Last updated: May 2026
PCG built a soil remediation tracking system for an EPA Superfund cleanup site. The system recorded volumes of contaminated soil removed, source and destination locations, contamination testing results, and remaining quantities still requiring treatment. A custom calculation engine projected forward to estimate how much soil remained, giving the client visibility into project timeline, cost, and regulatory progress for a federally supervised environmental cleanup.
EPA Superfund federal supervision oversight
CERCLA Compliance framework for cleanup tracking
Forward Projection engine for remaining remediation
Multi-source Volume, location, and testing data unified

What was breaking in soil remediation tracking before this project?

The client was managing an active Superfund cleanup under EPA oversight. Federally supervised environmental remediation comes with reporting obligations that the project sponsor cannot defer or simplify. Volumes of contaminated soil removed must be documented at the cubic yard level. Source locations and destination disposal sites must be traceable for every load. Contamination testing results must link back to the specific soil they describe. And the projection of how much soil remains to be treated, which determines the timeline and cost trajectory of the entire cleanup, must be defensible to the regulator.

Spreadsheets do not survive that scrutiny. They lose data integrity as multiple people edit them. They cannot enforce relationships between source location, destination, and testing record. They produce projections that no one can audit because the formulas drift over time. For a Superfund site under active EPA supervision, that is not an inconvenience. It is a regulatory exposure that grows with every reporting cycle.

Disconnected Data Soil volumes, source and destination locations, and testing results lived in separate spreadsheets and files with no enforced relationships between them.
No Forward Projection The client had no defensible calculation of how much soil remained to be treated, so timeline and cost projections to EPA were estimates rather than data-driven figures.
Audit Reconstruction Burden Every EPA reporting cycle required manual reconstruction of the chain from source soil to destination disposal to testing records.
Federal Compliance Risk Superfund sites operate under continuous EPA supervision. Reporting gaps or inconsistencies surface immediately and become part of the regulatory record.

For a Superfund cleanup, the consequences of weak tracking infrastructure compound over time. EPA does not forget reporting gaps. Timeline projections that turn out to be inaccurate get challenged in subsequent reviews. Funding decisions for the remaining cleanup phases depend on the credibility of the data presented. A tracking system that cannot defend its own outputs creates problems that outlive the cleanup itself.

What did PCG actually build for the EPA Superfund tracking environment?

PCG developed a database-backed tracking system designed specifically for federally supervised soil remediation. The architecture handled the complete data chain from contaminated source through testing through disposal destination, with a forward projection engine that produced defensible estimates of remaining work. Each component was built so that the data trail required by EPA auditors was captured at the moment work happened, not reconstructed afterward.

1
Soil volume tracking by source location

Every cubic yard of contaminated soil removed from the site was logged against its source location within the cleanup area. The system tracked extraction sequences, soil type, and the date and time of each removal. Source data became the anchor that every subsequent record linked back to.

2
Destination disposal site logging

Each load of removed soil was tracked from source to destination. Disposal site records included the receiving facility, transport documentation, and chain-of-custody. EPA reporting requires this trail. The system captured it as a structured record rather than a paper manifest reconstructed at the end of each reporting period.

3
Contamination testing results linked to soil

Testing results from soil samples were linked directly to the specific soil they characterized. Test method, lab, results by analyte, and date were captured against each source location. When a question arose about the contamination profile of soil sent to a specific disposal facility, the answer was a query rather than a manual file search.

4
Custom forward projection calculation engine

The system included a calculation engine that projected forward to estimate remaining soil quantities still requiring treatment. Inputs included treated volumes, contamination boundaries, treatment effectiveness, and remediation rates. The engine produced timeline and cost projections that were defensible to EPA because the calculations were transparent and the underlying data was queryable.

5
Regulatory progress visibility for the client

The system gave the client real-time visibility into project timeline, cost trajectory, and regulatory progress against the EPA-approved cleanup plan. Quantities removed, quantities remaining, projected completion, and costs to date were available without manual rollup from spreadsheets. EPA reporting cycles became data extracts from the live system.

