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Track Record · Case Study

Forever Chemicals in the Groundwater

A military base used AFFF firefighting foam for 30 years. PFOS seeped into the aquifer. The municipal well field is 800 meters downgradient. We asked seven questions — starting with when contamination reaches the wells and ending with which remedy the base should choose. The screening estimate and full uncertainty analysis imply very different urgency, while choosing a remedy requires the higher-fidelity model. The contaminant everyone is watching for arrives second.

By Michael Key · ORCID

4 ppt
EPA MCL (PFOS/PFOA)
59.7%
Monitored Systems With a Reported PFAS Detection
(UCMR5 Jan 2026 release; ~95% of round complete)
1,693
Systems Exceeding MCL
97%
Of PFOS Detects > MCL

Source: EPA UCMR5 (Jan 2026, 10,299 monitored systems, 1.9M sample results). These are system-level monitoring summaries, not population exposure rates.

The Core Finding

Same Site. Same Data. Different Answers.

We asked the same question — when does the plume reach the well field? — at three levels of model fidelity. The answer changed every time. So did the recommended action.

96 yr
Screening (Domenico)
7175 yr
MODFLOW 6
19 / 49 / 72.8 yr
Within-horizon arrivals: P5 / P50 / P95

Plume arrival time at the municipal well field (800m downgradient). Of 200 arrival-time realizations, 47% did not reach the well within the 100-year horizon; the percentiles above are conditional on reaching it within that horizon.

Background

A Contamination Crisis in Slow Motion

PFAS are synthetic chemicals with carbon-fluorine bonds — the strongest in organic chemistry — making them nearly impossible to break down. In April 2024, EPA finalized maximum contaminant levels of 4 parts per trillion for PFOS and PFOA. We downloaded the EPA's UCMR5 monitoring dataset — 1.9 million sample results from 10,299 monitored public water systems. In this processed January 2026 snapshot, 59.7% of systems had at least one reported PFAS detection. Among systems where PFOS was detected, 97% exceeded 4 ppt. These are system-level monitoring results, not an estimate of the share of U.S. residents exposed.

Our scenario: a composite military base fire training area, parameterized from published USGS data for Joint Base Cape Cod — one of the best-characterized PFAS sites in the US, with 1,500 hydraulic conductivity measurements and a 1.2 km PFOS plume tracked since the 1970s. DoD has identified 700+ current and former installations with a potential PFAS release. That is an investigation inventory, not evidence that every installation has a Cape Cod-like plume or needs the same remedy.

Data: EPA UCMR5 (1.9M samples), USGS Water Quality Portal (62 monitoring wells at Cape Cod), published aquifer parameters. Full sources listed in the Sources section below.

Before We Start

Three Models. Two Dimensions of Fidelity.

This study uses three distinct models. But model complexity is only one dimension of fidelity. The other — and for this study, the more important one — is how honestly you treat uncertainty in the inputs.

The Models

Model A — Screening

Domenico Analytical

A closed-form equation for contaminant transport in a uniform aquifer. The standard EPA screening tool. One line of math, one answer, milliseconds.

Model B — 2D Transport

MODFLOW 6 GWF+GWT

USGS MODFLOW 6 solves groundwater flow on a 200×100 grid with spatially varying hydraulic conductivity. The industry-standard tool for contaminant transport. ~70s/sim.

Model C — Monte Carlo

200-Realization Ensemble

Runs Model B 200 times with different randomly sampled parameters. Instead of one answer, you get a probability distribution.

Deterministic vs. Stochastic

The first two models are deterministic: one set of inputs, one answer. The Monte Carlo is stochastic: it samples hydraulic conductivity (K), sorption coefficient (Kd), and source concentration from realistic distributions — because we don't know these parameters exactly, and pretending we do produces false confidence.

The biggest fidelity gap in this study isn't between models. It's between deterministic and stochastic analysis of the same transport model. MODFLOW 6 didn't change. What changed is whether we pretended we knew the sorption coefficient to two decimal places. That single assumption — known Kd — is what makes the plume look distant when it isn't.

