Airports across California are emerging as significant sources of PFAS contamination—and one site in particular has become an example of the problem: San Luis Obispo County Regional Airport. For nearly 50 years, PFAS compounds have been leaching into the groundwater beneath and surrounding the airport. The contamination is linked to the use of AFFF, a special firefighting substance mandated by the Federal Aviation Administration for use in aircraft fire emergencies and training exercises. 

“Airports were required for many years to have PFAS-related firefighting foams,” Zach explained. “That’s been phased out over time as they try to get to safer products, but because PFAS-related firefighting foams were once required to be stored and readily available at certain types of airports—particularly military and military-linked civilian ones—the facilities were also required to test them. So, you’d have highly concentrated mixtures of PFAS that were combined with water and sprayed to make the foam, and that was tested and used across a facilities’ properties, possibly even in undocumented areas.

AFFF is now widely known to contain high concentrations of PFAS, and its use at airports has left a persistent chemical footprint across California. In 2019, the California State Water Board directed 30 airports across the state to begin investigating PFAS pollution. Every single one showed some level of contamination. San Luis Obispo County Regional Airport was one, with more than 70 nearby wells—many of them private wells used by homes and local businesses—having shown PFAS impacts. For residents in San Luis Obispo, some of whom have lived across the street from the airport for decades, the news was unsettling.

However, San Luis Obispo has put together a formal response plan. Will other airports follow suit? That remains to be seen, but one thing that’s certain is that the San Luis Obispo County Regional Airport is an example of the broader challenges facing airport communities—and underscores the necessity of tools like the California Airport PFAS model to better understand and address the issue.

The California Airport PFAS model delivers powerful insight into a complicated—and still evolving—environmental challenge. Designed to be dynamic, interactive, and accessible, the model equips researchers and the public to make sense of extensive contamination data without needing in-depth site reports or insider knowledge.

Here are just a few key takeaways this model helps illuminate:

• Pinpointing the most impacted sites and samples: At a glance, users can identify which airport locations and specific samples show the highest PFAS concentrations. For example, the model indicates that San Luis Obispo County Regional Airport is associated with the highest analyte concentrations.
• Identifying dominant PFAS compounds: The model doesn’t just show where PFAS is present—it helps determine which specific analytes are most prevalent. For instance, histogram pages within the model show that San Luis Obispo County Regional Airport’s PFAS profile is dominated by PFHxS, PFOS, 6:2 FTS, and PFHxA. These trends can also be compared across other airports in the dataset.
• Making meaningful comparisons: The model equips users to compare any sample—or entire sets of samples—against others. This supports side-by-side evaluation of PFAS profiles between different airports or areas of concern and helps users spot similarities, differences, and outliers in the data.
• Spotting potential bias in the data: With tools that count how often each analyte was tested, the model highlights inconsistencies in sample coverage. That makes it easier to detect gaps in the dataset—like under-tested compounds—and avoid drawing premature conclusions.
• Leveraging geospatial insight: Because the data is georeferenced, users can overlay PFAS data with real-world geographic features like groundwater wells, agricultural zones, and infiltration pathways. This is critical when evaluating how PFAS may move through soil, groundwater, or surface water—and what communities or water sources might be at risk.

Of course, Zach Dickson emphasizes that the model is in demonstration mode, so findings aren’t automatically conclusions. They’re simply clues about how PFAS may be impacting airports and their surrounding areas so that researchers and the public can start developing a better understanding of what’s happening.

Creating a model for researchers and the public to explore PFAS in and around airports required multiple steps, including reducing datasets, validating data points, and building an intuitive presentation. To tackle everything, Zach used Surfer and Microsoft 365 tools—a powerful combination that helped him transform complex environmental data into something understandable and engaging. His process can be outlined in three main steps.

The first phase of the project started with Power Query, Microsoft 365’s data transformation tool. Zach began with a mountain of raw data—hundreds of thousands of points pulled from public environmental records—and needed to filter out noise, inconsistencies, and irrelevant entries.

Power Query made it possible to consolidate this information into a manageable dataset focused solely on PFAS samples from 27 California airports. The tool also equipped Zach to identify which records were meaningful and prepare the data for deeper analysis—all before a single map was made.

Once the data was reduced, Surfer became the central tool for verifying its integrity and bringing it to life spatially. With thousands of PFAS records to analyze, Zach used Surfer’s advanced mapping features to make sure everything aligned with real-world geography and environmental conditions.

Surfer’s pie charting and class posting tools proved especially valuable for visualizing the data. Each chart helped showcase the dominant PFAS analytes at a given location—letting him quickly identify which compounds were present and in what proportions. Zach also used BNA files to load California’s state, county, and city boundaries directly into Surfer. This allowed for highly detailed and zoomable maps that revealed both the location and relative impact of contamination at each airport. 

“Surfer presented this data in a way no other program could,” Zach said simply. 

Beyond visualization, Surfer played a key role in data validation. Zach explained, “Surfer will fail if your data isn’t structured properly. Microsoft will fail, too—but in a different way. Surfer tells me things I might not otherwise see.”  This made the software an essential part of Zach’s quality assurance and control process.

With the data validated and visualized, Zach turned to Power BI, Microsoft 365’s data modeling platform, to build the interactive experience users see today. Power BI allowed him to create an online dashboard that makes it easy to:

• Filter by site or analyte
• Compare concentrations between airports
• Visualize PFAS data across geography

This final layer of interactivity would equip researchers and the public to explore California’s airport PFAS data with ease and clarity to get the insights they need.