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Quantifying greenhouse gas emissions is a critical component of climate change research and environmental management. To facilitate long-term, high-frequency monitoring, UC Berkeley researchers have developed a fully autonomous methane flux chamber system. This continuously and remotely operable technology integrates a specialized methane sensor and an automated pump system within a flux chamber to measure gas exchange between the ground and the atmosphere. The system features a controller that manages evacuation and fresh air intake cycles based on real-time sensor data. Equipped with its own power source, data storage, and network connectivity, the device can operate in remote locations and transmit measurement data to external servers without the need for manual intervention.

Monitoring humidity and water vapor levels in industrial and consumer settings often requires electronic sensors or integrated chemical dyes that can be prone to failure or degradation. To simplify this process, UC Berkeley researchers have developed hydrochromic reticular materials that integrate color-changing functionality directly into a porous adsorbent framework. These materials consist of a metal-modified reticular structure where color transitions are intrinsically coupled to the adsorption and desorption of water molecules within the porous architecture. By providing a direct visual response based on the material's internal hydration state, this technology enables robust, real-time monitoring of water vapor without the need for external electronic components, separate indicators, or complex power sources.

The critical challenge of providing clean, potable water in arid and semi-arid regions can be addressed by technologies that efficiently harvest atmospheric water, particularly under low-humidity conditions. UC Berkeley researchers have developed novel thiazole-based Covalent Organic Frameworks (COFs) that serve as highly efficient sorbents for this purpose. These COFs are crystalline, porous materials characterized by high porosity, permanent pore structures, and a chemically tunable nature. The disclosed COFs demonstrate a significant advantage over alternatives by exhibiting a low-humidity water uptake onset, coupled with fast adsorption kinetics, a high water working capacity, and excellent cycling stability. Furthermore, the development includes scalable synthetic methods, such as microwave-assisted and reflux routes, which enable gram-level, practical production.

      The widespread occurrence of nutrient-rich and metal-contaminated wastewater presents an environmental challenge and untapped economic opportunity. Ammonia, copper, and phosphorous are prime targets. For example, ammonia is industrially produced by the Haber-Bosch process, a highly energy-intensive (~12.5 kWh/kg-N to convert N2 to ammonia, consuming 1-2% of global energy usage) and greenhouse gas-emitting (~1.2% of global CO2 emissions) technique. After use, primarily as fertilizer, nearly 50% of all U.S.-consumed ammonia ends up in municipal wastewater and animal feedlot retention systems. Technologies presently proposed for recovering critical nutrients and metals from wastewater are limited in scalability by high energy demands, costly chemicals or membrane requirements, low efficiencies, or fouling challenges.       UC Berkeley researchers have developed and demonstrated a low-cost, robust, and near-zero-energy reactor that simultaneously recovers ammonia and other valuable ions (e.g., P and Cu) from wastewater streams. The reactor is driven by sunlight or low-grade waste heat, such that it eliminates the need for external pumping—further cutting energy consumption and capital cost. The functional material is an inexpensive cloth that is also roll-to-roll compatible, making it economically scalable and easy to manufacture. The reactor can be implemented within wastewater streams including municipal wastewater, animal feedlot wastewater, and organic waste digestate. It may further be adapted to recover other valuable resources, such as lithium, from sources like mining wastewater and landfill leachate. It may even be extended beyond nutrient and metal recovery to separation or pre-concentration of volatile organic compounds such as ethanol and methanol from aqueous solutions.

Traditional environmental policymaking often struggles to efficiently target interventions to achieve multiple, complex air quality goals simultaneously across a geographic area. This innovation, developed by UC Berkeley researchers, addresses this challenge by providing a sophisticated, multi-objective optimization method for targeted reduction of air pollution. The method generates a comprehensive mitigation pathway by integrating several modules: a forward module to model pollutant concentrations, a target concentration surface that defines the policy goals, a prioritization module to assess uncertainty and importance via a prioritization covariance matrix, and a Bayesian inversion module to estimate optimum emissions required to meet the target. This systematic, data-driven approach culminates in a mitigation pathway that guides the performance of specific pollution control measures, offering a significant advantage over conventional, less targeted policy-making by ensuring resources are directed where they will have the maximum environmental impact.

