Technical Support Document 

Revision of December 2000 Regulatory Finding on the Emissions of Hazardous Air 

Pollutants From Electric Utility Steam Generating Units and the Removal of Coaland Oil-Fired Electric Utility Steam Generating Units from the Section 112(c) List: 

Reconsideration

October 21, 2005
1

Technical Support Document 

Revision of December 2000 Regulatory Finding on the Emissions of Hazardous Air 

Pollutants From Electric Utility Steam Generating Units and the Removal of Coaland Oil-Fired Electric Utility Steam Generating Units from the Section 112(c) List: 

Reconsideration

Section 1. Introduction 

Section 2. Marine (Open Ocean) Cycling 

Section 3. Utility Attributable Mercury in Marine Seafood Diet 

Section 4. Near-Shore Exposure Pathway 

Section 5. Aquaculture Exposure Pathway 

Section 6. Commercial Freshwater Pathway 

Section 7. Joint Consumption 

Section 8. Health Benefits and Costs 

Section 9. Evaluation of NESCAUM Report 

Section 10. 2010/2015 CMAQ Modeling Results 

Section 11. Global Source Impact 

Section 12. References

1. Introduction 

In the Technical Support Document (Effectiveness TSD) for the Revision of 

December 2000 Regulatory Finding on the Emissions of Hazardous Air Pollutants From 

Electric Utility Steam Generating Units and the Removal of Coal- and Oil-Fired Electric 

Utility Steam Generating Units from the Section 112(c) List (Revision Rule)(US EPA 

2005a) the Agency analyzed the mercury (Hg) exposure due to coal-fired electric utility 

steam generating units (“power plants” or “utilities”) as defined in the Revision Rule 

remaining after implementation of the Clean Air Interstate Rule (CAIR) and after 

implementation of both CAIR and the Clean Air Mercury Rule (CAMR). This analysis 

included a partly quantitative, partly qualitative treatment of the exposure from 

recreational and subsistence caught freshwater fish. Other pathways including 

commercial freshwater fish, estuarine fish, and marine fish were treated qualitatively. 

The quantitative component of the analysis focused on the recreational and 

subsistence freshwater fish pathway because, as described below, it is this pathway that 

leads to the greatest individual exposure due to utility-attributable mercury emissions. 

Based on a qualitative analysis, EPA concluded that the other pathways lead to smaller 

individual exposure levels and that the combined exposure from all the pathways would 

not be materially different than the exposure due solely to the recreational/subsistence 

fish pathway for the individuals most highly exposed to utility-attributable mercury. See 

70 FR at 16,102. 
2

This document expands on information presented in the Revision of December 

2000 Regulatory Finding on the Emissions of Hazardous Air Pollutants From Electric 

Utility Steam Generating Units and the Removal of Coal- and Oil-Fired Electric Utility 

Steam Generating Units from the Section 112(c) List: Reconsideration regarding the 

Agency’s assessment of utility attributable mercury concentrations in commercial 

freshwater fish, aquaculture, estuarine fish, and marine fish exposure pathways, including 

why EPA believes these pathways are not reasonably anticipated to result in a hazard to 

public health after reductions in power plant emissions due to CAIR and, independently, 

CAMR.

2. Marine (Open Ocean) Cycling 

The inclusion of the exposure pathway associated with marine (open ocean) fish 

in the original freshwater quantitative analysis supporting the Revision Rule does not 

materially change the results because the impact of power plant emissions on mercury 

concentrations in open ocean environments is limited. First, over half of the U.S. 

commercial fish supply is imported. Second, the majority of domestic commercial fish is 

caught in open ocean regions that have not been impacted by anthropogenic mercury 

releases to the same extent as the atmosphere, near-shore, or inland systems. This means 

that current fish tissue concentrations likely do not reflect present day atmospheric 

mercury concentrations or deposition rates (Mason and Gill, 2005; Kraepiel et al., 2003). 

EPA could not support extension of the Mercury Maps freshwater modeling framework 

to marine systems. Application of the Mercury Maps model to marine environments 

would be an extension of the modeling framework beyond the realm for which it was 

intended for application and has not been empirically evaluated. The power plant 

contribution to mercury in these fish (discussed in more detail below) is difficult to 

quantify with confidence at this time and is expected to be relatively small in pelagic 

marine species based on the analysis described below. 

Predatory marine fish are a significant source of methylmercury exposure for the 

U.S. population (Carrington et al. 2004). Exposure is a function of both the amount of 

mercury in fish and the quantities of fish consumed in the U.S. High levels of 

methylmercury in fish are generally the result of bioaccumulation in larger, older fish. 

In the case of marine fish, higher trophic level species tend to have comparable 

concentrations to top predators in freshwater ecosystems. In addition, the quantities of 

marine fish consumed by humans are larger than the quantities of freshwater fish. Based 

on the rationale described in detail below, EPA expects that utility-attributable mercury 

in these fish is a small fraction of their overall burden. 

It is extremely difficult to determine the response of oceans to changes in mercury 

emissions from human sources due to limited scientific understanding at this time. 

However, the best available science suggests that the significance of changes in marine 

fish mercury concentrations in response to reductions in power plant Hg emissions will 

be small and will require on the order of decades to centuries to be achieved. To further 

elucidate our rationale, we present the results of a sensitivity analysis below that shows 

the relative importance of changes in present day atmospheric deposition on the 
3

magnitude and timing of changes in ocean mercury concentrations in the Atlantic and 

Pacific Oceans. 

In the original analyses supporting the final Section 112 rule, EPA quantified 

reductions in methylmercury concentrations in freshwater fish associated with declining 

inorganic mercury emissions from coal–fired utilities but concluded that the science of 

Hg cycling in marine systems is not sufficiently advanced to allow for a similar 

quantification of this exposure pathway. Other studies (NESCAUM 2005, Trasande et al. 

2005) that did quantify the marine exposure pathway used assumptions for a central 

tendency estimate that are not supported by the literature on marine fate and transport of 

Hg, likely resulting in an overestimate of the power plant contribution to marine fish by 

an unknown but possibly large amount. We briefly discuss some of the assumptions of 

the NESCAUM report as they relate to marine fish in Section 9. 

When quantifying the relationship between power plant mercury emissions in 

deposition over coastal and marine areas the NESCAUM study relied on the REMSAD 

model, which appears to over-predict Hg deposition from US power plants. Next, using 

the approach applied in NESCAUM study for marine systems would require an 

additional assumption that present day concentrations in the surface ocean are tracking 

changes in atmospheric concentrations and deposition. This premise is not supported by 

the screening analysis detailed below for marine systems. The proportionality 

assumption is also not applicable for coastal ecosystems with significant riverine inputs 

or watershed areas (most coastal systems). 

One of the greatest uncertainties in coastal and marine systems is the rate and 

location of methylmercury formation. This is important because methylmercury 

formation rates determine bioavailability to fish and shellfish. The NESCAUM study 

assumed that changes in methylmercury concentrations in marine fish would be 

proportional to changes in deposition of (inorganic) mercury and surface water mercury 

concentrations. This actually embodies two assumptions – 1) changes in the surface 

water concentration of total mercury are proportional to changes in the air deposition of 

mercury and 2) changes in the methylmercury concentration in fish are proportional to 

the concentration of total mercury in the water. The literature offers no clear-cut 

guidance on how to address the second assumption. However, irrespective of this 

relationship between total Hg in water and MeHg in fish, the assumption of 

proportionality (first assumption) between changes in deposition and concentrations of 

Hg in the surface ocean is not consistent with some basic physical oceanographic 

principles that determine the magnitude and reservoir of Hg in the world’s oceans. For 

example, a number of studies have measured large fluxes of mercury lost through gas 

exchange (volatilization) at the ocean surface (Amyot et al., 1997, Mason et al., 2001, 

Rolfhus and Fitzgerald, 2004). In addition, monitoring data indicate that concentrations 

of mercury in surface waters among the different oceans are not equal, and that deep 

ocean water concentrations are very low and likely unaffected by anthropogenic mercury 

(Gill and Fitzgerald, 1988, Mason and Sheu, 2002, Laurier et al., 2004). This means that 

the large flows of ocean waters (laterally among oceans, oceanic upwelling and deep 

water formation) will dilute or add (depending on the flow) to the existing mercury in 
4

surface waters. A conceptual model of the various inputs and outputs of mercury, in 

addition to atmospheric deposition, is shown in Figure 2-1. A sensitivity analysis 

illustrating the magnitude of this uncertainty is presented below. 

EVASION ATMOSPHERIC 

DEPOSITION

RIVERS

LATERAL 

OCEAN 

FLOW

RESERVOIR 

Mw = CwVw

MARINE BOUNDARY LAYER Cair

DEEP WATER 

FORMATION

PARTICLE

SETTLING

kv

kO1

kO2

kp

Figure 2-1. Conceptual model of mercury cycling in the surface waters of the 

Atlantic Ocean. Inputs are shown as blue arrows and outputs in grey arrows. The 

concentration of mercury in surface waters will be a function of the combined inputs and 

losses of mercury over time, with atmospheric deposition representing only one 

component of the overall flux of mercury. 

Even if a proportional relationship between U.S. utility-attributable mercury 

deposition and marine methylmercury fish tissue concentration were a reasonable 

representation of the science, the saltwater species would nevertheless contribute only a 

very small amount of dietary utility attributable mercury because of the small 

contribution of the power plant emissions to the global pool. Annual emissions of 

mercury from U.S. utilities account for about 1.0 percent of total global emissions 

(including natural and recycled mercury). The total global emissions is estimated to be 

between 4400 and 7500 tonnes (US EPA 1997a), while total anthropogenic Hg emissions 

were approximately 2269 tonnes per year in 2001 (Pacyna and Munthe 2004). Overall, 

anthropogenic emissions from all sources in the United States still comprise less than 3 

percent of the global total (UNEP 2002). Even in coastal environments where EPA’s 

deposition models suggest that there is a higher contribution of Hg deposition by U.S. 

power plants, particularly the Atlantic and Gulf Coast area, the utility-attributable 

contribution to human mercury exposure in these regions is thought to be small as 

explained below. 
5

2.1 Model of Mercury Cycling in World’s Oceans 

Modeling the effect the reduction in Hg deposition from U.S. power plants would 

have on Hg concentration in ocean fish is complicated by non-linear relationships 

between changes in human emissions, atmospheric Hg deposition over the oceans, water 

column concentrations and fish Hg concentrations. In contrast to freshwater systems, 

there is a paucity of field data on factors controlling MeHg formation and concentrations 

in marine environments and it is not clear where the majority of methylation occurs in the 

ocean (see review by Mason and Gill, 2005). 

Mason and Sheu (2002) suggest that Hg in the ocean has only increased by 9 

percent relative to pre-industrial levels even though air releases have more than doubled. 

Several revisions to this estimate, including Mason and Gill (2005), have suggested a 

larger anthropogenic contribution to mercury in the world’s oceans of up to 60 percent in 

the Atlantic. This can be compared to the average global enrichment of the atmosphere 

which is between 200-500 percent. These revised estimates all support the premise that 

surface ocean concentrations are not tracking atmospheric deposition. Further supporting 

this premise are empirical data from the Pacific Ocean for water column mercury 

concentrations (Laurier et al., 2004) and tuna (Krapiel et al., 2004), which show no 

significant differences in concentrations over the last 20-30 years. Presently, there are no 

data to support the assumption that atmospherically deposited Hg would be preferentially 

converted to MeHg relative to the large reservoir of legacy Hg in marine environments. 

This preferential conversion would be one condition needed to achieve the assumed nearinstantaneous proportional reduction in marine species MeHg concentrations described in 

the NESCAUM study. Based on this information, EPA concludes that the linear approach 

employed in the NESCAUM study will likely lead to a significant overestimation of 

utility attributable exposure and an even greater overestimation of the benefits of 

reducing power plant emissions. 

At this time there are insufficient empirical and mechanistic data on the rate and 

location of MeHg formation in marine environments to constrain a detailed predictive 

model for MeHg cycling and accumulation in fish in the open ocean. However, for the 

purposes of developing a comparable quantitative model to the NESCAUM report and to 

provide a sensitivity analysis, EPA has adapted a recent modeling approach by Mason (in 

review) with results discussed in Mason and Gill (2005). This adapted model is used to 

investigate the influence of changing atmospheric deposition rates resulting from control 

of coal-fired utilities on concentrations of total Hg in the open ocean water. EPA 

recognizes that this assumption is a simplification of Hg bioaccumulation in marine 

environments and must be viewed as a preliminary assessment of the potential response 

of marine environments to changes in atmospheric Hg deposition and must be interpreted 

with caution. 

We selected the model approach discussed in Mason and Gill (2005) to describe 

Hg cycling in marine environments because it represents the interconnectedness of the 
6

different oceans through lateral transport of surface waters, upwelling, and deep-water 

formation in the North Atlantic. The model is based on the 16-box model for the world’s 

oceans published by Kahana, et al. (2004) (see Figure 2-2). Kahana et al.’s model is an 

expanded version of Stommel’s pioneering box model (Stommel, 1961), which originally 

described ocean circulation as a function of salinity and temperature. Inputs of Hg from 

major rivers globally are characterized using concentrations data from Cossa, et al. 

(1996), and flux data from the National Center for Atmospheric Research (NCAR) 

website (www.cgd.ucar.edu/cas/catalog/dai/runoff-table2-top50r.html). Losses of Hg 

through particulate settling and evasion are characterized using mercury-to-carbon 

(Hg:C) ratios for different oceans described in Mason, et al. (1994), and empirically 

measured values for different oceans, respectively. Overall, fluxes are constrained using 

empirical data on measured fluxes in each compartment and the Mason and Sheu (2002) 

global budget. Atmospheric deposition for each ocean was estimated from measured wet 

deposition rates over the oceans from existing data at that time, developed by Mason, et 

al. (1994), and revisited for the Mason and Gill (2005) analysis to update estimated dry 

deposition based on gradients in total gaseous mercury (TGM) concentrations in the 

marine boundary layer (MBL). 

