PNNL

PNNL specializes in detecting extremely low levels of radiation in the environment, which can be important markers of ecological and nuclear events. Emily Mace uses the laboratory’s unique ultra-sensitive radiation detectors and PNNL’s Shallow Underground Laboratory to uncover insights about a wide range of phenomena.

Mace specializes in measuring argon-37, which can indicate nuclear test activity, and argon-39, which can be used to understand groundwater recharge rates. These isotopes can be extremely difficult to measure at atmospheric levels because of their low natural abundance. Mace and colleagues have used measurements of argon-39 to estimate the age of groundwater samples from California’s San Joaquin Valley.

When studying aquifers, scientists can look at natural sources of radiation, called radiotracers, that provide information about the age of a sample. The most commonly used radiotracers are carbon-14 and tritium, which provide measurements of samples ranging from tens to thousands of years old.   

“Argon-39 is a radiotracer that fills a gap in the age range between tritium and carbon-14,” Mace said. “It allows us to look at things on a scale of hundreds of years, which supplements the current mix of data available for groundwater scientists.”

Mace is also helping to pioneer the use of machine learning to analyze pulse shape data—signals from radioactive decay events—collected in PNNL's Shallow Underground Laboratory.  

"Instead of having a subject matter expert go through the data to identify which pulse shapes are real radiation events and which ones are noise events (bad pulses), we can use a machine learning approach to analyze the data and allow for more accurate measurements," Mace said.

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“Tri-Cities Researchers Push Limits to Detect Secret International Nuclear Explosions.” October 19, 2020, Tri-City Herald.