Mass Balance Paradigm Software
The mass balance paradigm is an important new approach to evaluating Monitored Natural Attenuation (MNA) at chlorinated solvent sites. By using the mass balance approach, site managers can demonstrate that the assimilative capacity of a particular system is either capable (or incapable) of managing the mass flux of chlorinated solvents emitted from a source zone. In addition, a detailed mass balance at a site can provide valuable insight on:
- Which processes contribute to the overall assimilative capacity?
- How the source term might change over the long-term lifetime of the source?
- To what degree competing reactions interfere with solvent biodegradation processes?
- How sustainable biodegradation is likely to be over the long term?
However, the mass balance approach can be difficult to apply at sites with current solute transport models, particularly numerical models.
Most numerical models do not:
- Have the ability to directly provide key mass flux data
- Distinguish between mass loss due to different natural attenuation processes
- Simulate long-term behavior of sources at sites
The BIOBALANCE Toolkit was developed to address these shortcomings. Other notable developments incorporated in BIOBALANCE include:
- The ability to Assess stability of plumes originating from both vadose and submerged source zones.
- Evaluate plume stability (time and size) using an iterative approach that solves equations in BIOCHLOR and documents the relative contributions of various attenuation mechanisms.
- Examine the sustainability of anaerobic degradation processes based on an approximate balance of electron acceptor and electron donor.
- Provide an overarching accounting of mass balance results from the various modules in the form of a summary report.
The toolkit comprises of the following modules:
Source Module: The source module uses simple mass balance models to provide estimates of the reduction in Remediation Time Frame (RTF) for a given amount of source depletion. The module has the capacity to address the impact of different remediation strategies on the source mass and the mass flux from the source (e.g. reducing flux via a permeable reactive barrier, or reducing source mass from a source depletion technology). Both vadose zone and submerged sources can be modeled.
Competition Module: This module calculates how mass flux of competing electron acceptors such as dissolved oxygen, nitrate, and sulfate into the source zone translates into lost electron donor capacity. The impact of ferric iron reduction and methane generation is also included in the mass balance.
Donor Module: Users can estimate the sustainability of a source zone based on either NAPL composition data or dissolved constituent data. In this module, stoichiometric relationships are used to calculate the ratio of electron donor to the chlorinated solvent present in the source zone.
Plume Module: This module helps predict the benefit of remediation strategies on plume length and mass flux. Plume length vs. time and mass flux vs. distance curves are generated using an analytical groundwater model. The relative contribution of natural attenuation processes such as dispersion, sorption, degradation, and source decay to mass flux are calculated and presented in a graphical format.
Final Mass Balance: Key mass balances on solvents, donors, and competing electron acceptors over the lifetime of the source are integrated and presented. The spreadsheet tool uses hydrogeologic, geochemical, and contaminant data that are typically generated from MNA projects at chlorinated solvent sites to simulate the long-term behavior of sources at these sites.
Limited technical support is available from David Adamson.
The Biobalance Toolkit model requires a computer system capable of running Microsoft® Excel (2000/XP) for Windows (2000/XP) and Microsoft Word for Windows (2000/XP), and reading Adobe Acrobat pdf documents. Operation requires an IBM-compatible PC equipped with a Pentium or later processor running at a minimum of 450 MHz. A minimum of 256 MB of system memory (RAM) is strongly recommended. Computers not meeting these recommendations will experience slow running times and/or problems with memory.