Stanford University
SESUR student group

Potential Projects for Summer 2022

Projects for Summer 2022

SESUR applicants - Stanford Students

If you are interested in learning more or getting involved in one of these projects, you should contact the faculty member  and other mentors directly.  This list is not comprehensive however, and many other projects are possible.  Please visit this page often for project updates.  Also, feel free to explore all our faculty research areas and contact anyone whose research interests you.  For your reference, you can also view the project archives at the bottom of this page for an overview of previous year's submitted projects.

SURGE applicants - Non-Stanford Students

If you are interested in getting involved in one of these projects, please indicate so on your application. This list is not comprehensive however, and many other projects are possible. Feel free to browse the list of faculty research interests and indicate, on your application, anyone whose research interests you.

updated on 1/10/2022

Potential Projects

Investigating the Morphology of Impact Craters on the Moon using Unsupervised Machine Learning

Category(s): Natural Hazards, Planetary Science
Department: Earth and Planetary Sciences

Impact craters, the most prevalent topographic feature on the surface of the Moon, form when meteorites impact the surface at supersonic speeds. The integrated effect of impacts over time churns the rocky surface of the Moon into a thin, powdery layer of debris called the lunar regolith. Exposed regolith darkens over time due to physical and chemical interactions with the harsh environment of space. When fresh craters form, they overturn this dark regolith and expose bright soils. As a result, fresh craters are characterized by bright walls and ejecta blankets, but also by rays; linear features that extent up to tens of crater radii away from the crater rim. Studying fresh impact craters on the Moon could help us constrain the size distribution of impactors in the Earth-Moon system, explore the recent cratering rate of the Moon, and characterize lunar surface processes that have occurred in the past millions of years.

Due to their unique, easily distinguishable surface features, fresh craters are typically identified manually by human analysts in images. However, manually characterizing a large number of craters is difficult and, in the extreme case, unfeasible. In this project, we seek to employ machine learning to automatically characterize the maturity of all simple craters (whose size is between 1 and ~15 km) on the Moon. Using an Autoencoder, a type of an artificial neural network, we will analyze high-resolution images obtained by the Lunar Reconnaissance Orbiter to identify distinct morphometric features like bright ejecta and rays and derive the maturity of craters.

The project will involve data collection and pre-processing the images, and designing and employing an Autoencoder based on popular architectures. Students with coding background in Python, R, or Matlab are encouraged to apply. Prior experience in machine learning or statistics is not required. At the end of the summer, students will be mentored to compile their results in the form of a scientific conference abstract.

Skills/Interest/Background: Computer Programming, Geology, Machine Learning, Scientific Programming, Statistics

Developing Low-Cost Tools to Measure Natural Greenhouse Gas Emissions

Category(s): Climate Change, Food and Agriculture
Department: Earth System Science
Mentor: Alison Hoyt, Mentor: Jack Lamb

The natural environment is a significant source of greenhouse gases in the Earth’s atmosphere, but these contributions remain poorly constrained due to measurement limitations. Current techniques require expensive gas analyzers or collecting cumbersome gas samples, either of which creates barriers against comprehensive sampling. Meanwhile, greenhouse gas emissions from the natural environment can vary widely in space and time, requiring a highly resolved measurement scheme. In our group, we have been working to address these challenges by creating easy-to-use, low-cost greenhouse gas emission sensors. In this project, one or more students will assist with the development and production of greenhouse gas sensing tools. This project provides a wide variety of opportunities to get involved, and we will work with students to define a plan for summer research based on their interests and experience. Potential focus areas include electronics, software development, manufacturing, calibration, field testing, and user experience design. Students will take a leading role in developing engineering prototypes into user-ready tools for studying Earth’s climate.

A student project might look like one of these examples: Researching and developing a manufacturing strategy to build hundreds to thousands of units; Developing user interface software to interface with hardware, and process data; Researching unmet needs in greenhouse gas sensing and designing suitable tools; Preliminary field deployment and calibration of prototype sensors; Designing hardware/firmware protocols for a wireless sensor network, or something different depending on interest.

Interested students from any field are encouraged to apply, including but not limited to earth sciences, engineering, and computer science. Experience or interest in climate science, design, manufacturing, electronics, or software development would all be beneficial to the project.

Skills/Interest/Background: Chemistry, Computer Programming, Engineering, Field Work, Lab Work, Scientific Programming, Statistics

Applying machine learning techniques to induced seismicity

Category(s): Climate Change, Energy, Natural Hazards, Planetary Science
Department: Geophysics
Mentor: Greg Beroza, Mentor: Ryan Schultz

Any activity that changes the distribution of stress in the Earth’s crust has the potential to cause earthquakes.  A prominent research focus in recent years has been earthquakes caused by human activities (i.e., induced seismicity): both because of their ability to cause damage in exceptional cases and their ability to halt operations.  There is still much to understand about the causes, potential impacts, and mitigation strategies for these earthquakes.  In many cases, this problem has been exacerbated by a lack of data.  Fortunately, recent developments in machine learning techniques have been able to revolutionize the catalogue-building process in seismology.  The use of neural networks on large, labelled datasets allows for super-human level development of earthquake catalogues – often increasing the resolvable data by an order of magnitude from traditional approaches.

            In this project, we intend to use recently developed machine learning techniques to build a large catalogue of induced earthquakes.  Data will span almost a decade of continuous ground motion monitoring in Alberta, Canada – a region that has encountered a significant increase in seismic activity due to oil and gas operations.  The catalogue derived from this work will be used to better discern the causative activities, their potential impacts, and possible strategies to mitigate their risks.

We are seeking a self-motivated and enthusiastic student to help us implement the developed techniques on the continuous waveform data in the catalogue building process. We anticipate the student will develop some understanding of induced seismicity, its triggering mechanisms, and techniques for risk management. The student will develop state-of-the-art skills in earthquake catalogue development. A background in geophysics or machine-learning is not required.  Some prior experience with scientific programming, preferably with Python or MATLAB would be very helpful.