300 m

1500 m

4000 m

0.75 pM

0.9 pM

16 Mmol

0.9 pM

2.5 pM

4 Mmol

1.5 pM

161 Mmol

1.25 pM

56 Mmol

1.25 pM

74 Mmol

1.2 pM

365 Mmol

1.0 pM

2.0 pM

52 Mmol

DEEP

NA

Pacific-Southern 

Ocean loop

The Agulhas rings

Antarctic 

Overturning

2.0 pM

24 Mmol

Bottom flow into the Atlantic

North 

Atlantic 

overturning

Atlantic/

Mediterranean 

exchange

300 m

1500 m

4000 m

0.75 pM

0.9 pM

16 Mmol

0.9 pM

2.5 pM

4 Mmol

1.5 pM

161 Mmol

1.25 pM

56 Mmol

1.25 pM

74 Mmol

1.2 pM

365 Mmol

1.0 pM

2.0 pM

52 Mmol

DEEP

NA

Pacific-Southern 

Ocean loop

The Agulhas rings

Antarctic 

Overturning

2.0 pM

24 Mmol

Bottom flow into the Atlantic

North 

Atlantic 

overturning

Atlantic/

Mediterranean 

exchange

Figure 2-2. Conceptual model of the major oceanic circulation patterns adapted 

from Kahana et al. (2004). Also shown are average mercury concentrations (pM) and 

reservoirs (Mmol) of mercury in each of the ocean compartments based on the data and 

model discussed in Mason and Gill (2005). 

Advantages of this adapted modeling approach compared to previously published 

models of Hg cycling in the oceans include: 

1. The model treats different oceans and well-mixed components of these oceans 

in a discrete manner and constrains concentrations and fluxes using the most recent fielddata. 
7

2. The model is based on a simplified oceanographic model allowing for various 

depths of the mixed layer determined by the locations of the permanent thermoclines in 

each ocean rather than assumption of 100 meter mixed layer for all oceans. This is 

important because it determines the reservoir of mercury present in each ocean and 

affects the temporal responses of each ocean to changes in deposition. 

3. The model includes empirically based fluxes of Hg through evasion from 

surface waters, particulate settling and riverine inputs as well as advection resulting from 

major ocean circulation patterns. 

To model the potential response of marine fish to changes in Hg deposition resulting 

from the power plant regulation the following assumptions are necessary: 

1. Change in fish mercury concentrations will be proportional to the change in total 

mercury concentrations in the water column. 

2. Power plant regulation will not significantly affect ocean concentrations other than 

the Surface Atlantic and North Pacific. This means that we are assuming utility 

attributable mercury in the U.S. will not significantly change concentrations of 

mercury in other oceans (e.g., Antarctic and Indian Oceans, etc.) 

3. Rate constants describing the various inputs and outputs of mercury in surface 

waters (see Figure 2-1) can be reasonably characterized using available empirical 

data on measured mercury fluxes. Note that the NESCAUM modeling approach 

did not use rate constraints because it assumes that any change in ocean mercury 

concentrations will be proportional to changes in atmospheric deposition. 

Table 2.1 Comparison of major assumptions used in NESCAUM analysis to this 

analysis based on Mason and Gill (2005) 

Study Characteristics NESCAUM 

Analysis 

This 

Analysis 

Assume equilibrium between Hg in the ocean and 

atmospheric Hg deposition 

Yes No 

Assume change in total mercury concentration in the water 

is proportional to change in atmospheric mercury deposition 

Yes No 

Based on oceanographic circulation data (e.g., to 

characterize depth of well-mixed surface waters impacted 

by atmospheric deposition) 

No Yes 

Evasion of Hg0

, particulate transport, lateral advection of 

water (inputs and outputs of Hg), deepwater formation, 

upwelling included explicitly in model 

No Yes 

Assumes change in methyl mercury concentration in fish is 

proportional to change in total mercury concentration in 

water 

Yes Yes 

2.2 Results of Ocean Model Sensitivity Analysis 
8

Results for EPA’s sensitivity analysis are presented in tables 2.2 and 2.3. The 

adapted marine cycling model was first run to reflect steady state conditions in both 

ocean compartments (Atlantic and Pacific). The empirically constrained fluxes of 

mercury for both oceans indicate that neither ocean is currently at steady state. This can 

be seen in Figures 2-3 and 2-4 by virtue of the fact that adding all the input and output 

fluxes results in a net loss of mercury in the Atlantic and a net gain of mercury in the 

Pacific 

We can also use the empirical data to estimate the time needed to reach steady 

state in each ocean by calculating the sum of rate constants describing inputs and losses 

of mercury to each ocean. Rate constants were calculated by dividing the empirically 

constrained fluxes by the total reservoir of mercury in each ocean compartment. Using 

this methodology, the Atlantic Ocean is expected to reach steady state (ocean 

concentrations reflect present atmospheric deposition) in approximately 3 decades with 

on the order of a seven percent decline in fish mercury concentrations (Figure 2-3). The 

North Pacific has a somewhat larger reservoir of mercury and a deeper mixed layer (see 

Figure 2-2 and 2-4). Thus, the time to steady state (ocean concentrations reflect present 

atmospheric deposition) for the North Pacific is on the order of 2 centuries and results in 

a ten percent increase in mercury in fish if all other factors are constant. Note that these 

calculations assume no changes in mercury inputs over time (i.e., present conditions 

remain constant). 

Baseline Scenario Surface Atlantic

Marine Boundary Layer

Well-Mixed 

Surface Waters

300 m

2.48 Mmol/yr -2.17 Mmol/yr

-0.01 Mmol/yr

Sfc. Med. 

TGM = 1.75 ng/m2

0.50 Mmol/yr

Rivers

(CR=30 pM)

Particle 

Settling

-0.59 Mmol/yr

Upwelling 

Intermed. 

Atlantic

(Cw = 1.5 pM)

0.32 Mmol/yr

24.0 Mmol

Cw = 2.0 pM

Vw = 1.2 x 10 NA 6 m3

Deepwater

Form.

-1.13 Mmol/yr

0.32 Mmol/yr

Surface 

Antarctic

(Cw = 0.9 pM)

Figure 2-3. Model of mercury inputs and outputs in the surface Atlantic Ocean 

based on data from Mason and Gill (2005) and Mason (2005). 
9

Baseline Scenario North Pacific

Marine Boundary Layer

Well-Mixed 

Surface Waters

1500 m

1.33 Mmol/yr -1.13 Mmol/yr

-0.47 Mmol/yr

SPI 

TGM = 1. 50 ng/m2

0.14 Mmol/yr Rivers

(CR=30 pM)

Particle 

Settling

-0.05 Mmol/yr

Upwelling Deep 

Pacific & Indian

(Cw = 1.0 pM)

0.38 Mmol/yr

73.8 Mmol

Cw = 1.25 pM

Vw = 5.9 x 106 m3

Figure 2-4. Model of mercury inputs and outputs in the North Pacific based on 

data from Mason and Gill (2005) and Mason (2005). 

After running the model to steady state, a baseline scenario was developed to 

explore the potential contributions of utilities to the Atlantic and Pacific oceans. To do 

this, mercury inputs from atmospheric deposition were adjusted by the relative change in 

deposition forecasted in nearshore areas using the CMAQ model after power plant 

emissions are removed (2 percent in the Atlantic and 0.65 percent in the North Pacific). 

Because the changes in atmospheric deposition were taken from nearshore rather than 

offshore areas, they represent an upper bound for changes in deposition that might be 

attributable to U.S. coal fired utilities. In addition, changes in deposition resulting from 

the power plant regulation could also affect river inputs of mercury from North America 

to the Atlantic and Pacific Oceans. However, these changes are likely to be relatively 

small given the dominance of freshwater inputs to the ocean basins from South America 

and European rivers relative to North America. Such potential changes in river mercury 

concentrations have not been quantified at this time; thus, for the purposes of the 

sensitivity analysis we explore a range of reductions in riverine mercury inputs between 

zero and two percent. The upper bound of this analysis is likely a significant 

overestimate of potential changes in riverine mercury inputs to the oceans and should be 

caveated appropriately. As a sensitivity analysis, we also explore a range in potential 

atmospheric reductions associated with removal of U.S. utilities as a source of mercury. 

In the Atlantic ocean the range in atmospheric reductions explored is 0.5 percent and for 

the North Pacific it is 0.1 to 1 percent. 
10

Table 2.2 Sensitivity analysis for the Atlantic Ocean to assess potential change in 

mercury concentrations in marine fish observed at steady state as the result of 

control of power plant emissions. Note that changes are expressed as a fraction of 

the current fish mercury concentration. The top row shows a hypothetical, upper 

bound range for the change in mercury concentrations in riverine inputs to the 

ocean, the left column indicates the decrease in atmospheric deposition of mercury. 

 Hypothetical Decrease in Hg River Inputs 

 0.0% 0.5% 0.7% 1.0% 1.5% 1.8% 2.0%

0.5% -0.3% -0.4% -0.4% -0.5% -0.5% -0.6% -0.6%

1.0% -0.7% -0.8% -0.8% -0.8% -0.9% -0.9% -1.0%

1.5% -1.0% -1.1% -1.1% -1.2% -1.2% -1.3% -1.3%

2.0% -1.4% -1.4% -1.5% -1.5% -1.6% -1.6% -1.6%

2.5% -1.7% -1.8% -1.8% -1.9% -1.9% -2.0% -2.0%

3.0% -2.1% -2.1% -2.2% -2.2% -2.3% -2.3% -2.3%

3.5% -2.4% -2.5% -2.5% -2.5% -2.6% -2.6% -2.7%

4.0% -2.7% -2.8% -2.8% -2.9% -2.9% -3.0% -3.0%

Hypothetical 

Decrease in 

Hg 

Deposition* 

5.0% -3.4% -3.5% -3.5% -3.6% -3.6% -3.7% -3.7%

*

Note that the ranges in atmospheric deposition used above are meant to explore the 

sensitivity of model forecasted water/fish mercury concentrations to changes in 

atmospheric deposition. EPA’s analysis indicates that a 1% change in atmospheric 

deposition over the Atlantic Ocean is a reasonable upper bound for changes in 

atmospheric deposition resulting from reductions in utility emissions (see Section 3).
11

Table 2.3 Sensitivity analysis for the North Pacific to assess potential change in 

mercury concentrations in marine fish observed at steady state as the result of 

control of power plant emissions. Note that changes are expressed as a fraction of 

the current fish mercury concentration. The top row shows a hypothetical, upper 

bound range for the change in mercury concentrations in riverine inputs to the 

ocean, the left column indicates the decrease in atmost pheric deposition of mercury.

 Hypothetical Decrease in Hg River Inputs 

 0.0% 0.1% 0.2% 0.3% 0.4% 0.5% 1.0%

0.1% -0.1% -0.1% -0.1% -0.1% -0.1% -0.1% -0.1%

0.2% -0.1% -0.1% -0.1% -0.2% -0.2% -0.2% -0.2%

0.3% -0.2% -0.2% -0.2% -0.2% -0.2% -0.2% -0.3%

0.4% -0.3% -0.3% -0.3% -0.3% -0.3% -0.3% -0.4%

0.5% -0.3% -0.4% -0.4% -0.4% -0.4% -0.4% -0.4%

0.6% -0.4% -0.4% -0.4% -0.4% -0.5% -0.5% -0.5%

0.7% -0.5% -0.5% -0.5% -0.5% -0.5% -0.5% -0.6%

0.8% -0.6% -0.6% -0.6% -0.6% -0.6% -0.6% -0.6%

0.9% -0.6% -0.6% -0.7% -0.7% -0.7% -0.7% -0.7%

Hypothetical Decrease in 

Hg Deposition 

1.0% -0.7% -0.7% -0.7% -0.7% -0.7% -0.7% -0.8%

2.3 Conclusions regarding Ocean Mercury Cycling 

In summary, empirical data suggest that oceans are not at steady state. The 

analysis described above suggests that the Atlantic Ocean can be expected to reach steady 

state in approximately 3 decades if atmospheric deposition were to be held constant, 

while the North Pacific may take 200 years or more to reach steady state if atmospheric 

deposition were to be held constant. In addition, if all other environmental factors remain 

the same, our sensitivity analysis suggests that at steady state mercury concentrations will 

decline by approximately 7% in the Atlantic and increase by slightly more than 10% in 

the Pacific. This is consistent with observed declines in anthropogenic emissions in 

North America over the past several decades and increasing emissions from Asian 

countries affecting the Pacific Oceans (see Mason (2005) for more information). In both 

areas, EPA expects that for a given decrease in deposition, the decrease in fish tissue 

concentration will be less than the decrease in deposition (i.e., linear assumption is an 

overestimate). Furthermore, EPA believes that there is currently not enough information 

to conduct a quantitative assessment of the central tendency of the impact of changes in 

emissions from power plants on changes in marine fish Hg concentrations. Because of 

the inherent uncertainties in some of our assumptions and calculations presented above, 

we do not link the sensitivity analysis calculations presented above to the human 

exposure scenarios discussed in section 3 (below). Instead we use the results of the 

sensitivity analysis to aid in interpreting the results of the following sections. 

3. Utility-Attributable Mercury in Marine Seafood Diet 

EPA does not believe that there is a proportional relationship between air 

deposition and MeHg concentrations in marine fish tissue. In fact, as stated in Section 2, 
12

EPA expects that for a given decrease in deposition, the decrease in fish tissue 

concentration will be less than the decrease in deposition. However, due to the scientific 

uncertainty on this point, EPA feels that it is not appropriate at this time to use the results 

from Section 2 to create IDI values for marine fish. Instead, we conduct a bounding 

analysis of the utility attributable mercury in marine fish assuming a proportional 

relationship between utility-attributable mercury deposition decreases and MeHg fish 

tissue concentration. This is the same assumption as was used for the self-caught 

freshwater analysis and, for reasons stated in the Section 2, this likely overstates the 

utility-attributable contribution. Even with this upper bound assumption, the marine fish 

pathway results in only a small contribution to methylmercury consumption due to the 

small contribution of the U.S. power plant emissions to open ocean environments. 