The Investigations

Seven Questions. Seven Deep Dives.

Each question was answered at the fidelity it required. Click any card to see the full analysis, charts, and methodology.

Core Questions
Higher Fidelity

Scope: Three models (Domenico analytical, MODFLOW 6 GWF+GWT, Monte Carlo at 30–200 realizations per question), ~1,200 lines of Python, published USGS aquifer parameters, 1.9M EPA monitoring records. Limitations documented honestly: no unsaturated zone transport, no density-driven flow, no multi-species precursor reactions. Each question got the model it needed — nothing more.

The Fidelity Lesson

Finding the Right Model for the Decision

Each question above was answered at the fidelity it required. But scattered across seven questions, it's easy to miss the pattern: which dimensions of reality actually change the answer? Here it is in one place — four decisions evaluated at three model fidelities, showing where the answer converges and where it breaks.

Decision Screening (A) MODFLOW 6 (B) Monte Carlo (C)
Is there a problem? Yes — ~96 yr Yes, 7175 yr with heterogeneity Among within-horizon arrivals, P5 / P50 / P95 = 19 / 49 / 72.8 yr; 47% did not arrive within 100 yr
Which remedy? Can't evaluate P&T plausible P&T has lower NPV in 100% of 50 sampled remedy draws; NPV $31.9M flat
How much will it cost? Can't estimate ~$30M capex (no horizon view) $31.9M flat NPV; PRB $80.999.1M
Which species arrives first? Can't distinguish PFOA at 20yr, PFOS at 25yr Distribution per species

The deterministic models say P&T is plausible. In a 50-draw remedy comparison, P&T has lower modeled cost in every sampled realization under the encoded priors. Separately, 47% of the 200 arrival-time realizations did not reach the well within the 100-year horizon. The gap isn’t whether the conventional remedy is right; it’s whether you can test that choice across a stated distribution. This finite ensemble does not cover every physical condition or omitted process. Real aquifers have unknown K and Kd. A planning process that ignores both isn’t wrong by accident — it is incomplete on the questions that matter (does this work across the sampled uncertainty? is sharper data worth paying for?).

The Fidelity Lesson
The screening model says the plume is a century away. Among arrival-time realizations that reached the well within 100 years, P5 / P50 / P95 = 19 / 49 / 72.8 years; 47% did not reach it within the horizon. The screening model can’t evaluate remedies; a separate 50-draw remedy comparison gives P&T the lower modeled cost in every draw under these priors and puts the encoded value of added Kd characterization near $0M. The right model isn’t the most complex model — it’s the one that tests whether the decision holds across the encoded model and priors before you commit the capex.

Methodology note: Our composite scenario uses published USGS data from Joint Base Cape Cod — one of the most extensively studied PFAS sites in the US, with 1,500 hydraulic conductivity measurements and a 1.2 km PFOS plume tracked since the 1970s. Monte Carlo samples K from log-normal(mean=10, σlog=0.5), Kd from log-normal(mean=1.5, σlog=0.8) anchored to Anderson et al. (2019) AFFF-site Kd statistics (95% range ≈ 0.30–7.43 L/kg, with a 0.1 L/kg floor), and source concentration from normal(100, 25). Realization counts vary by question (Q1 arrival uses 200; Q3–Q5 use 50; Q6 uses 30 per MCL level). Note: the sensitivity table below reports the full Anderson 2019 literature range for Kd (0.5–20 L/kg); the MC log-normal centers within the site-relevant subset of that range.

Sensitivity

What Drives the Answer?

Across the 200-realization arrival-time ensemble, two parameters control 81% of the variance. Everything else is noise for this decision.

