Task 10: Bunkering Accident Characterization

Transcription

1 Gateway Pacific Terminal Vessel Traffic and Risk Assessment Study Task 10: Bunkering Accident Characterization Prepared for Pacific International Terminals, Inc. Prepared by The Glosten Associates, Inc. in collaboration with Environmental Research Consulting, Inc. File No March 2013 Rev. P0 Consulting Engineers Serving the Marine Community 1201 Western Avenue, Suite 200, Seattle, Washington TEL FAX

2 Contents References... ii Executive Summary... iii Scope of Work per Professional Services Agreement... v Appendix A: Characterization of Bunkering and Oil and Dry Bulk Cargo Transfer Incidents (Task 10), prepared by Environmental Research Consulting, 19 February Gateway Pacific Terminal VTS Study i The Glosten Associates, Inc. Bunkering Accident Characterization, Task 10, Rev. P0 File No , 22 March 2013

3 References 1. Task 2: Traffic Analysis, The Glosten Associates, Inc. in collaboration with Northern Economics, Inc., 22 March Appendix A of this report, Characterization of Bunkering and Oil and Dry Bulk Cargo Transfer Incidents (Task 10), prepared by Environmental Research Consulting, 19 February Gateway Pacific Terminal VTS Study ii The Glosten Associates, Inc. Bunkering Accident Characterization, Task 10, Rev. P0 File No , 22 March 2013

4 Executive Summary This Vessel Traffic and Risk Assessment Study (VTS) is being conducted by The Glosten Associates (Glosten) for the proposed Gateway Pacific Terminal (GPT) to be located at GPT/Cherry Point in Washington State. The purpose of the study is to assess the potential risks posed by new bulk carrier traffic that the proposed terminal will bring to the Puget Sound. Current vessel traffic levels and forecasted traffic levels are considered, including tugs and GPT-calling vessels. The area studied includes the designated Puget Sound vessel transit lanes, the maneuvering area near the planned GPT project at GPT/Cherry Point, the local anchorage areas, and the transit routes for tugs assisting GPT. Plans call for 487 total annual visits for the anticipated GPT-bound traffic at full throughput level in 2026 (Reference 1). Of the total vessel calls, it is projected that there will be 318 Panamax and 169 Capesize (up to 180,000 DWT) vessels. The GPT-bound vessels will be utilizing the established traffic lanes between Cape Flattery and Cherry Point. The Appendix A report, Characterization of Bunkering and Oil and Dry Bulk Cargo Transfer Incidents (Task 10),(Reference 2), provides data and analyses on transfer-related incidents that occur during bunkering operations and oil and dry bulk cargo transfer operations, including those incidents that provide the potential for spillage and those that involve actual spillage. Information on the nature and rates of bunkering incidents and their geographic locations will assist in determining the potential additional impacts of bunkering activities and dry cargo transfer operations with the presence of the Gateway Pacific Terminal (GPT). Incidents that occur as a result of errors during bunkering operations and oil and dry bulk cargo transfer operations are analyzed with respect to the following criteria: Historical incidents in the GPT study area during Incident occurrence by GPT subarea. Incident occurrence by activity (at-anchor or at-dock). Annual incident rates. Spillage rate per incident. Spill volume probability distributions. Potential reductions in spillage with the Washington Transfer Rule. The following key findings with respect to bunkering errors are presented in the Executive Summary of the report contained in Appendix A. Bunkering transfer errors occur at a rate of about 2.38 incidents per year, or about one incident every five months in the GPT study area. The greatest number of bunkering incidents involves the other vessel type category and occurs while docked. The greatest percentage of incidents occurs in Saddlebag, followed by Guemes Channel subarea. Gateway Pacific Terminal VTS Study iii The Glosten Associates, Inc. Bunkering Accident Characterization, Task 10, Rev. P0 File No , 22 March 2013

5 The probability of spillage in the event of a bunkering error is 0.92 with no difference by hull type (double or single). Spill volumes for bunkering errors are typically small, with 90% of incidents involving 200 gallons or less, and 95% of incidents involving 500 gallons or less. With the transfer regulations implemented and enforced, the incidence of bunkering errors could be reduced by 70%. The following key findings with respect to oil cargo transfer errors are presented in the Executive Summary of the report contained in Appendix A. Oil cargo transfer errors occur at a rate of about 2.38 incidents per year, or about one incident every five months in the GPT study area. The presence of GPT would have no effect on oil cargo transfer error incident rates as there are no oil cargo transfers associated with GPT. The greatest number of oil cargo transfer error incidents is from tankers, rather than tank barges, and they occur while docked. The greatest percentage of incidents occurs in Cherry Point, followed by Guemes Channel subarea. The probability of spillage in the event of an oil cargo transfer is 0.92, with no difference by hull type (double or single). Spill volumes for oil cargo transfer errors are typically small, with 90% of incidents involving 200 gallons or less, and 95% of incidents involving 500 gallons or less. With the transfer regulations implemented and enforced, the incidence of oil cargo transfer errors could be reduced by 70%. The following key findings with respect to dry cargo transfer errors are presented in the Executive Summary of the report contained in Appendix A. There is relatively little data on dry cargo spills due to any cause. The incident rate could be reduced by 70% if best practices similar to those in the Washington Transfer Rule were implemented at GPT. The Washington State Transfer Rule is presented in an appendix to the report contained in Appendix A. Gateway Pacific Terminal VTS Study iv The Glosten Associates, Inc. Bunkering Accident Characterization, Task 10, Rev. P0 File No , 22 March 2013

6 Scope of Work per Professional Services Agreement 1 Predicts the potential size and geographic impact of a contaminant release from a bunkering or cargo transfer accident. Consequences of a spill during bunkering operations may be moderated if it is reasonable to assume that transfer operations can be effectively boomed off prior to commencing operations. 1 Exhibit A, Scope of Services Task 10, Professional Services Agreement between Pacific International Terminals, Inc. and the Glosten Associates, Gateway Pacific Terminal Vessel Traffic and Risk Assessment Study, Effective Date June 18, Gateway Pacific Terminal VTS Study v The Glosten Associates, Inc. Bunkering Accident Characterization, Task 10, Rev. P0 File No , 22 March 2013

7 Gateway Pacific Terminal Vessel Traffic and Risk Assessment Study Characterization of Bunkering and Oil and Dry Bulk Cargo Transfer Incidents (Task 10) Prepared by Dagmar Schmidt Etkin, PhD Environmental Research Consulting 41 Croft Lane Cortlandt Manor, NY February 2013

