Policy Analysis Evaluating the Potential Efficacy of Mercury Total Maximum Daily Loads on Aqueous Methylmercury Levels in Four Coastal Watersheds S A R A H E . R O T H E N B E R G , * ,† R I C H A R D F . A M B R O S E , †,‡ A N D JENNIFER A. JAY§ Environmental Science and Engineering Program, Department of Environmental Health Sciences, and Department of Civil and Environmental Engineering, University of California, Los Angeles, California 90095
Received November 9, 2007. Revised manuscript received April 9, 2008. Accepted April 14, 2008.
Of the ∼780 U.S. EPA approved mercury total maximum daily loads (TMDLs), most specify a reduction in total mercury (HgT) loads to reduce methylmercury levels in fish tissue, assuming a 1:1 correspondence. However, mercury methylation is more complex, and therefore, proposed load reductions may not be adequate. Using multiple regression with microlevel and macrolevel variables, the potential efficacy of mercury TMDLs on decreasing aqueous methylmercury levels was investigated in four coastal watersheds: Mugu Lagoon (CA), San Francisco Bay Estuary, Long Island Sound, and south Florida. HgT and methylmercury levels were positively correlated in all watersheds except in Long Island Sound, where spatial differences explained over 40% of the variability in methylmercury levels. A mercury TMDL would be least effective in Long Island Sound due to spatial heterogeneity but most effective in south Florida, where the ratio between aqueous HgT and methylmercury levels was close to 1 and the 95% confidence interval was narrow, indicating a probable reduction in aqueous methylmercury levels if HgT loads were reduced.
Introduction Mercury (Hg) is a persistent pollutant and once released into the environment may be transformed to methylmercury (MeHg), a potent neurotoxin. In the U.S., 45 states and territories report fish consumption advisories due to elevated Hg levels within at least one water body (1). Under section 303(c) of the Clean Water Act, states and authorized tribes must adopt water quality criteria to protect designated uses, while section 303(d) requires states and tribes to identify, list, and establish priority ranking for waters that do not meet water quality standards. Currently, ∼8500 separate water bodies are identified on state 303(d) lists for Hg impairments in either water, sediments, and/or fish tissue (2). Listing requires the development of a total maximum daily load (TMDL), defined as the amount of pollutant a water * Corresponding author phone: (310) 267-4654; fax: (310) 2062222; e-mail:
[email protected]. † Environmental Science and Engineering Program. ‡ Department of Environmental Health Sciences. § Department of Civil and Environmental Engineering. 5400
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body can assimilate without exceeding water quality standards. To date, ∼780 Hg TMDLs are approved by the U.S. EPA (2). In 2001, the U.S. EPA recommended a fish tissue residue water quality criterion for MeHg (0.3 ppm) rather than a water column-based criterion, as fish consumption was considered to be the dominant exposure pathway for MeHg (3). To decrease MeHg levels, many states developed Hg TMDLs assuming a reduction in aqueous total Hg (HgT) loads would result in a 1:1 reduction in fish tissue MeHg concentrations (e.g., refs 4–6). However, the relationship between HgT and MeHg is more complex as Hg methylation is a process primarily mediated by microbes, specifically some strains of sulfate-reducing bacteria (SRB) (7, 8) and some closely related iron-reducing bacteria (9, 10). Environmental factors that promote microbial activity and/or increase the bioavailability of Hg, such as pH, temperature, organic matter, and dissolved iron and sulfide levels, affect Hg methylation potential (11–13). The correlation between HgT and MeHg levels may also be a function of ecosystem type (14), loading rates (15), and whether Hg is considered “legacy” Hg or newly deposited (16, 17). Using linear regression, the potential outcome of HgT load reductions on aqueous MeHg levels was compared within four U.S. coastal watersheds: Mugu Lagoon, CA (Calleguas Creek Watershed), San Francisco Bay Estuary, Long Island Sound (LIS) and Connecticut River, and south Florida. While data from three of the four sites were previously discussed (Mugu Lagoon (18), San Francisco Bay (19), and LIS 20, 21), the potential effect of HgT load reductions on MeHg water column concentrations was not thoroughly addressed. Given the ubiquitous nature of Hg in U.S. surface waters and the need for effective regulatory feedback, it is important to reanalyze these datasets. Unlike other metals that are not bioaccumulative, typical effluent limits are set for unfiltered HgT levels, and therefore, only unfiltered surface water HgT data were included in this analysis (40 CFR 122.45c). Both unfiltered and filtered aqueous MeHg levels were used as surrogates for fish tissue levels, as lower aqueous MeHg levels will likely lead to lower fish tissue MeHg levels.
