Environmental Engineering Reference
In-Depth Information
in a variety of ecosystem compartments over time (Harris
et al., 2007a). Modeling is an integral part of a national
Hg assessment because comparing and contrasting model
output and monitored data enables improved under-
standing of the exchange of Hg between reservoirs and
the important governing reactions. Global Hg models
(Selin et al., 2007; Dastoor and Davignon, 2009; Jae-
gle et al., 2009; Jung et al., 2009; Seigneur et al., 2009;
Travnikov and Ilyin, 2009) allowing assessment of the
input and export from the monitoring domain are
needed in support of regional modeling efforts (Bullock
and Jaegle, 2009; Keeler et al., 2009). Without knowl-
edge of the link between atmospheric Hg input and bio-
accumulation, the impact of changes in MeHg in fi sh in
response to changes in atmospheric inputs cannot be
properly assessed. Current atmospheric Hg models have
had some success in predicting the levels and trends
in ambient Hg levels in the atmosphere (Ryaboshapko
et al., , 2002, 2007a, 2007b; Lindberg et al., 2007), and
similarly, biogeochemical models of ecosystem cycling
of Hg and MeHg formation have been relatively success-
ful in the estimation of changes and trends (Hudson et
al., 1994; Gbondo-Tugbawa and Driscoll, 1998; Beals
et al., 2002; Roue-Legall et al., 2005; Trudel and Rasmus-
sen, 2006). However, the development of coupled atmo-
spheric and biogeochemical models for Hg is just begin-
ning, and a comprehensive research framework that
integrates observations covering a wide range of temporal
and spatial scales with modeling and process studies is
needed to support such efforts.
Although a monitoring program is primarily a data-
collection exercise, models are needed to extrapolate
between monitoring sites, to interpret data, and to criti-
cally examine the causality of the response of the indica-
tors to changes in atmospheric Hg deposition (Harris et
al., 2007a, 2007b). The models could also be used to guide
monitoring-site selection, although current efforts are
relying more on building the monitoring program around
existing sites and databases (Schmeltz et al., 2011). Aquatic
ecosystem modeling will be used to test anticipated
changes against the observed response and to ascertain
the magnitude of the response due to changes in Hg depo-
sition and allow for the exclusion or examination of the
impact of confounding factors. For example, it is entirely
possible that other factors, such as those impacting tro-
phic status and an organism's growth rate, could cause a
decrease in fi sh Hg concentrations even as atmospheric
deposition does not change. Models can be used to predict
the spatial and temporal patterns of atmospheric Hg con-
centrations and fl uxes under various future scenarios (e.g.,
Selin et al., 2008). The models could determine the relative
contributions of various sources of Hg over time, based on
emission inventories and other estimates of point source
and areal inputs, and estimate the likely Hg attenuation
rate and recovery timeline under various environmental
scenarios. Overall, models allow integration and synthesis,
and the data required to run them are a necessary part of
any monitoring plan.
Given the complexities in Hg cycling, currently no
simulation models accurately predict the response
of Hg concentrations (total or MeHg) in the various
compartments of terrestrial and aquatic ecosystems
to changes in Hg loading rates without modifi cation
of the model to a particular situation (Hudson et al.,
1994; Gbondo-Tugbawa and Driscoll, 1998; Beals et al.,
2002; Roue-Legall et al., 2005; Trudel and Rasmussen,
2006). Such models are needed in conjunction with
fi eld and laboratory studies to advance our understand-
ing of Hg cycling. Simulation models have only been
calibrated and tested against fi eld data from several
sites (e.g., Gbondo-Tugbawa and Driscoll, 1998; Beals
et al., 2002); therefore, their accuracy is limited by data
availability and by our understanding of the response
of more diverse systems. Further model development
requires the collection of specifi c fi eld data for validation.
Clearly, there is a critical need to develop models that
can reasonably simulate Hg and MeHg cycling and con-
centrations based on site characteristics and external Hg
loading.
A Mercury Monitoring Framework
As outlined and discussed in detail in the other chapters
in this topic, the link between Hg deposition and MeHg
bio-accumulation in aquatic food chains is complex and
involves many steps (Mason et al., 2005). Mercury in the
atmosphere is removed by both wet and dry deposition
to the biosphere. In surface waters, the dissolved Hg
II
spe-
cies can be reduced to Hg
0
, and if waters become satu-
rated with Hg
0
, then it is returned to the atmosphere via
evasion (Mason and Sheu, 2002). Reduction and reemis-
sion also occur in terrestrial ecosystems (St. Louis et al.,
2001; Mason, 2009). For Hg deposited to the watershed, its
route to the aquatic system is complex, and the timescale
of this pathway is not well known (Grigal, 2003). Most
of the total Hg input to watersheds remains sequestered
and is not transported to the associated aquatic system.
However, for some systems, this input is still signifi cant
as compared with direct deposition to the water surface.
The bioavailability of Hg supplied from the watershed to
methylating bacteria and the potential for reduction to
Hg
0
are still not well understood (Sellers et al., 1995; St.
Louis et al., 2001). In comparison, some research suggests
that Hg added directly to the water surface is effi ciently
transformed into MeHg and bio-accumulated (Harris et
al., 2007b). Sites of methylation are typically the upper
reaches of saturated, but anoxic, zones, such as sediments
and wetlands in both marine and freshwater ecosystems,
as the microbial communities responsible for Hg meth-
ylation are primarily sulfate-reducing bacteria (Benoit
