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One of the defining features of an arctic environment is permafrost, which covers almost 10% of Earth's surface and remains entirely frozen year round. With temperatures reaching more extreme levels more frequently, the U.S. Department of Defense (DoD) has awarded a two-year, $957,013 grant to Penn State Professor Ming Xiao, to investigate the effect on permafrost and how its melting could expose contaminants to the environment.

Xiao, a professor of civil and environmental engineering, conducts research in Alaska on permafrost and its effects on civil engineering infrastructure. For this project, awarded via DoD's Environmental Security Technology Certification Program, Xiao will use drone technology to study how permafrost interacts with contaminants like radioactive or toxic waste in former DoD facilities and military bases in Alaska.

In a Q&A, Xiao discussed the research and overcoming the challenges of studying extreme changes in extreme environments.

Why is it important to locate contaminants in the permafrost?

Many landfills and other legacy storages of hazardous waste were built in permafrost in the last century. During the construction of these waste containment facilities, however, builders did not consider the accelerated thawing of permafrost due to climate change.

Among the 344 formerly used defense sites in Alaska, 269 sites had hazardous, toxic and/or radioactive waste as of 2015. The contaminant movement interacts and varies with the permafrost degradation, making it difficult to predict and locate.

What is electromagnetic geophysical imaging? How is drone technology used in environmental and, more specifically, permafrost research?

Electromagnetic imaging allows us to reveal the inside of a structure by analyzing how electromagnetic waves, a type of radiation that can carry energy through objects or the air, interact with the structure. An example of electromagnetic imaging is an X-ray in the medical field.

In this project, we measure how the preexisting electromagnetic waves already in the air interact with the ground to reveal details beneath the soil surface. Traditional approaches to electromagnetic geophysical imaging use instruments that are either dragged along the ground's surface or inserted into the ground to reveal sub-surface features.

While this approach is effective, it is exceedingly slow, expensive and inefficient. Additionally, some areas we need to image, such as ponds or areas contaminated with hazardous waste, are inaccessible using the traditional approach.

In our project, we will use a drone-based system to conduct geophysical imaging, a relatively new technique that is more efficient, cost-effective and adaptive to the environments we wish to research.

How does the drone system handle environmental factors like extreme cold or harsh terrain? Did environmental factors influence the development of the system?

A big advantage of the drone system compared to traditional imaging techniques is that the drone can easily navigate harsh terrain, as it is above the ground. We face some other issues, however. Extreme cold is a challenge for the drone batteries—at freezing point, or 32°F, our drone batteries can only last 10 minutes. We must be very mindful of the flight time, because we don't want the expensive drone and measurement instrument to fall out of the sky if the battery runs out.

Another significant environmental challenge is the wind. The instrument carried by the drone needs to stay stable to collect good data, but wind speeds in the Arctic can easily reach over 20 miles an hour. We must strategically coordinate our drone flights with the weather to get good data and not risk our system.

Are there specific types of environmental contaminants that the system is best at identifying and characterizing?

Electromagnetic geophysical imaging is exceptionally good at detecting electrically conductive or resistive sub-surface features. You can find pockets of permafrost, regular soil, water, ice and contaminants at different depths within the Arctic soil—each of these materials has a different electrical resistivity, meaning they can appear in the images created by electromagnetic geophysical surveys.

Whenever we are imaging the sub-ground, we are usually searching for environmental contaminants, not just to locate them, but to examine how they interact with the soil and other materials surrounding them.

There are some issues we may encounter when finding these contaminants, though. As climate change causes the permafrost to thaw, ice turns into water and drains away, and the contaminants buried in the frozen soil that were expected to stay frozen started to move with the water. This makes the contaminants more difficult to identify, as they distribute differently and are no longer contained to specific areas in the soil.

Another big challenge is the mathematical model we use to process the data collected by the drone-mounted instrument. The drone technology we use to collect our measurements is relatively new, meaning a valid and trustworthy mathematical model to process our collected data does not yet exist. Developing a method to accurately interpret the data collected by our drones will be one of our research focuses.

In your proposal, you mention how this system could be employed relatively inexpensively. How did your team find a balance between cost and features?

To get the most out of our system, we are comparing the technology we are developing in this project with the results we saw with traditional ground-based or manned aircraft-based geophysical surveys. We compare data quality, the time it takes to survey the same area and financial expenses associated with the new technology and the existing approaches.

We will develop a matrix to evaluate these factors, which inform us which areas our technology excels at, as well as the areas we need to improve.

What is the biggest issue your team has overcome during development?

Feasibility of the technology. Before we submitted the proposal, we conducted trial tests in 2024 in Utqiaġvik, Alaska, the northernmost town in the United States. We particularly learned how the electromagnetic wave's signal strength affected imaging results; we also used the newly collected data to develop a robust model for the data processing. The exploratory mission guided us in the project development and gave us confidence that the technology and approach are feasible.

Aside from Xiao, other researchers on the project include Mine Dogan, an environmental geophysicist at Western Michigan University; Anna Wagner and Taylor Sullivan, researchers at the Cold Regions Research and Engineering Laboratory (CRREL) Engineer Research and Development Center of the US Army Corps of Engineers; doctoral students Xueyang Wang, a civil engineering doctoral student at Penn State; Brandon Tulban a geological and earth sciences doctoral candidate at Western Michigan University; and Jon Maakestad, a technician at CRREL who will assist in data collection.