by Linda Cook, Jill Ready, PG, Steve LaRosa with Weston & Sampson

 “An ounce of prevention is worth a pound of cure.” This well-known statement by Benjamin Franklin, originally penned in the Pennsylvania Gazette in the 1730s to highlight the importance of fire prevention, holds great significance for data quality control in environmental site investigations today. As the science surrounding per- and polyfluoroalkyl substances (PFAS) has grown and evolved, so too has the importance of adequate PFAS data quality control. While the environmental and health risks of PFAS are widely discussed, cost-benefit analyses for poor versus high-quality PFAS data have received limited attention. For brownfield sites in particular, where site assessment and cleanup activities are often being completed with limited United States Environmental Protection Agency (EPA) Brownfields grant funding, data quality can deeply impact grantees’ abilities to achieve their goals for sites undergoing assessment and cleanup. This article will evaluate the total cost of quality in PFAS analyses, emphasizing the strategies necessary to generate the best data for your projects and clients.

The Cost of (Poor) Quality

In his 1956 Harvard Business Review essay “Total Quality Control,” Armand Feigenbaum introduced “The Cost of Quality” concept for industrial manufacturing businesses. The concept introduced four categories of quality-related costs: prevention, appraisal, internal failure, and external failure (Figure 1). Today, the Cost of Quality concept is applicable to PFAS testing, where poor data can lead to costly missteps and far-reaching consequences (Table 1). The costs of poor-quality PFAS data are also often unpredictable, making them impossible to anticipate, schedule, or budget.

Figure 1. Illustration of the four quality cost categories as introduced by Armand Feigenbaum in "The Cost of Quality."

Table 1: The costs of poor-quality PFAS data can be significant and far reaching and are often unpredictable.

If data are determined to be of such poor quality that they are unsuitable for their intended use, additional sampling and analysis may be required to address data gaps. In the most serious of cases, field investigations may need to be completely re-performed, resulting in a loss of previously invested resources, reducing the availability of Cooperative Agreement funds for use on other priority sites, and impacting public trust.

Inaccurate data can also lead to costly and more unnecessary and aggressive approaches for treating and managing PFAS-impacted resources. For instance, if a laboratory produces results that are consistently biased high, it may prompt remedial actions that are more extensive and expensive than required.

Financial penalties for exceeding regulatory thresholds are another potential cost consequence of inaccurate PFAS data. Inaccurate PFAS results can lead to non-compliance with regulatory PFAS standards, which may result in fines and/or enforcement actions.

Beyond financial implications, poor quality data can also impact project timelines, have social and emotional consequences, and damage brand reputations. For brownfield sites undergoing assessment and cleanup with funding provided by EPA Brownfields grants, delayed project timelines can result in projects not being completed before the end of the grant performance period, necessitating the use of funds for grant extension requests that may or may not be approved.

Why PFAS Testing Is So Challenging

PFAS testing involves specialty analytical methods that are particularly difficult to perform accurately for several reasons, including their ubiquitous presence, regulatory requirements, method complexity, and a growing selection of ancillary methods. In particular, the common presence of PFAS in lab equipment, field supplies, and consumer products increases the potential for cross-contamination during both sample collection and analysis. Testing methods demand ultra-low detection limits (often in the parts-per-trillion range), advanced instrumentation, and rigorous controls. Not all labs are up to the task, yet many have rushed to meet surging demand without the experience or infrastructure to deliver reliable results.

Complicating matters further, standard methods only detect a fraction of the estimated 10,000+ PFAS compounds. Newer techniques like Total Oxidizable Precursors Assay (TOPA), Adsorbable Organic Fluorine (AOF), and Extractable Organofluorine (EOF) attempt to estimate total PFAS content, but vary in accuracy, comparability, and validation. Without standardized reporting protocols, reviewing data from different labs becomes both time consuming and error prone.

Building a Foundation of Quality

Investing in high quality data saves money, reduces risk, and improves outcomes. A robust PFAS sampling and testing program aimed at generating high-quality data involves two core strategies: prevention and assessment.

Prevention Strategies:

• Define Objectives Early: Align project teams, regulators, and labs on compounds of concern, detection limits, and intended data use.
• Use Qualified Labs: Vet your proposed laboratories carefully for PFAS-specific experience. Avoid selecting based on lowest price alone.
• Develop a detailed Site-Specific Quality Assurance Project Plan (QAPP): The QAPP should address PFAS-specific requirements and outline Data Quality Objectives.
• Train Sampling Teams: Use PFAS-free materials and emphasize the importance of documentation and adherence to protocols.
• Implement a Quality Management System: Oversee and maintain data quality throughout any sampling and analysis program, evaluating for areas of improvement and ensuring data integrity.
• Include Quality Control Samples: Standard reference materials and blind quality control samples help track laboratory performance and catch anomalies early.

Assessment Strategies:

• Field Oversight: Document and review field practices to ensure adherence to protocols.
• Laboratory Oversight: Review laboratory protocols and practices to monitor performance.
• Data Review: Perform independent data validation and usability assessments throughout the project to evaluate data reliability. Incorporate reviews of comprehensive data packages including all supporting documentation and raw data (known as a Level 4 data report). This review will ensure that data used for project decisions are accurate, complete, and defensible.

For Brownfield Sites, Data Quality Is Non-Negotiable

Brownfield sites often have complex histories and liability considerations. Introducing unreliable PFAS data to brownfield site assessment and cleanup projects can lead to financial, legal, and environmental consequences for environmental professionals, grantees, municipalities, and the public. However, investing in high-quality data can simplify decision-making, reduce risks, and improve project outcomes.

While rigorous testing and oversight may increase upfront costs, those expenses are far less than the cost of poor-quality data. As the demand for PFAS testing grows and regulatory standards evolve, robust approaches to data quality will be increasingly necessary.

For brownfield sites with limited time and funding for assessment and cleanup, high-quality PFAS data are invaluable, enabling informed decisions, improving stakeholder confidence, and helping maximize the use of grant funds. Investing in prevention and rigorous quality assessment from day one is the surest way to protect people, budgets, and reputations.

(A longer version of this article was originally published in the June 2025 issue of the Journal of the New England Water Works Association, Inc.)

The Authors:

Linda Cook is a Senior Technical Leader with Weston & Sampson in their Reading, MA office. She can be reached at cook.linda@wseinc.com. Jill Ready, PG, is a Project Manager with Weston & Sampson in their Manchester, NH office. She can be reached at ready.jill@wseinc.com. Steve LaRosa is a Senior Technical Leader with Weston & Sampson in their Waterbury, VT office. He can be reached at larosas@wseinc.com.