Great Lakes Environmental and Molecular Sciences GLEAMS Center webbased Decision Support System tool

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Great Lakes Environmental and Molecular Sciences
(GLEAMS) Centerweb-based Decision Support System
toolsfor assessing human and ecological health
risk

• MTRI
• Dr. Robert Shuchman
• Colin Brooks
• Eric Keefauver
• Ben Koziol
• Dr. Tyler Erickson

Western Michigan University Dr. Chuck Ide
www.wmich.edu/env/
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GLEAMS

• Partnership between MTRI (formerly part of
  Altarum/ERIM) and the Western Michigan University
  (WMU) Environmental Institute funded by EPA
• Address the legacy of contamination on the Great
  Lakes and their watersheds
• Help local state stakeholders understand this
  legacy
• Develop watershed-scale methods to assess and
  protect human and ecosystem health
• Used the Kalamazoo River watershed as a example
  site
• Expanded to Lower Fox River, WI (Green Bay)
• Modeled PCBs and water quality
• Added mercury and gene expression tools
• http//www.greatlakesdecisionsupport.org
• Science
• GIS
• Modeling
• Outreach
• Great Lakes information

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Example Decision Support System (DSS) Scenarios

• You live in Allegan, Michigan, near the Kalamazoo
  River
• Member of a local watershed group trying to
  understand risks
• A community leader helping local citizens
  understand impacts of the legacy of pollution
• Another audience Person working on fish
  consumption guidelines
• Where are the risky areas? What are the risks?
• Kalamazoo River PCBs
• Used MDEQ reports for assessing risk
• Baseline Ecological Risk Assessment (263 pages)
• Human Health Risk Assessment (169 pages)

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Food Web Modeling for PCB bioaccumulation
mink
eagle
human
Predators
bass
carp
Consumers
benthic invertebrates
algae
Source
sediment
surface water
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Start River basin
Dams
Paper Companies
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Interpolated polygons
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Sample at that location
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Accumulation in fish
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Accumulation in people
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Modeling cleanup scenarios

• Cleanup scenario
• Sediment concentration reduced 80
• Calculate effect on health risk
• Cancer risk down to 1.3 / 100,000

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Integration WMUs gene and protein expression
research results into a mapping interface

• Display areas where PCB contamination has cause
  gene or protein damage in carp
• Label with levels of gene/protein expression
• Allow users to query data, find out more about
  variables
• Help page on GLEAMS portal discussion research
• Gene protein expression another way of
  expressing risk
• Working closely with Chuck Ide

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mRNA Gene Expression DSS Tool
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Protein DSS Tool
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ALWAS
Automated Lagrangian Water Quality Assessment
System
ALWAS is an inexpensive, automated,
free-floating, sail-powered or jet-driven water
quality measuring and watershed evaluation
system. It is capable of making a wide range of
measurements, as rapidly as every 40 seconds.
Data can be transmitted in real-time or stored
for later retrieval and analysis.

• Water Properties, including
• Temperature
• Barometric Pressure
• Conductivity / Salinity
• Dissolved Oxygen
• pH
• Turbidity
• Depth
• Oxidation-Reduction Potential
• Chlorophyll-a
• Blue-Green Algae

• GPS Data, including
• Geographic location
• (Latitude and longitude)
• Speed and Heading
• Quality metric
• Number of visible satellites
• Time and date

ALWAS deployed along Kalamazoo River

• Optional Measurements
• Nitrates
• Ammonium
• Chlorides

ALWAS Software allows for -Real-time wireless
data transmission at over a distance of 1
mile. -Automatic data download to a geographic
database (ESRI shapefile) and Excel
spreadsheet. -GIS mapping capabilities
Example of ALWAS Data.
For more information, please contact Robert
Shuchman at 734.649.0937 or shuchman_at_mtu.edu
Patent Pending
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ALWAS Kalamazoo sites2004 2006

• Calculate National Sanitation Foundation Water
  Quality Index (WQI)
• User-friendly explanation of WQI available at
  http//www.nsf.org/consumer/just_for_kids/wqi.asp

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ALWAS DSS Mapping water quality

• Water Quality Index calculated at sample points
  along the river using ALWAS data as the input

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ALWAS WQI DSSdemonstrating WQI scenarios
WQI for drinking water emphasis on low
turbidity, neutral pH
WQI for habitat emphasis on temperature, pH, DO
WQI for recreation emphasis on depth,
temperature, pH

• Different WQI decision support scenarios can be
  modeled with GLEAMS WQI tool

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ALWAS example 9/2006 data for Maple Riverand
WQI calculation
Dissolved oxygen (gt 7 mg/L state standard)
pH 6.5 8 desirable
Turbidity (gt5 NTU problematic drinking H20 state
std.)
Derived WQI

• All areas had a WQI of 60-80, in the Good range
• 0-20 poor, 20-40 fair, 40-60 average, 60-80 good,
  80-100 excellent

