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Dredge Data Evaluation. TRC Meeting March 15 2005 Don Yee. Objectives. Compile dredge testing data for San Francisco Bay Compare collection and analytical methods Compare analytical results Test hypotheses on SF Bay sediment characteristics. Compiled Data.

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Dredge data evaluation

Dredge Data Evaluation

TRC Meeting March 15 2005

Don Yee


Objectives
Objectives

  • Compile dredge testing data for San Francisco Bay

  • Compare collection and analytical methods

  • Compare analytical results

  • Test hypotheses on SF Bay sediment characteristics


Compiled data
Compiled Data

  • State effort to develop sediment quality guidelines occurred concurrently, including compilation of selected dredged material testing data

  • Draft database released November 2004

    • ~40 dredging studies in SF Bay

    • 11 monitoring studies (includes Hunter’s Point, Alameda)


Spatial distribution

Central Bay most stations

Spatial Distribution





Reported organics

Subset of common PAHs reported

Reported PCBs as Aroclors or congeners, study specific

“Total PCBs” differ (ND=0 case)

Dredge data most sum Aroclors or sum congeners = 0

Monitoring data avg Aro/cong = 1.7

Reported Organics


Comparing data

Large % of organics NDs challenging for comparison

ND assumptions have large influence particularly on sums

Non-parametric statistics more resistant to NDs, but MDL/RL differences and non reporting among different studies can bias outcome

Comparing Data


Hypotheses seasonality
Hypotheses: Seasonality

Seasonality in historic RMP sediment data (5cm surface grabs) found not significant, therefore…

  • Seasonality in dredge cores even less likely

    • Cores composited for analysis

    • Relatively infrequent revisits in dredging may leave gaps


Test seasonality
Test: Seasonality

Include areas dredged multiple times, perhaps covering different times of year

  • Relatively infrequent revisits in dredging = poor seasonal coverage

  • Deeper coring and compositing may dilute seasonal signal

    Wilcoxon and Tukey HSD test

  • Comparing Dec-May “wet” vs Jun-Nov “dry”

  • Central Bay stations alone


  • Result seasonality
    Result: Seasonality

    • Wet vs dry season

      • As, Cd, Cu, Mn, Ni significantly (p <0.05) different, with wet > dry

      • Hg, Se not significant

      • Consistency among elements and types of test


    Seasonality alternative
    Seasonality (Alternative)

    • Oakland 38 and 42 ft projects large portion of dry data (50 ft project split in both seasons)

      • Deeper sediments include relatively uncontaminated Bay muds

    • Excluding data still showed significant wet and dry differences (both tests, same metals)


    Hypotheses interannual trend
    Hypotheses: Interannual Trend

    • Negligible interannual trends in sediment concentrations

      • RMP surface sediments show few/ no significant interannual trends for most contaminants

      • Interannual dredge trends likely confounded by differences in sampled locations & signal diluted by compositing.


    Test interannual trend
    Test: Interannual Trend

    Include dredging data over multiple years

    • Subsets

      • Central Bay stations

      • Group by collection year

    • Nonparametric (Kruskal Wallis) and parametric tests (Tukey HSD)


    Result interannual trend
    Result: Interannual Trend

    • Significant (p <0.05) differences among years for various metals.

    • No consistency among metals for years with significant differences

    • Compare enough categories, and “significant” differences will be found


    Alternative interannual trends
    Alternative: Interannual Trends

    • Use smaller scale: Benicia Harbor only

      • Small well defined area, expect less variation

      • 3-4 samples per year for 3 years

    • Significant differences

      • 1996 > 1997 or 2000: As, Cd, Cr, Hg (p < 0.05)

      • 1996 frequently nigher than other stations



    Hypotheses depth integration
    Hypotheses: Depth Integration

    • Sediment contaminant concentrations at depth are not significantly different from surface concentrations

    • Deep dredging will encounter clean Bay sediments and average lower contaminant concentration than surface samples


    Test depth integration
    Test: Depth Integration

    • Subset to focus on area around Oakland

      • Dredge data in port dominated by deepening project samples

      • Latitude & longitude from all Oakland dredging projects

      • Monitoring data for surface sediments in same box

    • Wilcoxon and Tukey HSD test


    Result depth integration
    Result: Depth Integration

    • Concentrations for nearly all metals Oakland monitoring > dredge data

      • As, Cd, Cu, Pb, Hg, Ni, Se, Ag, Zn statistically significant difference

      • Cr only metal higher in dredge sediment

      • Generally consistent among metals

      • Significant differences on As, Cd, Se, Zn even removing BPTCP, LEMP, Alameda NAS data



    Result depth integration part 2
    Result: Depth Integration Part 2

    • Examine differences in dredge vs monitoring in Suisun Bay.

      • Hg statistically significantly higherin monitoring (surface sediment) data

      • Cr only metal higher in dredge sediment

      • Differences hold even dropping LEMP, BPTCP data



    Conclusions
    Conclusions

    • Dredge data analytical methods sufficient for most trace elements

    • Organics analyses usable only for PAHs due to extensive ND results

    • Dredge data may show seasonality in Central Bay

      • Larger number of samples provides power

      • Similar trends among metals evidence of real effect

      • Significance holds even removing obviously biasing data sets (e.g. Oakland deepening projects)


    Conclusions cont d
    Conclusions (cont’d)

    • Segment scale dredge data show no interannual trends (Central Bay)

      • Significant results found in many comparisons, but inconsistent among trace elements

      • Significance may be artifact of numerous (year) categories

    • Smaller scale dredge data may show trends

      • Narrower sampling focus reduces lateral and vertical variability


    Dredge data useful with care
    Dredge Data Useful (with care)

    • Awareness of collection, analytical, and reporting conventions

    • Selecting the right subset to reduce biases

    • Inconsistent “significance” may not be significant


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