Waste Disposal & Management
Compliance-First Intelligence for Waste Programs
EnviTrace keeps hazardous waste generators, MSW operators, and nuclear licensees in sync with RCRA, CERCLA, Basel, NRC, and IAEA obligations while giving planners the forecasting tools they need.
Why EnviTrace
Waste management that aligns law, logistics, and finance
We stitch together manifests, monitoring data, permit conditions, and board-ready narratives so every shipment, cell expansion, or disposal campaign has traceable justification.
Cradle-to-Grave Compliance
Map generators, transporters, treatment, storage, and disposal facilities to RCRA, CERCLA, and state overlays before regulators do it for you.
Multi-Stream Intelligence
Unify municipal solid waste, industrial residuals, medical waste, and radioactive materials in a single monitoring and reporting stack.
Stakeholder-Ready Storylines
Pair emissions reduction, environmental justice, and rate-base narratives with the evidence boards, councils, and investors require.
Program Lane
Hazardous + MSW Orchestration
Digital manifests, landfill capacity modeling, materials recovery forecasts, and Basel-compliant export tracking in one workspace.
Program Lane
Radioactive Waste Strategy
Dose accounting, ISFSI asset tracking, barrier performance modeling, and Joint Convention reporting support for DOE and commercial fleets.
Program Lane
Community + Finance Alignment
Link waste diversion KPIs, tipping fee scenarios, and climate finance cases so boards see the payback alongside compliance certainty.
Need the source material?
Dive into the Waste Resource Hub
Pull the statutes, treaty texts, nuclear safety requirements, and academic trendlines that shape every waste program decision.
Explore ResourcesRelated publications
- ChemML: Physics-Informed AI/ML of Geochemical Datasets for Characterization, Parameterization, and Prediction of Contaminant Transport and Remediation Processes (2023) — V.V. Vesselinov, T.L. Kliphuis — DOE
- Identification of the release sources in advection-diffusion system by machine learning combined with Green function inverse method (2018) — V.G. Stanev et al. — Applied Mathematical Modelling
- Long-term stability of dithionite in alkaline anaerobic aqueous solution (2018) — K. Telfeyan et al. — Applied Geochemistry
- Nonnegative Tensor Factorization for Contaminant Source Identification (2018) — V.V. Vesselinov, B.S. Alexandrov, D. O'Malley — Journal of Contaminant Hydrology
- CHROTRAN 1.0: A mathematical and computational model for in situ heavy metal remediation in heterogeneous aquifers (2017) — S.K. Hansen et al. — Geoscientific Model Development
- Contaminant source identification using semi-supervised machine learning (2017) — V.V. Vesselinov, D. O'Malley, B.S. Alexandrov — Journal of Contaminant Hydrology
- Two-Stage Fracturing Wastewater Management in Shale Gas Development (2017) — X. Zhang et al. — Ind. Eng. Chem. Res.
- Contaminant point source localization error estimates as functions of data quantity and model quality (2016) — S.K. Hansen, V.V. Vesselinov — Journal of Contaminant Hydrology
- Parameter estimation and prediction for groundwater contamination based on measure theory (2015) — S.A. Mattis et al. — Water Resources Research
- A combined probabilistic/non-probabilistic decision analysis for contaminant remediation (2014) — D. O’Malley, V.V. Vesselinov — Journal on Uncertainty Quantification, SIAM/ASA
- Groundwater remediation using the information gap decision theory (2014) — D. O’Malley, V.V. Vesselinov — Water Resources Research
- Isotopic evidence for reduction of anthropogenic hexavalent chromium in Los Alamos National Laboratory groundwater (2014) — J.M. Heikoop et al. — Chemical Geology
- Robust Decision Analysis for Environmental Management of Groundwater Contamination Sites (2014) — V.V. Vesselinov, D. O'Malley, D. Katzman — Vulnerability, Uncertainty, and Risk Quantification, Mitigation, and Management
- Data and Model-Driven Decision Support for Environmental Management of a Chromium Plume at Los Alamos National Laboratory (LANL) (2013) — V.V. Vesselinov et al. — Waste Management Symposium, Phoenix, AZ
- AGNI: Coupling Model Analysis Tools and High-Performance Subsurface Flow and Transport Simulators for Risk and Performance Assessments (2012) — V.V. Vesselinov, G. Pau, . Finsterle — Computational Methods in Water Resources (CMWR)
- Contaminant remediation decision analysis using information gap theory (2012) — D. Harp, V.V. Vesselinov — Stochastic Environmental Research and Risk Assessment (SERRA)
- Decision support based on uncertainty quantification of model predictions of contaminant transport (2010) — V.V. Vesselinov, D. Harp — Computational Methods in Water Resources (CMWR), Barcelona, Spain
Related presentations
- ChemML: Understanding groundwater flow and contaminant transport using machine learning (2022) — V.V. Vesselinov, T. Kliphuis — American Geophysical Union, San Juan, Puerto Rico
- Decision Analyses for Groundwater Remediation (2017) — V.V. Vesselinov, D. O'Malley, D. Katzman — Waste Management Symposium
- Uncertainty quantification and experimental design based on unsupervised machine learning identification of contaminant sources and groundwater types using hydrogeochemical data (2017) — V.V. Vesselinov, D. O'Malley, B. Alexandrov — AGU Fall Meeting
- Groundwater Remediation using Bayesian Information-Gap Decision Theory (2016) — D. O'Malley, V.V. Vesselinov — AGU Fall Meeting
- ZEM: Integrated Framework for Real-Time Data and Model Analyses for Robust Environmental Management Decision Making (2016) — V.V. Vesselinov, D. O'Malley, D. Katzman — Waste Management Symposium
- Model-Assisted Decision Analyses Related to a Chromium Plume at Los Alamos National Laboratory (2015) — V.V. Vesselinov, D. O'Malley, D. Katzman — Waste Management Symposium
- A Social Dynamics Dependent Water Supply Well Contamination Model (2014) — J. Bakarji, D. O'Malley, V.V. Vesselinov — DOE LANL Presentation
- Model-free Source Identification (2014) — V.V. Vesselinov, B. Alexandrov — AGU Fall Meeting
- Data and Model-Driven Decision Support for Environmental Management of a Chromium Plume at Los Alamos National Laboratory (LANL) (2013) — V.V. Vesselinov et al. — Waste Management Symposium
- AGNI: Coupling Model Analysis Tools and High-Performance Subsurface Flow and Transport Simulators for Risk and Performance Assessments (2012) — V.V. Vesselinov, et al. — XIX International Conference on Computational Methods in Water Resources (CMWR 2012)
- Model-driven decision support for monitoring network design based on analysis of data and model uncertainties: methods and applications (2012) — V.V. Vesselinov, D. Harp, D. Katzman — AGU Fall meeting (invited)
- Environmental Management Modeling Activities at Los Alamos National Laboratory (LANL) (2010) — V.V. Vesselinov, et al. — Department of Energy Technical Exchange Meeting, Performance Assessment Community of Practice, Hanford