Site Descriptions and Regulatory Background Mugu Lagoon, CA. Mugu Lagoon is a shallow (255 pM, California’s Toxics Rule criterion for HgT, 40 CFR 131.38), which triggered the development of a TMDL (approved by the U.S. EPA, March 2007). Potential sources of HgT and MeHg include six water treatment facilities, urban runoff, military runoff (22), historical use of agricultural fungicides (23), Hg runoff from Rocketdyne, a rocket-testing facility (24), and atmospheric deposition of Hg from local annual fires and long-range sources. In the winter and summer of 2005, Hg cycling was investigated in surface water, pore water, and sediments at 10 sites throughout the lagoon, within four habitats: mudflats, tidal creeks, marsh plain, and upland (18). All fieldwork followed high tide, although some sites were measured during neap tide and some during spring tide. Laboratory analyses were completed at the University of California, Los Angeles. San Francisco Bay Estuary. The San Francisco Bay is the largest estuary in the western U.S. Between 1996 and 2002, the entire estuary was 303(d) listed for Hg, due to elevated Hg levels in fish tissue (2). Sources of Hg included runoff 10.1021/es702819f CCC: $40.75
2008 American Chemical Society
Published on Web 06/25/2008
TABLE 1. Summary Statistics for Each Site: Sample Size (n), Mean, Standard Deviation (SD), and Range for Unfiltered HgT, Unfiltered MeHg, Filtered MeHg, and Percent MeHg (of Unfiltered HgT)a (1)
n
mean
SD
range
HgT (pM) unfiltered MeHg (pM) filtered MeHg (pM)
29 29 18
22 1.2 0.35
21 1.7 0.35
0.88-86 0.064-7.5 0.069-1.4
(2)
n
mean
SD
range
HgT (pM) unfiltered MeHg (pM) filtered MeHg (pM)
129 95 66
70 0.45 0.23
85 0.46 0.26
0.70-440 0.060-2.3 0.015-1.6
(3)
n
mean
SD
range
HgT (pM) unfiltered MeHg (pM)b filtered MeHg (pM)
45 34 9
12.8 0.543 0.340
8.85 0.582 0.332
1.36-46.2 0-2.91 0.060-0.990
(4)
n
mean
SD
range
HgT (pM) unfiltered MeHg (pM) filtered MeHg (pM)
248 219 318
7.0 0.73 0.11
5.4 1.1 0.14
0.35-32 0.075-8.5 0.010-1.3
n unfiltered % MeHg filtered % MeHg
unfiltered % MeHg filtered % MeHg
28 18
mean
SD
range
9.3 2.2
12 2.1
0.84-43 0.17-7.3
n
mean
SD
range
95 65
1.6 0.66
2.4 0.95
0.092-13 0.0037-4.9
unfiltered % MeHg filtered % MeHg
n
mean
SD
range
34 9
5.86 2.40
9.21 2.67
0-43.2c 1.20-7.12
n unfiltered % MeHg filtered % MeHg
217 110
mean
SD
range
10 9.8
9.4 9.0
0.93-54 1.2-45
a (1): Mugu Lagoon, CA (data from ref 18). (2): San Francisco Bay Estuary (data analyzed in ref 19 and available from www.sfei.org/rmp). (3): LIS and Connecticut River (at Haddam, CT) (data from refs 20 and 21). (4): Florida Everglades (data from www.epa.gov/storet). b For just the particulate aqueous fraction, n ) 23, mean ) 0.681, SD ) 0.630, and the range did not change. c When two observations were removed, mean ) 3.84, SD ) 3.06, and the range ) 0.270-9.67.
from historical Hg and gold mines, urban runoff, wastewater discharges, atmospheric deposition, and resuspension of historical deposits of Hg-laden sediment deposited in the San Francisco Bay (5, 19). Conaway et al. (19) characterized the distribution of HgT and MeHg in aqueous- and solid-phase samples at 26 sites throughout the southern, central, and northern reaches of the San Francisco Bay Estuary (data also available from www.sfei.org/rmp). Aqueous samples were analyzed at the University of Maryland Chesapeake Biological Laboratory and/or Brooks Rand LLC in Seattle. LIS and Connecticut River. LIS is one of the nation’s largest urbanized coastal estuaries. LIS was not 303(d) listed for Hg as prior analysis of fish tissue fell below the listing criterion of 0.1 ppm (Paul Stacey, CDEP, personal communication, (25)). Freshwater sources to LIS, including the East River and portions of the Connecticut River, Housatonic River, and Thames River, are 303(d) listed for Hg, and there is a statewide freshwater fish consumption advisory in Connecticut for Hg (2). Aqueous- and solid-phase samples were analyzed at the University of Connecticut and reported by Vandal et al. (20) and Balcom et al. (21). For this statistical analysis, only samples collected at 8000 km2 of
the south Florida Everglades (27). Atmospheric deposition from local urban point sources is considered the primary source of inorganic Hg(II) to the watershed (28–31). The dataset for south Florida was obtained from the U.S. EPA Storet website (www.epa.gov/storet) and includes only aqueous samples analyzed by Frontier Geosciences, Inc. Fieldwork was completed between December 1994 and June 2004, at 49 sites within the Everglades agricultural area and water conservation areas. Although runoff from the Everglades flows into the Florida Bay Estuary, this portion of the watershed is fresh water.