8 Contents Contents... 2 List of Tables... 4 List of Figures... 5 Purpose... 7 Executive Summary... 7 Notes on Data... 9 Data Sources... 9 Data Limitations... 9 Caution on Interpretation of Return Periods Nomenclature Notes on Vessel Types Subareas Historical Data Analysis Transfer Incidents Errors in Tanker Transfer Operations Errors in Bulk Carrier Transfer Operations Bunkering Error Incidents Historical Analysis of Incident Number and Rate Bunkering Incidents at Dock vs. at Anchor Geographic Locations of Bunkering Error Incidents Probability of Spillage with Bunkering Errors Typical Spill Volumes for Transfer-Related Incidents Oil Cargo Transfer Incidents Historical Analysis of Incident Number and Rate Cargo Transfer Incidents at Dock vs. at Anchor Geographic Locations of Oil Cargo Transfer Error Incidents Probability of Spillage in Oil Cargo Transfer Error Incidents Dry Bulk Cargo Transfer Incidents Potential Impacts of Oil Spillage due to Transfer Errors Typical Dockside or Vessel-Side (At-Anchor) Spills Impacts of Dockside or At-Anchor Spills of Crude Oil Impacts of Spills of Heavy Bunker Fuel ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

9 Impacts of Spills of Diesel Fuels Potential Impacts of Dry Cargo Spills from Transfer Errors Nature of Bulk Commodity: Coal Nature of Bulk Commodity: Petroleum Coke Nature of Bulk Commodity: Metals and Ores Nature of Bulk Commodity: Waste Ore Materials Nature of Bulk Commodity: Inorganic Salts Nature of Bulk Commodity: Fertilizers Nature of Bulk Commodity: Organic Materials Nature of Bulk Commodity: Sand, Rocks, and Gravel Nature of Bulk Commodity: Clay Nature of Bulk Commodity: Cement Nature of Bulk Commodity: Gypsum Nature of Bulk Commodity: Limestone/Dolomite Environmental Significance of Dry Cargo Inputs Relative Impact Rankings Regulatory Impact on Transfer Error Rates per Transfer Operation Estimated Reductions in Transfer Errors with Washington Transfer Rules Estimated Reductions in Transfer Errors with Transfer Rule Pre-Booming Issues References Appendix: Department of Ecology Oil Transfer Rules Designating the Person-In-Charge (PIC) Pre-Transfer Conference Pre-Loading or Cargo Transfer Plan Communication between PICs Safe Transfer Operational Requirements Work Hours Oil Transfer Equipment Requirements Oil Transfer Equipment Testing Pre-Booming Regulations for Oil Transfer Operations ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

10 List of Tables Table 1: Data Collected on Historical Vessel Incidents...9 Table 2: VTS Vessel Incidents by Vessel Type and Incident Cause Table 3: Bunkering Error and Cargo Transfer Error Incidents in GPT Study Area ( )...13 Table 4: VTS Vessel Incidents Involving Bunkering Errors Table 5: VTS Vessel Incidents Involving Bunkering Errors (Docked vs Anchored)...15 Table 6: Bunkering Incidents Involving VTS Vessels by Subarea Table 7: Percentage Bunkering Incidents Involving VTS Vessels by Subarea Table 8: Annual Rates of Bunkering Incidents Involving VTS Vessels by Subarea Table 9: Daily Rates of Bunkering Incidents Involving VTS Vessels by Subarea Table 10: Rates of Bunkering Incidents per Vessel Days at Anchor by Subarea Table 11: Rates of Bunkering Incidents per Vessel Days at Dock by Subarea Table 12: Bunker Spill Probabilities for All GPT VTS Vessels...18 Table 13: Spill Volumes for Transfer-Related Incidents...19 Table 14: VTS Vessel Incidents Involving Oil Cargo Transfer Error Table 15: Incidents Involving Oil Cargo Transfer Errors (Docked vs Anchored)...20 Table 16: Oil Cargo Transfer Incidents by Subarea Table 17: Percentage Oil Cargo Transfer Incidents by Subarea Table 18: Annual Rates of Oil Cargo Transfer Incidents by Subarea Table 19: Daily Rates of Cargo Transfer Incidents by Subarea Table 20: Rates of Cargo Transfer Incidents per Vessel Days at Anchor by Subarea Table 21: Rates of Cargo Transfer Incidents per Vessel Days at Dock by Subarea Table 22: Dry Cargo Incidents (Spills and Potential Spills) in US Waters Table 23: Dry Cargo Incidents Reported in US Waters Table 24: Causes of Dry Cargo Incidents in US Waters Table 25: Bulker Dry Cargo Incident Rates in the Entire US...24 Table 26: Amounts of Dry Cargo Spillage by Cause...24 Table 27: Interrelated Factors that Affect Oil Spill Impacts...25 Table 28: Relative Environmental Impact Scores by Oil Type...26 Table 29: Impact Risk by Oil Type/Season for GPT Study Area Zones...26 Table 30: Oil Volumes and Slick Spread Expected for Transfer-Related Spills...28 Table 31: Water Surface Coverage Million Gallon Crude Spill in San Juan Islands...31 Table 32: Shoreline Area Impact Million Gallon Crude Spill in San Juan Islands ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

