Toxic Substances Hydrology Program
New Version of NAS (Natural Attenuation Software) Available
NAS (Natural Attenuation Software) is a software package that provides a decision-making framework for determining the time needed to clean up ground-water contamination sites. The package has been upgraded with the release of version 2.2.0. This new version:
NAS was developed by the U.S. Geological Survey (USGS), Virginia Polytechnic Institute and State University (Virginia Tech), and the U.S. Navy to help environmental cleanup professionals estimate how far plumes will migrate and how long natural attenuation processes will take to clean up contamination.
ESTCP Evaluation Project
The Environmental Security Technology Certification Program (ESTCP) is funding a project to evaluate NAS's ability to estimate cleanup times associated with combining the remediation of a contaminant source-area with the use of Monitored Natural Attenuation (MNA) to remediate the remaining downgradient contaminant plume. Project investigators are applying NAS to eight contamination sites across the Nation to test the software's predictive capability and the utility of the estimates it provides. ESTCP is a Department of Defense (DOD) program that promotes innovative environmental technologies through demonstration and validation projects at DOD contamination sites.
NAS Demonstration Sites
NAS Training Courses – Technology Transfer
The USGS and Virginia Tech have conducted a series of short courses on "Estimating Times of Remediation Associated with Monitored Natural Attenuation and Contaminant Source Removal." The courses are part of an effort by the USGS Toxic Substances Hydrology (Toxics) Program to provide or transfer the technology it develops to stakeholders that can benefit from the information and methods. These short courses on NAS present a decision-making framework and methodology for assessing MNA and estimating timeframes required for natural attenuation processes to lower contaminant concentrations to regulatory goals.
USGS Information on Environmental Simulation Models