RSI Small-Scale Proposal Call: Fall 2020
The RSI's small-scale grants are open to lead PIs who have their primary affiliation with one of Caltech's academic divisions and the ability to conduct research on campus. The program prioritizes funding proposals addressing significant challenges and opportunities associated with climate change and the stewardship of natural resources.
The Fall 2020 application period opens on October 1, 2020 and closes on November 10, 2020.
The Los Angeles Aqueduct provides one third of the water for Los Angeles, diverting it from the Owens River. Within ten years of the diversion, Owens Lake dried up and caused numerous air quality and sustainability issues. As the L.A. Department of Water and Power continues efforts to revive Owens Lake amid climate change by recharging the groundwater basin, we will apply a new technology, Distributed Acoustic Sensing (DAS), to advance the groundwater monitoring and management in the Owens valley. DAS converts fiber optic cables around the lake into sensitive seismic arrays with which we can measure mechanical changes of rocks caused by groundwater fluctuations. The time-dependent seismic images of the aquifers under Owens Lake will add a new dimension to our ability to measure the injection, withdrawal and intra-basin movement of groundwater, with the goal that these tools will help ensure sustainable management of underground aquifers.
This project will monitor ocean warming by inferring basin-scale deep ocean temperature changes from sound waves that are generated by repeating earthquakes. The ocean absorbs over ninety percent of the heat trapped on Earth by increasingly abundant greenhouse gases, but large natural temperature fluctuation pose a challenging sampling problem. By making use of some of the information generated by the tens of thousands of shallow submarine earthquakes that occur every year, this project aims to grow this approach into a program that significantly augments existing ocean observing systems, helping diagnose the planetary energy imbalance and improve predictions for the future rate of warming.
This project will create a physically-informed machine learning model for the relationship between land subsidence and groundwater abundance in California's Central Valley aquifer system. Integrating observable deformation and pressure relationships using Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) measurements of surface deformation with groundwater withdrawal measurement patterns, we aim to develop a new statistical framework for future subsidence responses to groundwater use. The resulting model opens up the possibility of machine learning-based decision making for sustainable groundwater management and infrastructure development.
This project will develop novel bio-composite materials from algae and agricultural waste. Algae, and algae-derived biopolymers, are promising components for sustainable materials, because of their diversity and composition. During growth, algae consume large quantities of CO2 and can grow on land unsuitable for agriculture and/or in wastewater. The use of agricultural waste fibers as reinforcement fillers allows for efficient repurposing of biomass, which would otherwise be disposed of in landfills. We will use different waste streams and algae strains to control mechanical properties. Our aim is to develop biomaterials that can replace industrial and consumer plastics, engineered wood and particleboards.
This project will apply modern technology including distributed camera networks, machine learning, and molecular sequencing, to census population dynamics of insects in several distinct ecosystems. We aim to develop and share novel, low-cost and accurate methods for measuring both species diversity and population density with the scientific community and amateur insect enthusiasts alike. In doing so we hope to spur more entomological monitoring efforts worldwide, generating insights to inform conservation models for a wide diversity of ecosystems, towards reversing deleterious effects of human impact.
This project will investigate the development of a "green" method for the enantioselective formation of carbon–carbon bonds using a catalyst based on iron, the most earth-abundant transition metal, from readily available starting materials. Because carbon–carbon bonds form the primary backbone of most organic compounds, which play critical roles in fields such as pharmaceutical science, polymer chemistry, and biology, the discovery of versatile and efficient methods to generate carbon–carbon bonds under mild conditions (and control stereochemistry, when relevant) is a highly important objective for sustainable manufacturing.
This project will investigate new, reliable techniques for polymerization and immobilization of redox-active species on high-surface area carbon, to develop heterogeneous, slurry redox flow batteries. Flow batteries have been identified as a key component for grid scale energy storage, but they currently suffer from low energy densities and high $kWh costs. Our approach aims to directly address these constraints to dramatically improve energy densities (>1000 Wh/L) in symmetric, non-aqueous redox flow batteries.
This project will demonstrate the feasibility of an open-source toolkit for soil synthetic biology, with the goal of bootstrapping a larger effort that would enable the use of engineered microbes to understand and modulate the complex dynamics of the rhizosphere. We will identify and characterize genetically tractable microbes capable of long-term persistence; create a toolbox of genetic parts for gene circuits and pathways in soil conditions; and design, build and test a stimulus-response circuit operating in soil. Long-term applications will include engineering microbial communities to optimize nutrient uptake by plants to improve their survival against environmental hazards such as drought, toxins and pathogens.
This project aims to identify crop-specific beneficial microbial partnerships as a first step towards identifying microorganisms that could be engineered as rhizosphere additives. Microbial communities found in the domain of the soil in the vicinity of plant roots (i.e., the "rhizosphere") significantly impact the ability of plants to grow and evade pathogens, yet they are susceptible to climate-related stressors. We aim to translate a recent discovery made from studies of a Caltech citrus rhizosphere (i.e., that certain bacteria can protect fungi from biotoxins known to accumulate in warmer, drier soils) to the rhizosphere of citrus and pistachios.