While the EPA CMAQ model does extend into the Atlantic and Gulf Coast 

region, and could potentially be used to determine the utility-attributable portion of 

mercury deposition in 2020 after the implementation of CAIR, the modeled deposition in 

the open ocean region is quite small. Using CMAQ would indicate that the average postCAIR utility attributable portion for the Atlantic and Gulf Coast Ocean in 2020 would be 

less than one percent. Another measure of open ocean mercury deposition may be drawn 

from the U.S. power plant contribution to the total global mercury pool. U.S. 

anthropogenic Hg emissions are estimated to account for roughly three percent of the 

global total, and emissions from the U.S. power sector are estimated to account for about 

one percent of total global emissions (US EPA 1997a). Since both estimates are in the 

range of one percent, EPA believes that changes in power plant Hg emission in this rule 

will have a very small impact through this exposure pathway. 

3.1 Index of Daily Intake for Average Seafood Consumption by the General U.S. 

Population 

In order to describe the utility-attributable portion of Hg in the typical seafood 

diet, we used the Index of Daily Intake (IDI) values, as was described in the 

Effectiveness TSD (U.S. EPA, 2005a). The IDI is an index of exposure to Hg due solely 

to power plants. An IDI of 1 or greater indicates that an individual exposure to mercury 

from power plants is equal to or exceeds the EPA reference dose (RfD) for mercury due 

solely to utility-attributable mercury exposure. 

This index uses the RfD for Hg of 0.1 microgram per kilogram body weight per 

day (ug/kg-bw/day) as a reference point. The IDI is defined as the ratio of exposure due 

solely to power plants divided by the reference dose. The Hg exposure due solely to 

power plants is calculated as 

Equation 3.1: Exposure due to power plants 
13

Consumption rates are generally given in ounces of cooked fish, therefore, the 1.5 in this 

equation reflects the increase in the concentration of Hg from cooking. It should be noted 

that this implies a concentration factor of .667 of initial fish weight. Carrington et al. 

(2004) report less concentration of methylmercury occurring from cooking (i.e. a 

concentration factor between 1 and .737) , making the use of a concentration factor of 

.667 an upper bound assumption of the amount of methylmercury in cooked fish. This 

exposure value is then divided by the RfD of 0.1 to obtain the IDI. 

The Effectiveness TSD (EPA 2005a) lists the IDI values for freshwater fish 

consumption at various rates of consumption in Table 6-4. To create an equivalent table 

for marine fish consumption, we require the concentration of methylmercury in seafood 

and consumption rates. Carrington et al. (2004) provide a table (Table 3.2) of the 

mercury concentration for 42 commercial finfish and shellfish seafood species. This is a 

relatively comprehensive list, containing 99 percent of the market share for commercial 

seafood, and includes fish in both open ocean and near shore areas. The Hg 

concentration for the seafood diet of the general population can then be estimated by 

summing the product of Hg concentration times market share for each species. This 

produces an estimate of a mean Hg concentration of 0.104 ppm for the seafood diet of the 

general population. Note that this is the Hg concentration from all sources in all 

countries; U.S. power plants account for a small fraction of this total. 

Consumption rates of marine fish can be obtained from the Exposure Factors 

Handbook (US EPA 1997b). The mean intake of all fish species (marine, freshwater, 

estuarine, and aquaculture) for the general population is 20.1 grams per day (g/day) with 

an estimate of the 95 percent consumption level of 63 g/day. For marine fish alone, the 

best estimate of general population consumption is 14.1 g/day. If we assume the 

distribution of marine fish is proportional to total fish consumption, then the 95th

percentile of marine fish consumption would be approximately 44 g/day. 

The 95th percentile consumption value of 65 g/day of all fish (marine, freshwater, 

estuarine, and aquaculture) is generally consistent with Carrington and Bolger (2002) 

estimate of seafood consumption, based on data from the U.S. Department of Agriculture 

Continuing Survey of Food Intake by Individuals. Adjusting their data to account for the 

consumption of high-frequency consumers, they estimate a 95th consumption rate for all 

seafood1 of 62.7 g/day. They also estimate consumption rates of 6.8, 41.5, 62.7, 123.2, 

141.3, and 206.6 g/day for the median, 90th, 95th, 99th, 99.5th, and the 99.9th percentile, 

respectively. This information can be used to estimate the consumption rate at very high 

levels of consumption. 

Table 3.1 below lists the mercury exposure, in μg/kg-bw/day, from all sources at 

the various rates of consumption described above. Values of 0.1 or greater, which occur 

 

1 Carrington and Bolger (2002) use records of seafood-consumption events. We assume that this includes 

consumption from all fish (marine, freshwater, estuarine, and aquaculture). As such, the tables in this 

section that include high-end consumption values must be interpreted as if all of the consumer’s fish diet 

came from marine fish. 
14

at consumption levels between 90 and 95 percent, imply that some individuals are 

experiencing levels of Hg above the RfD due to fish consumption. It is very important to 

note, however, that this is the Hg exposure from all sources. This includes natural 

sources as well as man-made sources, both U.S. and from other countries. It also 

assumes that the mercury concentration in fish tissue consists entirely of MeHg, biasing 

the estimates upward. 

Table 3.1 Mercury Exposure from Seafood Consumption from all Sources 

(units in μg/kg-bw/day) 

Consumption Rate g/day

Mean Marine Fish Intake 14.1 0.03 

95% Long-Term Marine Fish Intake 44 0.10 

Mean Total Fish Intake 20.1 0.05 

95% Long-Term Total Fish Intake 63 0.15 

Median Carrington & Bolger Seafood Consumption 6.8 0.02 

90% Carrington & Bolger Seafood Consumption 41.5 0.10 

95% Carrington & Bolger Seafood Consumption 62.7 0.15 

99% Carrington & Bolger Seafood Consumption 123.2 0.29 

99.5% Carrington & Bolger Seafood Consumption 141.3 0.33 

99.9% Carrington & Bolger Seafood Consumption 206.6 0.48 

Note: Mean fish tissue methylmercury concentration from all sources is 0.1 ppm. 

The scaling method used for freshwater fish assumed a proportional relationship 

between reductions in air deposition of Hg and MeHg concentrations in fish. This 

relationship has been documented in the MMaps approach (US EPA 1997a, US EPA 

2001). The MMaps model assumes that, in steady-state, changes in MeHg 

concentrations in fish are proportional to changes in Hg inputs from atmospheric 

deposition. This solution only applies to situations where air deposition is the only 

significant source of Hg to a water body, and the physical, chemical, and biological 

characteristics of the ecosystem remain constant over time. These conditions do not hold 

in open ocean systems. As discussed in the previous section, assuming proportionality 

would most likely overstate the change in MeHg concentration in marine systems given a 

change in the atmospheric deposition of Hg. This means that assuming proportionality to 

calculate the marine fish Hg levels due to utilities would likely overstate the contribution 

of those utilities. This assumption could be useful, however, to produce an estimate that 

likely overstates the utility-attributable Hg levels in marine fish. If this utility attributable 

estimate is deemed not to represent a hazard to public health, we can reasonably conclude 

that a more realistic estimate, although not currently quantifiable, would also not 

represent a hazard to public health. Using the bounding assumption of proportionality 

between reductions in Hg deposition and reductions in fish tissue concentrations, then we 

can produce an approximation of the IDI for the 2001 base case. 

Broadly speaking, global Hg deposition comes from three sources, approximately 

one-third comes from natural sources (e.g., volcanoes), one-third comes from the 
15

emissions of modern man-made sources, and one-third from redeposition.2

 Mercury 

emissions from the U.S. power sector are estimated to account for about one percent of 

total global emissions (US EPA 1997a). We use this one-percent as the bounding 

estimate of the open ocean fish concentration reductions that could be expected from a 

100 percent reduction in power plant emissions in 2001.3 This assumes proportionality 

between emissions and open ocean fish concentrations, likely an overestimate, and so is 

used in this bounding calculation .4

 Multiplying the exposure factors in Table 3.1 by this 

one percent and dividing by the RFD of 0.1 produces the IDI values for marine fish 

consumption in Table 3.2 below. Since all values in Table 3.2 are all well below one, we 

can conclude that Hg emissions from U.S. power plants do not cause a health concern 

and do not significantly contribute to the U.S. general public’s exposure to Hg due to 

marine fish consumption. 

Table 3.2 IDI values for Seafood Consumption for the General U.S. Population 

(units in IDI values) (2001) 

Consumption Rate g/day

Mean Marine Fish Intake 14.1 0.00 

95% Long-Term Marine Fish Intake 44 0.01 

Mean Total Fish Intake 20.1 0.00 

95% Long-Term Total Fish Intake 63 0.01 

Median Carrington & Bolger Seafood Consumption 6.8 0.00 

90% Carrington & Bolger Seafood Consumption 41.5 0.01 

95% Carrington & Bolger Seafood Consumption 62.7 0.01 

99% Carrington & Bolger Seafood Consumption 123.2 0.03 

99.5% Carrington & Bolger Seafood Consumption 141.3 0.03 

99.9% Carrington & Bolger Seafood Consumption 206.6 0.05 

Note: Mean fish tissue methylmercury concentration from all sources is 0.1 ppm. The 

utility attributable fraction of that concentration is used for calculating IDI values. 

 

3.2 IDI for Consumption of Species with Very High Methylmercury Concentrations 

The results above use a mean fish tissue MeHg concentration of an average 

seafood diet, proportional to the market share for commercial seafood. This understates 

the Hg exposure from an individual who eats proportionally more high-Hg fish than the 

average consumer. As an extreme assumption, we consider the MeHg concentration for a 

 

2 see http://www.epa.gov/mercury/control_emissions/global.htm 

3 Another possible measure would be data from the CMAQ model used for the Revision Rule. Using the 

difference between Hg deposition in the coastal Atlantic and the Gulf of Mexico region in the base case and 

the 2020 zero-out CMAQ run, it is estimated that U.S. power plants contribute an average of less than onepercent to total deposition in this area. Averaging the entire Atlantic and Gulf Coast ocean area modeled 

by CMAQ implies an average change in atmospheric deposition of 0.65 percent in 2020 using a “zero out” 

of utility mercury emissions from a post-CAIR baseline. We use the estimate of the contribution of U.S. 

power plant emissions to the global pool of one percent rather than the value from the CMAQ model 

because it provides an upper bound estimate. 

4 By 2020 after CAIR and furthermore after CAMR, this fraction would decline. 
16

fish with a concentration of 1ppm.5

 This is one of the highest Hg concentrations from 

marine fish and represents a type of fish that a person might potentially eat on a regular 

basis. 

As an extreme assumption, we consider an individual whose fish consumption 

comes exclusively from a marine species with a methymercury concentration of 1.0 ppm. 

Table 3.3 uses this MeHg concentration of 1.0 ppm, the one percent change in MeHg 

concentration, and the various consumption levels from Table 3.1. Again, the IDI value 

never exceeds one, even for a 99.9 percent consumption level. Given that this assumes 

someone exclusively eating a fish with one of the highest marine Hg concentrations and 

eating at the highest consumption rate, it is reasonable to conclude that U.S. power plants 

do not significantly contribute to the U.S. exposure to Hg from marine fish consumption. 

Table 3.3 IDI values for Exclusive Consumption of Marine Species with High 

Methylmercury Concentration 

(units in IDI values) 

Consumption Rate g/day

Mean Marine Fish Intake 14.1 0.03 

95% Long-Term Marine Fish Intake 44 0.10 

Mean Total Fish Intake 20.1 0.05 

95% Long-Term Total Fish Intake 63 0.15 

Median Carrington & Bolger Seafood Consumption 6.8 0.02 

90% Carrington & Bolger Seafood Consumption 41.5 0.10 

95% Carrington & Bolger Seafood Consumption 62.7 0.15 

99% Carrington & Bolger Seafood Consumption 123.2 0.29 

99.5% Carrington & Bolger Seafood Consumption 141.3 0.33 

99.9% Carrington & Bolger Seafood Consumption 206.6 0.48 

Note: High fish tissue methylmercury concentration from all sources is 1.0 ppm. The 

utility attributable fraction of that concentration is used for calculating IDI values. 

3.4 Conclusions Regarding the Marine Pathway 

In summary, EPA believes that the utility-attributable portion of Hg in the 

seafood diet is not significant. However, EPA is soliciting comments on the IDI 

constructed above as well as other methods to account for commercially important 

marine fish that have relatively high Hg concentrations. 

4. Estuarine Near-Shore Exposure Pathway 

 

5 Carrington, Montwill, and Bolger (2004) report a mean Hg concentration of 0.97 ppm and a median 

concentration of 0.86 ppm for swordfish. 
17

Despite the lack of a comprehensive quantitative analysis, EPA finds that the 

available data support our position that the utility attributable U.S. population wide 

exposure to methylmercury from estuarine fish and shellfish will likely be small relative 

to that from recreational self-caught freshwater fish described in previous sections of the 

Effectiveness TSD. In general, coastal finfish species of the same age/size and trophic 

level as freshwater fish have relatively lower mercury concentrations (Mason and Gill, 

2005). 

Overall methylmercury exposure from coastal fish and shellfish is likely smaller 

than exposure from a comparable amount of freshwater fish. First, coastal fish of the 

same age/size and trophic level as freshwater fish generally have relatively lower 

mercury concentrations (Mason and Gill, 2005). Second, shellfish tend to have a lower 

fraction of methylmercury relative to their total mercury burden than freshwater fish 

(Bloom et al. 1992, Joiris et al. 2000, Mikac et al. 1985), which further lowers 

methylmercury exposure from all coastal species. 

When compared to overall landings of marine fish in the U.S., domestically 

caught estuarine fish and shellfish (defined as those harvested within 3 miles from shore) 

make up only 38 percent of the total 2001 commercial fish and shellfish landings in the 

U.S. (NMFS 2002) Based on the average mercury content of estuarine fish and shellfish, 

a conservative (high) estimate of total mercury exposure is approximately 23 percent of 

the total mercury intake from the U.S. Commercial Seafood Market (described below). A 

comparably larger fraction of the seafood consumed in the U.S. originates from open 

ocean/marine areas discussed in section 2. The utility attributable fraction of this 23 

percent will also be very small as indicated by data showing that: 1) Utility attributable 

mercury deposition in near-shore areas is small relative to inland areas where recreational 

fishing occurs; 2) Legacy mercury sources and inputs from watershed areas in most 

coastal systems will further lower the percentage of utility attributable mercury in 

estuarine fish and shellfish. 

