1 / 23

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.

jamesshelton
Download Presentation

A Methylmercury Budget for San Francisco Bay

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

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) 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

More Related