Environmental Cleanup

Most importantly, PBMO™'s modular organizing logic allows decision makers to deploy a unique blend of physics-based simulators with machine learning, expert systems (management criteria), and formal optimization techniques than has heretofore been possible.


Remedial systems designed to restore contaminated environments to beneficial use are increasingly required to address multiple objectives. Engineered remedies must decontaminate or contain pollutants in complex media while minimizing factors such as cleanup time, cost and energy inputs, and secondary waste generation. Remedial designs are often constrained by surrounding property use, adjacent contamination, sensitive habitats, and/or regulatory requirements. While environmental simulation models can support remedial design, models alone cannot identify an optimal solution that balances multiple objectives, design options, and constraints.

To address these deficiencies, HGL has developed PBMO to link environmental modeling with management optimization. The PBMO tool identifies optimal remedial design and operational approaches that lead to timely and cost-effective cleanups. By linking modeling and computational optimization, PBMO can realistically capture important site physics and financial constraints; achieve a coherent interpretation of disparate site data using all relevant information; and produce structured, credible solutions acceptable to stakeholders and regulators.

See animations below describing specific applications of PBMOTM to support remediation optimization:
Pump & Treat Optimization for Adjacent RDX and TNT Plumes at Umatilla Army Depot, Umatilla, OR (Runtime 4:28)
Remedial Design Optimization for a 4-Mile-Long Carbon Tetrachloride Plume Using PBMO™ at a Superfund Site in Nebraska (Runtime 5:02)
Application in Developing Optimal Exit Strategy at Former Fort Ord in California (Runtime 6:14)


  • Cost-Efficient Remedial Design
  • Remedy-in-place Evaluation
  • Operation and Maintenance Optimization
  • Assessment of Optimal Exit and Site Completion Strategy

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