The following sections outline EPA’s rationale for concluding that utility 

attributable human exposure resulting from consumption of estuarine fish is small. First, 

we discuss the major scientific uncertainties in the estuarine exposure pathway. Second, 

we review the data on consumption of estuarine fish and shellfish in the United States 

and the relative exposure to mercury from this source compared to other pathways. 

Finally, we review the utility attributable deposition estimates in near-shore area of the 

United States and discuss how this may affect concentrations in estuarine species. 

4.1 Uncertainty in the Near-Shore Fish Exposure Pathway 

EPA believes that the state of the science currently does not support a nationalscale quantitative analysis for this component of the exposure pathway. The most 

important difficulty in conducting this analysis is determining the response of coastal and 

estuarine systems to changes in atmospheric mercury deposition. Some studies have 

assumed an instantaneous proportional relationship between declines in deposition and 

concentrations in estuarine fish to complete their exposure analysis. However, such an 
18

assumption has not been endorsed by EPA or the scientific community as an appropriate 

method for characterizing the effects of emissions reductions on estuarine fish 

concentrations. 

A proportional relationship between mercury deposition and the methylmercury 

concentration in fish was developed and has been evaluated for application for certain 

freshwater water bodies across the U.S. if air deposition is the only significant source of 

mercury to a water body (US EPA 1997a, US EPA 2001). As described above, such a 

relationship is thought to be an overestimate for marine systems so can be used in a 

bounding calculation. Applying such a relationship to estuarine systems extends this 

assumption beyond the realm of application for which this model was developed for 

freshwater systems and, unlike marine systems, it is not known whether it would likely be 

an overestimate for all estuaries. External sources of methylmercury to estuaries, like 

other aquatic systems, are typically small such that in situ methylmercury production 

accounts for the majority of mercury in fish (Mason and Benoit 2003). Mercury cycling 

in estuarine areas differs significantly from both the open-ocean and freshwater 

environments. Because estuaries are much shallower than open ocean areas, active 

methylmercury production in estuarine sediments is an important source of mercury for 

fish and shellfish residing in these regions (Hammerschmidt et al, 2004, Cossa and 

Gobeil, 2000, Lawson et al., 1998). Unlike freshwater systems, most estuaries have 

significant inputs of tidal water, which generally dilutes incoming mercury from rivers, 

streams, and direct atmospheric deposition. In addition, because of the saline 

environments found in estuaries, the geochemistry of these systems differs significantly 

from inland lakes, affecting the rate and magnitude of methylmercury production (Heyes 

et al., 2005). There is, however, a paucity of data and modeling describing mercury 

cycling in coastal areas compared to freshwater and marine environments. This limits 

our ability to develop a comprehensive quantitative assessment of the exposure pathway 

at this time. 

Some empirical observations of mercury cycling in coastal ecosystems often show 

total mercury concentrations are not necessarily good predictors of ambient 

methylmercury concentrations (Benoit et al., 2003). In addition, such an estimate likely 

overestimates the response of coastal ecosystems to changes in atmospheric deposition if 

all other ecosystem characteristics remain constant. A number of studies have shown that 

the production and bioavailability of mercury in coastal ecosystems is a function of 

environmental characteristics like total organic carbon, sulfides concentrations in water 

and sediments and temperature (Benoit et al, 1999, Sunderland et al, 2005). When the 

methylation potential of estuarine systems is limited by some environmental or 

geochemical characteristic of the ecosystem, small changes in inorganic mercury 

deposition from the atmosphere are unlikely to significantly impact methylation rates and 

ultimately fish methylmercury concentrations. Fish methylmercury concentrations in 

coastal ecosystems that have been significantly impacted by legacy mercury sources (e.g., 

San Francisco Bay, CA, Lavaca Bay, TX) are also unlikely to be affected by small 

changes in atmospheric deposition because they receive the majority of their mercury 

from watershed sources and from contaminated sediments (Bloom et al, 1999, Sager, 

2002, Conaway et al., 2003). 
19

Most coastal areas in the United States are highly populated and therefore receive 

significant mercury loadings from land based sources through wastewater effluents and 

other industrial contamination. In addition, most coastal regions are likely to have 

relatively deep active sediment layers relative to freshwater systems due to mixing 

processes that occur when rivers and tidal waters meet. Effectively, a deeper active 

sediment layer allows coastal systems to store legacy contaminants and allows 

historically released mercury to interact with the water column, undergo methylation and 

accumulate in the food-web, slowing the ecosystems response to changes in mercury 

inputs (Sunderland et al., 2004). Coastal systems with deep active sediment layers that 

contain large amounts of legacy Hg from past anthropogenic contamination and large 

contributions from watershed-based Hg sources will respond very slowly to changes in 

emissions from utilities, and the magnitude of this response will also likely be small. 

Finally, the life cycles of marine species (fraction of time spent in near-shore 

relative to pelagic environments) needs to be considered to accurately model mercury 

bioaccumulation. Many of the coastal and estuarine species, listed in Table 4.1 below, 

spend a portion of their lifecycle in near-shore areas and the remainder in open-ocean 

regions. This behavior is likely to further lower the significance of utility-attributable 

mercury in the U.S. on methylmercury concentrations in these species. 

Based on this, EPA believes that a simple linear relationship that assumes 

instantaneous changes in Hg levels in fish and shellfish across all estuarine systems in the 

U.S. is proportional to changes in atmospheric deposition does not appropriate reflect the 

best available information on mercury cycling in coastal ecosystems. As such, we cannot 

conduct a comprehensive, national-scale quantitative analysis of this pathway for all 

estuary and coastal regions.6

 

4.2 Consumption of Near-Shore Species in the United States and Associated 

Mercury Exposure 

To assess the total mercury exposure from consumption of fish and shellfish in 

the United States, we analyzed commercial landings data from the National Marine 

 

6

 EPA has distinguished between estuarine and open ocean (marine systems) in this analysis. Bounding 

calculations were possible for marine systems because of the relative homogeneity of human influences on 

mercury cycling in marine systems compared to estuarine systems. Specifically, open-ocean environments 

are isolated from local variability in methylmercury formation rates and biotic concentrations that are 

commonly observed in estuaries. This is because open ocean environments do not exhibit the same 

variability in geochemical properties affecting methylmercury formation as estuaries (i.e., the deep water 

column means that methylmercury production in the sediments has a negligible effect on water column 

concentrations). Finally, we believe that the analysis for the open ocean environment is justifiable because 

it is a sensitivity analysis taking into account the limited nature of the data on mercury fate and transport in 

the open-ocean. Given the regional differences in utility attributable mercury deposition to estuaries in the 

US, the fraction of mercury deposited that is converted to methylmercury, and fish methylmercury 

concentrations, we felt that it would be unrealistic to attempt to develop a national estimate of changes in 

mercury exposure resulting from changes in utility mercury deposition in all estuaries across the US at this 

time because of the heterogeneity of estuarine systems and that it would be more appropriate to present a 

qualitative assessment. 
20

Fisheries Service (NMFS, 2002). For this analysis, we define estuarine species as those 

caught within 0-3 miles of the U.S. coastline. Total commercial fish production in 2001 

was 4.4 million tonnes, with 3.9 million tonnes as finfish and 0.5 million tonnes as 

shellfish. Of the total commercial catch, 63% of the shellfish and 34% of the finfish in 

2001 were caught within 0-3 miles from the shore. This estimate includes some species, 

such as menhaden, that are also used for animal feed or other purposes. As a sensitivity 

analysis we subtracted out menhaden, resulting in a somewhat lower percentage of finfish 

(excluding menhaden) coming from the near-shore area. 

Using the product of mean mercury concentrations and percent of the commercial 

market for each species from Carrington et al. (2004), we are able to rank the Hg 

exposure from the top 25 species in the US commercial seafood market (Table 4.1). We 

then multiply each finfish or shellfish species by the overall fraction caught in coastal 

waters to provide a conservative estimate of the relative mercury exposure from coastal 

species. As illustrated in Table 4.1, the fraction of mercury exposure from fish caught in 

near-shore waters in the U.S. commercial seafood market is roughly 35 percent of the 

total. However, the utility-attributable fraction of mercury exposure from fish and 

shellfish will be much smaller as outlined below. 

This estimate of total exposure from estuarine species is thought to be 

conservative (high) because it is based on total mercury concentrations in fish and 

shellfish rather than methylmercury concentrations, the mercury species in fish that is 

toxicologically most significant. It is fairly well established that shellfish in general will 

have a lower fraction of total mercury present as methylmercury (%MeHg) in their 

tissues than predatory fish. For example, Mikac et al. (1985) found that marine mussels 

had 5-27% of mercury in the organic form, while Mason et al. (2000) found between 50-

80% of the mercury in crayfish was present as MeHg. Thus, it appears that there is 

considerable variation in estimates of the fraction of methylmercury contained within the 

tissue of invertebrates. This lowers methylmercury exposure typically associated with 

certain species by assuming measured total mercury concentrations are equivalent to 

methylmercury concentrations. 

Table 4.1. Estimated mercury intake from species harvested within three miles from 

shore based on the Hg content of the top 25 species in the U.S. Commercial Seafood 

Market. 

Species % Hg Intake 

by Species1

% Coastal 

Estimate 2

Tuna, albacore (canned) 17.9% 6.1%

Tuna, light (canned) 15.9% 5.4%

Haddock, hake, and monkfish 8.7% 3.0%

Pollock 7.1% 2.4%

Tuna, fresh 6.5% 2.2%

Cod 6.5% 2.2%

Swordfish 3.9% 1.3%

Lobsters, American 3.8% 2.4%
21

Catfish 3.0% 1.0%

Crabs 2.8% 1.8%

Lingcod and scorpionfish 2.5% 0.9%

Salmon 2.2% 0.8%

Flatfish 2.0% 0.7%

Halibut 1.9% 0.6%

Shrimp 1.7% 1.1%

Bass, saltwater 1.5% 0.5%

Anchovies, herring, and shad 1.5% 0.5%

Shark 1.2% 0.4%

Orange Rougy 1.0% 0.4%

Lobsters, spiny 1.0% 0.6%

Grouper 0.9% 0.3%

Snapper, porgy, and sheepshead 0.7% 0.3%

Squid 0.7% 0.2%

Sablefish 0.7% 0.2%

Skate 0.5% 0.2%

Percent Total 96.2% 35.4%

1 Ranking for %Hg Intake column is based on %Market and average Hg content for each 

species in Carrington et al., 2004. 

2 Percent coastal intake was estimated using 2001 landings data averages of 34% of all 

finfish harvested from 0-3 miles from shore (near-shore areas) and 63% of all shellfish 

(NMFS 2002). 

4.3 Utility Attributable Mercury Deposition in Near-shore Areas 

The significance of utility-attributable mercury for estuarine species is expected to 

be a small component of their overall body burden because of the prevalence of legacy 

contaminants, watershed based mercury sources and other atmospheric mercury sources 

in these regions. When analyzing mercury exposure in most coastal regions, it is 

apparent that the utility-attributable portion of this exposure will be limited. For 

example, the Pacific Coast accounts for over 65 percent of the productions of fish species 

listed in table 4-1 (NMFS 2002) and will be negligibly impacted by utility-attributable 

mercury deposition. This is reinforced by EPA’s deposition modeling, which indicates 

that coal-fired utilities will not significantly impact Hg levels on the Pacific Coast. As a 

bounding analysis, if we recalculate the potential fraction of total mercury exposure that 

can then be affected by changes in utility deposition from Table 4.1, we are left with 35 

percent of the original 35 percent of total exposure from the U.S. commercial seafood 

market. In other words, only slightly more than 12 percent of the total mercury exposure 

from the consumption of marine fish can be from the consumption of coastal and 

estuarine fish from the Gulf coast, southeast Atlantic and New England. Only a small 

fraction of that 12 percent can be attributed to utility-attributable mercury as discussed 

below because utility deposition comprises only a small fraction of the mercury that is 

present and available for methylation in the Gulf coast, southeast Atlantic and New 

England. 
22

EPA’s modeling of deposition due to mercury emissions from Utilities in 2001 

suggests that Utilities represent between 0 and 10 percent of the total deposition in the 

Gulf Coast, 5 to 20 percent in the Southeast Atlantic, 0 to 10 percent in the New England 

coastline, and 20 to 30 percent in the Chesapeake Bay area. In 2020 after CAIR (and 

furthermore after CAMR) the deposition due to mercury emission from utilities falls to a 

range between 1 percent and 12 percent for the Gulf and Southeast Atlantic coasts. Most 

Gulf and Southeast Atlantic Coast areas will experience approximately 2 percent of total 

deposition from utilities. Most areas of the New England coastline will experience 

slightly over 2 percent of total deposition from utilities, with a maximum utilityattributable deposition of 7 percent. After CAIR in 2020, utility attributable deposition 

will be highest close to shore off the Northeastern States but will still be less than 7 

percent, compared to up to 19 percent in the highest freshwater fishing areas (see Table 

2.6 of the Effectiveness TSD). 

The Chesapeake Bay represents 6.5 percent of total U.S. landings (NMFS 2002) 

and is likely one of estuarine ecosystems most sensitive to atmospherically deposited 

mercury from US power plants because of the significance of coal fired power plants (20-

30 percent of total in 2001) to overall atmospheric mercury deposition rates and its 

relatively small watershed to water surface area ratio (resulting in a greater importance of 

the atmospheric pathway compared to many other estuary ecosystems). Utility 

attributable deposition after CAIR is expected to be in the range of 8.5 percent (and will 

be reduced even further following CAMR) of the total deposition. The percent of total 

deposition attributable to utilities for the Chesapeake Bay watershed is somewhat less 

that the 8.5 percent for the Chesapeake Bay itself. EPA’s analysis of projected mercury 

deposition rates after implementation of CAIR and CAMR show some of the largest 

reductions in mercury deposition are expected to occur in the Chesapeake Bay region. 