11 Table 33: Modeled Wildlife Injury Million Gallon Crude Spill in San Juan Islands...31 Table 34 Fish and Invertebrate Injury Million Gallon Crude Spill in San Juan Islands...32 Table 35: Estimated Water Surface Coverage Crude Spills in San Juan Islands...32 Table 36: Estimated Shoreline Area Impact - Crude Spills in San Juan Islands...32 Table 37: Water Surface Coverage 1.05 Million Gallon Bunker Spill in Strait of Juan de Fuca...33 Table 38: Shoreline Area Impact Million Gallon Bunker Spill in Strait of Juan de Fuca...34 Table 39: Modeled Wildlife Injury Million Gallon Bunker Spill in Strait of Juan de Fuca...34 Table 40: Fish and Invertebrate Injury Million Gallon Bunker Spill in Strait of Juan de Fuca...34 Table 41: Estimated Water Surface Coverage - Bunker Spills in Strait of Juan de Fuca...34 Table 42: Estimated Shoreline Area Impact - Bunker Spills in Strait of Juan de Fuca...35 Table 43: Water Surface Coverage 2.73 Million Gallon Diesel Spill in Strait of Juan de Fuca...35 Table 44: Shoreline Area Impact Million Gallon Diesel Spill in Strait of Juan de Fuca...36 Table 45: Modeled Wildlife Injury Million Gallon Diesel Spill in Strait of Juan de Fuca...36 Table 46: Fish and Invertebrate Injury Million Gallon Diesel Spill in Strait of Juan de Fuca...36 Table 47: Estimated Water Surface Coverage - Diesel Spills in Strait of Juan de Fuca...36 Table 48: Estimated Shoreline Area Impact - Diesel Spills in Strait of Juan de Fuca...37 Table 49: Suspected Ecological Impacts of Dry Cargo on Fishery Resources and Habitats...44 Table 50: Potential Water-Column Effects from Dry Bulk Commodities...45 Table 51: Ranked Relative Impacts of Dry Cargo Commodities...47 Table 52: Bunkering Errors per Vessel Transit-Day for Bulk Carriers With and Without Transfer Rule...50 Table 53: Dry Cargo Transfer Errors Bulk Carriers With and Without Transfer Rule...51 Table 54: Summary of Current Analysis Results...52 Table 55: Transfer Locations with Currents Potentially Exceeding Boom Capability...53 Table A1: Recommendations on Bulk Oil Transfer Operations...60 List of Figures Figure 1: Geographic Subareas in Study Area...12 Figure 2: Annual Incidence of Bunkering Error and Oil Cargo Transfer Error Incidents...13 Figure 3: Locations of Bunkering Incidents Figure 4: Locations of Bulk Carrier Bunkering Incidents Figure 5: Probability Distribution of Spill Volume for Transfer-Related Oil Spills...19 Figure 6: Locations of Oil Cargo Transfer Error Incidents Figure 7: Theoretical Fresh Slick Size for 95 th and 99 th Percentile Dock Spills ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

12 Figure 8: Theoretical Fresh Slick Size for 21,000-Gallon Dock Spill...29 Figure 9: 50 th Percentile Scenario Surface Water Oiling...30 Figure 10: 95 th Percentile Scenario Surface Water Oiling...30 Figure 11: Oil Spills in California Waters Related to Oil Spill Transfer...48 Figure 12: Oil Spills and Transfer Operations in California Waters...49 Figure 13: Oil Loss from Boom through Entrainment with Increasing Current Speed ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

13 Gateway Pacific Terminal Vessel Traffic and Risk Assessment Study Characterization of Bunkering and Oil and Dry Bulk Cargo Transfer Incidents Purpose This report provides data and analyses on transfer-related incidents that occur during bunkering operations and oil and dry bulk cargo transfer operations, including those incidents that provide the potential for spillage and those that involve actual spillage. Information on the nature and rates of bunkering incidents and their geographic locations will assist in determining the potential additional impacts of bunkering activities and dry cargo transfer operations with the presence of the Gateway Pacific Terminal (GPT). The Statement of Work also includes a forecast the potential size and geographic impact of a crude oil cargo, refined product cargo, or vessel bunker fuel release from a bunkering or cargo transfer accident, as well as a dry bulk cargo release due to a transfer accident. That part of Task 10 will be conducted in the Monte Carlo simulation modeling. Executive Summary Incidents that occur as a result of errors during bunkering operations and oil and dry bulk cargo transfer operations were analyzed with respect to the following criteria: Historical incidents in the GPT study area during ; Incident occurrence by GPT subarea; Incident occurrence by activity (at-anchor or at-dock); Annual incident rates; Spillage rate per incident; Spill volume probability distributions; and Potential reductions in spillage with the Washington Transfer Rule. The following are the key findings for bunkering errors are: Bunkering transfer errors occur at a rate of about 2.38 incidents per year, or about one incident every five months in the GPT study area; The greatest number of bunkering incidents involve other vessels and occur while docked; The greatest percentage of incidents occurs in Saddlebag, followed by Guemes; The probability of spillage in the event of a bunkering error is 0.92 with no difference by hull type (double or single); Spill volumes for bunkering errors are typically small, with 90% of incidents involving 200 gallons or less, and 95% of incidents involving 500 gallons or less; and With the transfer regulations implemented and enforced, the incidence of bunkering errors could be reduced by 70%. Potential environmental impacts from bunkering spills were analyzed. In general, spills due to bunkering errors will be relatively small. For bunker spills involving heavy oils, there will be some shoreline impacts 7 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

14 that vary from 0.1 acre to about 4 acres. Oiling of birds may occur, but impacts to fish and invertebrates would be relatively low given the lower toxicity of heavy oils. When diesel fuel replaces heavy fuel oil for bunkers by about 2016 (due to regulations aimed at reducing air pollution), spills would cause greater impacts to fish and invertebrates than to shorelines due to the higher toxicity, but lower persistence and adherence of diesel. The following are the key findings for oil cargo transfer errors: Oil cargo transfer errors occur at a rate of about 2.38 incidents per year, or about one incident every five months in the GPT study area; The presence of GPT would have no effect on oil cargo transfer error incident rates as there are no oil cargo transfer associated with GPT; The greatest number of oil cargo transfer error incidents are from tankers, rather than tank barges,and occur while docked; The greatest percentage of incidents occurs in Cherry Point, followed by Guemes; The probability of spillage in the event of an oil cargo transfer is 0.92 with no difference by hull type (double or single); Spill volumes for oil cargo transfer errors are typically small, with 90% of incidents involving 200 gallons or less, and 95% of incidents involving 500 gallons or less; and With the transfer regulations implemented and enforced, the incidence of oil cargo transfer errors could be reduced by 70%. Note that the spillage probability with transfers of bunkers and oil cargo are identical because the incident rates rely on the same base data on spillage during transfers. The data from the analyses of previous international historic data do not distinguish between the transfers of bunkers and the transfers or oil cargo. The transfer operations in those data are merely characterized as oil transfers. Potential environmental impacts from oil cargo spills were analyzed. In general, spills due to oil cargo transfer errors will be relatively small. The impacts would depend on the oil cargo type. For cargo transfer spills involving heavy oils, there will be some shoreline impacts that vary from 0.1 acre to about 4 acres. Oiling of birds may occur, but impacts to fish and invertebrates would be relatively low given the lower toxicity of heavy oils. If diesel cargo were to spill, it would cause greater impacts to fish and invertebrates than to shorelines due to the higher toxicity, but lower persistence and adherence of diesel. Crude oil spillage would cause some shoreline oiling of about to 0.5 acres, depending on the spill amount. There would likely be some impacts to wildlife, though less than for the heavy oil, and some localized impacts to fish and invertebrates, though less than for the more toxic diesel spillage. The following are the key findings for dry cargo transfer errors: There is relatively little data on dry cargo spills due to any cause; and The incident rate could be reduced by 70% if best practices similar to those in the Washington Transfer Rule were implemented at GPT. Environmental impacts for spillage of dry bulk commodities are not well understood. A synopsis of known information is presented. Impacts would be expected to be limited to the immediate area of dry cargo transfers at the GPT facility. 8 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