Materials and Methods Laboratory Methods. For all four sites, EPA Methods 1630 and 1631 (32, 33) were employed for the determination of aqueous MeHg and HgT, respectively, using established protocols (34–38). Reported HgT and MeHg detection levels were acceptable (Mugu Lagoon 1.2 and 0.067 pM; San Francisco Mugu Lagoon (0.014) > LIS (0.013) > San Francisco Estuary (0.0032). All four were below the recommended translator for estuarine environments (0.19 (3)). This disparity reflects the importance of site-specific calculations and may also be due to the low number of sites used to develop the national translator (n ) 2 (3)). When trying to determine the effect of HgT load reductions, MeHg translators are not effective due to site-specific differences and the lack of linearity between MeHg and HgT levels in some watersheds. For the remainder of this analysis, unfiltered MeHg levels are used for regression models. Spatial Heterogeneity. LIS was the only site where the concentration of HgT did not add information to the regression model (see eq 10 and Figure 1). Instead, spatial differences in MeHg levels between east LIS, west LIS, and Connecticut River were more important and explained 40% of the variability in MeHg levels (Table S2 and Figure S1). LIS was the only site with two connections to the Atlantic Ocean: through the East River/NY Harbor to the west and through the Race and Block Island Sound to the east. Vandal et al. (20) reported spatial differences in the distribution of HgT and MeHg levels across LIS and attributed this to higher wastewater treatment effluent from the East River (in the western end of LIS), which traveled eastward where seawater dilution was higher. Hammerschmidt and Fitzgerald (44) observed a spatial gradient (high to low, west to east) in HgT levels and methylation potential in the sediments. Regression VOL. 42, NO. 15, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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results confirm the importance of spatial differences; MeHg levels were on average 8.1 times higher in west LIS as compared to east LIS (8.1 is the ratio of the intercepts between the two regions, 10(-0.27)/10(-2.7-0.91); see SI). Spatial variability also added information to the regression model for the San Francisco Estuary (eq 9, Table S2). Residuals indicated the model overpredicted in the central and northern reaches of the estuary but underpredicted in the southern reaches (Figure S1). In addition, salinity levels were spatially dependent, with lowest salinity measured near freshwater inputs where MeHg levels were also highest. Conaway et al. (19) reported higher MeHg levels in the southern reach of the estuary, where wastewater treatment plants are concentrated. The authors suggested wastewater emptying into the southern reach may be an external loading source of MeHg or high nutrient inputs may enhance Hg methylation. Although Hg inputs are high in the northern reach due to historical gold mining, MeHg levels in surface water are on average 2.1 times higher in the southern and central areas (2.1 ) 10(1.3)/10(1.3-0.32); see SI). Spatial variability within a water body is not usually addressed by regulators; most TMDL analyses assume the assimilative capacity within a water body is homogeneous. These results demonstrate subregions may differ significantly, and therefore, one TMDL may not restore beneficial uses throughout an entire water body. Importance of Additional Parameters. For Mugu Lagoon and the San Francisco Estuary, additional water quality parameters and site characteristics were measured, which added information to the regression model. For Mugu, the correlation coefficient (r2) increased from 0.30 to 0.58 when temperature and pH levels were included in the model (Table S1a); for San Francisco, r2 increased from 0.28 to 0.65 when temperature, salinity, and pH levels were included (Table S1b). Warmer temperatures enhance microbial activity, which may increase Hg methylation (10, 45), while pH levels affect mercury-sulfide speciation (18). In San Francisco, salinity levels were likely a proxy for spatial variability (i.e., freshwater was highest in the southern reach, where wastewater inputs and MeHg levels were also higher). Other parameters may be important determinants for MeHg levels, although for these coastal sites, HgT levels may be the only constituent that can be regulated through a Hg TMDL. It is important to acknowledge estimates for south Florida and LIS would likely differ if additional parameters were available for these sites. The values for r2 were 0.32 and 0.41, respectively, indicating a high fraction of variability in MeHg levels was unexplained. For comparison, simple linear regression models were determined for MeHg levels at Mugu and San Francisco without additional parameters. The new regression estimates