4.4 Conclusions Regarding the Near-Shore Pathway 

As discussed above, populated coastal regions like the Chesapeake Bay and 

Baltimore Harbor (Mason and Lawrence, 1999) will receive significant land-based 

mercury inputs from wastewater effluents, municipal waste discharges and historical 

mercury contamination that are slowly leaching from the watershed. In addition, legacy 

mercury stored in the active sediment layers of these systems will continue to supply 

coastal systems with inorganic mercury for many decades. These types of inputs to 

coastal ecosystems lower the overall significance of small changes in atmospheric 

deposition to the overall magnitude of mercury in coastal systems. These estimates of 

utility attributable deposition following CAIR, combined with the magnitude of 

commercial fish landings data from the Eastern U.S. coastline further reinforces that 

exposure from this source is small. 

Although we are not currently able to quantitatively estimate IDI values associated with 

various levels of consumption of estuarine fish, the available information suggests that 

they will be bounded by the freshwater recreational/subsistence IDI values presented in 

the Effectiveness TSD (US EPA 2005a). We therefore continue to use the IDI values in 

Table 6.4 of the Effectiveness TSD as our estimate of the maximum individual risk. In 
23

addition, we will use the utility attributable MeHg in the 85th percentile freshwater fish as 

a bound of the utility attributable MeHg in estuarine fish. 

5. Aquaculture Exposure Pathway 

Due to the unique nature of the aquaculture pathway and gaps in the available 

data, it is not possible to conduct a quantitative assessment of the utility-attributable 

exposure from mercury in farm-raised fish. However, based on the available information 

we are able to conclude that the contribution of aquaculture to utility-attributable mercury 

exposure is small. By breaking this potential exposure pathway into three main 

components that are discussed below, we outline our rationale for determining that 

utility-attributable exposure due to consumption of aquaculture is small. 

First, we find that farm-raised fish accounts for only 10 percent of total 

commercial fish production in the U.S (NMFS 2002), which limits the relative 

importance of consumption of aquaculture species harvested in the US that could 

potentially be affected by U.S. power plant mercury deposition compared to other fish 

sources. Second, the main aquaculture species are salmon and catfish, which are 

generally low in mercury. Third, the fraction of the mercury attributable to power plants 

in farm-raised fish is likely much smaller than other wild fish because their diet is 

specifically engineered from a number of different protein sources that may not 

necessarily originate in the U.S. and are therefore not appreciably affected by utilityattributable mercury. Further, the fish meal used to make fish feed is usually derived 

from smaller fish, which are generally lower in mercury than are larger fish. Because the 

mercury residue in fish tissues is mainly the result of dietary biomagnification, uptake of 

mercury from the water column (which may potentially be affected by power plant 

emissions) by farm-raised is expected to be small. Given this information, it is 

reasonable to conclude utility-attributable mercury from this particular pathway will not 

add significantly to the overall population body burden. 

5.1 Quantity of Fish Produced in Marine and Freshwater Aquaculture 

 

In 2001, total aquaculture production in the U.S. was 371,470 metric tons, 

compared to total commercial finfish that were domestically caught in the same year of 

3,738,769 metric tons (NMFS 2002).7 Because only U.S. aquaculture is relevant from 

the standpoint of assessing utility-attributable mercury exposure, these numbers indicate 

that U.S. aquaculture is at most 10 percent of the other fish landings within the country. 

In short, potential utility-attributable mercury exposure from U.S. aquaculture is small 

relative to other types of fisheries. 

5.2 Mercury in Aquaculture Fish from Direct Deposition versus Fish Feed 

It is well known that the major pathway of mercury accumulation in fish is 

through the diet rather than uptake from water (e.g., see review by Rodgers 1994). The 

 

7 This estimate includes some species, such as menhaden, that are also used for animal feed or other 

purposes. 
24

process whereby contaminants accumulate in organisms to many times the concentrations 

found in the ambient environment as larger organisms eat smaller organisms is known as 

“biomagnification.” For example, it is not uncommon to see concentrations of mercury in 

predatory wild fish that are a million times higher than the methylmercury concentration 

in water because of dietary biomagnification. Direct uptake of a contaminant from the 

ambient environment is known as “bioconcentration” and both of these processes 

together are known as “bioaccumulation.” 

Because the major pathway of mercury accumulation in fish tissue occurs through 

biomagnification of methylmercury, concentrations of mercury in the diet of aquaculture 

species are most relevant for determining their ultimate tissue Hg residue. In order for 

utility-attributable mercury to be significant in farm-raised fish, a significant fraction of 

the diet would need to be composed of fish that are affected by utility-attributable 

mercury. This is not the case as illustrated below. 

Two key ingredients of fish feed, for which economic data exist, are fish meal and 

fish oils. In 2002, approximately 28 percent (148 million pounds) of the U.S. supply of 

fish meal was imported and the remaining 72 percent (389 million pounds) was 

domestically produced (NMFS, 2003, p. 83). Data on the U.S. supply of fish oils shows 

that it is roughly 50 percent imported and 50 percent domestically produced (NMFS, 

2003, p. 83). The mercury concentration in domestically produced fish meal and fish oil 

depends on where the fish were caught. Only 16 percent of U.S. domestic commercial 

landings occur on the Atlantic coast, versus 83 percent on the Gulf and Pacific coasts 

(NMFS, 2003, p. 6). Of U.S. commercial landings, only 36 percent occur within 0 to 3 

miles from U.S. shores, while 61 percent occur between 3 and 200 miles of U.S. shores 

(NMFS, 2003, p. 19). Because Gulf coast, U.S. Pacific coast, internationally landed fish, 

and Atlantic coast fish caught greater than 3 miles off shore are expected to see a very 

small decrease in exposure to U.S. utility-attributable Hg emissions, only a small fraction 

of the U.S. supply of fish meal and fish oil is expected to see a significant change in Hg 

exposure. Therefore, while the dynamics of Hg contained in imported fish meal and fish 

oil is largely unknown, the mercury contained in this fish is likely from the global pool, 

of which US power plants represent about 1 percent. 

In contrast to dietary mercury accumulation from fish oil and meal, much smaller 

contributions are expected from ambient Hg concentration and wild food sources and 

ingredients in fish food other than fish oil and fish meal. Any geographic analysis of 

deposition with regard to fish farm location would assume that reductions in atmospheric 

deposition would directly impact farm-raised fish Hg loads through bioconcentration, 

which is not the case as described in detail above. Regional changes in Hg emissions and 

subsequent atmospheric deposition resulting from the Revision Rule are not expected to 

have a direct impact on the content of Hg in farm-raised fish. 

In summary, EPA finds that it is the location of the fish caught to make fish feed 

that is relevant, as opposed to the location of aquaculture farms. 

5.3. Summary of the Aquaculture Exposure Pathway 
25

In summary, the limited available data indicate that Hg body burdens in 

aquaculture fish are less than or equal to their wild counterparts, and mercury in 

aquaculture fish is predominantly the result of the mercury content of fish feed. The fish 

feed used in US aquaculture comes from a variety of sources including the Gulf Coast, 

the Atlantic Ocean, US Pacific Coast, and internationally landed fish – fish that have 

small utility-attributable mercury levels. Therefore, while there are insufficient data 

available to conduct a full quantitative assessment, EPA believes that the existing 

information support the conclusion that that utility-attributable mercury exposure from 

aquaculture is small and that all individuals or groups of individuals who consume 

aquaculture fish are likely to ingest utility-attributable methylmercury at levels that are 

reflective of the levels ingested from the types of marine fish that comprise aquaculture 

fish feed. 

6. Commercial Freshwater Exposure Pathway 

EPA’s claim that freshwater commercial fish are not a significant pathway is valid 

since 17 million pounds/year (lb/yr) is small when compared to recreational freshwater 

fish consumption of 377 million lb/yr, or 22 times the Great Lakes commercial haul.89 

Further even though utility attributable deposition is comparatively higher around the 

Great Lakes and the bordering areas (including the states of Michigan, Indiana, Illinois, 

and Ohio and other surrounding areas) in comparison with the rest of the United States, it 

is still only a small percentage of mercury deposition from all sources. The typical 

percent of total deposition that is attributable to utilities in these areas is approximately 

10 percent. Thus, following the assumptions in Mercury Maps, only approximately 10 

percent of the mercury in the fish found in this area is attributable to utilities. In addition, 

the areas in the Great Lakes that are affected do not experience a disproportionately high 

deposition rate compared to the surrounding land area, where recreational freshwater fish 

are caught, so the commercial freshwater pathway is still expected to be small relative to 

the recreational/subsistence freshwater pathway. 

Because exposure is determined at the population level, the determination for 

including this pathway is whether adding it (population exposed times exposure rate) will 

significantly alter the cumulative distribution of total exposure rates. As described above, 

the commercial freshwater harvest is small compared to recreational freshwater 

consumption, the percent of utility-attributable deposition in the primary commercial 

freshwater harvesting area is 10 percent, and those levels are not disproportionate to the 

areas for recreational freshwater harvest. These facts lead the EPA to conclude that 

including the commercial freshwater pathway in the exposure model would result in a 

 

8 Recreational freshwater fish consumption was calculated by multiplying the population of fishers 

(27,900,000 (US FWS 2002)) by both the percent of recreational fishers who consume their catch (0.84 

(average of values presented in West at al. 1989, Chemrisk 1991, and West et al 1993 as presented in EPA 

1997b)), and the number of friends and family with whom the average recreational fisher shares his or her 

catch (2.5 (EPA 1997b)) and converting to pounds. 

9 The Great Lakes commercial haul is 0.2% of the total commercial haul of finfish (8.2 billion pounds) 

(NMFS 2002). The marine haul represents the most significant fraction of the total haul and is discussed 

elsewhere. 
26

relatively small change in the general population level exposure estimate. In addition, 

there is no reason to include this pathway to address its effect on the higher end groups 

(e.g. subsistence fishers) because most of the fish they eat is self-caught and it is highly 

unlikely, given the nature of their fishing activity, that more than a small fraction, if any, 

of their consumption is comprised of commercially caught freshwater fish. As such, we 

believe that the IDI values for this pathway are bounded by the freshwater 

recreational/subsistence IDI values. 

7. Joint Consumption 

In order to examine utility-attributable Hg exposure from total fish consumption 

quantitatively, it would be necessary to have information on the distribution of 

consumption of each type of fish – recreational freshwater, commercial freshwater, 

recreational saltwater, etc - as well as utility-attributable MeHg concentrations (either 

sufficiently accurate or upper-bound) for each type of fish. If we were able to identify 

the consumption of each type of fish as well utility-attributable MeHg concentration for 

each type of fish, then the IDI values from each type of fish could be calculated and 

added together to arrive at a total IDI value. Currently no such data exists. Regardless, 

for the reasons described above, EPA maintains that self-caught freshwater fish 

consumption represents the most significant exposure pathway for the populations with 

the highest utility-attributable exposure. 

At any given total fish consumption rate noted in our analyses, introducing 

aquaculture, marine, or estuarine fish into the diet of a self-caught freshwater fish 

consumer necessarily implies reducing consumption of self-caught freshwater fish (e.g., 

in order to maintain the same total fish consumption rate). As discussed in previous 

sections, because utilities contribute more Hg to freshwater fish species than to any other 

fish species, such substitution implies a lower IDI than is associated with consumption of 

self-caught freshwater fish alone, supporting the assertion that self caught freshwater 

consumption represents the primary source of utility-attributable Hg exposure. As can be 

seen in the seventh column of Table 6-4 of the Effectiveness TSD and Table 3.2 of this 

document, for any given consumption rate, the estimated IDI for self caught freshwater 

fish consumption is higher than the estimated IDI for marine fish consumption (for fish 

tissue methylmercury percentiles 50 percent or greater). Hence, for any given 

consumption rate, consumption of self-caught freshwater fish alone leads to a higher IDI 

than that of any other combination of fish, supporting our decision to focus our analysis 

on consumption of self-caught freshwater fish. 

Table 6.4 of the Effectiveness TSD (US EPA 2005a) shows an array of 

consumption values combined with percentiles of methylmercury concentration in 

freshwater fish. Results for 2020 with CAIR indicate that estimated IDIs are all well 

below 1 for the first three consumption rates. Estimated IDIs are over one for 99th 

percentile recreational fishers and mean subsistence Native Americans only when all of 

the fish consumed has MeHg concentrations at the 99th percent level, a convergence of 
27

factors which is unlikely to occur.10 See 70 FR 16024. While estimated IDIs for the 95th 

(170 g/day) and 99th percentile (295 (g/day) subsistence Native American consumers are 

above one for lower percentile MeHg concentration fish, it is unlikely that these 

consumers would add significant amounts of non-self-caught freshwater fish to their diets 

over the course of a year, but rather would substitute fish, again supporting our focusing 

on the consumption of self-caught freshwater fish. Finally, the IDI values for the 

combinations of fish consumption rates and MeHg concentrations bordering the 

combinations with IDIs above one are sufficiently below one that it is unlikely that a 

consumer in these combinations would add a sufficient amount of other fish (with lower 

utility-attributable MeHg concentrations than freshwater fish) to their freshwater fish diet 

to cause their IDI to exceed one. 

 Further, we have no evidence that high end consumers of self caught fish also 

consume other types of fish. It is highly unlikely that subsistence individuals eat 170 

g/day or 295 g/day of self caught freshwater fish and consume significant quantities of 

marine fish. Even if we were to assume that these consumers do eat additional fish, the 

additional MeHg ingested by these consumers is small as we have shown above. 

8. Health Benefits and Costs 

8.1 Introduction 

Below we describe a bounding analysis that includes the exposure pathways 

described in this TSD and self-caught freshwater fish. In this calculation, we use mean or 

central tendency estimates of variables when available. However, for several variables we 

are not able to provide such an estimate and we therefore use a conservative estimate that 

would overestimate the utility-attributable mercury exposure. The final calculation 

therefore represents a combination of central tendency estimates for some variables and 

conservative estimates for other variables. This analysis is a bounding analysis in the 

sense that the final health benefit estimate presented below is very likely to be above the 

true health benefits of improved neurological performance associated with reducing 

mercury emissions from power plants because of the compounding use of conservative 

estimates for certain variables.11 The bounding analysis approach supports our reasonable 

belief that the costs of reducing mercury emissions beyond CAIR under section 112 from 

power plants outweigh the health benefits of reduced utility-attributable mercury 

exposure. 