15 Notes on Data Data Sources Data on vessel incidents (as in Table 1) were derived from the databases developed for all vessel incidents used in the GPT Vessel Traffic and Risk Assessment Study. The original data were collated from US Coast Guard records, Washington Department of Ecology records, and various proprietary databases developed by Environmental Research Consulting (ERC) for projects conducted for Washington Department of Ecology, Washington State Joint Legislative Audit and Review Committee, National Academy of Sciences, and the American Petroleum Institute. Information on individual vessels was obtained from the US Coast Guard PSIX Vessel Database, Washington Department of Ecology, and various proprietary databases on vessels. Table 1: Data Collected on Historical Vessel Incidents Data Field GPT Subarea Vessel Type Incident Cause Activity Type Juan de Fuca West Juan de Fuca East Guemes Saddlebag Haro Strait-Boundary Pass Rosario Strait Cherry Point Bulk General Cargo Tanker Tug and Tank Barge 1 Other Miscellaneous Allision Collision Grounding Other, Non-Impact Transfer Error Anchored Docked Maneuvering Underway Categories Vessels in Vessel Traffic Study (VTS Vessels) All Vessels Data Limitations Data on vessel incidents were for reported and recorded incidents only. While incidents involving larger vessels, impact accidents, and incidents that involved spillage of oil or dry cargo are highly likely to have been reported, it is possible that other incidents may not have been reported to federal and/or state authorities and thus would not have appeared in these records. Incidents involving actual or potential dry bulk spillage are not consistently reported. 1 Referred to as tank barge in this report. 9 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

16 Caution on Interpretation of Return Periods A return period or recurrence interval gives an indication of the likelihood of an event, e.g., a collision once every 200 years. This does not imply that the event will happen regularly every 200 years or that it may occur only once in 200 years. In any given 200-year period, the event may occur once, twice, more often, or not at all. The return period is merely a reflection of the frequency with which the event has occurred in the past and is likely to occur in the future given various parameters. An event with a return period of two years is much more likely to occur than one with a return period of 20 or 200 years, but it is important to remember that unlikely events can occur. A so-called 100-year flood may occur more than once in 100 years, or may not occur at all. Nomenclature Bunker hull type: the type of hull (single or double) on the bunker fuel tanks of a general cargo vessel, bulk carrier, or tanker. Bunker: includes all types of bunker fuel (Bunker A, Bunker B, Bunker C, No. 6 fuel oil, intermediate fuel oil IFO), as well as diesel fuel (No. 2 fuel oil), and marine gas oil. Bunkering: the transfer of bunker fuels from one vessel to another or from a stationary facility (storage tank) to a vessel. Crude tanker: a tank ship (tanker) that is between 67,000 and 125,000 DWT 2 and usually carries crude oil rather than refined products. In these analyses it is the size of the vessel at issue not what its cargo may be. Cumulative probability 3 : the probability that a value (e.g., oil outflow of a certain percentage) will be less than or equal to that value. For example, if the cumulative probability of an oil outflow of 80% of the oil cargo is 95%, it means that there is a 95% chance that an oil outflow will be of 80% oil cargo or less. There is only a 5% chance that the oil outflow percentage will be larger. This is similar to the term percentile. The 95 th percentile spill is that spill volume for which there is only a 5% chance that the spill will be larger. Dry cargo: bulk commodities carried by bulk carriers, including coal, grain, sand, stone, etc. GPT VTS Vessels: vessels for which there are sufficient vessel traffic data and are included in the analysis of vessel traffic risk. Incident: an occurrence with a vessel that leads to the potential for spillage of oil or dry cargo or actual spillage. Oil transfer: any movement of oil cargo and/or bunkers from one vessel to another or from a stationary facility (storage tank) to a vessel Other Vessels: this category includes only GPT VTS vessels not in other categories of tanker, bulk, tug and tank barge, or general cargo, i.e., fishing vessels over 60 feet, tugboats, cruise ships, and regularly-scheduled ferries. Outflow percentage: the percentage of the adjusted cargo or bunker capacity on board the vessel that will be released or spilled with a particular incident. 2 The vessel size description for crude tankers is based on industry descriptions of crude tankers (for the lower limit) and the regulatory limit of tanker size in Puget Sound as the upper limit. 3 This is distinct from an alternative use of this term in statistical practice which means the probability of multiple events occurring at the same time. 10 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

17 Product tanker: a tank ship (tanker) that is between 22,000 and 67,000 DWT and usually carries refined products rather than crude oil. In these analyses it is the size of the vessel at issue not what its cargo may be. Articulated tank barges (ATBs) and integrated tank barges (ITBs) are in the product tanker size category. R 2 : the coefficient of determination is a value between 0 and 1 that describes how closely a regression curve (derived equation) fits the data. Based on the proportion of data variability that is accounted for in the statistical model (derived equation), a high R 2 means that the equation fits well and will more accurately predict future outcomes. Spill volume: the amount of spillage (for oil, this is in gallons; for dry cargo, this can be in cubic feet or a weight measurement) Tankers: tankers are tank ships that carry oil as cargo, including integrated tug barges (ITBs) and articulated tug barges (ATBs). Tank barge: a tank barge (carrying oil cargo) that may or may not be attached to a tug (towboat or tugboat) at the time of the incident. The analytical results apply only to the tank barge (oil spillage, probabilities) and not to the tug. Tugs are separately included under the category Other Vessel. Notes on Vessel Types The Bulk category refers to bulkers or bulk carriers that carry dry cargo. The Tug and Tank Barge 4 includes tank barges that are not attached to tugs at the time of the incident, as well as tank barges that are attached to a tug. The incidents involving tugs and tank barges only include the incidents that involve the actual or potential spillage from the tank barges and not from the tugs. Tugs are separately tracked. Tugs, which are part of the Other Vessel and Small Other Vessel categories, include tugboats that pull barges and towboats that push barges. Incidents involving tugs can occur when the tug is attached to a barge (or barges) or when it is separate from barges. It involves actual or potential spillage from the tug and not from any barges that it may be pulling or pushing. The Tanker category is split into product tankers and crude tankers based on their general size for the purposes of the historical incident analysis only. In the vessel traffic study product and crude tankers are merged into one category regardless of size or cargo type. Articulated tug barges (ATBs) and integrated tug barges (ITBs) are considered to be tankers. General Cargo Vessels includes freight vessels, car carriers, cargo vessels, and container ships that do not fall under the category of bulkers or tankers. Other Vessels includes fishing vessels over 60 feet, cruise ships, 5 and regularly-scheduled ferries regardless of size, and all tugs regardless of size. Miscellaneous Vessels includes fishing vessels, pleasurecraft, workboats, and other vessels that are less than 60 feet in length, freight barges of any size, as well as all vessels that may exceed 60 feet for which there are no traffic data available in the traffic study. The vessels for which there are no traffic data include: research vessels, military (public) vessels, offshore supply vessels, oil recovery vessels, industrial vessels, anchor handlers, workboats, and passenger vessels over 60 feet that are not specifically ferries or cruise ships. 4 In this report, the Tug and Tank Barge category is referred to as tank barge. 55 Cruise vessels are 300 GT or larger, deep draft, and require a Puget sound pilot. 11 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