Skills/Interest/Background: Computer Programming, Machine Learning, Mathematics, Physics, Scientific Programming, Statistics

Phytoplankton ecology and behavior in the Arctic Ocean

Category(s): Climate Change, Ocean
Department: Earth System Science
Mentor: Kevin Arrigo, Mentor: Stephanie Lim

Phytoplankton are the primary carbon fixers in the ocean and serve as the base of the marine food web. The Arrigo lab studies phytoplankton’s role in global biogeochemical cycles, primarily in the polar regions. This project will focus on phytoplankton in the Arctic Ocean, an ecosystem which is warming at twice the global rate and undergoing rapid changes, and seeks to characterize major patterns in phytoplankton ecology and behavior.

This project will use “The Gravity Machine” (, a vertical sinking column with a tracking microscope, to characterize phytoplankton sinking behaviors under various environmental conditions. Results may help explain the formation of the subsurface chlorophyll maximum, a persistent feature in the Arctic where phytoplankton congregate at a depth of 10s of m below the surface. Many theories explaining the subsurface chlorophyll maximum have been proposed, but they are difficult to test in the field, so we seek to apply new single-cell tracking technology to test these potential mechanisms in the lab. Altogether, a better understanding of phytoplankton behavior may help explain how phytoplankton in the Arctic will respond to climate change.

Interested students from any field are encouraged to apply, including but not limited to earth sciences, ocean sciences, and biology. A student would develop experimental design, laboratory, and data analysis skills.

Skills/Interest/Background: Biology, Lab Work

Memoirs of a Mineral: Unraveling records of magma storage preceding silicic volcanic eruptions

Category(s): Dynamic Earth, Evolution of Earth, Natural Hazards
Department: Earth and Planetary Sciences

Volcanic eruptions pose a significant hazard to society, particularly when they are explosive. Magma viscosity is correlated with magma silica content and explosivity, such that silicic magmas (~>65 wt% SiO2) are particularly prone to producing dangerous, explosive eruptions. Volcanoes that erupt such magmas have generated some of the largest and most explosive eruptions in Earth’s history. Identifying and monitoring potentially eruptible silicic magma bodies in the modern Earth’s crust via geophysical observations (e.g., seismic studies) has proven challenging. Therefore, to understand and predict the future behavior of active silicic magmatic systems, scientists must utilize the rock record left behind by past eruptions. The minerals that grow in magma before an eruption and are preserved in erupted rocks can provide especially rich information about a magmatic system. In particular, the chemical compositions of minerals can reflect important information about magmatic conditions, such as temperature, pressure, and magma composition. Furthermore, minerals grow outward, developing layers like the rings of a tree, such that we can use core-to-rim variations in mineral chemistry of individual crystals to investigate changes in magmatic conditions through time.

Ultimately, the goal of the project is to better understand the behavior of eruptible silicic magmas in the crust. The specific approach will be to assess the conditions of silicic magma storage which led to eruption via mineral geochemistry. The student will acquire data via analytical instrumentation on campus to characterize mineral chemistry from silicic volcanic rocks from Nevada. Following data analysis, the student may apply various petrologic tools, including but not limited to geothermometers and geobarometers, to obtain critical information about silicic volcanic systems and the magmatic storage conditions that lead to eruptions.

We are looking for an enthusiastic student with background knowledge in Earth sciences and chemistry, who has quantitative skills and experience with Excel or other programs/coding languages useful for data manipulation and plotting. Experience with mineralogy and igneous petrology is helpful, but not required. 

Skills/Interest/Background: Chemistry, Computer Programming, Engineering, Geology, Lab Work, Scientific Programming, Statistics

Carbon content of Colombian peatlands

Category(s): Climate Change, Freshwater
Department: Earth System Science
Mentor: Alison Hoyt, Mentor: Scott Winton

Peatlands are ecosystems with soils composed almost entirely of partly decomposed organic matter. They cover just 3% of the world’s land surface, but store as much carbon as all the world’s trees and terrestrial vegetation. Peatlands in tropical areas are sensitive to disturbance and if they are drained or burned, carbon lost to the atmosphere is irrecoverable because peat takes hundreds or thousands of years to form. Protection of peatlands is, therefore, a global priority for climate change mitigation, but conservation planning is difficult because of a poor understanding of peatland distributions in tropical areas, especially South America. For example, the two published estimates of peat volume in Colombia vary by two orders of magnitude (3 to 327 km3).

Knowledge of tropical peatland distributions and carbon stocks must improve in order to develop natural climate solution strategies involving peatlands. This project focuses on how much carbon is stored in Colombian peatlands.

We are seeking an enthusiastic student to work in the terrestrial carbon laboratory with peat cores recently collected from swamps in the Colombian Amazon. Activities will include, grinding soil in a ball mill, weighing soil subsamples on a microbalance, packing analytical tins and operating lab instruments. Previous experience with soils or in a laboratory setting may be useful but is not required. Students will visualize results using data software. R is preferred, especially if the student has a background or interest in learning coding skills, but Excel is also acceptable if that is what the student prefers.

Skills/Interest/Background: Chemistry, Lab Work, Statistics

Reaction Modeling and Analysis for Carbon Dioxide and Hydrogen Storage

Category(s): Climate Change, Energy
Department: Energy Sciences & Engineering

Due to approaching decarbonization and net-zero emission targets, considerable attention has been given to advancing methods of carbon dioxide (CO2) and hydrogen (H2) storage. In a theorized clean energy economy, CO2 and H2 are securely stored underground in naturally occurring formations due to various trapping mechanisms involving physical impedances and chemical reactions. However, immense variability in the physical regime, pore-scale geometry, and geophysical reactive chemistry exists in such systems, making them elusive to modeling efforts, but fruitful in opportunities for further model development and analysis.

Activities in this project revolve around model development and analysis for reactive transport in geological CO2 and H2 storage systems. We are interested in the utilization and improvement of our state-of-the-art, multi-scale model development code, Symbolica, for analyzing the complex reactions present in such systems. In particular, we look to investigate 1.) how side reactions in geological storage systems affect reactive timescales and chemical outcomes, and 2.) how large scale, geological temperature gradients affect reactive physics.

