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A Methylmercury Budget for San Francisco Bay Donald Yee, San Francisco Estuary Institute.

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Presentation on theme: "A Methylmercury Budget for San Francisco Bay Donald Yee, San Francisco Estuary Institute."— Presentation transcript:

1 A Methylmercury Budget for San Francisco Bay Donald Yee, San Francisco Estuary Institute

2 Mercury Conceptual Model System is complicated, simplified by single box model Slow response (decades) MeHg matters most (to biota)

3 Methylmercury Conceptual Model Need to track MeHg MeHg <1% of totHg Poor MeHg:totHg correlation Differences from Hg 1 Box Model Methylation & demethylation Potentially rapid (days- months) Sed-water exchange Meth Demeth

4 WWMMBD? What Would the MeHg Mass Budget Do? Synthesize- do Bay data make sense given… –Loading, production, degradation, sed-water exchange, and other processes? Quantitative conceptual model of MeHg –ID key factors for MeHg fate Feasibility/needs of refined model(s) –E.g. temporal & spatial detail What it won’t/can’t do –Identify “hot” spot impacts (1 box) –Predict long term fate (no Hg linkage)

5 MeHg 1 Box Model Adapted from PCB 1 box model –One water compartment –One sediment compartment (10cm mixed layer) –Daily time step –Annually uniform (no seasonality) –Constant uniform mixing –Equilibrium partitioning Simplifications worked for PCBs, PBDEs

6 External Loads (Imports) +Direct atmospheric (wet) deposition 0.1 g/d Area x literature rain MeHg x local rainfall +Delta (Mallard Island) discharge 9.8 g/d Flow x concentration (Region 5 MeHg TMDL) +Local watersheds 4.9 g/d RMP measured watersheds (extrapolated) +Wetlands (upper range estimate) 2.0 g/d Volume x (incoming - outgoing) concentrations +POTWs (16 largest, ~95% discharge) 0.8 g/d Flow x concentration = 17.6 g/d total

7 Internal Load- MeHg Production Function of multiple factors- –Would need complex C & S & Hg model Next best- lab incubation production rates? –Marvin-DiPasquale et al anaerobic incubations Assume portion of sediment layer methylates –Methylating zone in fraction (30%) of sediment

8 Loss Processes Bio-uptake = “export” from Bay 0.13 g/d –Small fish biomass (CDFG) x concentration (RMP) 1-Box Model Losses Volatilization –Air/water partitioning (Lindqvist & Rodhe 1985) Outflow (through Golden Gate) –Tidal mixing (Connolly), assume ocean MeHg ~0 Burial –Fuller sedimentation 0.88cm/yr (~9% of mixed layer)

9 Modeled Processes Degradation –Sediment: Marvin-DiPasquale demethylation rates = 0.083/d (decay) Assume demethylating zone (70% of mixed layer) –Water: Krabbenhoft Petaluma water half life~7 days (0.10/d decay) Benthic flux –In daily resuspension & de/sorption Large uncertainties some parameters –Some have small ~no effect

10 Base Case Run Base case = averaged –initial concentrations (from RMP monitoring) –loading/process parameter values Quick steady state, within ~5% of T 0 –Sediment mass ~ –Water mass lower

11 Base Case Run Mass (inventory) vs daily flux/degrade/produce Water Mass –Net sediment to water exchange, ext load = Degradation>, GG outflow, >> bio-uptake,volatilization Total (Water+Sediment) –Production ~balances degradation >> all other processes * Flux box measurement similar: ~.014 kg/d (Choe et al) Mass in Water0.236kg Ext. Load0.018kg/d Sed to Water*0.021kg/d Water Degrade0.024kg/d GG Outflow0.014kg/d Bio-uptake<0.001kg/d Volatilize<0.001kg/d Mass in Sediment30.8kg Methylate1.82kg/d Sed Degrade1.79kg/d Sed to Water0.021kg/d Burial0.007kg/d

12 Hot &@%$! Model Responds Fast!? Seasonal de/meth rates (winter -30%) ~month response! Yes, but… –Model oversimplifies (mixing, equilibrium) –Processes vary on microscale (e.g. de/methylation) –Still a good order of magnitude tool