18 The term VTS Vessels is used in the analyses of historical incident data to refer to all vessel categories except for Miscellaneous vessels. These vessels are part of the vessel traffic study portion of the overall study because vessel traffic data exists for those vessel categories and because there is a risk of spillage from those vessels. Subareas The geographic subareas used in the study and in these analyses are shown in Figure 1. Figure 1: Geographic Subareas in Study Area Historical Data Analysis 6 Vessel incident data for the GPT VTRAS geographic area was analyzed for the years 1995 through Vessel incidents included in the study encompassed all incidents in which spillage occurred or that had the potential for spillage of oil and/or bulk cargo. Complete analyses of these data are presented in a separate report. Only the incidents specifically related to transfer errors are discussed in this volume. Transfer Incidents Table 2 shows a breakdown of VTS vessel types for incidents attributed to transfer errors. Transfer errors for bulk carriers, general cargo vessels, and other vessels are related to bunkering. Most of the incidents related to tanker 7 transfer errors, and all of the tank barge transfer errors 8 are related to the transfer of oil cargo, rather than bunker fuel. Bunkering incidents and oil cargo transfer incidents are analyzed separately in this report. The annual numbers of incidents of each type are shown in Figure 2 and Table 3. Note that transfer errors related to dry bulk cargo are not included in the data in these tables. There were no recorded incidents of dry cargo spillage from a bulk carrier during in the GPT study area. Dry cargo spillage is addressed separately in a section of this report as well as in the report GPT Characterization of Likely Accidents and Consequences (Task 5). 6 Based on Etkin 2013b. 7 A tanker can have a bunkering incident or an oil cargo incident. Only one tanker bunkering incident was recorded during the study time period. 8 Transfer errors involving the transfer of bunker fuel from bunkering barges is considered as an oil cargo transfer error rather than a bunkering error in these analyses. 12 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

19 Annual Number of Incidents Table 2: VTS Vessel Incidents by Vessel Type and Incident Cause General Avg. Return Bulk Tanker Tank Barge Other Total Cargo Annual Years Table 3: Bunkering Error and Cargo Transfer Error Incidents in GPT Study Area ( ) Year Bunkering Errors % Total Cargo Transfer Total Transfer % Total Errors Error Incidents % 2 2.6% % 3 3.9% % 1 1.3% % 1 1.3% % 3 3.9% % 2 2.6% % 6 7.9% % % % 1 1.3% % 1 1.3% % 1 1.3% % 2 2.6% % 1 1.3% % 2 2.6% % 2 2.6% % 1 1.3% 5 Total % % Bunkering Cargo Transfer Figure 2: Annual Incidence of Bunkering Error and Oil Cargo Transfer Error Incidents 13 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

20 A total of 76 transfer error incidents occurred in the GPT study area during the years 1995 through 2010, or about 4.8 incidents annually. Of these half were bunkering errors and half were oil cargo transfer errors. The annual number of bunkering incidents averaged 2.4, or one incident every five months. The annual number of cargo transfer error incidents was also 2.4, or one incident every five months. For all vessel types, all subareas, the historical transfer error rate at anchor is 6 incidents/16,082 days = incidents/day. For all vessel types, all subareas, the historical transfer error rate at dock is 70 incidents/16,893 days = incidents/day. The overall transfer rate is 76/32,975 = incidents/day. Note that both incidents recorded as "bunker error" and "[cargo] transfer error" are included in these incident counts. Errors in Tanker Transfer Operations There are two types of oil transfer operations that occur with tankers oil cargo transfers and bunker fuel transfers (bunkering). If there is a reported error (i.e., a transfer error ) in a cargo transfer operation, there is a probability of 0.92 that there will be a spill. Likewise, if there is an error during bunker transfer operations, there is also a probability of 0.92 that there will be a spill. There are different probabilities of the events of oil cargo transfer errors and bunker transfer errors occurring. In the course of 16 years ( ), there have been 27 transfer error incidents involving tankers in the GPT study area. 9 One of those incidents involved bunker spillage during bunkering operations. The other 26 incidents involved the spillage of oil cargo during transfer operations. For both oil cargo transfer-error related incidents and bunker transfer-related incidents there appeared to be no issue of both bunker fuel and oil cargo spilling during transfers. This is because oil cargo transfer operations are generally conducted separately from bunkering operations. The relative rate of bunkering errors to cargo transfer errors can be applied to the overall incident rate. That is, 1/27 or 3.7% of transfer errors in tankers results in the spillage of bunker fuel and 96.3% of transfer errors results in the spillage of oil cargo. It is important to note that the probability distribution functions of oil volume spilled from tankers due to oil cargo transfer operations and bunker transfer operations are different. Errors in Bulk Carrier Transfer Operations Likewise, there are two types of transfer operations in bulk carriers bunker fuel transfers (bunkering) and dry bulk cargo transfers. These are independent events with different probabilities and outcomes. The two types of incidents are addressed separately in this report. There were no recorded incidents of dry cargo spillage from a bulk carrier in the GPT study area during Bunkering Error Incidents The historical incident rate and geographic location of transfer errors occurring during bunkering operations (bunkering errors) were analyzed. Historical Analysis of Incident Number and Rate Based on the historical analyses, the key findings related to bunkering incidents are shown in Table 4. Overall, there were 33 incidents, of which 85% were from other vessels. There was an average of Etkin 2013b. 10 Dry cargo spillage is addressed separately in a section of this report as well as in Etkin 2013a. 14 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

