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A Methylmercury Budget for San Francisco Bay

A quantitative model to track the fate of methylmercury in San Francisco Bay, identifying key factors and informing management strategies.

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A Methylmercury Budget for San Francisco Bay

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  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) Demeth Sed-water exchange Demeth Meth

  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 T0 • 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)

  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

  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

  18. 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

  19. 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

  20. Discharges from… • Wetlands • Wetland Goals est. 40k acres wetland (1.6e8 m2), 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

  21. 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)

  22. Bio-uptake “Loss” • Phytoplankton? • Cloern 2002-2004 productivity ~210gC/m2y • Hammerschmidt MeHg 0.5ng/g ww =5ng/g dw • LakeMichMassBal algal MeHg = 30 ppb dw • C→CH2O, 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/m3 (Suisun lowest, Central highest, mostly anchovies) mean ~0.17g/m3 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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