the long term fate of pcbs in san francisco bay jay a. davis san francisco estuary institute

The Long Term Fate of PCBs in San Francisco Bay

Jay A. Davis

San Francisco Estuary Institute

Regional Monitoring Program

Regional Monitoring Program for Trace Substances in the San Francisco Estuary

Innovative partnership between government, dischargers, and scientists

$ 3 million/year of stable funding Began in 1993 World class monitoring www.sfei.org

PCB Concentrations in San Francisco Bay Fish Fillets, 2000

PCBs in mussels

1981-2000

ng/g lipid

~ 50% decline

Questions

Why is the Bay responding so slowly? How long will it take for fish to be safe to eat? What would the response be with reduced inputs? How large are the inputs? What studies are needed to better understand PCB

fate in the Bay?

A PCB Mass Budget

A first step toward a PCB mass budget for the Bay Followed approach described by:

– Gobas et al. 1995 (EST 29: 2038-2046)– Mackay et al. 1994 (JGLR 20: 625-642)

One-box model for the whole Bay A water and sediment model Individual congeners PCB 118 used as “typical” PCB Report benefited from extensive peer review

Input Data

Approximately 30 input parameters– Physical data for the Bay– Flow– Sediment budget– RMP concentration data– Chemical properties

Sensitivity analysis conducted on all parameters

Combined External Loads

Volatilization

Outflow

Dissolved PCB

Sorbed PCB

Dissolved PCB

Sorbed PCB

Burial

Water

Active Sediment Layer

Buried Sediment

Dissolved PCB

Particulate PCB

DegradationDegradation

Degradation Diffusion

Depositionand

Resuspension

PCB Fate in Bay Water and Sediment

Predicted Long Term Trends in PCB Mass with Varying Loads

Year

0 10 20 30 40 50 60 70 80 90 100

PC

B M

ass

in B

ay (

kg)

0

500

1000

1500

2000

2500

3000

50% of present

25% of present

10% of present

80 kg

40 kg

20 kg10 kg 0 kg

Predicted Trends in PCB Mass for Different PCB Congeners

MASS IN BAY

VOLATILIZATION

OUTFLOW

DEG SEDIMENT

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

YEAR

PC

B 1

18

MA

SS

(K

G)

Predicted Long Term Trends in PCB Mass with Varying Depth of the Active Sediment Layer

Year

0 10 20 30 40 50 60 70 80 90 100

PC

B M

ass

in B

ay

(kg

)

0

1000

2000

3000

4000

50005 CM 10 CM 15 CM 20 CM 25 CM

Conclusions

At this stage, the value of the model is in showing the response to ranges of input values, not in the precision of estimates

The most influential parameters included degradation half-life in sediment, Kow, outflow, average PCB concentration in sediment, and depth of the active sediment layer

Sediment dynamics are very important, including mixing and erosion/burial

Conclusions (continued)

The model suggests that annual loads from 1982 to 2000 were in the 0 to 20 kg range

Annual inputs of 10 to 20 kg could significantly delay declines in PCBs

Different PCB congeners are predicted to have very different response times

For more information or a copy of the report: jay@sfei.org

Next Steps for PCB Fate Modeling in San Francisco Bay

Food web model coming soon (Frank Gobas and John Wilcockson)

Sediment

Amphelisca sp(Amphipod)

Potamocorbula amurensis(Bivalve)

Shiner PerchJack Smelt Small Croaker Large Croaker

Harmothoe sp(Polychaete)

Crangon sp(Shrimp)

Neanthessuccinea

(Polychaete)

Theora lubrica(Bivalve)

Zooplankton

Phytoplankton

Sediment

Amphelisca sp(Amphipod)

Potamocorbula amurensis(Bivalve)

Shiner PerchShiner PerchJack SmeltJack Smelt Small CroakerSmall Croaker Large CroakerLarge Croaker

Harmothoe sp(Polychaete)

Crangon sp(Shrimp)

Neanthessuccinea

(Polychaete)

Theora lubrica(Bivalve)

Zooplankton

Phytoplankton

Modeling PCB Trophic Transfer

Mass Budget for a White Croaker

Dietary Uptake

Growth Dilution

Metabolism

Fecal Egestion

Gill Elimination

Gill Uptake

Next Steps for PCB Fate Modeling in San Francisco Bay

Quantify uncertainty of estimates Go multibox

The Multibox Model

Collaboration with Dave Schoellhamer (USGS, Sacramento)

Builds on existing model calibrated for salinity

RMP really interested in 5 boxes

Next Steps for PCB Modeling in San Francisco Bay

Better characterization of sediment dynamics

Also need better estimates of: Degradation rates Outflow Average concentrations Historic long term trends

Next Steps for Management

Look for manageable PCB loads Watch out for “PCBs” of the future (e.g.,

PBDEs)