21 incidents annually, or approximately one incident every 5 months. For bulk carriers, the incident rate was 0.13 per year, or one incident every 8 years. Table 4: VTS Vessel Incidents Involving Bunkering Errors Vessel Type Number of % Total Bunkering Average Incidents Average Incidents Return Incidents Incidents Per Year Per Day Years Tanker 1 3% Bulk 2 5% General Cargo 3 8% Other 32 84% Total % Bunkering Incidents at Dock vs. at Anchor Bunkering can occur while docked or while anchored (if from another vessel). Vessel incidents were further broken down by cause and activity for each vessel type within the VTS vessels, as shown in Table 5. The vast majority, 92%, of incidents occur while docked rather than anchored. One incident occurs while docked every six months. One incident occurs while anchored every 5.3 years. Note that according to the GPT permit, GPT bulkers will not be bunkering at the GPT dock itself. Table 5: VTS Vessel Incidents Involving Bunkering Errors (Docked vs Anchored) Docked Anchored Vessel Type Total % Avg. Return % Avg. Return Number Per Day Number Per Day Total Annual Years Total Annual Years Tanker % % n/a Bulk % % n/a Gen. Cargo % % Other % % Total % % Geographic Locations of Bunkering Error Incidents The locations of VTS vessel bunkering incidents that occurred during are in Table 6. Percentages of total incidents are in Table 7. Annual incident rates are in Table 8. Daily rates are in Table 9. Table 6: Bunkering Incidents Involving VTS Vessels by Subarea Juan De Vessel Juan De Haro Fuca Guemes Saddlebag Type Fuca East Strait West Rosario Strait 15 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills Cherry Point Tanker Bulk Gen Cargo Other Total Table 7: Percentage Bunkering Incidents Involving VTS Vessels by Subarea Juan De Vessel Juan De Haro Rosario Cherry Fuca Guemes Saddlebag Type Fuca East Strait Strait Point West Total Tanker 0% 0% 0% 3% 0% 0% 0% 3% Bulk 0% 3% 0% 0% 0% 0% 3% 5% Gen Cargo 0% 5% 0% 3% 0% 0% 0% 8% Total

22 Table 7: Percentage Bunkering Incidents Involving VTS Vessels by Subarea Juan De Vessel Juan De Haro Rosario Cherry Fuca Guemes Saddlebag Type Fuca East Strait Strait Point West Total Other 3% 3% 29% 39% 0% 0% 11% 84% Total 3% 11% 29% 45% 0% 0% 13% 100% Table 8: Annual Rates 11 of Bunkering Incidents Involving VTS Vessels by Subarea Juan De Juan De Vessel Haro Rosario Cherry Fuca Fuca Guemes Saddlebag Total Type Strait Strait Point West East Return Yrs Tanker Bulk Gen Cargo Other Total Return Yrs Table 9: Daily Rates of Bunkering Incidents Involving VTS Vessels by Subarea Juan De Vessel Juan De Haro Rosario Cherry Fuca Guemes Saddlebag Type Fuca East Strait Strait Point West Total Tanker Bulk Gen Cargo Other Total The data in Table 8 on annual rates of incidents have been converted into rates per vessel days at anchor and vessel days at dock in Tables 10 and 11. Note that not all time at dock and at anchor is devoted specifically to bunkering activities. Table 10: Rates of Bunkering Incidents 12 per Vessel Days at Anchor 13 by Subarea Juan De Vessel Juan De Haro Rosario Cherry Fuca Guemes Saddlebag Type Fuca East Strait Strait Point West Total Tanker Bulk Gen Cargo * Other * 0 0 * 0 Total Note annual rate means the number of incidents per year. 12 While there are reported incidents in zones shown as *, there are no corresponding vessel transit data. 13 Based on total at-anchor times for ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

23 Table 11: Rates of Bunkering Incidents 14 per Vessel Days at Dock 15 by Subarea Juan De Vessel Juan De Haro Rosario Cherry Fuca Guemes Saddlebag Type Fuca East Strait Strait Point West Total Tanker * Bulk Gen Cargo Other * * * 0 0 * Total A map of the locations of the bunkering incidents is shown in Figure 3. Figure 4 shows the locations of the two bulk carrier incidents. Figure 3: Locations of Bunkering Incidents Red = other vessels; teal = bulk carriers; green = tanker; yellow = general cargo Note that because of the large number of incident location markers on the map and multiple incidents in the same location there is overlap of markers in several cases. Figure 4: Locations of Bulk Carrier Bunkering Incidents Location A = Port of Port Angeles; Location B = Cherry Point 14 While there are reported incidents in zones shown as *, there are no corresponding vessel transit data. 15 Based on total at-dock times for ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

24 Probability of Spillage with Bunkering Errors When a bunkering error occurs, there is the potential for spillage but a spill does not necessarily occur. The probabilities of bunker spillage by vessel type, cause, and hull type are shown in Table 8. Note that for tankers, there is a separate probability for bunker spillage and oil cargo spillage. Note that there is no difference between hull types with regard to bunkering spills. There is also no difference between vessel types. For all vessel types and hulls, the probability of spillage is estimated at The reason that the probability is so high is most likely attributable to the fact that the error is generally discovered when a spill, however small, does occur, with a few exceptions. The practices used in bunkering are similar in the different vessel types with spillage generally coming from hoses rather than from the vessel itself. The probabilities in Table 12 are based on studies conducted on US oil spills. 16 Note that the spillage probability with transfers of bunkers and oil cargo are identical because the incident rates rely on the same base data on spillage during transfers. The data from the analyses of previous international historic data do not distinguish between the transfers of bunkers and the transfers or oil cargo. The transfer operations are merely characterized as oil transfers. Table 12: Bunker Spill Probabilities for All GPT VTS Vessels 17 Vessel Type Incident Cause Hull Bunker Spill Probability Single (BH Tankers (V t ) Bunkering Error s ) 0.92 Double (BH d ) 0.92 Bulk Carriers Single (BH Bunkering Error s ) 0.92 (V b ) Double (BH d ) 0.92 General Cargo Single (BH Bunkering Error s ) 0.92 Vessels (V g ) Double (BH d ) 0.92 Other Vessels Single (BH Bunkering Error s ) 0.92 (V o ) Double (BH d ) 0.92 Typical Spill Volumes for Transfer-Related Incidents Bunker oil and cargo oil outflow is generally independent of vessel tonnage for the GPT VTS vessels being analyzed in this study. This is because the oil outflow generally comes through a hose and not from a breach of the cargo or bunker tank. The transfer operation is usually halted as soon as possible after the leak is discovered and the amount of actual spillage is related to the pumping rate, the time until leak discovery, and the time it takes to turn off the pumps/equipment. Generally, spills due to transfer errors are smaller than the spills that occur with impact accidents (collisions, allisions, and groundings). The data shown in Table 13 and Figure 5 are the spill volumes associated with a large number of transfer-related spills reported in US waters. [These data include transfers of cargo.] While the maximum observed transfer-related spillage is 500,000 gallons, the maximum for a particular vessel s bunker spillage when the vessel contains less than 500,000 gallons in bunker fuel would naturally be the bunker capacity of the vessel. Sixty percent of spills are 10 gallons or less. Ninety percent of spills are 200 gallons or less. 16 Etkin and Michel 2003; Herbert Engineering et al Based on Etkin and Michel 2003; Michel and Winslow 1999, ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

