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Online
Model Predicts Chemical Behaviors in the Great Lakes Environment Syracuse Research Corporation (SRC) has produced an online,
interactive modeling application for predicting the fate of chemicals within
the Great Lakes environment. The project, led by Dr. Mario Citra of SRC, set
out to produce an easy-to-use application that would allow users to determine
several important factors relating to how chemicals behave once they have been
released into the Great Lakes environment. These include:. ·
Where in the environment does the chemical tend
to accumulate (such as in water, soils, sediments, air or fish)? ·
How long is the chemical retained in the Great
Lakes environment before it degrades or is transported to another region? ·
What concentration in the environment would be
produced by a given level of emission? ·
What is the potential for a chemical to travel
to the Great Lakes region from far away? ·
And more. By providing this capability through an online interface
that is easy to access and use, the model gives users a powerful tool for
answering their questions about the behavior of a given chemical in the Great
Lakes system. The modeling program may be run with as little input as the
chemical’s Chemical Abstract Service (CAS) identification number (of
which 33 million are available) although more detailed characteristics may be input
as well. The model’s ease of use and availability over the Internet
make it a great tool for use in educational settings. While much information can be generated by the model without
specifying chemical quantities, knowing how much of a chemical is emitted into
the environment allows a user to obtain even more information, such as
predicted concentrations in air, water, soils, sediments and fish. It also
allows the user to determine the likelihood that a certain concentration known
to be a high-risk level would be exceeded. While users can enter their own
emissions information, the website also includes links to pesticide application
data from the CropLife Foundation and air emissions data from the Great Lakes
Regional Toxic Air Emissions Inventory, which together provide useful release
information on more than 350 toxic substances. While the standard version of the model provides the easiest
option for less advanced users, there is also a version that allows the use of
Monte Carlo statistical techniques to assess the uncertainty in the models
predictions. This option allows users to enter a range of possible values for
important variables, rather than entering a single value. The model then
computes the likelihood of possible outcomes given that range of inputs. For
example, rather than simply predicting that a given chemical’s
concentration in water would be 2 grams per liter, the results might say it is
90% likely that the concentration would be between 0.5 and 5 grams per liter,
with a most like value of 2. Examples are given on the model’s website to
assist users in choosing a range of values. The model is configured to represent each of the five Great
Lakes basins (Huron, Ontario, Michigan, Erie and Superior). The user is
able to choose which of these five they would like to use as the basis for the
model. The program then automatically loads the proper environmental
characteristics for that lake basin (such as area and depth of surface
water). By modeling with the same inputs but different lake basins
selected, comparisons can be made as to how chemicals might behave differently
in the different basins. Although the model allows the selection of individual
lake basins, the geography within each basin model is not specific enough to
allow release points to be defined. Rather, the air and water of each basin are
modeled as a single, well-mixed, box. While other models may be more complex or offer additional
capabilities, this modeling program has the advantage of being easy to access
and use. Potential applications include investigating the behavior of new or
unstudied chemicals; comparing emissions and monitoring data; and calculating
expected concentrations of chemicals in the environment or the likelihood that
such concentrations will exceed known risk values. It is expected to find uses
in places such as governmental agencies, research laboratories and educational
classrooms, among others. The model is available at the SRC website: http://glad.syrres.com. Additional documentation is available at: www.glc.org/glad/projects/citra06 Contact: Mario J. Citra, Syracuse Research Corporation, (315)452-8406
or citra@syrres.com Jon Dettling, Great Lakes Commission, 734-971-9135 or dettling@glc.org |