 

10 In addition to the particular combinations shown in the table, there are a multitude of other combinations 

of fish consumption rates and methylmercury concentrations possible. For example, Table 6.4 shows that 

the 99th percentile recreational fisher consuming 47 grams per day of fish with the 99th percentile of utility 

attributable mercury concentration would have an IDI value of 1.12. An individual consuming slightly less 

than 47 grams per day of fish with the 99th percentile of utility attributable mercury concentration would 

also have an IDI value greater than 1. Similarly, an individual consuming 47 grams per day of fish with 

slightly less than the 99th percentile of utility attributable mercury concentration would also have an IDI 

value greater than 1. 

11 Note that the assumptions in this bounding analysis are different from those in the marine cycling 

section and this section should not be considered as an extension of that analysis. 
28

8.2 Outline 

The benefit calculation will follow directly from the IDI values presented in Table 

6-4 of the Effectiveness TSD (US EPA 2005a) and Table 3.2 of this TSD. These IDI 

values represent an estimate of exposure due to power plants and, equivalently, the 

reduction in exposure that would occur if power plant mercury emissions were 

eliminated. Using a dose-response relationship, we translate these IDI values into 

neurological improvements, using intelligence quotient (IQ) points as a surrogate. We 

then estimate the monetized value of these IQ point increments and discount these future 

monetized benefits to account for the ecosystem response time. These discounted benefits 

can then be compared with the discounted costs, taking into account the important 

uncertainties described elsewhere. 

8.3 IDI values 

We use the IDI values from Table 6-4 of the Effectiveness TSD and this TSD. For 

the purposes of estimating total benefits of reducing mercury emissions from power 

plants, we use the mean fish consumption rate for each pathway. The mean consumption 

rate is 8 g/day freshwater fish and is 14.1 g/day for the marine pathway (US EPA 1997b). 

The IDI values can be converted to ppm of mercury in hair by first multiplying it 

times 5.4, which is a conversion factor between the mercury in blood (in ppb) and 

exposure of someone exposed to mercury at the RfD. In other words, an exposure of 0.1 

μg/kg/day of MeHg (i.e., the RfD) is associated with 5.4 ppb in blood (see the onecompartment model for MeHg in IRIS (US EPA 2002a) for more detail12), and then 

dividing by the 4, which is the conversion ratio between blood mercury and hair mercury 

(250 ppb blood mercury = 1 ppm hair mercury).13 

8.4 IQ decrements 

EPA has chosen to focus on quantification of intelligence quotient (IQ) 

decrements associated with prenatal mercury exposure as the initial endpoint for 

 

12 The one compartment model converts the concentration of MeHg in blood (in μg/L) to daily dietary 

intake (in μg/kg/day) using the equation d = (c*b*V)/(A*f*bw), where c is the blood concentration (μg/L), 

b is the elimination constant (days-1), V is the volume of blood (L), A is the absorption factor (unitless), f is 

the fraction of absorbed dose taken up by blood (unitless), and bw is the body weight (Kg). Using the 

recommend values in IRIS (b=0.014, V=5, A=0.95, f=0,059, bw=67), substituting the RfD value of 0.1 

μg/kg/day for d and solving for c, we arrive at a conversion factor of 5.4. Note that others have equated the 

RfD to a maternal blood equivalent of 5.8 ppb. This estimate does not take into account the fact that the 

RfD was rounded to one significant digit and was not based on a single measure for the RfD critical 

endpoint. (see Table 2 at http://www.epa.gov/iris/subst/0073.htm) Rather, EPA based this RfD for this 

assessment on several scores from the Faroes measures, with supporting analyses from the New Zealand 

study, and the integrative analysis of all three studies. We therefore take the RfD of 0.1 ug/kg/day as the 

starting point of this calculation and then apply the one compartment model. 

13 http://www.epa.gov/iris/subst/0073.htm 
29

quantification and valuation of mercury health benefits.14 The IQ dose-response analysis 

uses data from three major prospective studies investigating potential neurotoxicity of 

low-level, chronic mercury exposure. Epidemiological studies of prenatal mercury 

exposure conducted in the Faroe Islands (Grandjean et al. 1997), New Zealand 

(Kjellstrom et al. 1989, Crump et al. 1998), and the Seychelles Islands (Davidson et al. 

1998, Myers et al. 2003) have examined neurodevelopmental outcomes through the 

administration of tests of cognitive functioning. 

A statistical analysis was conducted to integrate data from the three studies to 

produce a single estimate of the IQ dose-response relationship. Details of the analysis, 

including statistical model formulation, selection of input values, results and sensitivity 

analysis are reported in Ryan (2005). For the analysis in this section, EPA is using a 

linear model that goes through the origin to fit population-level dose-response 

relationships to the pooled data from the three studies. The application of a linear model 

should not be interpreted to suggest that any of the three studies used have data showing 

health effects from methylmercury exposure at or below the RfD.15 It is also important to 

note that the use of a linear model applied to all exposed individuals is done for purposes 

of developing an upper bound estimate of the IQ detrimental effect of MeHg. In effect, it 

assumes that all exposed individuals are exposed above the RfD.16 This assumption 

 

14 There is limited evidence directly linking IQ and methylmercury exposure in the three large 

epidemiological studies that were evaluated by the NAS and EPA. Based on its evaluation of the three 

studies, EPA believes that children who are prenatally exposed to low concentrations of methylmercury 

may be at increased risk of poor performance on neurobehavioral tests, such as those measuring attention, 

fine motor function, language skills, visual-spatial abilities (like drawing), and verbal memory. For this 

analysis, EPA is adopting IQ as a surrogate for the neurobehavioral endpoints that NAS and EPA relied 

upon for the RfD. 

In the Faroes Island Study, a full scale IQ evaluation was not conducted. However, two core 

subtests were evaluated (Similarities and Block design) and one supplementary test was conducted (Digit 

Span). The Similarities and Block Design tests are reported to be well correlated with the full WISC-R 

battery (0.885, see Bellinger (2005)), but how the Digit Span test relates is not reported. In the EPA 

analysis, we assume that it relates similarly. In the Faroes study, performance scores on the Similarities and 

Block Design tests were not shown to be statistically related to cord blood or maternal mercury levels; the 

Digit Span test did show a statistical relationship with cord blood mercury. 

Both the New Zealand and Seychelles study administered the WISC IQ test (WISC III in 

Seychelles, WISC R in New Zealand). A reanalysis of the New Zealand data found a positive association, 

but it was not statistically significant. No significant associations were seen in the Seychelles study. As 

displayed in Figure 5 of Ryan (2005), the confidence intervals for full scale IQ in both these studies include 

zero. However, Ryan conducted an integrative analysis, combining results from all three studies. When 

combined, the statistical power of the analysis increases. While the size of the dose-response relationship 

declined relative to past studies with a statistically significant finding, Ryan found a statistically significant 

relationship between IQ and mercury. The confidence interval did not include zero. 

15 The RfD is an estimate (with uncertainty spanning perhaps an order of magnitude) of a daily exposure to 

the human population (including sensitive subgroups) that is likely to be without an appreciable risk of 

deleterious effects during a lifetime (EPA 2002). EPA believes that exposures at or below the RfD are 

unlikely to be associated with an appreciable risk of deleterious effects. It is important to note, however, 

that the RfD does not define an exposure level corresponding to zero risk; mercury exposure near or below 

the RfD could pose a very low level of risk which EPA deems to be non-appreciable. It is also important to 

note that the RfD does not define a bright line, above which individuals are at risk of adverse effect. 

16 From recent data (MMWR November 5, 2004 / 53(43);1018-1020, 

http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5343a5.htm), we know that 5.7% of women of 
30

produces an upper bound, but is not consistent with the fact that most of the U.S. 

population is below the RfD and at these lower levels of exposure EPA believes that 

there is not an appreciable risk of deleterious effects occurring. 

The model makes use of dose-response coefficients for IQ. These coefficients 

express a central estimate of the average reduction in children’s scores in tests of IQ (or 

other tests of cognitive performance) for a one unit change in the mercury body burden of 

the mother during pregnancy. The model also incorporates coefficients for other 

cognitive tests conducted in the studies, in an effort to obtain more robust estimates of the 

IQ relationship that account for within-study (endpoint-to-endpoint) variability as well as 

variability across studies. A Bayesian hierarchical statistical model was used to estimate 

the integrated dose-response coefficient. This is similar to the approach used by the NRC 

panel to calculate a benchmark dose value integrating data from all three studies (NRC 

2000). A more technical description of these same methods has been provided by Coull et 

al. (2003). 

The statistical analysis produced a dose-response relationship, integrating data 

from all three studies, with a central estimate of an IQ change of -0.13 IQ points (95% 

confidence interval -0.28, -0.03) for every ppm of mercury in maternal hair. 

An IDI value can be converted to an IQ decrement by first converting it to a blood 

equivalent mercury level (in ppb) and then converting it to a hair mercury level (in ppm), 

as described above. The result can then be multiplied by the estimated dose-response 

coefficient of 0.13 to produce an IQ decrement. In other words: 

( )( ) ( )

( )( )( ) ( ) * 0.1755

4

* 5.4 * 0.13

Conversion between blood (ppb) and hair (ppm)

* Blood equivalent of RfD * IQ decrement per 1ppm hair

IDI IDI

IDI IQ Decrement

=

⎭

⎬

⎫

⎩

⎨

⎧ =

⎭

⎬

⎫

⎩

⎨

⎧ =

For example, an individual born to a mother exposed above the RfD due to non-US 

power plant sources and with an IDI value of 1.0 is estimated to experience a 0.1755 

decrement in his or her IQ due to the utility-attributable exposure according to the 

equation above. 

Applying this equation to all exposed individuals, in effect, assumes that all 

individuals are above the RfD due to non-US power plant sources and the utilityattributable exposure is in addition this level. As mentioned above, this will produce 

larger estimate of the IQ decrements attributable to power plants than if each individual’s 

exposure (above or below the RfD) were known and accounted for. To produce an upper 

bound estimate for this analysis, we falsely, but conservatively, assume that all 

individuals are above the RfD from non-U.S. power plant sources. 

 childbearing age have blood Hg levels above the RfD-equivalent level used by the CDC. Thus the 

assumption that all exposed individuals are above the RfD is extremely conservative. 
31

8.5 Monetized value of IQ decrements 

The valuation approach for assessing losses associated with IQ decrements is 

based on an approach used by EPA to assess benefits for reductions in lead exposures 

(EPA, 2000a). For that analysis, EPA used results from a study by Salkever (1995) to 

estimate the effects of IQ loss on expected future earnings and years of education. 

Salkever analyzes data from the National Longitudinal Study of Youth (NLSY) and uses 

a three equation regression model to estimate the relationships between IQ levels, 

educational attainment, and expected future earnings. The results of this study indicate 

that the average effect (for men and women combined) of a one point decrease in IQ is: 

1. A 2.379 percent decrease in future earnings; and 

2. A 0.1007 decrease in years of schooling. 

To estimate the expected monetary value these effects, EPA first estimated the 

average present value of future earnings at the time of birth for a person born in the U.S. 

Using earnings data from the 1992 Current Population Survey (CPS) and discounting at a 

3 percent annual rate, this present value was estimated to be $366,021 in 1992 dollars. 

EPA then estimated the average direct and indirect costs associated with one additional 

year of schooling. Based on Department of Education data, the average annual 

expenditure per student was estimated to be $5,500, and the average annual opportunity 

cost (lost income from being in school) was estimated to be $10,925. Assuming that these 

costs were incurred at age 19 (based on an average of 12.9 years of education among 

those over age 25 in the U.S.) the combined present value of these two costs at time of 

birth (discounted at 3 percent) were estimated to be $9,367 per additional year of 

schooling in 1992 dollars. 

Combining these estimates with the results from the Salkever (1995) study 

summarized above implies that the average present value of net earnings losses 

associated with a one point decrease in IQ is $7,765 in 1992 dollars. This value is 

calculated as the average present value of lost earnings per IQ point loss ($8,708 = 

$366,021 * 0.2379) minus the partially offsetting change in average education costs per 

IQ point loss ($943 = $9,367 * 0.1007). Corrected for inflation using the GDP deflator, 

the average present value of net earnings losses per IQ point loss is $8,807 in 1999 

dollars. The value per IQ estimate using a 7 percent discount rate is $1,580 per IQ 

point.17 In keeping with our desire to produce an upper-bound estimate and given the 

uncertainty in the appropriate value per IQ point, we use the estimate of $8,807. 

8.6 Undiscounted Benefits 

 

17 EPA acknowledges that lost earnings from IQ loss is not the conceptually correct metric for valuing 

benefits of reduced mercury exposure besides the fact that IQ is being used as a surrogate for other subtle 

neurobehavioral endpoints. Ideally, we should use a measure of willingness-to-pay (WTP) to avoid these 

endpoints caused by mercury exposure. However, there is a lack of informative research on which to form 

an estimate of WTP. 
32

Multiplying this value times the IQ decrement for any given IDI value produces 

the estimated undiscounted economic value for that IDI. In other words, this is the 

economic value that the individual would gain if he or she were no longer exposed to any 

utility attributable mercury, which is why it is listed as a benefit. This benefit value can 

also be viewed as the economic loss associated with utility-attributable, post-CAIR 

mercury exposure. 

8.7 Total Benefits 

Since there is a lag between the decrease in deposition and the decrease in 

methylmercury exposure, this economic value must be discounted over some number of 

years to arrive at the economic value of eliminating utility-attributable mercury 

deposition. For freshwater systems, this lag is between 10 and 50 years. As a 

conservative estimate, we can assume a 15 year lag and a 3% discount rate. 