This project will develop an experimental system for the detailed study of the anaerobic microbial community and their interactions in seagrass beds. Vegetated coastal habitats such as seagrass meadows (e.g., Zostera marina) are considered critical ecosystems for carbon burial in the marine environment. Zostera is one of a few marine angiosperms with an extensive root system that facilitates long-term carbon sequestration, within rhizosphere-associated anoxic sediments. Compared to their terrestrial counterparts, relatively little is understood about the impact of microbial activities within the rhizosphere-processes that ultimately influence net carbon storage. We will leverage Caltech's Kerckhoff Marine Laboratory facilities, local university collaborations, and our expertise in marine microbial ecology to study two key processes within the anoxic seagrass rhizosphere: root-associated nitrogen-fixation and methanogenesis.
The Great Human Experiment By The Numbers
PI: Rob Phillips
Research Team: Griffin D. Chure, PhD, Avi Flamholz, PhD, Tine Valencic, and Nicholas S. Sarai
The Division of Physics, Mathematics and Astronomy
Ecology and Biosphere Engineering Initiative
This project will establish resources that carefully present the state of human impacts on the planet from a compelling quantitative perspective. Our aim is to clarify the facts, explain why the orders of magnitude of the various parameters have the values that they do, and elucidate what the quantitative consequences of proposed mitigation strategies are in order to meet various sustainability challenges.
We will purchase and use a PICARRO G2401-m CO2/CH4/CO/H2O analyzer, to enhance multiple projects at Caltech aimed at improving climate change predictions and developing geoengineering technologies to mitigate impacts. Specifically, the instrument would facilitate investigation of the climatic impacts of shipping vessel emissions, quantification of fugitive CH4 emissions in residential environments, and development of reactors to sequester CO2 in the ocean.
We will purchase and use a spectroscopic water isotope analyzer that will enhance multiple Caltech projects within the RSI's Climate Science, Water Resources and Ecology and Biosphere Engineering Initiatives. The stable isotope composition of water ( 2H/1H, 17O/16O, and 18O/16O ratios) has very broad utility as a tracer for this ubiquitous compound, and the instrument thus facilitates investigation across many relevant disciplines including: (paleo)climate and meteorology, hydrology, limnology, global biogeochemistry, microbiology, ecology, and soil science.
This project will use ultrasound standing waves – a low-cost, scalable, and energy-efficient platform capable of arranging microbes in 3D space – to enhance sunlight capture and increase biomass production. If successful, this technology could not only enable the cost-effective production of biomass for high value commodities, but also have positive environmental impact, including carbon sequestration and wastewater treatment.
This project is an interdisciplinary collaboration between Caltech and JPL for CO2/Lidar data collection and analysis examining spatial variations in diffuse emissions of carbon dioxide from volcanic areas in Costa Rica. The tropical CO2 fertilization effect is the single largest uncertainty in the terrestrial contribution to projections in climate. This pilot study will address how tropical ecosystems respond to increasing CO2, by surveying a modern ecosystem where local CO2 increases are measurable and can be related to vegetation response. We will also use the dataset for volcanic hazards studies to evaluate links between the observed pattern of CO2 variations and the tectonic structure and seismicity of the regions around the volcanoes.
This project involves participation in a major Southern Ocean field program, SOLACE, to observe the ocean's biological pump in the Antarctic Circumpolar Current. The ocean's biological pump is a major component of Earth's carbon cycle that allows the ocean to take up anthropogenic carbon emissions from the ocean. The Southern Ocean has made the largest contribution to uptake of anthropogenic carbon, yet studies linking physical and biogeochemical mechanisms of carbon export from the upper ocean have been limited. Our group at Caltech will deploy and pilot multiple sub-surface ocean gliders — autonomous ocean robots — to collect physical and biogeochemical properties in the upper ocean. We anticipate that the project's observations, the first of their kind in the Southern Ocean, will help to improve our mechanistic understanding of carbon cycling in this region and its representation in climate models.
This project will use a suite of hydrocarbon measurements, and their economic trends, to improve the diagnosis of methane emissions from one its largest contributors – energy production. The increasing abundance of methane contributes significantly to global warming. Mitigating such emissions is therefore important for reducing anthropogenic climate change. Methane emissions result from numerous natural and anthropogenic activities. Using multiple alkane tracers, we will apportion losses from this sector to before and after the post-gas processing processes. We anticipate that the result from this research can inform the policy solutions.
This project seeks to build an integrated framework for the control and market design of future low-carbon energy systems. The incorporation of renewable energy into the power system (grid), requires moving from a centrally managed and optimized system design to a distributed design, where decentralized agents learn and interact with dynamic, real-time pricing and market mechanisms (smart grid). Achieving this transformation requires new tools that interface between multi- agent learning and market design. We aim to develop and test these tools which, if successful, would enable intelligent real-time control for hundreds of thousands of distributed energy resources such as energy storage, renewables, or smart energy homes. A successful control framework would take into account the individual objectives, guarantee each participant's welfare and maintain the overall energy system stability and reliability.