What we learned on this project

Superfund sites fail their tracking obligations in a specific way. The site team usually has the data. They just cannot produce it in the form EPA requires within the timeline EPA expects. A tracking system that captures data at the moment of work and structures it for the format regulators ask for changes the equation. The data was always there. The infrastructure to surface it was not.

The forward projection engine was the part that created the most strategic value, beyond the regulatory reporting. A project sponsor who can produce a defensible estimate of remaining cleanup work has a different conversation with EPA, with funders, and with internal stakeholders than a project sponsor who is producing best-guess timelines from spreadsheets. The number itself is less important than the auditability of how the number was produced.

What changed after the system went into production?

The most immediate change was that EPA reporting cycles stopped being reconstruction projects. The data trail from source soil through testing through disposal destination was already captured and structured. Reports became data extracts. The team's effort moved from assembling reports to running the cleanup.

Outcome Result How it was achieved
EPA reporting timeline Data extracts, not reconstructions Source-to-destination chain captured at the moment of work, structured for regulator format
Forward projection of remaining work Defensible to regulator Custom calculation engine with transparent inputs and queryable underlying data
Source-to-disposal chain of custody Continuous and complete Every load tracked from source location through destination disposal facility
Contamination testing traceability Linked at the source-record level Testing results attached directly to the soil they characterized, by source and date
Project timeline visibility Real-time Treated volumes, remaining volumes, and projected completion available on demand
Cost trajectory tracking Tied to actual cleanup data Costs attributed to source locations and treatment phases as work progressed

The strategic value of the system extended beyond EPA reporting itself. Real-time projection of remaining cleanup work changed the client's ability to manage the project against budget and schedule. Decisions that had previously waited for the next reporting cycle could be made on current data. Funding conversations that had been based on best-guess timelines became conversations grounded in defensible projections.

What capabilities does this kind of system provide for federally supervised environmental cleanup?

The infrastructure built for this Superfund site addresses a problem class that appears across every environmental remediation project under federal or state regulatory oversight. The capabilities below apply to CERCLA Superfund work, RCRA corrective action, state-led brownfield cleanups, voluntary cleanup programs, and any operation where soil, groundwater, or other contamination is being tracked from contaminated source through treatment or disposal.

Source-to-destination chain of custody

Every cubic yard of contaminated material tracked from source location through transport through destination disposal facility. The chain that EPA and state regulators require is captured automatically at each handoff rather than reconstructed at the end of reporting cycles.

Defensible forward projections

A calculation engine that estimates remaining cleanup work based on transparent inputs and queryable underlying data. Project sponsors can produce timeline and cost projections that hold up to regulator review and stakeholder scrutiny.

Testing data linked to physical soil

Contamination testing results connected directly to the specific source location, sample, and material they describe. When a question arises about the contamination profile of material sent to a specific facility, the answer is a query against linked records, not a manual file search.

Real-time regulatory progress visibility

Treated volumes, remaining volumes, projected completion dates, and cost trajectory available on demand against the EPA-approved cleanup plan. Project decisions stop waiting for the next reporting cycle to be made on current data.

Technology stack

ComponentTechnology
Database layerRelational database with enforced source-destination-testing relationships
Calculation engineCustom forward projection logic with transparent input parameters
Data captureSpreadsheet and database integration for field data entry
Chain of custodySource location, transport, and destination logged as linked records
Testing integrationLab results linked at the source-record level by sample, method, and date
Reporting layerEPA-format data extracts produced from live system queries
Compliance frameworkCERCLA / Superfund supervision with EPA reporting alignment

Does this apply if your cleanup is smaller than a full Superfund site?

The architecture scales down as well as up. State-led brownfield cleanups, voluntary cleanup programs, RCRA corrective action sites, and private remediation under regulatory oversight all face the same core problems as a Superfund site: source-to-destination chain of custody, testing data linked to physical material, defensible forward projections, and reporting that aligns with regulator format. The engineering decisions on this project transfer directly to cleanups an order of magnitude smaller.