Parameter Range Variance Share Decision Impact
K (hydraulic conductivity) 1–100 m/d ~51% Determines whether plume arrives in years or decades
Kd (sorption) 0.5–20 L/kg ~30% Controls PFOS vs. PFOA differential arrival
Gradient (i) 0.002–0.008 ~18% Secondary; scales with K
Porosity / Dispersivity 0.2–0.4 / 5–50 m ~2% Affects plume width, not arrival

K and Kd together drive 81% of the arrival-time variance. That’s where a characterization budget would have the most leverage — but whether to spend it depends on what decision is on the table. For this site, with containment already the lower-cost remedy in all 50 sampled realizations under these priors, sharper Kd doesn’t change the build (see Q5: VOI ≈ $0M). For a site weighing monitored natural attenuation (MNA) vs. active remediation, the same measurement could be worth millions. Sensitivity tells you where the leverage is; VOI tells you whether to pull it.

Sensitivity from Q1 tornado diagram (arrival time) and Q5 variance decomposition (cleanup time). Q1 ensemble: 200 realizations, USGS-sourced parameter ranges.

Can You Trust These Numbers?

Model Validation

Before projecting remediation scenarios, we ran our MODFLOW 6 model against real monitoring data from Joint Base Cape Cod — one of the most extensively studied PFAS sites in the country. 62 USGS monitoring well measurements, same model, same algorithm.

Model ConfigurationPredicted Plume Frontvs. Observed (2,700 m)Explanation
Cape Cod params (K=95, Kd=0.4) 2,990 m +11% Site-specific data matches observed plume
Generic literature params (K=10, Kd=1.5) 780 m −71% 3.5x ratio of observed to predicted (equivalent to 71% under-prediction relative to observed) without site data
Full 3D model (10 layers, 200K cells) 2,910 m +8% Vertical structure matches qualitatively

The honest reading: With published USGS aquifer parameters (K=95 m/d, n=0.39, back-calculated Kd=0.4 L/kg), our model predicts the plume front within 11% of what USGS actually measured. Generic literature parameters miss by 3.5x. This is why site characterization matters — and why the conditional arrival distribution among realizations that reached the well within 100 years (P5 / P50 / P95 = 19 / 49 / 72.8 years) captures variation the deterministic base case misses. The 47% that did not reach within the horizon remain outside those percentiles. The 3D model confirms vertical structure: PFOS peaks at 25–35m depth, consistent with recharge pushing the plume downward.

Observed data: 49 PFOS detections (1.3–610 ng/L) at 62 monitoring wells, USGS Water Quality Portal (2019–2020 sampling). Predicted: MODFLOW 6, 200×100 grid, 55-year simulation.

Methodology

What We Modeled and What We Didn't

Transport modeling uses USGS MODFLOW 6 (v6.6.3). Aquifer properties from Joint Base Cape Cod USGS studies (K=60–110 m/d, n=0.39, αL=0.96m from 1,500 borehole flowmeter tests). National context from EPA UCMR5 (1.9M samples). Every parameter sourced.

ParameterBase ValueRangeSource
Hydraulic conductivity (K)10 m/d1–100 m/dUSGS, Gelhar (1992)
Effective porosity (n)0.300.20–0.40Freeze & Cherry (1979)
PFOS Kd1.5 L/kg0.5–20 L/kgAnderson et al. (2019)
Source concentration100 ppb50–200 ppbDoD fire training area (FTA) data
Decay rate≈0“Forever chemicals”

What we didn't model: Unsaturated zone transport, density-driven flow, multi-species precursor reactions, air-water interface sorption, co-contaminant interactions. Each would increase fidelity — and each would increase computation 10–100x. The open question is: which of these actually changes the remedy selection decision? That’s the follow-up study.

Reality Check — March 2026

What's Actually Happening

The analysis above answers “what if.” This section answers “what is.” Real contamination has been measured. Real regulations have been finalized. Real remediation is underway. Here's how reality maps onto our model.

What's Coming: The Scale of the Problem

We downloaded the EPA's UCMR5 monitoring dataset — 1.9 million sample results from 10,299 public water systems. The numbers are stark.