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Equivalent tools for mercury predict human
health risk using GIS data models

• Goal Develop a tool to help users understand if
  local fish consumption is likely to lead to
  mercury exposure above EPA reference doses, esp.
  for women of 18-45, using spatial sediment data
  as starting point
• Used documented Wisconsin DNR Lower Fox River
  database
• Capture complexity of modeling health risk from
  mercury in a valid user-friendly on-line
  mapping interface
• Enable user interaction, selection of scenarios
  help community members to understand level
  locations of risks

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The Complexity of Mercury Modeling

• Most common aquatic mercury chemical species
• Elemental, inert (Hg0)
• Divalent, reactive (Hg2)
• Organic (MeHg)
• The first two, non-biologically available forms
  (elemental and divalent) are the most common
  often accounting for greater than 90 of total
  environmental mercury.
• Opposite is true for biological uptake gt 90 of
  tissue-bound mercury is MeHg
• Mercury methylation typically occurs in the
  inactive, anoxic sediment layer of lakes and
  streams regulated by sulfide concentration,
  sulfate-reducing bacteria, pH, DOC/TOC, and
  temperature.
• Mercury speciation model incorporates
  hydrodynamics as well as chemical kinetics to
  track speciation
• Challenge is the static methylation,
  demethylation, oxidation, and reduction rates
  which are variable and influenced by the
  properties listed above
• Another challenge is models do not currently
  enable mercury to move between finite elements.
  Hence, it is important to note that the
  speciation model is derived from a finite
  element model
• Bioaccumulation modeled using a generalized
  hydrophobic bioaccumulation model.
• Wide species applicability and simplified
  calibration procedure
• Challenging to incorporate the effects of weight
  and age, highly sensitive to changes in
  bioconcentration factor
• Human Health
• Two methods to assess health risks. Both
  originate from EPA recommendations
• RfD (reference dose) ? acceptable blood mercury
  level that can be physiologically maintained
  resulting in no noticeable health effects ?
  0.0001 mg MeHg/kg body weight-day (female and
  children), 0.0003 (male)
• TRC (tissue residue criterion) ? fish tissue
  concentration that when consumed will not result
  in a RfD above the recommended value
• A simple calculation involving body weight,
  dietary intake, and fish tissue concentration

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Generalized Mercury Model Diagram
Elemental - Divalent - Organic (methyl)
Elsayed, N.B. 2002. A finite element model of
mercury species fate in the Detroit River water
column and sediment. Dissertation. Wayne State
University, Detroit, MI. EPA Water Quality
Criterion. 2001. Water Quality Criterion for the
Protection of Human Health Methylmercury. Office
of Science and Technology, Office of Water. U.S.
Environmental Protection Agency. Washington, D.C.
EPA-823-R-01-001. Fox River Food (FRFood) Model.
2001. Fox River Food (FRFood) Model
Documentation Memorandum, Lower Fox River,
Wisconsin Remedial Investigation and Feasibility
Study. ThermoRetec Consulting Corporation.
Prepared for Wisconsin Department of Natural
Resources. SERAFM. 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,
Office of Research and Development. Washington,
D.C. EPA-600-R-063-073. (Recommended by Dr.
Elsie Sunderland, EPA ORD, Boston)
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Example Data
1998 Mercury sediment concentrations from WDNR
Low Fox River Environmental Information
Management System (Jeff Kreider)
Predicted Fish Tissue Concentration (mg MeHg/kg
fish)
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Example Health Risk Scenarios

• Scenarios can be run under different
  bioconcentration levels to incorporate
  uncertainties associated with fish ecology (e.g.
  unconstrained movement ranges, size variability,
  age, etc.).
• Bioconcentration factors were calibrated to in
  situ fish tissue concentrations using a Monte
  Carlo-based optimization procedure.
• The range of bioconcentration factors allows
  the food web model to demonstrate a valid range
  of concentration predictions.
• Final integration with the Fox River GLEAMS IMS
  site is being completed this month info below
  through a mapping (DSS) interface

Weight (kg) / age / RefDose (mg MeHg/kg)
BioConc. Level / Typical Consumption / High
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Mercury Tool Demo Querying data through tool
for Lower Fox River
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Mercury Tool Demo Bioaccumulation levels in fish
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Mercury Tool DemoAre the risk criteria exceeded?
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GLEAMS Portal - DSS link
Contact info Colin Brooks Environmental Sciences
Lab Manager / Research Scientist Michigan Tech
Research Institute 3600 Green Court, Suite
100 Ann Arbor, MI 48105 colin.brooks_at_mtu.edu Ph
734-913-6858 Fax [phone] Robert
Shuchman 734-913-6860 shuchman_at_mtu.edu Chuck
Ide 269-387-5951 charles.ide_at_wmu.edu

• GLEAMS Portal www.greatlakesdecisionsupport.org
• WMU Environmental Institute www.wmich.edu/env/
• MTRI www.mtri.org