were 0.51 ( 0.33 (Mugu) and 0.39 ( 0.13 (San Francisco). Both estimates of the slope increased, although 95% CIs were wider, indicating less certainty. Potential Effect of HgT Load Reductions. Using the regression coefficients for HgT levels, the potential effect of HgT load reductions on aqueous MeHg levels was evaluated for each impaired site (eqs 8, 9, and 11). Mugu Lagoon. The Calleguas Creek Metals TMDL (including Hg) recommended ∼85% reduction in HgT aqueous loadings to reduce MeHg levels in fish tissue in Mugu Lagoon (4). Proposed HgT reductions were based on median MeHg levels in predator fish tissue (0.55 ppm) and the percentage reduction required to meet numeric targets (4). An 85% reduction in HgT loadings may result in a 51% decrease in average aqueous MeHg levels (51% ) 1-0.150.38; 95% CI: 17-71%). From the previous section, using the results from simple linear regression (slope ) 0.51 ( 0.33), a 62% reduction in MeHg levels is expected (95% CI: 29-80%). Because of the wide CI using either estimate (>50%), it is difficult to predict the effectiveness of decreased HgT loadings. A higher number 5404
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of samples is needed to reduce uncertainty in the regression estimate. Additionally, to reduce MeHg levels in surface water by 85%, a minimum 99% reduction in HgT loads is required (82% ) 1 - 0.010.38), which is not likely achievable. San Francisco Bay. Assuming a 1:1 proportional relationship between reduction in HgT loads and average MeHg fish tissue concentrations, the San Francisco Bay Mercury TMDL recommended a 43% overall reduction in HgT loadings (5). On the basis of the regression model, this may result in a 15% decrease in MeHg levels (15% ) 1-0.570.28; 95% CI: 9.6-19%). For comparison, using the simple linear regression result from the previous section (slope ) 0.39 ( 0.13), a 20% reduction is predicted (95% CI: 14-25%). Compared to results for Mugu Lagoon, CIs for both estimates were not as wide (∼10%), but due to the large ratio between HgT and MeHg levels, a higher reduction in HgT loadings is necessary. For example, if HgT levels were reduced by 85% (as recommended for Mugu Lagoon), aqueous MeHg levels may decrease by 41% (41% ) 1-0.150.28; 95% CI: 29-51%). San Francisco was the only site where the dissolved MeHg levels were not correlated with HgT concentrations (Regression Models), indicating more uncertainty in achievement of numeric targets. South Florida. Of the four sites analyzed, a Hg TMDL in south Florida would have the greatest effect on MeHg levels due to the low ratio between HgT and MeHg (100:84) and the relatively low level of uncertainty (95% CI: 68-100%). The Everglades Mercury TMDL Pilot Study found a nearly 1:1 linear relationship between Hg deposition and uptake in fish tissue (30). The Everglades study employed two modeling methods, one to simulate the atmospheric transport of Hg from point sources in southern Florida to the Everglades and one to estimate the fate and transport of Hg within the aquatic environment as well as bioaccumulation in the food web (30). In addition to providing a linkage between these parameters and Hg air deposition, results from the model predicted fish tissue levels would fall below 0.5 ppm within 40 years, if atmospheric emissions were reduced by 85%. Using the regression estimate, an 85% decrease in HgT concentrations may correspond to an 80% reduction in aqueous MeHg levels (80% ) 1-0.150.84; 95% CI: 72-85%). Compared to the other three watersheds, reductions in HgT loadings in south Florida would have the greatest impact on aqueous MeHg levels. Importance of Site-Level Characteristics. Results in the previous section showed the stronger the relationship between HgT and MeHg levels, the more likely a Hg TMDL will be effective. The strength of the relationship between HgT and MeHg levels may be a function of site-level characteristics (i.e. macrolevel variables), including the number of tidal outlets, average precipitation levels, median HgT levels in precipitation, and percent wetland coverage. These are discussed next. The number of tidal outlets may impact MeHg levels by affecting residence time in a watershed. The three coastal sites (Mugu Lagoon, San Francisco Bay, and LIS) are open to the ocean, where tidal flushing may export MeHg to the ocean. This was more evident in LIS, where there were two outlets to the Atlantic Ocean. In south Florida, water from Lake Okeechobee travels thousands of kilometers through wetlands where inorganic Hg(II) may be methylated before reaching the Everglades National Park and ultimately emptying into the Florida Bay Estuary. The lack of tidal influence leads to increased residence time in the Everglades, which may contribute to higher in situ Hg methylation. Average precipitation levels and median HgT levels in precipitation may both contribute to variability in MeHg levels within a site. Recent studies from METAALICUS in the Experimental Lakes Area of Canada showed newly deposited atmospheric Hg is more bioavailable than legacy Hg (17). In
