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A mass balance model for the fate of PAHs in the San Francisco Estuary Ben K. Greenfield Jay A. Davis San Francisco Estuary Institute Presented at the.

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Presentation on theme: "A mass balance model for the fate of PAHs in the San Francisco Estuary Ben K. Greenfield Jay A. Davis San Francisco Estuary Institute Presented at the."— Presentation transcript:

1 A mass balance model for the fate of PAHs in the San Francisco Estuary Ben K. Greenfield Jay A. Davis San Francisco Estuary Institute Presented at the Calfed Science Conference, January, 2003

2 Source: U.S.G.S./Center For Land Use Interpretation

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4 Population Growth, Bay Area - 1860 to 2000 Data Source: MTC and ABAG, 2002 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000 186018701880189019001910192019301940195019601970198019902000 (Each Color is a Bay Area County)

5 Mass balance models Understand compound fate Identify research priorities (e.g. chemical properties) Synthesize available data Estimate loading rate

6 Simple mass balance model Mackay et al. (1994) Equilibrium partitioning based on chemical properties Single pool of interacting water and sediment Daily rate constants Spreadsheet format

7 Combined External Loads Volatilization Outflow Dissolved PCB Sorbed PAH Dissolved PAH Sorbed PAH Burial Water Active Sediment Layer Buried Sediment Dissolved PAH Particulate PAH Degradation Diffusion Deposition And Resuspension

8 2 ring – naphthalene 3 ring – phenanthrene 4 ring – fluoranthene and benz(a)anthracene 5 and 6 ring – e.g. benzo(b)fluoranthene Fluoranthene Benz[a]anthracene

9 Year 012345 PAH in Bay Percent Original Mass 50 100 Naphthalene Phenanthrene Fluoranthene Benz(a)anthracene Benzo(b)fluoranthene 0 Turnover Rate

10 Year 05101520 Percent Original Mass 0 25 50 75 100 Phenanthrene Fluoranthene Benzo(b)fluoranthene PCB 118 PAHs

11 Loss Pathways of PAH Mass in Estuary Assuming No Load (One Year Simulation) Compound NFB(a)aB(b)f Proportion of Total 0.0 0.2 0.4 0.6 0.8 1.0 Volatilization Outflow Degradation Mass Remaining

12 Compound NPFB(a)aB(b)fDaB(a)p Degradation Rate (d -1 ) 0.0001 0.001 0.01 0.1 1 10

13 Vary by PAH Compound Water Side MTC Air Side MTC Henry's Law Constant Kow Degradation Water Degradation Sediment Proportion of Total 0 20 40 60 80 100 Uncertainty for Benzo(b)fluoranthene 0 20 40 60 80 100 Sensitivity to Different Chemical Parameters Water Side MTC Air Side MTC Henry's Law Constant Kow Degradation Water Degradation Sediment

14 Losses Degradation Volatilization Outflow Burial Inputs? Loading Point Source Air Deposition Rivers Storm Drains Trend?

15 Inputs? Loading? Trend? Losses Degradation? Volatilization Outflow Burial

16 Total PAHs (µg/kg) Sediment Trends Year 1990199219941996199820002002 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Total PAHs (  g/kg lipid) Bivalve Trends Year 199319941995199619971998199920002001 0 1000 2000 3000 4000 5000 6000

17 1990 1980 From Pereira, W.E., et al. 1999 Marine Chemistry Dated Sediment Core Chemistry

18 Inputs? Loading? Trend? Losses Degradation? Volatilization Outflow Burial

19 Loading rate (kg/yr) Degradation rate (d -1 ) 300< 0 20000 10,0000.0002 20,0000.00035 460,0000.01 Literature Estimates

20 Result summary Loss rates (half life) 2 ring PAH - 3 week 4 ring PAH - 1 year 5 ring PAH - 6 years Degradation rate uncertainty causes considerable model uncertainty Obtained upper bound on degradation rate and lower bound on loading rate

21 Significance of findings Much more rapid expected response to management changes than PCBs Future priorities:  Local degradation rates  Dr. Michael Montgomery (NRL) - experimental data on Bay sediments  Local sediment-water partitioning

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23 Acknowledgments Don Yee Jon Leatherbarrow Sarah Lowe Cristina Grosso Patricia Chambers


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