We are seeking an enthusiastic student to research the reaction networks, pore-scale geometries, and typical physical parameters relevant in geological CO2 and H2 storage systems. Reactive transport models will then be generated using Symbolica and solved using numerical analysis. Students with experience in Mathematica and python are preferred, and basic knowledge in CO2 or H2 sequestration and reactive systems is desired, but not required. Experience conducting literature reviews and working independently is also a plus.

Skills/Interest/Background: Chemistry, Computer Programming, Engineering, Mathematics, Scientific Programming

Carbon Dynamics of a Mixed Coral-Seagrass Ecosystem in Palau

Category(s): Climate Change, Ocean
Department: Earth System Science
Mentor: Rob Dunbar

Even if the anthropogenic CO2 emissions are greatly reduced over the next 20 to 30 years, modeling studies show that we must deploy large-scale and effective carbon dioxide removal (CDR) technologies if we wish to prevent the most dangerous outcomes of future climate change. Blue CDR refers to C uptake by marine systems. Natural coastal systems such as algal and seagrass beds, mangrove forests, estuaries, and coral reefs are already known to process large amounts of marine C, and research on whether management practices can enhance coastal blue CDR is accelerating.
This project involves working with a team of Stanford faculty, staff, and students to conduct in-situ measurements of C system transformations in mixed coral reef/seagrass communities in the Republic of Palau. This work builds on several years of pilot projects and can be linked with participation in the BOSP Stanford Palau class offered during the early summer quarter 2022. We note that at the moment the university has given us a green light to teach the BOSP undergraduate course in Palau next summer and we expect to support a limited number of undergraduate research projects after the course ends. The SESUR student(s) will participate in fieldwork on shallow marine reefs and seagrass beds as well as analytical work in a lab in Palau. If covid conditions require remote work only, Dunbar will aid the student in the development of mixed biophysical/biogeochemical models of these systems – the kinds of models that are eventually used to determine the cost-effectiveness of specific coastal CDR strategies.

Skills/Interest/Background: Biology, Chemistry, Field Work, Lab Work, Physics

Human Dimensions of using Marine Environmental DNA to Monitor Ocean Biodiversity

Category(s): Human Dimensions and Sustainability, Ocean
Department: Emmett Interdisciplinary Program in Environment & Resources
Mentor: Nicole Ardoin, Mentor: Meghan Shea

Scientists and conservationists are increasingly using environmental DNA (eDNA; the bits of DNA that organisms leave behind in the environment) as a way to measure biodiversity, including in ocean environments. eDNA has the potential to make monitoring marine ecosystems much easier and cheaper, but there are still many big scientific questions about what eDNA samples actually represent. In order to advance the use of marine eDNA, we need a lot of scientific work, but we also need a better understanding of how scientists, policymakers, and the public think about the promises and pitfalls of the technology.

We are seeking research collaborators to assist with one of several potential social science projects: 1) Scientific Perspectives of Marine eDNA: this project will involve assisting with transcription and coding of interviews conducted with interdisciplinary scientists participating in an oceanographic research cruise that involved eDNA data collection to better understand how different types of scientists think about the value of eDNA. 2) Media Representations of Marine eDNA: this project will involve systematically identifying media articles about marine eDNA, categorizing and recording the kind of information included in the articles, and analyzing that information to better understand how journalists depict the potential uses of marine eDNA. Research collaborators will learn more about the science of marine eDNA, gain experience with qualitative/quantitative content analysis, and if interested, contribute to drafting a manuscript on the project findings.

There are no required qualifications for these projects, but you would be an especially good fit if at least one of the qualifications below applies to you: Excitement to learn more (and read a ton of articles) about marine environmental DNA, experience conducting a large literature review, experience conducting semi-structured interviews of doing qualitative data analysis, interest in environmental communication, experience with statistical analysis. If you are interested in marine environmental DNA but not the particular projects outlined, there may be opportunities to design or contribute to other related projects, including projects involving scientifically collecting and analyzing eDNA samples in the field; please don’t hesitate to reach out to Meghan Shea.

Skills/Interest/Background: Biology, Statistics

BOULDERING: Assessment of meter-size rocks around impact structures on Moon, Mars, and asteroids

Category(s): Dynamic Earth, Evolution of Earth, Natural Hazards
Department: Earth and Planetary Sciences

Unless they were protected by thick atmospheres, the surfaces of planetary bodies in the Solar System have been bombarded by meteors through time, leaving behind an abundance of impact craters. Upon impact, rock fragments are ejected from the crater cavity and deposited elsewhere on the surface, where they may form secondary craters - a process that is poorly understood to date. In principle, the density of impact craters on a given surface allows planetary scientists to age that surface, provided that they can distinguish secondary from primary craters. Secondary craters increase crater density and distort crater statistics, which ultimately biases age estimates. Characterizing the size and velocity distribution of ejected rock fragments is a key unknown towards accurate age determinations.

Our group seeks to close that knowledge gap through quantitative measurements of boulder populations that can be detected on high-resolution spacecraft imagery of various planetary surfaces, such as the Moon’s, using deep learning. Specifically, our goal is to compile size and shape distributions of boulder populations on a variety of planetary bodies to evaluate the influence of impactor and terrain properties on the ejection mechanisms and its influence on the evolution of the surfaces of planetary bodies.

The focus of the project will be to map boulder populations from spacecraft imagery and to conduct size and shape analyses. The selected student(s) will compare their findings with previously published data and discuss whether their results support or contradict previous studies. This project is geared towards students interested in pursuing a graduate curriculum in planetary geosciences. Students will learn how to map rocks on planetary surfaces such as the Moon, Mars, and asteroids and analyze their distributions with the help of a Geographical Information System (GIS) software such as QGIS or ArcGIS. Students will also gain some familiarity with programming to conduct statistical analyses of their results. Interested students should have some basic programming skills (python) and interest in Remote Sensing / Geospatial data / GIS / Planetary Geosciences.

Skills/Interest/Background: Computer Programming, Geology, Machine Learning, Physics, Scientific Programming, Statistics

Tidal Heating of Habitable Red Dwarf Planets

Category(s): Dynamic Earth, Planetary Science
Department: Earth and Planetary Sciences

Terrestrial planets orbiting in the habitable zone around red dwarf stars have very short orbital periods relative to the Earth and thus are subjected to significant tidal effects.  If the planets have a non-zero eccentricity, one of these effects could be significant internal heating due to tidal dissipation and could equal or even surpass the tidal heating of Jupiter’s moon Io.  The habitability of such worlds is not well understood, and consequently, the tidal heating rates in such planets need further exploration.