UC Berkeley researchers have developed a novel dispersion system for agricultural and environmental payloads, including seeds, soil amendments, miniature soil sensors, and so forth. Dispersive packages are biodegradable and biomimetically designed with similarities to natural seeds. Aerodynamic properties control large-area dispersions, while importantly, tunable gyroscopic properties are programmed for penetration parameters, such as depth, upon impact. Payload distribution can be fine-tuned accounting for local soil moisture and grain-size.

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Outdoor wireless sensor and camera networks are important for environmental monitoring and public-safety surveillance, yet their real-world deployment still relies heavily on expert intuition and exhaustive simulations that fail to scale in many landscapes. Traditional coverage-maximization techniques evaluate every candidate position for every node while factoring in every other node, the task complexity becomes intractable as node count or terrain granularity grows. The challenge is sharper in three-dimensional topographies where ridges, valleys, and plateaus block line-of-sight and invalidate two-dimensional heuristics. Moreover, once nodes are in the field, relocating them is slow and costly if new blind spots emerge or missions evolve.

Researchers at the University of California, Davis have developed a sustainable alternative to Portland cement by utilizing alkali-activated binders (AAB) with biomass ash, significantly reducing greenhouse gas emissions.

Traditional air quality monitoring often lacks the resolution to pinpoint specific emission sources within a city, leaving "hyperlocal" pollution spikes undetected. To address this, researchers at UC Berkeley have developed INFE²R, a sophisticated method for detecting and refining airborne pollutant emissions at a neighborhood scale. The system utilizes a Weather Research and Forecasting (WRF) module to generate high-resolution meteorological inputs, which are then processed through a Stochastic Time Inverted Lagrangian Transport (STILT) module to create a source-receptor transfer matrix. By combining prior emission estimates with a cross-dimensional assimilation of both fixed and mobile sensor measurements, the platform employs Bayesian inversion to generate highly accurate posterior emission estimates. This allows for a granular understanding of how pollutants move and accumulate in specific urban localities.

      Pebble bed reactors (PBRs) are an emerging advanced nuclear reactor design where fuel pebbles constantly circulate through the core, as opposed to housing static fuel assemblies, generating numerous advantages including the ability for online refueling versus expensive shutdowns. Online refueling is overall beneficial but poses an operation challenge in that the pebbles must be measured and analyzed for burnup characteristics very quickly (in under 40 seconds), without much time to cool down, challenging the high Purity Germanium (HPGe) detectors historically used for burnup measurements. HPGe detectors can normally only be operated up to tens of thousands of counts per second, far below radiation rates from freshly discharged fuel, and are therefore operated at large distances from sources, with significant shielding. Only a small fraction of detected counts comes from burnup markers, yielding high uncertainty, or can be completely masked by effects of Compton scattering within the detectors.      To overcome the challenges of using HGPe detectors to measure burnup in continuously fueled reactors, UC Berkeley researchers have developed a novel technology capable of measuring gamma rays within a fine energy ranges and without the interference of Compton scattering. The device is also significantly cheaper than HPGe detectors and offers a reduced detector footprint. Nuclides including but not limited to Np-239, Eu-156, and Zr-95 can be measured and analyzed for burnup, path information through the core, and fast and thermal fluence. Furthermore, precise measurement of the Np-239 content provides better data for reactor safeguard purposes. The technology offers meaningful improvements in measurement accuracy, footprint, and cost, for PBRs and other continuously fueled reactors, such as molten salt reactors (MSRs).

      Effective thermal management remains a critical challenge in designing and operating next-generation electronics, data centers, and energy systems. Devices are steadily shrinking and handling increased power densities. Traditional cooling strategies, such as heat sinks and immersive cooling systems, fall short in delivering the targeted, localized cooling needed to prevent or address thermal hotspots. Current solutions for localized hotspot cooling require active, energy-intensive methods like pumping of coolants and complex thermal architecture design.       To overcome these challenges, UC Berkeley researchers present a transformative passive method for localized, autonomous cooling of hotspots. The cooling system delivers effective, localized cooling across various device surfaces and geometries, including those geometries wherein cooling media must move against gravity. The benefits of the present system will be appreciated for computer chip and other electronics cooling, microgravity applications, battery thermal management. Beyond thermal management, the underlying system may also open novel avenues in fluid manipulation and energy harvesting.

Researchers at the University of California, Davis have developed advancements in understanding exodermal differentiation in plant roots highlighting the role of two transcription factors in plant adaptation and survival.