25 Probability Table 13: Spill Volumes for Transfer-Related Incidents 18 Spill Volume Probability Cumulative Probability 1 gallon gallons gallons gallons gallons gallons gallons ,000 gallons ,000 gallons ,000 gallons ,000 gallons Probability Cumulative Probability ,000 10, ,000 1,000,000 Gallons Figure 5: Probability Distribution of Spill Volume for Transfer-Related Oil Spills Oil Cargo Transfer Incidents The historical incident rate and geographic location of transfer errors occurring during oil cargo transfer operations were analyzed. Historical Analysis of Incident Number and Rate Based on the historical analyses, the key findings related to bunkering incidents are shown in Table 14. Overall, there were 38 incidents, of which 68% were from tankers, 32% from tank barges. There were on average 2.38 incidents annually, or approximately one incident every 5 months. For tankers, the annual incident rate was 1.63, or one every 7 months. For tank barges, the annual incident rate was 0.75 or one in every 1.3 years (once every 16 months). 18 Etkin ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

26 Table 14: VTS Vessel Incidents Involving Oil Cargo Transfer Error Vessel Type Number of Incidents % Total Oil Cargo Average Incidents Transfer Incidents Per Year Return Years Tanker 26 68% Tank Barge 12 32% Total % Cargo Transfer Incidents at Dock vs. at Anchor Oil cargo transfers can occur while docked or anchored. Vessel incidents were broken down by cause and activity as in Table 15. The majority, 92%, of incidents occur while docked rather than anchored. One incident occurs at dock every six months. One incident occurs at anchor every 5.3 years. Table 15: Incidents Involving Oil Cargo Transfer Errors (Docked vs Anchored) Docked Anchored Vessel Type Total % Avg. Return % Avg. Return Number Per Day Number Per Day Total Annual Years Total Annual Years Tanker % % Tank Barge % % n/a Total % % Geographic Locations of Oil Cargo Transfer Error Incidents The locations of VTS vessel cargo transfer incidents that occurred during are in Figure 6 and Table 16. Percentages of total incidents are in Table 17. Annual and daily incident rates are in Tables 18 and 19, respectively. Table 16: Oil Cargo Transfer Incidents by Subarea Vessel Type Juan De Fuca West Juan De Fuca East Guemes Saddlebag Haro Strait Rosario Strait 20 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills Cherry Point Tanker Tank Barge Total Table 17: Percentage Oil Cargo Transfer Incidents by Subarea Juan Juan Haro Vessel Type De Fuca De Fuca Guemes Saddlebag Strait West East Rosario Strait Cherry Point Tanker 0% 8% 16% 0% 0% 0% 45% 68% Tank Barge 0% 3% 16% 0% 0% 0% 13% 32% Total 0% 11% 32% 0% 0% 0% 58% 100% Table 18: Annual Rates 19 of Oil Cargo Transfer Incidents by Subarea Juan Juan Haro Rosario Cherry Vessel Type De Fuca De Fuca Guemes Saddlebag Strait Strait Point West East Tanker Tank Barge Total Return Yrs Annual rate means the number of incidents per year. Total Total Total Return Yrs

27 Table 19: Daily Rates of Cargo Transfer Incidents by Subarea Juan De Juan De Haro Vessel Type Fuca Guemes Saddlebag Fuca East Strait West Rosario Strait Cherry Point Tanker Tank Barge Total The data in Table 18 on annual rates of incidents have been converted into rates per vessel days at anchor and vessel days at dock in Tables 20 and 21. Note that not all time at dock and at anchor is devoted specifically to oil cargo transfer activities. Total Table 20: Rates of Cargo Transfer Incidents per Vessel Days at Anchor 20 by Subarea Juan De Vessel Juan De Haro Rosario Cherry Fuca Guemes Saddlebag Type Fuca East Strait Strait Point West Total Tanker Tank Barge Total Table 21: Rates of Cargo Transfer Incidents per Vessel Days at Dock 21 by Subarea Juan De Vessel Juan De Haro Rosario Cherry Fuca Guemes Saddlebag Type Fuca East Strait Strait Point West Total Tanker Tank Barge Total Figure 6: Locations of Oil Cargo Transfer Error Incidents Red = tanker; yellow = tank barge. Note that because of the large number of incident location markers on the map and multiple incidents in the same location there is overlap of markers in several cases. A = Port of Port Angeles; B = Anacortes refinery (6 tanker/6 tank barge incidents); C = Ferndale refinery/intalco Aluminum; D = Cherry Point refinery (8 tanker/1 tank barge incidents); E = Blaine harbor 20 Based on total at-anchor times for Based on total at-dock times for ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