This project will explore the tidal heating rates of different varieties of terrestrial planets in or near the habitable zone of red dwarf stars.  By using the virtual planet simulator VPlanet, the heating rates of planets with varying masses and core-mass fractions will be characterized as a function of eccentricity.  One of the biggest unconstrained parameters when predicting tidal dissipation rates is the material response to deformation.  Using the VPlanet software, this response will be tracked and predicted for the varying types of terrestrial planets.  

We are seeking a student who is interested in tackling planetary science problems using computer modeling.  Some familiarity with coding and remote computing will be useful:  The VPlanet software will be run on remote computing with the results most easily being analyzed through a local coding language, such as MATLAB or python.

Skills/Interest/Background: Geology, Physics, Scientific Programming

Remote sensing of smallholder agriculture

Category(s): Food and Agriculture, Human Dimensions and Sustainability
Department: Earth System Science
Mentor: David Lobell

Hundreds of millions of smallholder farmers around the world face challenges of climate change and inadequate soil nutrition. This project will work towards improving datasets used to study and inform management in these systems, with an emphasis on using new satellite sensors. Among the potential specific topics are: (i) estimating peanut yields and aflatoxin contamination in Malawi using high-resolution optical data (ii) estimating oil palm age in Nigeria using lidar, radar, and optical data, (iii) estimating soil erosion vulnerability in Ethiopian farmland using radar and optical data, (iv) predicting maize response to fertilizers in Kenya and Tanzania, (v) estimating canopy nutrient stress in India using optical data. The specific project will be decided closer to the summer based on student interests and data availability.

This is a good project for students with a strong coding background (especially R or python) and a desire to gain familiarity with remote sensing data and methods.

Skills/Interest/Background: Computer Programming, Machine Learning, Scientific Programming, Statistics

Developing the First Marine Nitrous Oxide Budget for the North American West Coast

Category(s): Climate Change, Ocean
Department: Earth System Science

Nitrous oxide (N2O) is a powerful greenhouse gas and the most prominent source of ozone depletion, today. In the ocean, N2O is produced and consumed by microbes and can be transported thousands of kilometers by ocean currents before being released into the atmosphere. The North America West Coast (NAWC) is a highly productive coastal upwelling region with dynamic chemical, biological, and physical characteristics, but its role in global N2O cycling is presently unknown. This project will support the first-ever N2O budget for the NAWC. Specifically, this project will help i) identify how N2O is being produced in the NAWC, ii) quantify how much N2O is released to the atmosphere, and iii) investigate how ocean physics plays a role in N2O dynamics in the region.

We are seeking an enthusiastic student interested in global biogeochemical cycling, climate change, and greenhouse gases. Interest in oceanography is a plus, but by no means required. Preferably, the student will have taken general chemistry and have basic coding experience (MATLAB, Python, or R).  The student will get to choose which region along the NAWC – from British Columbia, Canada to San Diego, California – they will focus their project on. Through this project, the student will learn fundamental laboratory techniques, including how to operate a mass spectrometer, as well as perform data analysis and visualization. 

Skills/Interest/Background: Chemistry, Lab Work, Scientific Programming

What works and what doesn't? Assessing Marine Protected Areas as Social-Environmental Systems

Category(s): Climate Change, Human Dimensions and Sustainability, Ocean
Department: Emmett Interdisciplinary Program in Environment & Resources, Department: Earth and Planetary Sciences
Mentor: Rob Dunbar, Mentor: Ryan OConnor

The whole world is made up of Social-Environmental Systems of every scale and style. Among the most cherished, intricate, and delicate of these human-nature interactions are marine systems, where for generations humans have found resources, recreation, and cultural significance above and below the waves. Today these kinds of systems are under threat from global climate change, ocean acidification, pollution, overfishing, and so many other challenging stressors. The international community has responded, in part, by protecting portions of the ocean – some large, others small – through marine governance strategies like Marine Protected Areas (MPAs) and Marine Sanctuaries. But how do we know if these governance strategies are effective? This is the question that we are seeking to explain, and we need your help.

A team of Ryan O’Connor, a marine social ecologist and PhD student in E-IPER, and Professor Rob Dunbar, Geological Sciences, is engaged in an ongoing effort seeking to understand how MPAs and Marine Sanctuaries around the globe are assessed, what defines success and failure, and what kind of implications these strategies and definitions have on the development of marine governance. As an integral part of this team, the research intern would develop a deep and valuable awareness of the literature surrounding marine governance, gain expertise in novel and emerging strategies for determining success in MPAs and Marine Sanctuaries, and contribute to the growing knowledge base of how marine governance interacts with a changing climate and a warming ocean. 

Our team is seeking a student with excitement and enthusiasm for marine science and policy and a willingness to dive deep into the subject through literature review, specific case studies around the world, and the possibility for fieldwork assessing existing MPAs. While comfort with scientific literature is helpful, no prior experience in the field is necessary, and all perspectives and backgrounds are welcome to apply. Even if you’re completely new to the Environmental Sciences or to the Ocean and want to learn more, we’re interested in hearing from you! 

Skills/Interest/Background: Biology, Field Work, Lab Work, Statistics

How Do Mass Extinctions Change Ecosystems?

Category(s): Climate Change, Evolution of Life, Ocean
Department: Earth and Planetary Sciences
Mentor: Jon Payne, Mentor: Jood Al Aswad

As a result of climate change, many species are expected to shift their geographic ranges or go extinct over the next century. Those range shifts and extinctions will alter the structure of ecosystems globally. Similar changes have occurred in deep time, and the fossil record can be used to anticipate the pattern and magnitude of such changes.

For this project, we will quantify how the spatial continuity of ecosystems changes across mass extinction events, and test whether that change results from environmental change versus ecological interactions. If necessary, this project can be conducted remotely: most (if not all) of the work will be done using a computer and the R and R Studio software. The student will work with data on the biogeography of marine invertebrate animals before and after the end-Cretaceous extinction event.