MetricValueContext
Monitored systems with at least one reported PFAS detection 59.7% 6,148 of 10,299 systems
PFOS detections exceeding 4 ppt MCL 97% Nearly every detection is an exceedance
Median detected PFOS concentration 6.8 ppt Nearly twice the legal limit
Systems currently exceeding MCL 1,693 Each must remediate or find alternative supply
DoD installations identified with a potential PFAS release 700+ Federal screening inventory; not 700+ confirmed Cape Cod-like plumes or remedies

The Regulatory Landscape

EventDateImpact
EPA finalizes 4 ppt MCL for PFOS/PFOAApr 2024Potential-release sites proceed through investigation and, where warranted, cleanup
EPA proposes a PFOA/PFOS exemption option and a separate rescission rule for four other PFAS provisionsMay 2026Both actions remain proposed; the 2024 final rule still supplies the current enforceable text
Several states propose 2 ppt or lowerOngoingOur Q6 shows site NPV is flat but exceedance footprint scales 4×
UCMR5 monitoring ~95% completeJan 202659.7% of monitored systems in this snapshot have at least one reported PFAS detection

Specific Sites in the Pipeline

SiteStatusEstimated CostKey Challenge
Joint Base Cape Cod, MA Active remediation since 2015 $100M+ (ongoing) 1.2 km plume in sand/gravel; 6,200-acre zone
Pease AFB, NH Remedial investigation/feasibility study (RI/FS) underway, report mid-2026 Estimate pending final RI/FS Municipal water supply contaminated
Luke AFB, AZ Preliminary assessment complete Estimate pending final RI/FS Arid climate reduces recharge but concentrates plume
Broader DoD potential-release inventory 718 current and former installations identified with a potential PFAS release as of June 2024 More than $9.3B in estimated future investigation and cleanup costs beginning in FY2025 GAO’s bounded estimate, not a lifecycle ceiling; inclusion does not establish a plume, remedy, or site cost

The portfolio number and the site model answer different questions. GAO reported more than $9.3 billion in estimated future PFAS investigation and cleanup costs beginning in fiscal year 2025; it did not present that figure as a full lifecycle ceiling. The $32M containment NPV belongs only to the composite Cape Cod-parameterized scenario. DoD’s 718-site count is a potential-release inventory whose sites differ in plume evidence, soils, wells, investigation stage, and whether remediation will be required. The uncertainty is therefore both which sites ultimately require action and what that action entails (see Q6).

The Remediation Market

The PFAS remediation market is expanding. Clean Harbors, Arcadis, Tetra Tech, Geosyntec — the companies doing this work face a fundamental challenge: deterministic models do not quantify containment across the encoded uncertainty, and they can’t tell a client when a $500K characterization spend would be wasted. The Monte Carlo work isn’t about pricing the tail bigger — at this site the cost is flat. It tests both the recommended remedy and the decision to stop spending on data across the sampled priors; it does not prove performance under every unmodeled condition.

Recommendations

What We'd Recommend

Seven questions, three model fidelities, hundreds of Monte Carlo runs across the questions — and now grounded in what's actually being measured, regulated, and remediated.

Bottom Line
Containment is the lower-cost modeled remedy at this site in all 50 Monte Carlo realizations sampled under the encoded priors. That is not proof across every physical condition. Under these priors, narrowing Kd uncertainty did not improve the encoded remedy decision enough to justify its modeled characterization cost. Screening is fine for “is there a problem?” It can’t answer “is the obvious remedy robust?” or “is sharper data worth paying for?” — the questions that matter.

For Remediation Contractors

Don’t lead with PRB premium pricing here — P&T wins on NPV by ~$50M ($31.9M vs $80.999.1M) and contains the plume in all 50 sampled realizations under the encoded priors. The contract risk isn’t the cleanup time; it’s scope creep if the MCL tightens to 0.5 ppt and the exceedance fraction quadruples (Q6). Price the wells, document the basis, and build a re-opener for regulatory shifts.

For Site Owners

Resist the urge to fund a $500K Kd campaign reflexively. At this site the VOI is essentially zero — sharper sorption data doesn’t change the build, the schedule, or the bill. The right next investment is operations: get the wells on, document the capture zone, and put characterization money toward sites where it actually flips a decision.