Mathematically, this means that we should divide our undiscounted value by 

approximately 1.6 (= 1.03^15) to arrive at the present value of eliminating utilityattributable mercury emissions18. In other words: 

* ( ) $8,807 * ( ) $5,552 * ( ) 1.03

1

* * ( ) 1

1

15

IQ Decrement IQ Decrement

IQ Decrement

of IQ Decrement

Monetary Value

Discount Rate Monetary Value

Period

Discount

⎟ = ⎠

⎞ ⎜

⎝

⎛ =

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

+ =

For example, an individual born to a mother exposed to methylmercury at an IDI 

of 1 would suffer an economic loss of, roughly, $1,000, assuming non-power plant 

exposures are already above the RfD. Table 8.1 below lists the economic loss associated 

with individuals exposed to various levels of utility-attributable mercury and at various 

consumption levels. 

Table 8.1: Economic Loss from IQ Decrements associated with Mercury Exposure due to 

Freshwater Fish Consumption in 2020 after CAIR 

 At a consumption rate of 8 grams per day, the mean rate for a freshwater 

fisherman, the economic loss from IQ decrements associated with utility-attributable, 

 

18 Using a 3 percent discount rate produces a higher benefits estimate, which is desirable to produce an 

upper bound estimate. Conducting an additional analysis using a 7 percent discount rate, which would be 

standard in a regulatory economic analysis, would require dividing by 2.8. 

2020 with CAIR MeHg % 5th 10th 15th 25th 50th 75th 85th 90th 95th 99th

Discounted Benefits (in dollars) ppm 0 0.001 0.002 0.004 0.01 0.02 0.027 0.035 0.052 0.102

g/day

EPA EFH Mean Recreational Fisher 8 $ 2 - $ 4 $ 7 $ 19 $ 37 $ 50 $ 65 $ 97 $ 190 $ 

EPA OW 90th Percentile General Population 17.5 $ 4 - $ 8 $ 16 $ 41 $ 81 $ 110 $ 142 $ 212 $ 415 $ 

EPA EFH 95th Percentile Recreational Fisher 25 $ 6 - $ 12 $ 23 $ 58 $ 116 $ 157 $ 203 $ 302 $ 593 $ 

EPA EFH 99th Percentile Recreational Fisher 47 $ 11 - $ 22 $ 44 $ 109 $ 219 $ 295 $ 382 $ 568 $ 1,115 $ 

EPA EFH Mean Subsistence Native American 60 $ 14 - $ 28 $ 56 $ 140 $ 279 $ 377 $ 488 $ 725 $ 1,423 $ 

EPA EFH 95th Percentile Subsistence Native American 170 $ 40 - $ 79 $ 158 $ 395 $ 791 $ 1,067 $ 1,383 $ 2,055 $ 4,032 $ 

EPA EFH 99th Percentile Subsistence Native American 295 $ 69 - $ 137 $ 274 $ 686 $ 1,372 $ 1,852 $ 2,401 $ 3,567 $ 6,996 $ 
33

post-CAIR mercury exposure from freshwater fish consumption ranges between zero and 

$190, depending on the amount of deposition. For example, in a watershed with the 85th

percentile utility-attributable mercury deposition, self-caught freshwater fish are assumed 

to have a utility-attributable methylmercury concentration of 0.027 ppm. This translates 

to a discounted economic loss of approximately $50 per birth. 

A similar analysis can be done using the IDI values for marine fish consumption 

and estuarine and coastal fish consumption. For marine fish consumption, we use the IDI 

values reported earlier in this TSD. Since the marine environment produces a longer time 

lag between deposition reductions and exposure reductions, the discount factor for this 

calculation will be slightly different. We use a 3 percent discount rate over 30 years, 

which is the shorter of the two lag times described in Section 2.3, the Marine Cycling 

section, of this TSD. The results of this calculation are reported in Table 8.2. 
34

Table 8.2: Economic Loss from IQ Decrements associated with Mercury Exposure 

due to Marine Fish Consumption in 2020 after CAIR 

2020 with CAIR MeHg Mean 

Discounted Benefits (in dollars) ppm 0.1 

g/day 

Mean Marine Fish Intake 14.1 $ 2 

95% Long-Term Marine Fish Intake 44 $ 7 

Mean Total Fish Intake 20 $ 3 

95% Long-Term Total Fish Intake 63 $ 9 

Median Carrington & Bolger Seafood Consumption 6.8 $ 1 

90% Carrington & Bolger Seafood Consumption 42 $ 6 

95% Carrington & Bolger Seafood Consumption 63 $ 9 

99% Carrington & Bolger Seafood Consumption 123 $ 18 

99.5% Carrington & Bolger Seafood Consumption 141 $ 21 

99.9% Carrington & Bolger Seafood Consumption 207 $ 31 

Assuming a maternal fish consumption rate of 14.1 grams per day of marine fish, which 

is the mean marine fish intake rate, an individual prenatally exposed to utility-attributable 

methylmercury in 2020 would suffer a lifetime economic loss of around $2 from IQ 

decrements. 

8.8 Aggregate Benefits 

 

As described above, the benefits of eliminating mercury emission from U.S. 

power plants in 2020, after the implementation of CAIR, can be estimated by summing 

the economic loss associated with their damage. This is done by multiplying the 

economic loss value times the numbers of births to mothers in each consumption range. 

If we assume that consumption is log-normally distributed, then we can do this by 

multiplying the economic loss for the mean consumption rate times the total number of 

births. 

According to the U.S. Census, the U.S. population in 2001 was roughly 280 

million people (BOC 2005), and there were approximately 4 million births according to 

the CDC’s National Center for Health Statistics (CDC 2002). However, because the 

consumption self-caught fish represents the highest level of utility-attributable exposure, 

it is important to make a distinction between births to self-caught freshwater fishermen 

and those to the general public. Assuming that the ratio of births to individuals for the 

general population holds for the 58 million self-caught freshwater fishers described in 

CAMR, this implies approximately 830,000 births to self-caught freshwater fishers and 

approximately 3.2 million births to the rest of the general public. 

The consumption rate for these two groups can be obtained from the U.S. EPA’s 

Exposure Factors Handbook (US EPA 1997b), which recommends using a mean 

consumption rate for the general population of 20.1 grams of fish per day, with 14.1 

grams associated with marine fish and 6 grams per day of freshwater or estuarine fish 

(including aquaculture consumption). These are the consumption rates we assume for the 

general public. The recommended mean consumption value for freshwater anglers is 8 
35

grams per day of self-caught freshwater fish and we will assume a value of 14.1 grams 

per day from the consumption of marine fish. Multiplying the number of births for each 

group times the economic loss value produces an estimate of the economic benefits of 

eliminating the post-CAIR mercury emission from U.S. power plants. 

The economic loss for an individual consuming self-caught freshwater fish is 

given in Table 8.1. It would be reasonable to conduct a population level analysis using 

the average MeHg exposure at the average consumption level from Table 8, which would 

imply a loss value of $19. However, to maintain a clear upper bound estimate, we use the 

economic loss value $50 for the mean consumption value for the watershed with the 85th

percentile of mercury deposition.19 Multiplying $50 times the 830,000 births to 

freshwater fishers implies an upper bound aggregate economic loss of $41.5 million for 

the consumption of self-caught freshwater fish. 

The upper bound estimate of the individual loss value for marine fish consumed 

by both freshwater fishermen and the general public is $2, as given in Table 8.2. 

Multiplying $2 times the 4 million births from both groups implies an upper bound 

aggregate economic loss of $8 million for the consumption of marine fish. $1.6 million 

of this accrues to freshwater fishers and $6.4 to the rest of the general public. 

Table 8.3 summarizes the fact that the upper bound estimate of the aggregate 

economic benefits of reduced IQ decrements from eliminating utility-attributable 

mercury exposure in 2020 after CAIR are approximately $50 million plus some 

additional amount from the consumption of commercial freshwater, estuarine, and 

aquaculture fish by the general public. The best estimate of the individual economic loss 

from the consumption of these fish is not known because a best estimate of the IDI values 

for these pathways has not been estimated. Therefore a best estimate of the aggregate 

economic loss is unknown. However, we are able to calculate an upper bound estimate as 

described below. 

Table 8.3: Upper Bound Estimate of the Aggregate Economic Benefits of Reduced IQ 

Decrements from Eliminating Utility-Attributable Mercury Exposure in 2020 after the 

Implementation of CAIR 

Population Births Consumption 

Rate (g/day)

Value Benefits 

Freshwater Fishers 58 million 830,000 

 Freshwater Fish 8 $50 $41.5 million

 Marine Fish 14.1 $2 $1.6 million

 

19 If fish were consumed equally from all watersheds, it would be appropriate to use the mean utility 

attributable methylmercury concentration for this calculation. The mean utility attributable methylmercury 

concentration based on available information is .016 ppm. To allow for the possibility that fish are 

generally consumed from areas with a higher utility attributable methylmercury concentrations than the 

mean, we use a utility attributable methylmercury concentration of 0.027 ppm, corresponding to the 85th

percentile. It is highly unlikely that consumption of freshwater fish would be so skewed towards 

waterbodies with such high methylmercury. Therefore this assumption is thought to overestimate the actual 

utility attributable exposure from freshwater fish consumption. 
36

General Public 222 million 3.2 million 

 Freshwater, Estuarine, 

 and Aquaculture Fish 

6 $V B

 Marine Fish 14.1 $2 $6.4 million

Total = $49.5 million + B

As described in Section 4, EPA finds that the utility attributable exposure to 

methylmercury from estuarine fish and shellfish will likely be small relative to that from 

freshwater fish and so the IDI values for this pathway is bound by the freshwater 

recreational/subsistence IDI values presented in the Effectiveness TSD (US EPA 2005a). 

Therefore the bound for the IDI value from estuarine consumption for the mean 

consumption rate of 6 g/day will be 75 percent (6g/8g) of the IDI value for the 

recreational fisher consuming fish from the 85th percentile watershed at the mean 

consumption level. 

Similarly, as described in Section 5, EPA believes that the utility-attributable 

mercury exposure from aquaculture is small and exposure to utility-attributable MeHg 

from aquaculture fish will be lower than the levels ingested from the types of marine fish 

that comprise aquaculture fish feed. Therefore, the $50 value for 8 g/day of freshwater 

fish consumption and the $2 value for 14.1 g/day of marine fish consumption can be used 

to create an upper bound our estimate of $V above. 

As described above, the U.S. EPA’s Exposure Factors Handbook (US EPA 

1997b) recommends a consumption rate of 6 g/day of freshwater, estuarine, and 

aquaculture consumption for the general public. Table 8.4 lists the possible combinations 

of marine equivalent and freshwater equivalent fish that could be used to make up the 6 

g/day. 

Table 8.4: Upper Bound Estimates of Economic Loss from IQ Decrements associated 

with Mercury Exposure due to Freshwater, Estuarine, and Aquaculture Consumption by 

the General Public in 2020 after CAIR 

 Freshwater equivalent consumption (g/day) 

 0 1 2 3 4 5 6 

0 $38 

1 $31 

2 $25 

3 $19 

4 $13 

5 $7 

Marine equivalent 

consumption (g/day) 

6 $1 

 

For example if all of the consumption were marine and aquaculture fish, then the 

economic loss value would be $1. This is because 6 g/day is about 40% of the 14.1 g/day 

of marine fish consumption with an associated economic loss of $2. 40% of $2 is 

(rounding up) about $1. In contrast, if all of the fish were estuarine or freshwater fish, 

then the economic loss would be $38. This is because 6 g/day is 75% of the 8 g/day for 

freshwater fishers with an associated economic value of $50. So 75% of $50 is $38. 
37

 Given this, the highest estimate possible for $V in Table 8.4 is $38. Substituting 

this value in Table 8.3 above would produce a total upper bound estimate of $168 

million. This, however, is a dramatic overestimate of the upper bound estimate of 

benefits. It assumes that the 6 g/day of commercial freshwater, estuarine, and 

aquaculture fish consumed by the general public is as contaminated as the 85th percentile 

of self-caught freshwater fish. In other words all aquaculture fish and all estuary fish, 

including fish from the estuaries on the Pacific coast, are as contaminated as self-caught 

fish. It is, however, useful to state that the aggregate economic benefits of reduced IQ 

decrements from eliminating utility-attributable mercury exposure in 2020 after the 

implementation of CAIR can not be higher than $168 million. 

8.9 Costs 

The methodology for estimating the total annual monetized benefits of CAMR are 

described in the Cost TSD (US EPA 2005b). Under the base-base assumptions, the total 

annual monetized cost of the CAMR is estimated to be approximately $750 million in 

2020.20 

8.10 Summary 

As can be seen from this analysis, the total monetized costs of CAMR exceed the 

total monetized benefits presented here of eliminating all utility-attributable mercury 

emissions remaining in 2020 after the implementation of CAIR. It should again be 

pointed out that the analysis estimates the upper bound monetized benefits associated 

with the potential neuro-toxicity (represented by IQ decrements as a surrogate) of low 

level, chronic mercury exposure. This is the endpoint about which we have the most 

certainty and which we can monetize (see Section 8.4 above). Furthermore, these 

estimates were based on a number of assumptions intended to produce an upper bound 

estimate of the benefits for this endpoint. In contrast, the cost estimate is based on the 

estimated cost of the cap-and-trade program of CAMR which does not eliminate all 

mercury emissions from U.S. power plant. Furthermore, it is generally accepted that, all 

else equal, the cost of cap-and-trade programs are less than other regulatory approaches. 

By 2020 CAMR reduces between 16 percent and 32 percent of the remaining mercury 

emissions, depending upon the species, but does not eliminate all mercury emissions 

from U.S. power plants (See table 3 on page 4 of US EPA 2005c). Given that the 

monetized costs of reducing 1/3 of the current emissions (by one of the lowest cost 

emission reduction schemes available) exceeds the upper bound of monetized benefits of 

reduced IQ decrements, it is reasonable to conclude that the cost of requiring further 

 

20 See table 7-19. The cost associated with monitoring emissions, reporting, and record keeping for 

affected sources is not included in these annualized cost estimates, but EPA has done a separate analysis 

and estimated the cost to be about $76 million (see final CAMR preamble Section VI.B. Paperwork 

Reduction Act). Under the sensitivity analysis described in the Cost TSD, the total annual monetized costs 

are estimated to be $560 million in 2020 (See Cost TSD). We use the estimate of $750 million in 2020 

because it reflects our best estimate, although we note that the conclusions that annual costs exceed annual 

health benefits would equally apply if we were to use the sensitivity analysis cost estimate of $560 million. 
38

reductions in U.S. power plant Hg emissions beyond CAIR would outweigh the benefits 

presented here. 

