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A Methylmercury Budget for San Francisco Bay

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Predict long term fate (no Hg linkage) MeHg 1 Box Model. Adapted from ... Delta (Mallard Island) discharge 9.8 g/d. Flow x concentration (Region 5 MeHg TMDL) ... – PowerPoint PPT presentation

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Title: A Methylmercury Budget for San Francisco Bay


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 lt1 of totHg
  • Poor MeHgtotHg 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 wont/cant 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 life7
    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
  • Degradationgt, GG outflow, gtgt bio-uptake,volatiliza
    tion
  • Total (WaterSediment)
  • Production balances degradation gtgt all other
    processes
  • Flux box measurement similar .014 kg/d (Choe
    et al)

12
Hot _at_! 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 gt 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
(No Transcript)
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 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

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/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 (growth0.3/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 (lt1 of phyto?)
  • Expect less (short term) cycling than algae,
    irreversible net loss by incorporation into
    higher trophic levels
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