professor of operations research and statistics at the MIT Sloan School of Management.

The logistics sector contributes to 20–25% of greenhouse gas emissions, a third of which stems from road freight. Two decarbonization opportunities arise from the deployment of a charging infrastructure for electric vehicles along medium- and long-haul routes, and from the emergence of digital platforms to consolidate shipments across logistics providers. This project exploits the complementarities between these two opportunities to develop theoretical and data-driven insights toward the deployment of a scalable charging infrastructure on highways. The first phase will develop an optimization approach to identify effective centralized structures of charging networks and to quantify the benefits of pooling investments across multiple stakeholders (e.g., fleet owners, logistics service providers, government agencies, and private investors). The second phase will design collaborative mechanisms to enhance the adoption of electrified vehicles and the deployment of a charging infrastructure, while capturing the constraints of logistics operations and of electric vehicle technologies. Methodologically, this project will contribute new algorithms in large-scale integer optimization (building upon vehicle routing and facility location methodologies) and mechanism design (building upon network formation games and pricing mechanisms). Practically, it will contribute new decision tools and policy recommendations to support the ongoing transition toward the electrification and decarbonization of long-haul logistics.

Dara Entekhabi, Bacardi and Stockholm Water Foundations Chair; Professor of Civil and Environmental Engineering; Professor of Earth, Atmospheric and Planetary Sciences

Aquifers are widely used in irrigated agriculture for food production. These subsurface natural reservoirs are tapped into by pumping wells that withdraw water for irrigation. The aquifers are replenished with the recharge hydrologic flux which is the vertical flow of water in the near surface soil where precipitation enters the soil. Thus, the natural rate of recharge flux is indeed the sustainable rate of groundwater use. Important as this flux is, there is no systematic mapping of it. There are no in situ instruments that can be widely deployed to map recharge. While isotopes of water are often used to estimate recharge at a field site, this approach is expensive and labor intensive. Aquifers around the world are being woefully over-exploited. To manage and restore them, we need mapped estimates of recharge. This project aims to provide global groundwater recharge maps using NASA’s Soil Moisture Active Passive (SMAP) satellite data. Our approach combines satellite measurements with precipitation data and land surface models to develop reliable methods for estimating groundwater recharge globally. This research will provide insights and tools for sustainable groundwater management, supporting effective policy-making and strategic planning to ensure water security in the face of climate change. Our research emphasizes global applicability, demonstrating how a better understanding of groundwater recharge can inform sustainable management practices worldwide. 

Randolph Kirchain, Director, MIT Concrete Sustainability Hub and Principal Research Scientist, MIT Materials Research Laboratory

An important part of any firm’s sustainability strategy is creating physical infrastructure with a small impact on the environment. This means creating buildings that are efficient to operate, designed to be durable while using materials efficiently and constructed from low-carbon materials. For most buildings and horizontal construction, the largest source of carbon emissions comes from operational energy consumption. After operational impacts, the next issue to confront is reducing the embodied carbon association with building and horizontal construction, maintenance, and end-of-life. For most commercial facilities, the single largest sources of embodied carbon are associated with the production of cement-based products. This proposal will provide the knowledge and tools for MCSC members to benchmark their current construction-related embodied carbon status, understand the existing and emerging strategies to reduce that carbon, and to identify the scalable low-carbon cement-based product solutions most suited to their application and context. This proposed work will explore strategies to reduce the carbon burden of both buildings and horizontal construction (e.g., parking facilities and  courtyards). Solutions will focus on binder technologies to reduce the carbon emissions associated with cement-based product materials, with a second phase to this project focusing on strategies to use cement-based products efficiently and effectively.

Darcy McRose, Assistant Professor, Department of Civil and Environmental Engineering at MIT

Although the use of nitrogen fertilizers is essential for agricultural productivity, much of the fertilizer applied to fields is lost before it reaches plants. One particularly problematic fate for nitrogen fertilizer is its conversion to the climate-active gas nitrous oxide (N₂O) by soil microbes. This microbial transformation is ubiquitous in crop soils and makes agriculture a major anthropogenic source of N₂O. Several synthetic small molecule inhibitors that target the microbes responsible for nitrification, the first step in the process, are in use today. More recently, plant-derived inhibitors have emerged as a complementary strategy to combat N₂O release from soils. While these biological nitrification inhibitors (BNI) are incredibly promising, we lack a mechanistic understanding of how they affect soil microbes and how their efficacy fluctuates under different environmental conditions. This proposal will address key knowledge gaps in our understanding of how biological nitrification inhibitors alter N₂O release from pure microbial cultures, simple microbial consortia, and crop soils. Our goal is to provide quantitative information needed to assess the feasibility of using these inhibitors and to identify optimal management practices. We are particularly interested in producing results that can be translated to management practices, such as changes in the timing of BNI additions or alterations in irrigation patterns (which largely control soil oxygen) that might make these interventions most effective. 