For Monitoring Programs

PFOA travels faster than PFOS (lower Kd). At sites with mixed AFFF contamination, PFOA arrives at the well field 5 years earlier. If your monitoring plan only tests for PFOS, you're missing the leading edge. Test for the full PFAS suite — PFOA and PFHxS are your early warning system.

Compliance Deadlines

The 2024 final rule requires compliance by April 2029. On May 18, 2026, EPA proposed an option for eligible systems to request two additional years, to 2031, while keeping the 4 ppt PFOA and PFOS limits. EPA separately proposed rescinding the PFHxS, PFNA, HFPO-DA, and Hazard Index provisions. Neither proposal is final as of July 25, 2026, so the final rule’s 2029 deadline remains the current baseline. In the processed January 2026 UCMR5 snapshot, 1,693 monitored systems exceeded at least one final-rule MCL. States with stricter standards — New Jersey (58% exceedance), Massachusetts (40%), North Carolina (39%) — face the earliest and most expensive compliance requirements.

The Right Fidelity for This Decision
Screening says the plume is a century away. MODFLOW 6 with heterogeneous geology says 7175 years. Among 3D arrival-time realizations that reached the well within 100 years, P5 = 19 yr, P50 = 49 yr, and P95 = 72.8 yr; 47% did not reach the well within the horizon. The screening model can’t evaluate remedies. MODFLOW 6 does not quantify the choice across the sampled uncertainty. The Monte Carlo — the same transport model run as a finite ensemble — finds P&T has lower modeled cost in all 50 sampled remedy realizations under these priors and shows that Kd characterization buys nothing within the encoded decision model. Each model tells you something the simpler one can’t. GAO’s more-than-$9.3-billion estimate covers future DoD investigation and cleanup costs beginning in FY2025 across a 718-installation potential-release inventory; it is neither a lifecycle ceiling nor this site result scaled across the portfolio.

Model results and source-data snapshot: March 2026. Regulatory text reviewed: July 25, 2026. EPA regulations, state MCL proposals, and UCMR5 monitoring data are evolving.

Sources

Sources

Regulatory & Monitoring Data
EPA (2024). PFAS National Primary Drinking Water Regulation, 89 FR 32532. EPA (2025). Announced intent to retain PFOA/PFOS limits and pursue rulemaking. EPA (2026). Proposed PFOA/PFOS Compliance Extension Rule and Proposed PFAS Rescission Rule. EPA UCMR5 Occurrence Data (Jan 2026, 10,299 systems). EWG PFAS Contamination Map (9,728 sites).

Transport & Sorption
Domenico (1987). Analytical transport model. J. Hydrology 91:49–58. Anderson et al. (2019). PFAS Kd values. J. Contaminant Hydrology 220:59–65. Brusseau (2018). Air-water interface sorption. Sci. Total Environ. 613–614:176–185. Gelhar et al. (1992). Field-scale dispersivity. Water Resources Res. 28(7):1955–1974.

Hydrogeology
Bear (1972). Dynamics of Fluids in Porous Media. Freeze & Cherry (1979). Groundwater. Walter et al. (2018). USGS SIR 2018-5139. Cape Cod MODFLOW model. LeBlanc et al. (1991). Cape Cod tracer test. Water Resources Res. 27(5):895–910.

Remediation Costs
EPA (2021). PFAS Treatment Technologies. EPA/600/R-21/164. ITRC (2023). PFAS Technical and Regulatory Guidance. GAO (2025), Persistent Chemicals: 718 current and former installations identified with a potential PFAS release as of June 2024; nearly all had completed initial assessment and site inspection.

Validation Data
USGS via Water Quality Portal. 62 monitoring well measurements at Joint Base Cape Cod (2019–2020). 49 PFOS detections, 1.3–610 ng/L, plume front ~2,700 m after 55 years.

Modeling Tools
Langevin et al. (2024). MODFLOW 6. Groundwater. USGS MODFLOW 6 v6.6.3 with GWT transport model.