We are seeking enthusiastic students who are interested in conducting research in biology, geology, paleontology, or other related fields. No prior coding experience is necessary. The student will develop skills in study design, coding, and data analysis.

Skills/Interest/Background: Biology, Computer Programming, Geology, Scientific Programming, Statistics

Rightsizing direct air capture: Policy and resource needs for an ambitious U.S. carbon removal strategy

Category(s): Climate Change, Energy, Food and Agriculture, Freshwater, Human Dimensions and Sustainability
Department: Earth System Science, Department: Emmett Interdisciplinary Program in Environment & Resources

Meeting ambitious climate goals, including limiting warming to 1.5°C, increasingly requires permanently removing past emissions from the atmosphere at a large scale. Despite the significant assumed capacity for carbon dioxide removal (CDR) in global models, its technologies and practices remain underdeveloped compared to other climate solutions like renewable energy. As the largest cumulative emitter in history, the U.S. bears the responsibility to develop and deploy a portion of the CDR necessary to meet global climate goals enshrined in the Paris Agreement.

Our project focuses on direct air capture (DAC), a CDR approach that captures CO2 from ambient air. In its recent bipartisan infrastructure deal (the “Infrastructure Investment and Jobs Act” of 2021), Congress set aside over $3.5 billion for U.S. DAC deployment. Advocates hope that any investment of this scale will help lower the costs of DAC and contribute to a burgeoning negative emissions economy. But how much DAC-based CDR should the U.S. aim to achieve? Is Congress’s recent investment enough? And what impacts on energy, water, land, food systems, and the economy would DAC have at scale?

A student researcher would assist in answering these questions using the Global Change Analysis Model (GCAM): an integrated, multi-sector model that integrates human and Earth system dynamics. Together, we would evaluate local, national, and global human and environmental effects of DAC deployment at various scales. Ultimately, the goal is to inform policymakers, industry, and communities of the potential costs and benefits of DAC. We are seeking an enthusiastic student interested in using quantitative methods to help guide ambitious, equitable climate policy. Basic coding experience (Python or R) is preferred but not required.

Skills/Interest/Background: Computer Programming, Engineering, Machine Learning, Scientific Programming, Statistics

Toxic Soil: Assessing Heavy Metal Contamination in Urban Gardens across the San Francisco Bay Area- Using Soil Biogeochemistry to Combat Environmental Injustice

Category(s): Food and Agriculture, Human Dimensions and Sustainability
Department: Earth System Science
Mentor: Scott Fendorf, Mentor: Alexis Wilson

Urban agriculture can be defined as areas within cities used for growing crops or raising small livestock, either for personal consumption or sale. Various forms of urban agriculture exist including home, community, and school gardens. Urban gardens are important to communities of color in particular because they are spaces for spiritual healing, building and sustaining communities, social and environmental activism, and reconnecting with land and culture. The combination of urban food insecurity and soil contamination becomes an Environmental Justice issue because research indicates that communities of color (Black, Indigenous, Latino/Hispanic, Asian/Pacific Islander) and low-income communities disproportionately face food insecurity and exposure to environmental pollution.

Because these sites exist in urban areas, there is a risk that gardens may be built on sites with contaminated soils or are actively being contaminated by various sources. Heavy metal(loid)s, such as lead (Pb), cadmium (Cd), chromium (Cr), and arsenic (As) are common urban soil contaminants due to anthropogenic activities which raise contaminant concentrations such as past and current industrial activity, hazardous waste, and metal-containing products (e.g. leaded paint). While researchers have broadly characterized overall patterns of soil contamination in urban areas, levels of metal contamination and exposure threats are still lacking for urban agricultural spaces. As such, the overall goal of this research is to use an interdisciplinary approach, using Environmental Justice and Community-Based Participatory Research as foundational frameworks, to advance our understanding of the threat of soil contamination to urban gardens across the San Francisco Bay Area, specifically focusing on marginalized communities. This research is conducted in partnership with community organizations across the Bay Area, and includes field and lab work using quantitative and qualitative techniques.

This project provides a wide variety of opportunities for involvement, and we will work with students to define a plan for summer research based on their interests and experience. The student will either collect and analyze samples from urban gardens or conduct and analyze qualitative interviews of urban gardeners. Potential focus areas include fieldwork (soil and plant sampling), lab work (measuring heavy metal concentrations, soil pH, soil chemistry), qualitative interviews, data analysis (comparing results across sites, creating charts and graphs), and developing/maintaining community partnerships, etc. Cities we may work in include Oakland, Richmond, Palo Alto, and East Palo Alto, and San Jose, California.

A student project might look like one of these examples:
Students may: Choose a subset of urban garden sites and develop a relevant research question around heavy metal concentrations in soil and/or plant samples and other variables such as neighborhood demographics (race, income, gender), environmental conditions (atmospheric pollution), proximity to pollution sources, etc. Activities may include: fieldwork (collecting soil and plant samples at urban gardens), lab work (preparing samples, analyzing for heavy metals , measuring soil characteristics (pH, water content)), geospatial mapping, etc. If remote: activities would focus on data analysis and presentation (graphical representations of the data) rather than field and lab work OR Assist in interviewing urban garden users and managers focused on the topic of their knowledge and perception of the risk of soil contamination and analyzing the resulting data. Activities may include: recruiting participants, interviewing participants (in person or remotely), distributing surveys and analyzing the data, geospatial mapping, etc. If remote: activities can all be done remotely.

Interested students from any field are encouraged to apply, including but not limited to earth sciences, engineering, and social science/humanities. Experience or interest in soil science, environmental justice, community-based research, food and agriculture, and/or climate science would all be beneficial to the project.

Skills/Interest/Background: Chemistry, Field Work, Lab Work

Exploring Motivations and Support Systems of Youth Climate Activists in the Bay Area

Category(s): Climate Change, Human Dimensions and Sustainability
Department: Emmett Interdisciplinary Program in Environment & Resources
Mentor: Nicole Ardoin, Mentor: Alison Bowers

Successfully addressing climate change issues requires collective effort at multiple scales. The youth climate movement represents one piece of the solution. In this project, we will conduct semi-structured interviews with youth climate activists to examine their motivations and support systems.

