SERAFM Conceptual Model

SERAFM Conceptual Model - SERAFM is a process-based, steady-state modeling system based in a spreadsheet framework incorporating a series of process modules.

serafmexposureassessmentmercuryhgsurface waterpondstreamriver

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Initial contribute: 2019-12-16

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United States Environmental Protection Agency
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Detailed Description

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Quoted from: https://www.epa.gov/ceam/serafm-conceptual-model 

SERAFM Conceptual Model - SERAFM is a process-based, steady-state modeling system based in a spreadsheet framework incorporating a series of process modules. SERAFM predicts speciated mercury concentrations (Hg0, HgII, MeHg, HgT) in water (filtered and unfiltered) and sediments, and total mercury concentrations in fish tissue. Using this information exposure risk hazard indices are estimated for a series of exposed wildlife. Three scenarios of historical contamination from contaminated sediments, reference conditions, and feasible remediation concentrations are simultaneously and instantaneously predicted. SERAFM is not a priori predictive, but rather requires site-specific calibration. This is a challenge due to the limits of understanding in mercury process science, and is inherent in any process-based modeling structure. SERAFM was specifically developed to serve as a screening-level tool to investigate mercury cycling and exposure concentrations in water bodies and associated impacted wildlife exposure risk, as well as a research tool to investigate mercury processes within the watershed and water body.


Audience

Engineer, Scientist, Biologist, Researcher


Abstract

SERAFM is a steady-state, process based mercury cycling model designed specifically to assist a risk assessor or researcher in estimating mercury concentrations in the water column, sediment, and fish tissue for a given water body for a specified watershed. SERAFM predicts mercury concentrations in these media for the species Hg0, HgII, and MeHg. The model runs three simultaneous scenarios. One scenario is for historically contaminated sediment, where the total mercury concentration in sediments is known. This scenario would be effective, for example, for modelling a Superfund site where the sediment is acting as a loading source to the system. In this first case, the total mercury concentration in the sediment is entered into the model as a known parameter. The second scenario is a hypothetical background or reference condition, which is defined as the condition as if no historical loading of mercury had occurred at this site. Therefore, the mercury concentrations in water and sediment are calculated with no known mercury sediment concentration, but rather the total mercury concentration sediment is directly calculated by the model. Mercury loadings to the water body come from atmospheric deposition and watershed erosion and runoff, and, in this scenario, the water body sediments act as a sink rather than a possible source to the system. Using the calculated results of these two scenarios, a third scenario is run as a proposed, possible sediment clean-up goal using a linear interpolation of the calculated sediment concentration and the hazard indices of the identified most sensitive species as a gauge for the proposed clean-up sediment concentration. Then, from this information, the concentrations of mercury in the water body and fish tissue are calculated, and wildlife and human hazard indices are calculated. The series of sub-modules within SERAFM include: mercury loading (watershed and atmospheric deposition); abiotic and biotic solids balance (soil erosion, settling, burial, and resuspension), equilibrium partitioning; water body mercury processes; and wildlife risk calculations.

SERAFM is solved using a steady-state assumption, therefore all differential, governing equations are solved by setting the differential to zero. Being a CSTR model, there are no required boundary or initial conditions. To solve the system of linear equations a function was written using Visual Basic for Applications (VBA) in Microsoft Excel 2003©. This is required because Microsoft Excel cannot solve a system of simultaneous, coupled equations. The specific function, called LINEAR_SOLVE, uses L-U Decomposition to solve the given linear algebra equation: A*x=b, where A is an m x n matrix, x is an n x 1 matrix, and b is an m x 1 matrix. By using a VBA function, the model predictions are updated instantaneously whenever any parameter is changed. The function was compared to analytical solutions for several test cases to validate that the function was operating properly.


Applications and Possible Uses

  • Prediction and evaluation of steady-state mercury cycling in an aquatic ecosystem consisting of a river reach or lake (stratified or well-mixed) and its associated watershed.
  • Prediction of risk (hazard indices) for wildlife exposed to a water body with mercury contaminated sediments (such as historical industrial releases).
  • Investigate impact of mercury deposition to a water body.
  • Investigate sensitivity of processes and model parameters.

Model History

SERAFM was originally developed in response to ERASC Request #10 in 2003 to address developing a remediation goal for mercury in sediments for exposed wildlife, particularly at historically contaminated sites, such as at a Superfund Site. Additionally, the application of a proprietary process-model demonstrated the need for the US EPA's own mercury process-based water body model that allowed for transparency and ease-of-use. SERAFM is designed to be self-explanatory, flexible for use in different modeling scenarios, and self-contained with modules being housed in separate worksheets linked through an entire spreadsheet workbook.

SERAFM has been used in its steady state mode for modeling current scenario conditions of mercury dynamics in five ecosystems across the US, and adapted to evaluate the temporal response of changes in mercury concentrations in support of the Clean Air Mercury Rule.


Technical Support / Training

Currently there is no planned SERAFM training. Technical questions can be made directly to the author Chris Knightes (Knightes.Chris@epa.gov)


Quality Assurance/Quality Control

SERAFM has undergone peer review both externally and internally. SERAFM has been reviewed by two USEPA federal employees as well as one academic reviewer.


Related Sites

 


References of Published SERAFM Applications and Uses

Knightes, C.D. 2007. Development and test application of a screening-level mercury fate model and tool for evaluating wildlife exposure risk for surface waters with mercury-contaminated sediments (SERAFM). Environmental Modelling & Software. 23:495-510.

Brown, S., Saito, L., Knightes, C.D., Gustin, M. 2007. Calibration and Evaluation of a Mercury Model for a Western Stream and Constructed Wetland. Water, Air, & Soil Pollution 182(1-4):275-290.

Knightes, C.D. and R. B. Ambrose. 2006. Development of An Ecological Risk Assessment Methodology for Assessing Wildlife Exposure Risk Associated With Mercury-Contaminated Sediments in Lake and River Systems. U.S. Environmental Protection Agency, Athens, GA. Publication No. EPA/600/R-06/073.

US EPA. 2005. Regulatory Impact Analysis of the Clean Air Mercury Rule. Office of Air Quality Planning and Standards, Air Quality Strategies and Standards Division. Chapter 3: Ecosystem Scale Modeling for Mercury Benefits Analysis and Appendix A: Mercury Load Reduction Analysis and Response. EPA-452/R-05-003. March.

Knightes, C.D. SERAFM: An Ecological Risk Assessment Tool for Evaluating Wildlife Exposure Risk Associated with Mercury-Contaminated Sediment in Lake and River Systems. Presented at EPA Science Forum 2005, Washington, DC, May 16 - 18, 2005.

Office of Solid Waste and Emergency Response. 2005. Human Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities. September. Chapter 2: Characterizing Facility Emissions. EPA530-R-05-006.

Brown, S. 2006. Modeling Mercury Behavior in a Contaminated Desert Stream and Constructed Wetland. M.S. Thesis. University of Nevada, Reno. February 14.


Model Download

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US EPA (2019). SERAFM Conceptual Model, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/d31ffabd-1bb4-4b77-9448-2b2b72823466
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Contributor(s)

Initial contribute : 2019-12-16

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Authorship

:  
United States Environmental Protection Agency
:  
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