Deborah French McCay, PhD Applied Science Associates (ASA) South Kingstown, RI, USA

Transcription

1 Risk Assessment Issues from Potentially- Polluting Wrecks: Screening Modeling Approach Applied to Wrecks in US RULET Database with NOAA OR&R, Research Planning Inc, and Environmental Research Consulting Deborah French McCay, PhD Applied Science Associates (ASA) South Kingstown, RI, USA

2 Approach for Reducing Risk of Oil Releases from Wrecks Goal: ID wrecks with greatest oil spill risk Highest potential for leakage and Highest consequences (impacts) 3 Tiered Approach: Triage wrecks to ID higher risk cases Perform impact analysis on higher risk wrecks Evaluate potentially highest risk wrecks in a cost-benefit analysis, which requires: Impact quantification (consider dose-response) Cost evaluation

3 SIMAP/ CHEMMAP Response Model Geographical Database User Input: Scenario, Winds Physical Fates Model Trajectory and Concentrations Hydrodynamics Model Current Data Exposure and Toxicity Model Areas, Volumes and Percentages of Biota Impacted by Habitat and Behavior Group Physical- Chemical and Toxicological Data Biological Database Population Impact Model Impacts as Lost Numbers, Biomass and Production

4 Toxic Components of Oil (Additive Effects) C-C-C-C-C-C Aliphatics = Straight chain hydrocarbons (e.g., alkanes) more volatile than soluble Σ Monoaromatic Hydrocarbons (MAHs) Benzene, Toluene, Ethylbenzene and Xylenes = BTEX highly soluble, highly volatile, moderately toxic Alkyl-substituted Benzenes soluble, less volatile, more toxic Polynuclear Aromatic Hydrocarbons (PAHs) Naphthalenes (2-ring PAHs) soluble, less volatile, more toxic with more alkyl chains, less soluble but more toxic 3 ring PAHs Phenanthrenes Fluorenes Dibenzothiophenes 4-ring PAHs parent compounds bioavailable larger PAHs insoluble

5 Dispersant Wind Water Surface Entrainment Thick Oil Sheens Resurfacing Current Turbulent Dispersion and Dissolution Sediment Surface Adsorption and Adherence to Particulates Sedimentation Subsurface Oil Release

6 Potential Effects of Oil Smothering / Coating [Floating oil] Mechanical (smothering, prevention of uptake and depuration, interference with motility, etc.) Thermal regulation (birds, mammals) Absorption of toxic compounds (via skin or gut) Toxicity Requires uptake into tissues Dissolved components (BTEX, PAHs) Acute and chronic Mechanical interference [Dispersed droplets] Clogging of feeding appendages and gills Impeding movements

7 Biological Exposure Model Organisms classified by behavior Wildlife % of time on water surface Habitats used Feathers & fur Fish and Invertebrates Swimming Drift with currents Stationary Movements of organisms are tracked to calculate exposure of individuals Impact a function of dose Wildlife Area swept by floating oil Slick thickness Fish and Invertebrates Concentration (water, sediment pore water) Exposure time Temperature

8 Validation Wildlife Exxon Valdez (Prince William Sound) Total Birds eagles murres puffins guillemots murrelets other alcids gulls cormorants procellariids sea ducks grebes loons Model Field log10 (# killed)

9 Validation Fish and Invertebrate Toxicity Oil bioassays (French McCay, 2002; Envir. Tox & Chem Vol. 10) 24 data sets (2 to 91 species tested) For all data sets: model not significantly different from observed North Cape Oil Spill (RI, Jan 1996): Lobsters Field estimate 9 million Model estimate 8.3 million (using best estimate of toxicity) Stranded on beaches: 3 million

10 Screening Approach Develop list of priority wrecks from RULET and other data sources Consider location, wreck status, likelihood of release, potential volumes of release RULET: Lisa Symons, John Wagner, Doug Helton (NOAA) RRI: Jacqueline Michel ERC Data: Dagmar Etkin of Environmental Research Consulting Group wrecks in Clusters based on geography, oceanography and oil type Select representative wrecks in Cluster to model

11 Stochastic Modeling Approach Identify maximum potential spill volume for cluster to model Input data: Long term (years) record of environmental data Winds Currents hydrodynamic model Environmental conditions Run model many times, randomizing Spill date and time, and so randomly sampling wind and current conditions that might occur Identify and examine worst case for: Floating oil area swept Shoreline oiling Water column contamination

12 Probability of Floating Oil Reaching Each Location J.D. Gill 155,000 bbl Heavy Fuel Oil Depends Primarily on Winds after Time of Release

13 Probability of Shoreline Oiling J.D. Gill 155,000 bbl Heavy Fuel Oil

14 Probability of Subsurface Entrained Oil Reaching Each Location J.D. Gill 155,000 bbl Heavy Fuel Oil Influence of Gulf Stream

15 Worst case run for surface oil exposure: Timing (days) J.D. Gill 155,000 bbl Heavy Fuel Oil

16 Worst case run for floating oil: Maximum concentrations for a catastrophic release of 155,000 bbls J.D. Gill 155,000 bbl Heavy Fuel Oil

17 Worst case run for shoreline oiling: Mass (g/m2) ashore for a catastrophic release of 155,000 bbls J.D. Gill 155,000 bbl Heavy Fuel Oil

18 Worst case run for subsurface oil: Maximum concentrations for a catastrophic release of 155,000 bbls J.D. Gill 155,000 bbl Heavy Fuel Oil

19 Estimate Impacts for Any Size Release in the Wreck Cluster Run 5 spill volumes (100, 50, 10, 1, and 0.1 percent of the maximum cargo + bunker capacity) allowing curve-fitting as a function of spill size, so impacts may be calculated for intermediate spill volumes

20 Regressions of Impact vs Volume Spilled: Area Swept Wildlife Oiled

21 Regressions of Impact vs Volume Spilled: Sand Shoreline Oiled

22 Regressions of Impact vs Volume Spilled: Wetland Oiled

23 Regressions of Impact vs Volume Spilled: Water Volume Where Toxic Concentrations

24 Risk: Likelihood of Spill * Likelihood of Various Spill Volumes Combined with Regressions of Impact vs Volume Spilled

25 Next Level of Analysis for Higher Risk Wrecks: Consequence/Impact Analysis Identify 5 th, 50 th and 95 th percentile conditions surface oiling (on water and shorelines) subsurface oil and dissolved aromatic concentrations Perform exposure and impact assessment modeling on these 3 scenarios provides range and measure of uncertainty Quantify expected impact as Area where wildlife oiled with a lethal dose or #s Volume of water impacted at lethal levels or kg Socioeconomic impacts Response costs