We seek to gain insight into the mechanisms required for individual and collective action and to identify the role of emotions in response to climate change. Our research will help inform how organizations and policymakers might more effectively interact with youth climate activists. We seek a student to collaborate with our team to first help with the identification of youth climate activists in the San Francisco Bay Area. Building on pilot interviews conducted in previous summers, we will conduct interviews with identified youth climate leaders and analyze the interview data to identify emergent findings to inform future research and practice.

Other than an interest in climate change, human behavior, and the social sciences, no prior experience is needed. We welcome students new to Earth and environmental sciences and will provide training in qualitative research methods, interviewing, and qualitative data analysis.

Skills/Interest/Background: Field Work, Lab Work

Examining impacts of drought-induced air pollution changes on human health

Category(s): Climate Change, Human Dimensions and Sustainability, Natural Hazards
Department: Earth System Science
Mentor: Marshall Burke, Mentor: Minghao Qiu

2021 is one of the driest years we have ever seen. Scientists project that many places in the world (e.g., Western US and much of Africa) will experience increasing drought risks. Most prior research that studied the impacts of droughts on human health has studied the “direct” impacts, e.g. through failed crops and poor nutrition. We propose to study the potentially very large indirect effects, including the increased likelihood of wildfires and large dust storms that can dramatically increase air pollution. 

This work will involve working with satellite data measuring climate and air pollution and applying methods from quantitative social sciences. With guidance from research mentors, the student will prepare and analyze data and assist with visualizing and interpreting results. Depending on the student's interests, there is flexibility in the geographical focus of the project (e.g., US or Africa) . We are particularly interested in students seeking to build data analysis skills in R or similar statistical packages (you don't need to have extensive experience, but familiarity with a statistical package is helpful).

Skills/Interest/Background: Computer Programming, Machine Learning, Scientific Programming, Statistics

Wildfire generated toxins and ecosystem recovery

Category(s): Human Dimensions and Sustainability, Natural Hazards
Department: Earth System Science

Elevated temperatures coupled with extended drought resulting from climate change have increased wildfire risks across California. Thirteen of the twenty most destructive wildfires on record have occurred within the past five years and are expected to increase in frequency and intensity. In addition to acute localized fire hazards, degraded air quality from smoke and dust impose disseminated and prolonged health risks. One large component of wildfire smoke and dust is derived from the combustion of plant material; however, ash compositional differences and their associated exposure risks based on vegetation type and fire severity are poorly understood. Plant ash can contain concentrated toxic metals that originate from soils.  When inhaled as smoke or dust, they can bring about harmful health effects. Additionally, the plant ash and thermally transformed surface soils represent the growth media for rebounding microbial communities. Physical-chemical properties of the plants and soils post-fire can affect bacterial and fungal community composition.

We have two projects where we ask: (1) how does varying fire severity and vegetation type affect ash toxicity? and (2) how does post-wildfire soil and ash influence microbial communities that serve as the basis for ecosystem recovery? 

We seek two summer researchers to work on already established field sites in Sonoma, Napa, and Lake counties across the North Coast Range of California. Both projects include a wide range of soil analyses, such as lab extractions to measure metal content, and microscopic analysis of ash and soil particles. The projects diverge, however, with one (“plant project”) focusing on the plant species (and resulting ash) and the other (“microbial ecology project”) on the soil microbial communities serving as the basis for ecosystem recovery. For the plant project, additional lab-based measurements will include homogenizing and ashing different vegetation types, analyzing ash microscopically, and estimating toxicity by simulated lung fluid extractions. For the microbial ecology project, additional techniques include isolating, culturing, and identifying fungal/bacterial communities in a range of post-wildfire soils using PCR and DNA sequencing. From pure cultures, we will archive representative isolates that can be applied for future recovery initiatives in wildland soils and plants. In both projects, field and lab experience will be gained but not required to apply. Some basic chemistry and biology coursework will be useful but by no means necessary, your mentors will help guide and teach you the skills necessary to continue as an independent researcher.

Skills/Interest/Background: Biology, Chemistry, Field Work, Geology, Lab Work

Understanding satellite measurements of vegetation water content for improved characterization of vegetation drought response

Category(s): Climate Change, Natural Hazards
Department: Earth System Science

Ecosystems are threatened by more common and more extreme droughts in a warming climate. Drought dries out plant tissues, reducing growth and photosynthesis and eventually causing plants to die. Thus, monitoring changes in vegetation water content (the water content of the plant tissues) has enormous potential for better understanding vegetation response to drought. Traditional measurements of vegetation water content are carried out on individual plants, and they are cost- and labor-intensive. Fortunately, advances in satellite microwave remote sensing techniques provide unparalleled spatial and temporal coverage to measure vegetation water content from space. However, many questions remain regarding how to interpret these measurements and their accuracy.

In this project, the student will have an exciting opportunity to compare satellite microwave observations sensitive to vegetation water content with a series of ground measurements and other remote sensing measurements, with the end goal of improving our understanding of the information that these microwave datasets provide as well as their limitations. If progress allows, this research could be presented at a research conference and/or journal publication. The ideal candidate will have experience manipulating data using a programming language such as Python, R, or Matlab. Background knowledge regarding remote sensing or ecohydrology is a plus, though not required. We seek candidates with a strong interest in learning analytical skills applicable to data analysis in earth science. 

Skills/Interest/Background: Biology, Scientific Programming

Geological storage of CO2 and caprock sealing integrity

Category(s): Energy
Department: Energy Sciences & Engineering

One approach to combating climate change is sequestering large volumes of CO2 that would otherwise be released to the atmosphere. This approach could be implemented over relatively short timescales. For this purpose, earth scientists use geological formations that have a very large storage capacity for CO2. Saline aquifers and depleted oil/gas reservoirs are among the top choices as storage formations because they have physical properties suited for injection of large volumes of CO2. It is most important that there is a good caprock (i.e., low permeability rock) above the target formation so that the injected CO2 cannot migrate upward and is trapped in place. These caprocks may have multiple cracks or faults in them that facilitate the gradual migration of CO2 away from the storage formation. On the other hand, when the CO2 is injected into a storage formation made of sandstone, it reacts with the minerals of the rock (mainly composed of quartz) as well as the in-situ water. Therefore, a CO2-saturated brine is produced that could be under- or super-saturated with respect to silica. The focus of this work is on interactions between the produced brine and shaly caprock. We hypothesize that the flow of this brine through the shale cracks or fractures could alter the overall permeability of the caprock, and hence, control the amount of CO2 that could be injected.