13 Parameter Sensitivity ScenarioMass SMass W Base Case30.8 kg0.236 kg Load /330.70.191 Load x331.00.370 WaterDegrade /330.90.317 WaterDegrade x330.60.134 SedDegrade /388.80.556 SedDegrade x310.40.123 Methylate /310.30.123 Methylate x392.00.574

14 WDMMBD? What Did the MeHg Mass Budget Do? Did Bay data make sense? –Base case near starting state- near “right” Baywide? –Non-unique solution (e.g. offsetting errors?) Feasibility/needs of refined model(s) –1 box driven by steady state/equilibrium –Basis for more detailed model? Much higher data needs Key factors affecting MeHg fate –External loads have small/medium effect –Very sensitive to de/methylation rates

15 Management Strategy – Dr. Evil Acquire $1 Million Option A- Control Methylation: Sterilize the Bay (thermonuclear device) Option B- Control Demethylation: Equip sharks w/ UV lasers to photodemethylate

16 Management Strategy -RMP Option C- RMP Mercury Strategy: –Where biota affected (food web entry) –ID disproportionate (high leverage) pathways –ID intervention opportunities –IF strategy finds locations where critical pathways (e.g. de/methylation) may be acted on THEN act (e.g.holding ponds, aeration, dredging, nutrient reductions, etc) –Monitor & model management effectiveness “adaptive management” (Unfortunately likely > $1 million)

17 Acknowledgements Too many to list… “If I have seen further it is by standing on ye shoulders of Giants” – Sir Isaac Newton

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19 Atmospheric (Wet) Deposition No local data –RMP MDN station only measured totHg Literature rainfall MeHg (avg 0.11 ng/L) … –Watras & Bloom (1989 Olympic Penins. WA 0.15ng/L) –Risch et al (2001-2003 Indiana, 0.06ng/L) –St Louis et al (1995, ELA area, 0.05ng/L) –Mason et al (1997, Still Pond, MD, HgT x %MeHg avg = 0.04ng/L) x Local annual precipitation (0.45m/y) = 0.10 g/d deposition Baywide

20 Discharges from… Delta (SWRCB Region 5) –Flow weighted avg concentration x mean annual discharge = 4.7g/d in Hg TMDL –Revised to w/ later data Local watersheds –Extrapolate w/ SIMPLE Model (modeling mine + urban + non-urban areas) Local MeHg data, extrapolated to Bay area (3.6 g/d) Local Hg data x MeHg%, extrapolated to Bay area (6.2 g/d) –Use average of above 4.9g/d

21 Discharges from… Wetlands –Wetland Goals est. 40k acres wetland (1.6e8 m 2 ), assume 0.3m overlying water every day –Petaluma marsh extrapolation ~50% water particulate settles -1.2g/d ebb tide dissolved conc ~2.5x flood tide (max 5x at Petaluma) +3.2g/d = net 2g/d load to Bay –USACE Hamilton AAF leaching assumptions 0.8%/d of net production = 4.0g/d load –Stephenson et al showed net import and export different events for Suisun Marsh May be difficult to refine net load

22 Discharges from… POTWs –Annual mean conc x discharge for 16 largest plants (loads for each plant calculated then summed) = 0.79g/d Conc range 0.04-1.3ng/L (mean ~0.42ng/L) Discharge 14-165e9 L/y (sum ~2.15e9g/d ~95% of discharge volume)

23 Bio-uptake “Loss” Phytoplankton? –Cloern 2002-2004 productivity ~210gC/m 2 y –Hammerschmidt MeHg 0.5ng/g ww =5ng/g dw –LakeMichMassBal algal MeHg = 30 ppb dw –C → CH 2 O, geomean MeHg 12ng/g –= 19.5g/d MeHg into phytoplankton? Phytoplankton rapid turnover (growth~0.3/d?), reversible “loss” from water/sed pools, loss estimate probably too high Small fish? –Slater (CDFG, IEP) young of year pelagic fish est. 0.01-0.25g/m 3 (Suisun lowest, Central highest, mostly anchovies) mean ~0.17g/m 3 ww biomass –RMP anchovy Hg 0.049µg/g ww = 0.13g/day MeHg into fish biomass (<1% of phyto?) –Expect less (short term) cycling than algae, “irreversible” net loss by incorporation into higher trophic levels


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