Communities heavily affected by air pollution levels often lack access to costly air quality monitoring. Berkeley is developing a network of low-cost aerosol black carbon detectors (ABCDs) to measure locally emitted pollution levels. The Clinic team built a website that stores and reports ABCD data through an interactive map, enabling the Berkeley team to conduct their community-engaged research effectively. (Note: This project was jointly completed with an engineering project that adapted the ABCDs to send data over modern networks).

CSIS is an American think tank that explores “practical ideas to address the world’s greatest challenges,” one of which is climate change. One difficulty is identifying public policy interventions that will both (1) effectively reduce greenhouse gas emissions and (2) be practical to implement in today’s international economic and political environment. The CSIS Clinic team has developed a model simulating the complex and dynamic interactions of international climate policy. This model will be used in tabletop simulations, helping CSIS staff understand political strategies for advancing global climate action.

Approximately 15% of global energy consumption is used to heat and cool buildings. Blue Frontier addresses this by developing A/C technology that offers up to 90% reduction in electricity use. By using liquid desiccants, they achieve more efficient cooling and dehumidification than traditional methods. However, this requires expensive sensors, increasing upfront costs. The Clinic team is designing software-based sensors to replace the physical ones. The team is leveraging machine learning algorithms, including random forest and neural networks and physics-based models, to create these sensors, making the technology more cost-effective and scalable.

A lab at UC Berkeley has conducted a study to spatiotemporally analyze the air quality in West Oakland using a fleet of 100 black carbon sensors. The HMC UC Berkeley Clinic team designed a solution to upgrade the data communication and integrate automated localization for this fleet of sensors to be used in an upcoming study to analyze the air quality of three California cities: Richmond, Stockton and Fresno.

Aligned with the mission of the Union of Concerned Scientists—a nonprofit that puts independent science into action and advocates for a healthy, safe, and just future—this project calls for an examination of water and energy usage patterns in artificial intelligence (AI) systems through a comprehensive literature review of data center operations. The research analyzes current reporting practices regarding AI’s environmental impact and evaluates resource consumption projections. As a complement to the literature review, the Clinic team developed an interactive informational website that defines key metrics and provides context around AI infrastructure’s environmental footprint.

GM Energy is focused on expanding and accelerating a holistic energy ecosystem through new products, software and services. To further this goal and consider more sustainable solutions, the GM Energy Clinic team is investigating a cost-optimized sodium-ion battery energy storage system (BESS) at a module level. The team is also performing market research on the future feasibility of sodium-ion batteries.

Helion aims to construct the world’s first commercial nuclear fusion power plant, capable of producing clean, low-cost energy through a process called magneto-inertial confinement. In order to produce the necessary magnetic field strength for this process, Helion must drive powerful electromagnets with short, high-current pulses. The Helion Clinic team is tasked with designing and manufacturing a transmission line prototype that can transmit large amounts of power to the electromagnets with minimal losses while maintaining a small physical footprint.

The Idaho National Laboratory Clinic team is analyzing large operational and event datasets to develop a method for estimating the operations and maintenance (O&M) costs associated with flexible operation of hydroelectric power plants. The team is also designing a control system exploring the feasibility of using industrial-scale Li-ion battery storage to minimize O&M costs. Understanding these costs will help operators make decisions on how their plants can support a clean energy future.

Argonne National Laboratory has been developing the Greenhouse gasses, Regulated Emissions, and Energy in Technologies (GREET) life cycle analysis model for almost 30 years. The team’s goal is to rebuild the GREET model with a more flexible and scalable programming backend to support a user-friendly interface, improve the robustness and efficiency of the life cycle analysis process involving user data input, processing, and modeling, and to expand the modeling functionality with enhanced user accessibility.

The Union of Concerned Scientists puts independent science into action and advocacy for a healthy, safe and just future. This project supports the UCS Western States program’s efforts to advance equity in federal infrastructure investments in California. The Biden Administration’s Justice40 initiative aims for 40% of certain investments to benefit disadvantaged communities. Our team analyzed two years of Bipartisan
Infrastructure Law investments against this goal and built a website with an interactive dashboard to hold government accountable to Justice40 outcomes.