We are looking for a motivated, hands-on undergraduate student to conduct and analyze flow-through experiments in our rock mechanics laboratory. The major task for this project is to collect high-quality laboratory data of caprock corrosion on a few samples with different mineralogical contents. You will learn how to analyze a fracture surface as well as well as elemental composition of the inlet and outlet fluids. Data analysis is a significant part of the study. No prior experience is needed for advancing the project, just be passionate about what you do.

Skills/Interest/Background: Chemistry, Engineering, Lab Work

Computational modeling of volcanic eruptions, earthquakes, and other natural hazards

Category(s): Dynamic Earth, Natural Hazards
Department: Geophysics
Mentor: Eric Dunham

Volcanoes, earthquakes, and tsunamis pose immediate hazards to human society. Our research group develops computational codes to model a wide range of physical processes associated with these hazards. Summer interns have opportunities to apply the theory of mechanics to understand these natural hazards. Students who enjoy mathematical analysis can help to derive equations and solve analytical problems; experience with differential equations, continuum mechanics, and Fourier transform would be useful. Students who enjoy programming can assist with code development; prior programming experience in MATLAB, Python, C++, or another language is required. A strong background in mechanics and/or programming is a must for all applicants since all projects involve computer simulations of solid and fluid mechanics problems. Previous experience with earth science is not required.

Skills/Interest/Background: Computer Programming, Engineering, Mathematics, Physics, Scientific Programming

Nitrogen fixation in the canopy: Exploring cryptic nitrogen sources in the boreal forest

Department: Earth System Science
Mentor: Rob Jackson, Mentor: Peter Pellitier

The boreal forest ecosystem is the largest contiguous ecosystem on Earth. However, climate change, in particular warming and increasing carbon dioxide concentrations, threatens the persistence and health of these forests. Nutrients such as nitrogen strongly limit the growth of these forest ecosystems. Understanding how boreal forests obtain nitrogen is critical to predicting how the forest will continue to offset anthropogenic emissions. Symbiotic nitrogen fixation represents a major input of nitrogen into the forest system, yet has very rarely been studied in the canopy where endophytic fungi and bacteria inhabit tree needles.

We are looking for a motivated student to develop and lead molecular techniques to extract DNA from spruce needles, in order to quantify the microbial communities that dwell within. Using this purified DNA pool, the student will quantify the abundance of genes involved in nitrogen fixation. The student will also utilize bioinformatic pipelines in R to process the sequence data. This project is set provide new insights into a cryptic nitrogen cycling pathway. The student can be expected to gain a wide array of skills in molecular biology including PCR, quantitative PCR, gel electrophoresis, bioinformatics and statistics. This project is best suited to a student with prior molecular biology experience or coursework.

Skills/Interest/Background: Biology, Computer Programming, Lab Work, Scientific Programming, Statistics

Stinson Beach Microbiome: diversity and function of bacteria and archaea in a subterranean estuary

Category(s): Climate Change, Freshwater, Ocean
Department: Earth System Science

At the land-sea interface, sandy beaches are among the most vulnerable ecosystems to the effects of global climate change. Sea level is projected to rise between 0.5 and 1 meter by 2100, critically endangering their very existence. Sandy beaches provide essential ecosystem services, including habitat for sensitive biota, protection of land from storm events and flooding, and water filtration and purification. Forced by tides and waves, large volumes of seawater are flushed through the beach daily. In addition, meteoric groundwater can percolate through the beach and discharge to the sea. In the subsurface of the beach is a subterranean estuary with steep chemical (salinity, oxygen, nutrient) and physical (temperature, moisture content) gradients. The beach can be viewed as a “biogeochemical reactor” where microorganisms mediate the transformation of nutrients, trace metals, and carbon within the subterranean estuary. 

Our research group is interested in characterizing the chemical and physical drivers of microbial diversity and metabolism within the subterranean estuary at Stinson Beach in Marin County, CA. As a student working on this project, you will hopefully have the opportunity to assist with field research and community outreach at Stinson Beach. You will gain fundamental skills in sample collection, laboratory techniques (e.g. DNA extraction and sequencing), and data analysis (e.g. bioinformatics and multivariate statistics). Based on your interests and experience, we will help you define an exciting and manageable summer project. Prior laboratory experience is helpful, but not required. If you have a general interest and enthusiasm for environmental science, microbial ecology, biogeochemistry, or molecular biology, please consider applying.

Skills/Interest/Background: Biology, Chemistry, Field Work, Lab Work, Scientific Programming, Statistics

Planned relocation as climate adaptation: Are destination sites safer than origin sites?

Category(s): Climate Change, Human Dimensions and Sustainability, Natural Hazards
Department: Earth System Science, Department: Emmett Interdisciplinary Program in Environment & Resources
Mentor: Chris Field, Mentor: Erica Bower

Facing mean and extreme sea-level rise and other coastal hazards, communities across the world are considering options to reduce their exposure, as well as their vulnerability. The planned relocation of whole communities to less exposed areas is gaining salience as a strategy for both disaster risk reduction and climate change adaptation. While planned relocations may have multiple objectives, and occur in the context of multiple drivers, the primary goal is generally assumed to be a reduction of hazard exposure. Yet little empirical research assesses how effective planned relocations are at reducing exposure, and on what time horizon.

Through spatial analysis of comparing coastal planned relocation cases, this project assesses the distance and change in elevation between origin and destination sites and compares this with global sea-level rise projections over time. This project also considers why destination sites are selected, and the role of risk assessments in informing this process, including exploring who initiates and implements assessments, the hazard types, and timelines considered, types of knowledge integrated, and level of community engagement.