addition, higher wet depositional flux of Hg is associated with increased MeHg levels in fish tissue (46). In Florida, atmospheric deposition is considered the primary source of inorganic Hg(II) to the Everglades Watershed (28–31), unlike Mugu Lagoon and San Francisco, where runoff (e.g., mining, urban, military, and agricultural) is more important (18, 19). Average precipitation levels are ranked as follows: south Florida (135 cm, (47)) > LIS (106 cm, Paul Stacey, CDEP, personal communication) > San Francisco (50.5 cm, (48)) > Mugu Lagoon (36.4 cm, (48)). Median HgT levels in precipitation are ranked as follows: south Florida (59.48 pM) > Mugu (50.43 pM) > San Francisco (47.45 pM) > LIS (29.18 pM) (ref 49 and Table S3). Higher MeHg levels in South Florida also may reflect higher Hg methylation rates due to greater percent wetland coverage. Wetlands are considered important sites for in situ Hg methylation due to environmental factors that promote microbial activity and increase the bioavailability of Hg (50–53). Even though millions of acres of the Everglades wetlands were lost to agricultural development in the last century (26), the water conservation areas are still wetland (Linda Crean, SFWMD, personal correspondence), which comprise ∼65% of the area for this analysis. Percent wetland at Mugu was similar to south Florida (64% (54)), while percent wetland was 16% of the San Francisco Bay surface area (55) and only 3% of the LIS drainage area (56). For macrolevel analysis, the concentration of MeHg was regressed on HgT levels for each of the sites, and then the slopes were regressed on macrolevel variables (Figure 2). For LIS, observations from east LIS were deleted, as these five observations were highly influential (n ) 33 with these sites and n ) 28 without). Intercepts for three of the regression models were comparable (Mugu: -0.75, San Francisco: -1.1, and Florida: -1.0), indicating at low concentrations of HgT the influence of HgT on MeHg levels was similar across these three sites (Figure 2a). The slopes varied as HgT levels increased, with higher net Hg methylation associated with no tidal outlets (r2 ) 0.98, p ) 0.01), higher median levels of HgT in precipitation (r2 ) 0.93, p ) 0.04), and higher percentage of wetland (r2 ) 0.76, p ) 0.13) (Figure 2b-d). Regression slopes were least correlated with average precipitation levels (r2 ) 0.05, p ) 0.78) (figure not shown). Results indicate lower atmospheric levels of Hg may decrease MeHg levels in surface water in the following order: south Florida > Mugu > San Francisco > LIS. Significant results (p < 0.05) for a small dataset are unexpected (n ) 4); however, additional sites are needed (at least 20) to verify these findings. Although this analysis is limited to four sites, these results suggest there are ways to improve Hg TMDLs. First, spatial variability should be addressed in TMDLs by developing separate load and wasteload allocations for regions of the water body where the assimilative capacity differs. Second, a 1:1 correspondence between HgT and MeHg levels may not be an accurate assumption. In sites where the regression coefficient for HgT is ,1, a higher margin of safety should be incorporated to ensure MeHg concentrations are reduced. Macrolevel analysis indicated higher HgT levels in precipitation are associated with a stronger relationship between HgT and MeHg levels; therefore, lowering atmospheric Hg emissions may decrease net Hg methylation. This is important as atmospheric emissions are a controllable source. Lastly, a substantial portion of MeHg variability in these four sites is unknown, even with additional predictors in the regression model (r2 ) 40-70%). Inclusion of more parameters is needed to develop a comprehensive picture of impaired sites.
Acknowledgments This work was funded by the Los Angeles Water Quality Control Board, the Calleguas Creek Municipal Water District,
the UC Toxics Substances Research and Teaching Program, and a NSF Career Award to J.A.J. (BES-0378483). The authors thank Profs. Bill Fitzgerald and Russ Flegal for permission to include their data and two anonymous reviewers who provided insightful comments.
Supporting Information Available Supporting Information includes text for laboratory methods and interpretation of regression coefficients, regression results (Tables S1 and S2), data from the Mercury Deposition Network (Table S3), and graphs of residuals for San Francisco Bay Estuary and Long Island Sound regression models (Figure S1). This material is available free of charge via the Internet at http://pubs.acs.org.
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