There’s a common understanding among PFAS remediation practitioners: Once you start sampling for PFAS, you should expect to find it—and plan for the likelihood of multiple sources.
Because per- and polyfluoroalkyl substances (PFAS) are ubiquitous, any site investigation may reveal the presence of these persistent, mobile, and increasingly regulated chemicals, even in areas where a local source isn’t expected.
Less certain is knowing an accurate breakdown of the amount of PFAS resulting directly from a facility’s contribution versus the amount traveling there from other sources—concentrations at a site that are not attributable to the site owner, also known as background concentration.
Once you start sampling for PFAS, you should expect to find it—and plan for the likelihood of multiple sources.
That’s an important distinction for businesses or public entities tasked with understanding PFAS impacts at their sites—and one that Barr’s PFAS experts work with clients to unlock.
“You often won’t get too far into a PFAS investigation before you start picking up detections,” explains senior hydrogeologist Evan Christianson. “At that point, the question becomes, ‘Where is it coming from?’ There are so many sources of PFAS, and without knowing something about background concentration at a site, you can end up doing (remediation) work that you may not need to do.”
A groundwater modeling expert who studies how PFAS moves underground, Evan helps clients understand their site’s PFAS history and how it may be moving in the environment. Using sampling data, leading-edge numerical modeling techniques, data visualization, and an emerging tool (machine-learning AI), Barr’s PFAS teams bring clarity to an otherwise fuzzy picture.
We chatted with Evan about the role groundwater modeling plays in understanding where PFAS comes from and where it might travel, as well as what draws him to this work.
We started looking at regional distributions of PFAS from varying sources in 2016, beginning with a few projects that had widespread impacts on private (drinking water) wells. At that time, there was very little regional data available, as most PFAS data collection was focused on sites with localized sources, so we often were starting from ground zero. In the past four years, a lot of states have ramped up their statewide sampling programs, and that data is just now starting to be digested and used.
Understanding PFAS contamination of drinking water was an early driver for a lot of our work. My background is hydrogeology and groundwater modeling, and I have supporting skills such as data processing and visualization. I leverage those skills to understand how PFAS might be moving within our groundwater systems.
PFAS is unique in that it is a family of many chemicals and the number that we test for is growing. We use machine-learning techniques to see patterns in the complex data. We pair machine learning with data visualization to help our clients understand what is going on.
Gathering and understanding PFAS data can be extremely complicated—from careful consideration of sampling techniques to interpreting that data.
Barr has a lot of experience gathering PFAS data and putting it into a larger perspective. We also have a data quality group that understands the nuances of emerging analytical methods, scientists who understand PFAS fate and transport, air-quality experts knowledgeable in regional issues, and an engineering group skilled at identifying an appropriate treatment technology for a given situation.
We contextualize the PFAS a client may be seeing in soil at their site or in their groundwater in relation to the larger, broader environmental picture. Because many statewide sampling efforts are still ongoing and regulatory criteria are still rapidly evolving, it’s a little early in the game to definitively say, ‘Here is the standard protocol and here’s what to tell the regulator.’ However, we can help a client better understand a complex dataset in relation to other sources so they can make informed decisions about their next steps.
I like finding patterns in complex data—finding meaning within something that, at first glance, is just overwhelming and looks like a bunch of numbers. Through investigation, modeling, and data visualization, we can understand the fundamentals of how PFAS is distributed across a site and how it might be moving.
That was the first project I worked on at Barr! It continues today and has gone through a few updates throughout my career. That project allowed me to become an expert on groundwater flow within the Twin Cities area. This is my home, and it’s nice that I can have a lot of project work here in this community. The model is publicly available for download, and it’s fun to go to conferences and hear people talk about using it as a reference or starting point for their own projects.
The innovation program provides funding and time for employees to test new technologies or ideas that could better solve our clients’ problems, improve a process, or develop a new service. It fosters a culture that encourages our staff to think creatively and to be open to new ideas. As the program’s administrator, I have seen firsthand how the program enables people to pursue their passion with support from the company.
Within the first year or two, I felt like I wouldn’t want to be anywhere else. This work fits with what I like to do. The glacial geology and the number of lakes and wetlands in Minnesota make modeling in this state particularly challenging compared to other places where I’ve done modeling. On the flip side, the data availability is some of the best in the country compared to elsewhere.
Contact our team to learn more about our wide range of PFAS services.
Evan Christianson, vice president and senior hydrogeologist, has 17 years of hydrogeologic experience focusing on the implementation of hydraulic models to solve complex water-quality and water-supply issues. He leads Barr’s Computational Hydrogeology Practice Group and specializes in groundwater flow modeling, geographic information systems, aquifer characterization, and development of custom quantitative methods for various modeling applications. Evan’s work covers a wide range of industry and government sectors, and he is an expert at numerous hydrogeologic modeling codes. He also has experience in geologic mapping, data processing and visualization, and developing groundwater monitoring programs. Evan has designed and calibrated more than 30 groundwater models.
In 2022, Evan’s family enjoyed a trip to Arizona and Utah. While the kids thought they were just going for a hike, Evan capitalized on the opportunity to teach them a little about geology.
Evan leads Barr’s Computational Hydrogeology Practice Group and Barr’s Innovation Program. Here, Evan is exploring cutting-edge virtual reality with fellow Barr hydrogeologists (from left) Sheryl Filby Williams, John Greer, and Ray Wuolo.
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