We are looking for a student who is both quantitative and qualitatively oriented, and who has experience, or is willing to gain experience, with spatial analysis.

Skills/Interest/Background: Computer Programming

Imaging the San Andreas Fault in three dimensions with gravity and seismic data

Category(s): Dynamic Earth, Evolution of Earth, Natural Hazards
Department: Geophysics

Do you want to understand how the Earth behaves beneath our feet? And explore how 100 million years of plate-tectonic evolution have created the complex three-dimensional pattern of faults beneath Los Angeles and southernmost California? Do you enjoy working with and visualizing large datasets? The geophysics community has developed multiple competing seismic-wavespeed models with resolutions of 1 to 10 km horizontally and vertically, depending on the depth of interest. These different models lead to different predictions of subsurface geology, for example including the dip of the San Andreas Fault that strongly affects the predicted seismic-energy radiation pattern in the next “Big One” in southern California. You will learn about and download these models (e.g. Seismic wavespeed is a sufficiently good proxy for rock density that one test for the validity of these models is whether they predict the observed gravity field.

You will learn to use commercial 3d gravity modeling software ( ), then convert the wave speed models into density models (e.g. ) and re-format or sub-sample (filter) appropriately for use with this software. Your goal is to assess which wave speed model most accurately predicts the observed gravity field (e.g. ) in particular over areas such as the southern San Andreas fault and Salton Trough. Can we test between specific geologic hypotheses (how steep is the San Andreas fault? how much magma is in the lithosphere beneath the Salton Trough?). The ideal student would be motivated to carry this through to a presentation at a professional meeting.

Skills/Interest/Background: Computer Programming, Engineering, Field Work, Statistics

Forecasting urban water quality using machine learning

Category(s): Energy, Food and Agriculture, Freshwater, Human Dimensions and Sustainability
Department: Earth System Science
Mentor: Kate Maher, Mentor: Zach Perzan

Nitrogen is one of the most ubiquitous, costly, and challenging environmental pollutants of the 21st century. At the same time, fertilizer production will struggle to meet the needs of a growing population. A new interdisciplinary research team at Stanford aims to tackle these two challenges by converting waterborne nitrogen pollutants into high-purity fertilizer.

Collaborators in the Dept. of Chemical Engineering have developed a new device for exactly this purpose; our research group is focused on forecasting water quality flowing into the device, so it can change its operation according to the forecast and optimize nitrogen removal. Using real-world water quality data from our industry partners (the water utilities of New York City and San Francisco), this project aims to forecast short-term nitrate concentrations based on current conditions. Some of the specific questions include: what water quality variables are most closely correlated with nitrate and nitrite? Does nitrate respond to any environmental variables (precipitation, temperature)? What statistical techniques (autoregression, exponential smoothing, long short-term memory network) are most suited for nitrate forecasting? In this project, the research student will develop strong data science and coding skills.

The project is open to students in any science background (including those outside earth or environmental sciences), though previous coding experience (Python, R, or Matlab) is preferred.

Skills/Interest/Background: Chemistry, Computer Programming, Machine Learning, Scientific Programming, Statistics

Mitigating Greenhouse Gas Leaks from Subsurface Seals

Category(s): Climate Change, Energy
Department: Geophysics
Mentor: Tiziana Vanorio, Mentor: Jihui Ding

Rising global concerns around the central role of greenhouse gases (e.g., carbon dioxide and methane) in climate change have impelled governments, scientists, and engineers to find ways of
reducing emissions. It is approximated that annual CH4 emissions from abandoned oil and gas wells are presently underestimated by 20% in the U.S. and 150% in Canada. Leaky wells result from property degradation of materials at interfaces, which tends to be major sources of leaking greenhouse gases. Unfortunately, the costs for a company to plug leaky wells are high and many of the available methods are unreliable. 
Thus, there is a clear need to pursue a renewed and sustainable effort aimed at well remediation and the long-term prevention of greenhouse gas leaks. This means we need to seek a win-win solution by achieving both mitigating greenhouse gas leaks and CCUS (carbon capture, utilization, and storge). It has become clear that CCUS costs should be discussed in the context of a broader energy system transformation to offset the costs of carbon removal with the practical benefits of climate change mitigation and CO2 reuse – whether the reuse is for energy production or material manufacturing.

At Rocks and Geomaterials Lab, we study rocks and material resources to marshal environmental solutions for fluid injection and storage in the Earth’s underground, energy sources, and manufacturing processes. In this project, we seek a highly motivated student to produce and characterize rock-cement composite samples representative of subsurface seals of interest. Because a major portion of greenhouse gas leaks come from cement-rock debonding, it is critical to create representative cement-rock composites for laboratory testing.

This project involves preparing samples, measuring sample porosity and permeability, and imaging microstructures of key samples. The student will be introduced to a wide range of laboratory techniques and closely mentored throughout the project to develop experimental and analytical skills. Prior lab experience is preferred but not required.

Skills/Interest/Background: Chemistry, Engineering, Lab Work, Physics

Development of an Interactive Website Interface for Site Selection Criteria of a Geological Carbon Storage

Category(s): Energy, Human Dimensions and Sustainability
Department: Energy Sciences & Engineering

Carbon capture and sequestration (CCS) will play a significant role in mitigating carbon emissions. One challenge is that CCS requires a long-term sequestration site capable of storing CO2 for the foreseeable future and having adequate capacity and injectivity. Many factors influence the suitability of a geological storage site ranging from the geology and geomechanical environment to injectivity and capacity parameters to the economics and social and political framework. All these factors need to be considered in the evaluation criteria. Developing a consistent methodology to screen potential geological storage sites is integral to the large-scale deployment of CCS technologies to ensure safe, secure, and economic sequestration.

This research project is to develop an interactive webpage that users can use to screen potential carbon storage sites. The site should be able to take user-uploaded data and score and rank potential sites based on developed site selection criteria. Potential outputs are heatmaps, maps of potential sites, chance of success charts, spider diagrams, and tables with the ranked sites.

We are looking for a researcher with a background in computer science. Experience with programming languages and website development is advantageous. Students will be mentored closely throughout the entire project.

Skills/Interest/Background: Computer Programming, Engineering
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