9. Evaluation of NESCAUM Report 

Recent analyses have attempted to account for exposures from Hg in marine fish, 

including “Economic Valuation of Human Health Benefits of Controlling Mercury 

Emissions from U.S. Coal-Fired Power Plants” (docket item OAR-2002-0056-5749) by 

Glenn Rice and James K. Hammitt, Harvard Center for Risk Analysis (NESCAUM 

Report) (NESCAUM 2005). 

EPA’s approach to modeling exposure and health benefits of reducing emissions 

from power plants differs in some important ways from the approach that NESCAUM 

chose. EPA believes that some of these differences simply reflect the large amount of 

uncertainty in the underlying science. Other differences reflect situations where the 

science and economics are fairly clear and EPA has concerns about the approach that 

NESCAUM took. 

For example, as noted earlier, the NESCAUM report attempted to quantify the 

marine exposure pathway but used assumptions that are not supported by the literature on 

marine fate and transport of Hg, likely resulting in an overestimate by an unknown 

amount. For example, the NESCAUM study assumes that Hg deposition from the 

atmosphere are tracking Hg concentrations in the surface ocean and that the changes in 

ocean fish MeHg concentrations will be proportional to changes in total Hg 

concentrations in the surface ocean. This proportionality assumption was used in 

Section 2 to provide an upper-bound estimate to show that the marine pathway is 

probably not a significant contributor to the mercury exposure from U.S. power plants, 

but we recognized that this was an upper bound estimate. Also, NESCAUM used 

REMSAD modeling which appears to over-predict Hg deposition from US power plants. 

The NESCAUM Report focused on estimating the benefits of reductions in 

mercury exposure from U.S. power plants and did not attempt to estimate upper-bound 

estimate of reducing mercury emissions for power plans. However, for the additional 

reasons noted below EPA believes that NESCAUM’s approach should be interpreted as 

producing an upper-bound estimate of the IQ benefits of reducing Hg emissions from 

power plants for two reasons. First, it does not appear that the NESCAUM Report took 

into account the timeframe for reduced exposure to MeHg this issue into account. This 

omission alone leads to the benefits in the NESCAUM Report being overstated by at least 

factor of two. Second, EPA commissioned Harvard researchers Dr. Louise Ryan and Dr. 

David Bellinger to perform an integrated analysis of the three major epidemiological 

studies (Faroes, Seychelles, New Zealand) and used the resulting relationship between 

exposure and neurological problems. NESCAUM relied in part on an unpublished study 

and produces estimated neurological benefits four to five times EPA estimates for this 

reason alone. 
39

9.1 Timeframe for costs and benefits 

It is important to consider the time in an economic analysis because future costs 

and benefits are discounted. EPA’s Revision Rule analyses took into account the 

timeframe for costs and benefits. As noted in Section 8, benefits were discounted to take 

into account the response times for the freshwater and marine ecosystems. Case studies of 

individual ecosystems show that the time necessary for aquatic systems to reach a new 

steady state after a reduction in Hg deposition rates can be as short as 5 years or as long 

as 50 years or more. The medium response scenarios also varied widely but were 

generally on the order of one to three decades. Overall, EPA concludes that the most 

likely appropriate response times for freshwater ecosystems to be considered in the 

national scale assessment range between 5 and 30 years, while recognizing that some 

systems will likely take more than 50 to 100 years to reach steady state. Our preliminary 

analysis of the temporal response of marine systems based on the model by Mason and 

Gill (2005) indicates that the Atlantic Ocean will take approximately three decades to 

reach steady state and the Pacific Ocean will take over two centuries. 

At 3 percent and two to three decades, present value benefits would decrease by 

about half. At 7 percent, present value benefits would fall even more. This shows the 

importance of taking into account the time lag between emissions reductions and 

exposure reductions. EPA does not believe that NESCAUM accounted for this important 

factor in its analysis and in so doing significantly overestimates benefits. 

9.2 IQ dose-response relationship 

In the benefits analysis presented above, EPA chose to focus on quantification of 

intelligence quotient (IQ) decrements associated with prenatal Hg exposure as the initial 

endpoint for quantification and valuation of Hg health benefits. Reasons for this initial 

focus on IQ include the availability of well-designed epidemiological studies assessing 

IQ or related cognitive outcomes suitable for IQ estimation, and the availability of wellestablished methods and data for economic valuation of avoided IQ deficits, as applied in 

EPA’s previous benefits analyses for childhood lead exposure. 

There is limited evidence directly linking IQ and MeHg exposure in the three 

large epidemiological studies that were evaluated by the National Academy of Sciences 

(NAS) and EPA. Based on its evaluation of the three studies, EPA believes that children 

who are prenatally exposed to low concentrations of MeHg may be at increased risk of 

poor performance on neurobehavioral tests, such as those measuring attention, fine motor 

function, language skills, visual-spatial abilities (like drawing), and verbal memory. For 

this analysis, EPA is adopting IQ as a surrogate for the neurobehavioral endpoints that 

NAS and EPA relied upon for the RfD. 

The NAS identified three well-designed studies (Faroes, Seychelles, New 

Zealand) of the neurotoxicological effects of MeHg. “Each of the studies was well 

designed and carefully conducted, and each examined prenatal MeHg exposures within 

the range of the general U.S. population exposures” (NRC 2000). In order to develop a 
40

dose-response relationship that reflects all three studies identified by the NAS, EPA 

commissioned Harvard researchers David Bellinger and Louise Ryan to perform an 

integrated analysis, combining results from all three studies. When combined, the 

statistical power of the analysis increases. While the size of the dose-response 

relationship declined relative to past studies with a statistically significant finding, Ryan 

found a statistically significant relationship between IQ and Hg. The confidence interval 

did not include zero. EPA used Ryan’s mean estimate -0.131 as a coefficient to relate 

changes in exposure (parts per million in hair) to IQ point changes. EPA also performed 

sensitivity analysis using coefficients of -0.108 and -0.233 also based on the work by 

Louise Ryan and David Bellinger. (Ryan 2005).21

NESCAUM appears to have used a coefficient of -0.60 based on an unpublished 

study (Cohen, et al. full reference unavailable) that is not included in the references. The 

paper upon which NESCAUM based its coefficient has not been submitted to the 

rulemaking docket, making it difficult for us to assess the NESCAUM approach. 

However, the reliance on a coefficient of -0.60 is not consistent with the work done by 

Harvard researchers Louise Ryan and David Bellinger or the other existing studies. 

9.3 Conclusion 

Unlike the analyses conducted for this reconsideration which provide an estimate 

of the upper-bound of IQ benefits associated with reduced mercury emissions from power 

plants, the NESCAUM Report estimates are presented as “central” or “best” benefits 

from marine fish Hg reductions. Further even if presented as upper-bound estimates, 

there is a disconnect between the derivation of quantitative results and the summary of 

the science since authors relied on a variety of unsupported assumptions. 

10. 2010/2015 CMAQ Modeling Results 

The Technical Support Document (TSD) for the Final Clean Air Mercury Rule: 

Air Quality Modeling, March 2005, describes in Section V.B. that the expected mercury 

deposition with CAIR plus CAMR in 2015 is expected to be similar to the mercury 

deposition with CAIR plus CAMR in 2020. Since the March 2005 CAMR TSD was 

prepared, a combined strategy consisting of the implementation of CAIR, CAMR and 

 

21 Ryan and David develop a linear model that goes through the origin to fit population-level doseresponse relationships to the pooled data from the three studies. The application of a linear model should 

not be interpreted to suggest that any of the three studies used have data showing health effects from MeHg 

exposure at or below the RfD. Use of a linear model that goes through the origin, rather than one that 

reflects a threshold effect is technically more simple and practical. It associates an increment of IQ benefit 

with a given reduction in exposure. A linear model allows us to estimate the benefits of reductions in 

exposure due to power plants without a complete assessment of other sources of exposure. Other models 

would require information on the joint distribution of exposure from power plants and other sources to 

estimate the benefits of reducing the exposure due to power plants, which would require much more precise 

information about consumption patterns. 
41

CAVR has been modeled with CMAQ for 2010, 2015 and 2020. The BART rule 

indicates that States that opt into the CAIR trading program do not have to do anything 

more for BART for their eligible utility sources. Therefore, CAIR satisfies BART for 

utilities for the CAIR States. Thus, in the CAIR States, there would be no further 

reductions in utility mercury emissions from BART. It is only, in the States where CAIR 

does not apply that the implementation of BART would possibly lead to additional 

mercury reductions over those that would occur with CAIR and CAMR. 

The total utility mercury emissions for the each of the Clear Skies CAIR-CAMRBART scenarios are shown in Table 10.1. More importantly, the utility mercury 

emissions of the most readily depositable form of mercury emissions (Reactive Gaseous 

Mercury) for each of these scenarios are also shown Table 10.1. It can be seen in Table 

10.1 that there is a large (approximately 11 ton) decrease in utility reactive gaseous 

mercury (RGM) emissions from 2001 to 2010. The reduction in RGM emissions from 

2010 to 2015 is approximately 2 tons and the reduction in RGM emissions from 2015 to 

2020 is only approximately 1 ton. 

The total modeled mercury deposition for 2010, 2015 and 2020 under 

CAIR/CAMR/BART are provided below in Figures 10.1 through 10.3. It can be seen in 

Figures 10.1 through 10.3 that the total mercury depositions with CAIR/CAMR/BART 

are very similar in 2010, 2015 and 2020. The reduction in total mercury deposition from 

2001 to 2010, 2015 and 2020 with the implementation of CAIR/CAMR/BART are shown 

in Figures 10.4 through 10.6. It can be seen in figures 10.4 through 10.6 that the 

difference in the decrease in total mercury deposition between 2010, 2015 and 2020 

relative to 2001 are fairly small. Figure 10.7 provides the reduction in total mercury 

deposition between 2010 and 2015 and Figure 10.8 provides the reduction in total 

mercury deposition between 2015 and 2020. It can be seen in Figure 10.7 that the 

reductions in total mercury deposition from 2010 to 2015 cover scattered areas of the 

country with the reductions less than 5 ug/m2. It can be seen in Figure 10.8 that the 

reductions in total mercury deposition from 2015 to 2020 cover only scattered small areas 

of the country with the reductions generally less than 5 ug/m2

. It can be seen by 

examining Figures 10.4, 10.7 and 10.8 that there is a much larger reduction in utility 

attributable mercury deposition from 2001 to 2010 than from 2010 to 2015. The 

reduction in utility attributable mercury deposition from 2015 to 2020 is even smaller 

than the reduction from 2010 to 2015. 

The mercury deposition reductions shown in Figures 10.4 through 10.6 look very 

similar to the reduction in mercury deposition that would occur from 2001 with the 

implementation of CAIR and CAMR in 2020, which were modeled under the CAMR 

rule, and are shown below in Figure 10.9. The additional reductions in 2020 total 

mercury depositions that would occur relative to 2001 with the implementation of BART 

in addition to CAIR and CAMR are provided in Figure 10.10. As can be seen in Figure 

10.10, the maximum additional reduction with BART is less than 4 ug/m2 in all locations. 

The additional reductions with BART are outside the eastern States covered by CAIR.
42

Table 10.1. Utility Mercury Emissions for Clear Skies Act CAIR-CAMR-BART 

Scenario (tons/year) 

Year Reactive Gaseous Mercury Total Mercury Emissions 

 

2001 20.6 48.6 

2010 9.7 32.1 

2015 7.2 28.7 

2020 6.1 25.5 

Figure 10.1. Total Mercury Deposition with CAIR/CAMR/BART: 2010 
43

Figure 10.2. Total Mercury Deposition with CAIR/CAMR/BART: 2015 

Figure 10.3. Total Mercury Deposition with CAIR/CAMR/BART: 2020 
44

 

Figure 10.4. Reduction in Total Mercury Deposition: 2010 with 

CAIR/CAMR/BART Relative to 2001 

Figure 10.5. Reduction in Total Mercury Deposition: 2015 with 

CAIR/CAMR/BART Relative to 2001
45

Figure 10.6. Reduction in Total Mercury Deposition: 2020 with 

CAIR/CAMR/BART Relative to 2001 

Figure 10.7. Reduction in Total Mercury Deposition with CAIR/CAMR/BART: 

2010 to 2015 
46

Figure 10.8. Reduction in Total Mercury Deposition with CAIR/CAMR/BART: 

2015 to 2020 

Figure 10.9. Reduction in Total Mercury Deposition with CAIR/CAMR: 2020 

Relative to 2001 
47

Figure 10.10. Reduction in Total Mercury Deposition with BART in addition to 

CAIR and CAMR: 2020 Relative to 2001 

11. Global Source Impact 

A CMAQ 2001 modeling run was performed after the CAMR rule was finalized 

to estimate the impact of global sources. In this model run, all mercury boundary 

condition input species to CMAQ that were obtained from the GEOS-CHEM global 

model were zeroed-out. By comparing this run with the 2001 base case run, which 

included the mercury boundary condition species input to CMAQ, the percent of total 

mercury deposition attributable to global sources can be estimated. The model estimated 

percent of total mercury deposition attributable to global sources is provided below in 

Figure 11.1. The scientific understanding of mercury atmospheric chemistry is still 

evolving. Changes in the current understanding of mercury chemistry could possibly 

lead to the need to change the mercury chemistry in the global GEOS-CHEM and 

regional CMAQ models. Thus, it should be noted that there is considerable uncertainty 

associated with the estimates of global source impacts. 
48

Figure 11.1. Percent of Total Mercury Deposition Attributable to Global Sources: 

2001 
49

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