Bradley D. Olsen, Alexander and I. Michael Kasser (1960) Professor of Chemical Engineering at MIT

The vast majority of plastic products and packaging sent to materials recovery facilities are multi-material or contain additives such as dyes, making it challenging to recover high purity bales of a single type of plastic. Even as we move towards mono-material, the mechanical and rheological properties of the specific grade of plastic used for a product are unknown. However, if plastic producers use recycled content from their own post-consumer products and packaging, it can greatly mitigate this issue, making mechanical recycling even more feasible. As plastics are already highly efficiently “barcoded” based on branding used to promote consumer recognition, this project will use these branding marks to effectively sort plastics by manufacturer type instead of plastic type using AI image recognition. This will enable manufacturers to either buy back or take back in exchange for a tax rebate their own products and use them most efficiently in recycling, as the grade and additives of the original product will be a match to the grade and additives of the new product. This workflow is well-suited for Extended Producer Responsibility (EPR) which places the onus of packaging recyclability on the producer or manufacturer and presents a potentially more effective and palatable alternative to the general plastic production taxes or bans being implemented in jurisdictions today. Because this technology could also be readily implemented with modest modifications to current system operations and without system-wide collective agreement on change, it presents an extremely promising approach for near-term action to improve circularity.

Georgia Perakis, interim dean and professor of Operations Research, Statistics and Operations Management at MIT Sloan School of Management; and Talia Tamarin-Brodsky, assistant professor in the department of Earth, Atmospheric, and Planetary Sciences at MIT. 

Due to rising temperatures and increased frequency of weather extremes under climate change, it is likely that weather will continue to have even larger impacts on the economy, whether influencing worker productivity during heat waves and extreme cold conditions or consumer transactions in retail stores. Using data from different types of retailers, machine learning models will be developed in combination with weather evolution models towards studying the long-, medium-, and short-term effects of weather characteristics on the retail industry, focusing on sales. With results that can be easily extended to study other sectors in the economy, this research is an important first step towards building a deeper understanding of how weather influences our economy.

Roberto Rigobon, professor of applied economics at MIT Sloan School of Management

Supporting researchers: Florian Berg, research scientist at the MIT Sloan School of Management; Esther Kohler, postdoctoral associate at the MIT Sloan School of Management; Florian Heeb, postdoctoral associate at the MIT Sloan School of Management

Voluntary carbon markets are predicted to play a crucial role in global efforts to reach Net Zero. However, recent evidence points to major flaws in current market practices. A particular issue is the missing additionality of many carbon offset projects. In this project, we will generate a unique database of carbon offset projects to develop metrics to detect failures in current additionality assessment practices. We will also use our insights to develop recommendations on how to improve these practices, in collaboration with industry experts and with a focus on natural sink projects. The findings of this project will be valuable for MCSC member companies that seek to include high-integrity carbon projects in their sustainability efforts. 

Sherrie Wang, assistant professor in the MIT department of Mechanical Engineering; Institute for Data, Systems, & Society (IDSS); and Laboratory for Information & Decision Systems (LIDS). Principal Investigator of the Earth Intelligence Lab. 

Soils are the largest terrestrial carbon reservoir, containing approximately 2,500 gigatons of carbon–more than three times the atmospheric carbon and four times that in all plants and animals. Monitoring and managing soil organic carbon (SOC) is essential for enhancing carbon sequestration and reducing greenhouse gas emissions. Although accurate SOC mapping is challenging due to spatial heterogeneity and the high cost of traditional soil sampling, hyperspectral satellite imagery offers a promising solution as it provides detailed information on soil properties over large areas with high spatial, temporal, and spectral resolution. This study will use hyperspectral satellite data and machine learning to map SOC in the United States, India, and Kenya. By combining data from government and private sources, we aim to identify spectral features for SOC prediction and assess their generalizability across regions. Our goal is to develop a robust predictive algorithm for global SOC mapping and enable the quantification of SOC changes over time to better understand soil carbon dynamics and inform climate change mitigation efforts. This project’s outcomes have the potential to drive significant advances in digital MRV technologies, contributing to the broader aim of decarbonizing agriculture and improving ecosystem resilience. 

Siqi Zheng, faculty director of the MIT Center for Real Estate and the Sustainable Urbanization Lab; Roberto Rigobon, professor of applied economics at MIT Sloan School of Management

Supporting researchers: Bram van der Kroft, MCSC postdoctoral fellow affiliated with the Aggregate Confusion Project; Chenhan Shao, doctoral student in the department of Urban Studies and Planning. 

Reducing carbon footprints of the built environment (buildings, physical infrastructure and supply chain systems) is crucial for achieving net-zero emission goals, as this sector accounts for approximately 70%-80% of global carbon emissions. However, buildings and infrastructure are not always constructed or retrofitted in an energy-efficient manner due to high upfront investments and financial feasibility concerns. While revealing and quantifying green premiums can stimulate investors’ willingness to pay for lower-carbon products and practices, in reality, green premiums vary significantly across asset classes, geographies, investor preferences, and policy regimes–complicating the transition to a more sustainable built environment. This project aims to develop a holistic framework of measuring green premiums using an economically grounded model calibrated on a geo-sector case study, with the capacity to be generalized to other settings. Additionally, we will develop an interactive toolkit to enable MCSC members to incorporate assessments of future regulatory developments, investor preferences for sustainability, and utility prices when evaluating green premiums. The white paper and toolkit simulation could provide critical input for long-term financial decisions and facilitate member companies’ decision-making in choosing the most cost-effective paths to achieving net-zero emissions.

Back to top