What makes this project transferable is not the regulatory framework. It is the problem class. Any environmental cleanup where contaminated material moves from source through testing through disposal, under any oversight regime, is carrying the same data integrity risk this Superfund site was carrying before the system went live. The risk accumulates invisibly until a regulator asks a question the data cannot answer in the form required.

PCG has built environmental compliance and remediation infrastructure since 1995. The work documented here is one of more than 500 production applications PCG has delivered, with environmental and regulatory compliance representing approximately one-third of that volume across 31 years.

Frequently asked questions about Superfund and environmental remediation tracking systems

Yes. PCG has built tracking infrastructure for federally supervised environmental cleanup work, including Superfund sites under EPA oversight. The architecture handles soil volume tracking by source location, destination disposal logging, contamination testing results linked at the source-record level, and a custom forward projection calculation engine for remaining cleanup work. Deployments have supported active CERCLA-regulated cleanups with continuous EPA reporting obligations.
The forward projection engine takes treated volumes, contamination boundaries, treatment effectiveness measurements, and historical remediation rates as inputs. It produces estimates of remaining soil quantities still requiring treatment, projected timeline to cleanup completion, and projected cost trajectory. The calculations are transparent and the underlying data is queryable, which is what makes the projections defensible to EPA reviewers rather than best-guess estimates.
Every load of removed soil is tracked from source location through transport through destination disposal facility. Records include the source location within the cleanup site, soil volume by cubic yard, transport documentation, receiving facility, and date and time of each handoff. Chain-of-custody requirements that EPA imposes for federally supervised cleanups are captured at the moment work happens rather than reconstructed at reporting time.
Testing results are linked directly to the source location, sample, and removal record they characterize. Records include test method, lab, results by analyte, and date. When a question arises about the contamination profile of material sent to a specific disposal facility, the answer is a query that returns the linked testing record rather than a manual file search through email attachments and lab reports.
Yes. The architecture transfers directly to state-led brownfield cleanups, voluntary cleanup programs, RCRA corrective action sites, and private remediation under any regulatory oversight regime. The data structures, chain of custody requirements, and projection logic are similar across regulatory frameworks. The forms and report formats differ. PCG configures the reporting layer to match the format the relevant regulator requires.
Yes. Most active remediation projects PCG works with already have historical data in spreadsheets, paper logs, and lab report files. The migration consolidates existing records, reconstructs the source-to-destination relationships where possible, and preserves the historical trail that regulators may request retroactively. Original files remain available for reference. The migration approach is documented before any data movement begins.
EPA reports become data extracts from the live tracking system rather than manual reconstructions assembled at the end of each reporting period. The data structure aligns with the format EPA expects, which removes the translation layer that consumes staff time at every cycle. Reports that previously required days of file assembly are produced as queries against the live system. Site teams spend reporting cycles running the cleanup rather than building reports.
Yes. Full source code ownership transfers to the client at project completion. All remediation data captured by the system belongs to the client. Documentation of the database schema, calculation engine logic, and operational procedures is delivered as part of the project. Clients are not dependent on PCG to maintain the system, although most engagements continue under a monthly support retainer for hosting, maintenance, and minor modifications.
About the engineer behind this project Allison Woolbert, Principal, Phoenix Consultants Group

Allison has been building custom software since the early 1980s, including work as a data analyst for the U.S. Air Force before founding PCG in 1995. The Superfund remediation tracking documented here is one of more than 500 custom applications PCG has delivered, with environmental and regulatory compliance representing approximately one-third of that volume across 31 years. Her direct involvement in every project is not a policy. It is how PCG operates. When you call, she answers.

Running a federally supervised environmental cleanup on spreadsheets that cannot defend their own projections? PCG has built environmental compliance and remediation tracking infrastructure since 1995. The diagnostic engagement takes two to three hours and produces a written scope before any development commitment.
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Project details documented with client permission. Specific identifying details about the Superfund site have been generalized. System capabilities and architecture reflect the actual production deployment.

PCG founded 1995. Allison Woolbert's personal experience in software development predates PCG's founding.