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Researchers at the University of California, Davis (“UC Davis”) have developed an optical absorber/emitter for thermophotovoltaics application with a tunable emission wavelength.

Researchers at the University of California, Davis have developed an approach to generating mechanical power from the earth's ambient thermal radiation using a Stirling engine.

      Probabilistic Seismic Hazard Analysis (PSHA) has become a foundational method for determining seismic design levels and conducting regional seismic risk analyses for insurance risk analysis, governmental hazard mapping, critical infrastructure planning, and more. PSHA traditionally relies on two computationally intensive approaches: Riemann Sum and conventional Monte Carlo (MC) integration. The former requires fine slices across magnitude, distance, and ground motion, and the latter demands extensive synthetic earthquake catalogs. Both approaches become notably resource intensive for low-probability seismic hazards, where achieving a COV of 1% for a 10−4 annual hazard probability may require 108 MC samples.       UC Berkeley researchers have developed an Adaptive Importance Sampling (AIS) PSHA, a novel framework to approximate optimal importance sampling (IS) distributions and dramatically reduce the number of MC samples to estimate hazards. Efficiency and accuracy of the proposed framework have been validated against Pacific Earthquake Engineering Research Center (PEER) PSHA benchmarks covering various seismic sources, including areal, vertical, and dipping faults, as well as combined types. Seismic hazards are calculated up to 3.7×104 and 7.1×103 times faster than Riemann Sum and traditional MC methods, respectively. Coefficients of variation (COVs) are below 1%. Enhanced “smart” AIS PSHA variants are also available that outperform “smart” implementations of Riemann Sum by a factor of up to 130.

Researchers at the University of California, Davis have developed a green technology designed for the efficient storage and discharge of heat energy sourced from intermittent green energy supplies.

Current methods for CO2­ ­capture and concentration (CCC) are energy intensive due to the reliance on thermal cycles, which are intrinsically Carnot limited in efficiency. Electrochemical carbon dioxide capture and concentration (eCCC) is a modular approach that can achieve significantly higher energy efficiencies than current thermal methods, however eCCC systems have been plagued by oxygen instability. The Yang lab has developed an eCCC approach that is over three times more efficient than any other reported redox carrier-based system and almost twice the efficiency of state-of-the-art alkanolamine-based systems.

Traditionally, land can be used for either crop growth or energy production. This technology optimizes the efficiency of land use by combining both. Researchers at the University of California, Davis have developed solar cell designs that absorb only specific solar photons (> 2.2 eV) to create electricity, while letting through beneficial light (< 2.2 eV) for efficient crop growth.

         Recent mass evacuation events, including the 2018 Camp Fire and 2023 Maui Fire, have demonstrated shortcomings in our communication abilities during natural disasters and emergencies. Individuals fleeing dangerous areas were unable to obtain fast or accurate information pertaining to open evacuation routes and faced traffic gridlocks, while nearby communities were unprepared for the emergent situation and influx of persons. Climate change is increasing the frequency, areas subject to, and risk-level associated with natural hazards, making effective communication channels that can operate when mobile network-based systems and electric distribution systems are compromised crucial.         To address this need UC Berkeley researchers have developed a mobile network-free communication system that can function during natural disasters and be adapted to most communication devices (mobile phones and laptops). The self-organized, mesh-based and low-power network is embedded into common infrastructure monitoring device nodes (e.g., pre-existing WSN, LoRa, and other LPWAN devices) for effective local communication. Local communication contains dedicated Emergency Messaging and “walkie-talkie” functions, while higher level connectivity through robust gateway architecture and data transmission units allows for real-time internet access, communication with nearby communities, and even global connectivity. The system can provide GPS-free position information using trilateration, which can help identify the location of nodes monitoring important environmental conditions or allowing users to navigate.

Professor Matthew Conley from the University of California, Riverside has discovered that catalysts used to generate polyolefin plastics also perform well in hydrotreatment reactions of plastic waste. This method works by treating plastic materials with known catalysts at 200⁰C to degrade  polymers into smaller alkanes in the presence of hydrogen. This technology is advantageous compared to existing methods since it does not require high temperatures​, has a relatively high yield (+80%)​, and can be applied to a variety of plastics to generate a feedstock of smaller polymers and monomers for further processing.  

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