PCB Movement in San Francisco Bay Food-Web Model

1. PCB Movement through the Food-Web of San Francisco Bay: Development of a Model • Frank A.P.C. Gobas1 and John Wilcockson2 • 1. School of Resource & Environmental Management • Simon Fraser University • Burnaby • British Columbia • Canada • 2. EVS Environmental Consultants • North Vancouver • British Columbia • Canada

2. Monitoring study • Fish consumption advisory, California Office of Environmental Hazard Assessment (OEHHA 1994) • SFB on the 303(d) impaired water body list (EPA) • TMDL study by the Regional Water Board of California (Clean Water Act) Loading CWater CSediment PCBs in San Francisco Bay

3. Total Daily Maximum Loading Study: I Loading CWater CSediment

5. Total Daily Maximum Loading Study: II Loading CWater CWater CSediment CSediment

7. Representative Species Composition

8. Target Species

9. San Francisco Bay Food-Web

10. Simplifying the Food-Web • Feasible • Transparent • Testable • Practical sampling program can be designed • Error is introduced

11. Model for uptake, elimination & bioaccumulation of PCBs in organisms other than phytoplankton & algae

12. Exchange of PCBs with water via the respiratory surface • Body Weight • Body composition (lipid content) • Temperature • Kow of PCB congener • Sorption to DOC and DOM • Pore water ventilation

14. Dietary Uptake of PCBs • Feeding rate • Body Weight • Body composition (lipid content) • Food Composition • Digestibility • Temperature • Kow of PCB congener

15. Other Factors • Growth • Egg deposition • Metabolic Transformation • Sediment-water Disequilibria

16. Uptake & elimination of PCB180 in White Croaker Gill Uptake: 265 pg/kg.d Metabolism 0 pg/kg.d Dietary Uptake: 106,275 pg/kg.d Growth: 91,100 pg/kg.d Gill Elimination: 1,740 pg/kg.d Fecal egestion: 13,700 pg/kg.d

17. Model Output BAF = CB / CW BSAF = CB / CS

18. Model Output White Croaker PCB180: BAF = 302,000 L/kg ww BSAF = 3.3 kg dry/Kg ww

19. Model Validation Field Measurement of PCB concentration Food-Web Model Model Calculation of PCB concentration Field Measurement of PCB concentration

20. Polychaete (Neanthes succinea) San Leandro Bay

21. Shiner Surf Perch San Leandro Bay

22. White Croaker San Leandro Bay

23. Model Uncertainty Model Bias = log (Cpredicted / Cobserved)

24. Model Uncertainty Species MB U n Neanthes succinea 1.5 1.6 5 Harmothoe (polychaete) 1.04 1.6 5 Shiner perch 1.03 4.09 29 White Croaker (juv) 1.25 2.46 30 Model Bias = log (Cpredicted / Cobserved) U = 95% confidence intervals of Model Bias n = number of PCB congeners available for comparison

25. Factors included in Model Uncertainty • Model Error • Parameterization Error • Analytical Error • Natural Variability

26. Model Application

27. Conclusions Developed and constructed a food-web bioaccumulation model of PCBs for San Francisco Bay (Excel spreadsheet). Tested the model against empirical field data from San Leandro Bay. Model Bias was between 1.03 and 1.57 (ideal =1). On average, PCB concentrations are in good agreement with actual observation. 95% confidence intervals of the model bias ranged between a factor of 1.6 to 4.09. Model application to San Pablo, Oakland and Red Wood illustrates that substantial differences in bioaccumulation patterns arise as a result differences in trophic structure.

28. Some other comments Food-web model does not include higher trophic level organisms. Include risk to wildlife as an endpoint to the TMDL.

30. Some other comments Food-web model does not include higher trophic level organisms.

31. Gw.Ew.Cw + Gd.Ed.Cd Cb = Gw.Ew + Gf.Ed + Vb (km +kg) Kbw Kbf Model Calculations

32. Factors included in Model Uncertainty • Model Error • Parameterization Error • Analytical Error • Natural Variability

33. Mass Balance Models Combined External Inputs Volatilization Water Dissolved Chemical Sorbed Chemical Water Water Inflow Outflow Resuspension Resuspension Resuspension Sediment-Water Sediment-Water Sediment-Water Degradation Diffusion Diffusion Diffusion Settling Settling Settling Dissolved Sorbed Bed Load Transport Bed Load Transport Chemical Chemical Sediment Sediment Degradation Burial

34. Mass Balance Models Combined External Inputs Volatilization Water Dissolved Chemical Sorbed Chemical Water Water Inflow Outflow Resuspension Resuspension Resuspension Sediment-Water Sediment-Water Sediment-Water Degradation Diffusion Diffusion Diffusion Settling Settling Settling Dissolved Sorbed Bed Load Transport Bed Load Transport Chemical Chemical Sediment Sediment Degradation Burial

35. Sediment-Water Distribution of PCBs in San Francisco Bay

37. Analysis of Observed total-PCB Concentration Data in the Lake Ontario Food-Web

38. Mineralization OC Z f Algae,Macro-phytes 26% 1 1 Suspended solids 4% 0.15 6.5 Bottom sediments 1.5% 0.058 17.3

39. Primary OC Production fSS/fW = (QPOC/QSSOC).(ZPOC/ZSSOC).(fP/fW) suspended OC fBS/fW = (QPOC/QBSOC).(ZPOC/ZBSOC) .(fP/fW) Burried OC

40. Phytoplankton Partitioning Model: BCF = k1/(k2+kg)

41. Uptake from Respiration Uptake from water = k1 x Weight x Dissolved Water Concentration Uptake Efficiency x Gill Ventilation Rate k1 = Weight Gill Ventilation Rate = 1400.Weight0.65 / Oxygen Concentration Uptake Efficiency = 1 / (1.89 + (1.55/Kow)) Calculation of Uptake via the respiratory tract

43. San Francisco Bay Water

44. Polychaete (Neanthes succinea)

45. Shiner Surf Perch

46. White Croaker

47. Model Uncertainty 95% of the actual PCB concentration data in biota are within a factor of 2.5 of the predicted concentration.

48. Lessons Learned Model input requirements are not large. Food-web model is robust. Do not confuse model sensitivity and uncertainty. Uncertainty of the food-web model for PCBs has been consistently a factor of 2 to 3.