28 Probability of Spillage in Oil Cargo Transfer Error Incidents When an oil cargo transfer error occurs, there is the potential for spillage but a spill does not necessarily occur. The probability of oil cargo spillage for tankers and tank barges is 0.92 regardless of hull type (based on studies conducted on US oil spills 22 ). The reason that the probability is so high is most likely attributable to the fact that the error is generally discovered when a spill, however small, does occur, with a few exceptions. The practices used in oil cargo transfers are similar in tankers and tank barges with spillage generally coming from hoses rather than from the vessels themselves. Note that the spillage probability with transfers of bunkers and oil cargo are identical because the incident rates rely on the same base data on spillage during transfers. The data from the analyses of previous international historic data do not distinguish between the transfers of bunkers and the transfers or oil cargo. The transfer operations are merely characterized as oil transfers. Dry Bulk Cargo Transfer Incidents Spillage of dry cargo from bulkers has not been regularly or systematically recorded by Washington Department of Ecology or by the US Coast Guard for the years for Washington State. Reports to the National Response Center (and the US Coast Guard) for the entire US has only been sporadic. Much of this is due to lack of information on the impacts of these spills and the fact that spillage of dry cargo residues has long been considered to be part of the routine operations of loading, unloading, and transport of bulk dry cargo on bulker vessels. This has led to irregular reporting of incidents. In US Coast Guard (and National Response Center) records there have been occasional reports of spills of dry bulk cargo from either barges or bulkers, as shown in Table 22. The fact that so few incidents were reported does not necessarily indicate that these spills do not occur, but rather than when they do they are considered minor or inconsequential because of the nature of the commodities and the lack of stringent regulations requiring reporting, or the lack of knowledge of existing regulations. Table 22: Dry Cargo Incidents (Spills and Potential Spills) in US Waters Year Number of Incidents Barges Bulkers Total Etkin and Michel 2003; Herbert Engineering et al Includes inland navigable waterways. From ERC spill databases. 22 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

29 Table 22: Dry Cargo Incidents (Spills and Potential Spills) in US Waters Year Number of Incidents Total Total In all of the US, there have been only 47 dry cargo incidents with spillage or potential spillage reported in 16 years (or 2.9 per year), of which only 10 were from bulkers rather than freight barges (or 0.21 per year). The commodities spilled (or potentially spilled) have included those shown in Table 23. Fifty-seven percent of the incidents involved coal. One of the bulker incidents occurred in Washington waters, though both outside of the area of the GPT study zones. In 2010, there was a spill of an unknown amount of coal at the United Harvest facility on the Columbia River in Kalama, Washington. Table 23: Dry Cargo Incidents Reported in US Waters Commodity Barges Bulkers Total Cement Coal Concrete Fertilizer Grains Lime Limestone Sand Sulfur Taconite (Iron Ore) Wood Chips Total The spill (or potential spill) causes have included those shown in Table 24. Table 24: Causes of Dry Cargo Incidents in US Waters Cause Barges Bulkers Total Number % Number % Number % Impact Accident 0 0% 2 20% 2 4% Other Non-Impact Error 32 86% 6 60% 38 81% Transfer Error 5 14% 2 20% 7 15% Total % % % Of the bulker incidents, two (20%) involved groundings. Note that there were no incidents involving collisions or allisions. There have been many collisions, allisions, and groundings of bulker vessels in US waters over the course of the 16-year time period, with an annual average of about 40 incidents per year that cause spillage of at least 50 gallons bunkers 26, while there have been only two groundings of bulkers have caused any spillage of dry cargo. That would translate to a probability of for a bulker grounding to cause spillage of dry cargo. There have been no incidents of collisions or allisions causing spillage or potential spillage of dry cargo. With no groundings of bulkers in Washington waters, this leaves a probability of zero for spills of dry cargo. 24 Includes inland navigable waterways. From ERC spill databases. 25 Includes inland navigable waterways. From ERC spill databases. 26 Etkin ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

30 Another more conservative approach is presented in Table 25. These are estimates of probabilities of spillage by cause per transit based on the number of incidents that occurred in the US over 16 years and the approximate number of port visits. (It can be assumed that each port visit is one day.) It is conservatively estimated that all of the incidents described above caused some spillage even though the records do not necessarily indicate that. Table 25: Bulker Dry Cargo Incident Rates in the Entire US GPT Cause Incidents in 16 years Estimated Transit- Days in 16 years 27 Probability of Incident Involving Spillage of Dry Cargo 28 Per Transit-Day Impact Accident 2 155, Other Non-Impact Error 6 155, Transfer Error 2 155, The probability of a dry cargo spill is independent of the probability of a bunker spill in bulk carriers. The amount of spillage from the historical data is uncertain in most cases because of the lack of follow-up after the initial reports, and difficulties in estimating the amount of spillage after material sank into the water. In one case, 500 pounds of taconite (iron ore) was reported to have spilled from a bulker in the St. Lawrence River in 1995 due to unknown causes. The paucity and inaccuracy of data on spill amounts of dry cargo presents a challenge for estimating a probability distribution of spill volumes. There are also no outflow models to estimate the amount of dry cargo that would be spilled in different types of accidents. The typical amounts of reported (and verified) spillage by cause are shown in Table 26. Table 26: Amounts of Dry Cargo Spillage by Cause 29 Dry Cargo Amount (tons) Transfer Error 0 2 tons Other Non-Impact Error 0 1,000 tons 30 Impact Accident 0 2 tons Potential Impacts of Oil Spillage due to Transfer Errors The environmental and socioeconomic impacts of spillage due to transfer errors depend on a number of interrelated factors: 31 Geographic location; Proximity to sensitive ecological and socioeconomic resources; Level of sensitivity of resources at risk; Oil type; Quantity spilled; Season of spillage event (weather conditions, migratory patterns); 27 Based on estimated 9,700 port visits (transits) annually (from Etkin 2010). 28 This is independent of the probability that there will be an incident that could cause a bunker oil spill. 29 Includes inland navigable waterways. From ERC spill databases. 30 The highest amount occurs when the entire vessel sinks. 31 French-McCay et al. 2004; NRC ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

31 Winds and currents at the site at the time of spillage and in its aftermath; Sea state (wave height) at the site at the time of spillage and in its aftermath; Degree and type of spill mitigation measures (spill response, preventive booming, etc.); and Effectiveness of spill mitigation measures. The ways in which these factors affect spill impacts and are interrelated are summarized in Table 27. Table 27: Interrelated Factors that Affect Oil Spill Impacts Factor Varied Values Spill Impacts 32 Interrelated Factor(s) Affect on Spill Impact High toxicity Higher temperatures increase Volatile Lower dissolution Temperature evaporation rate Distillates High evaporation Cleanup response Cleanup response not usually possible (Gasoline, Non-persistent Proximity of water Proximity to water intakes and jet fuel, Low adherence intakes and fish larvae presence of fish larvae can increase kerosene) Shorter-term moderate fish (seasonal) impacts kill, water quality impacts Oil type Location Sensitive Resources Light Fuels (Diesel, No. 2 fuel, marine gas oil) Crude Heavy Oils (Bunker C, No. 6 fuel oil, IFO) Wetlands Fish Wildlife Cultural High toxicity High dissolution Moderately high evaporation Low persistent Low adherence Moderate-term fish kill, water quality impacts Moderate toxicity Moderate dissolution Moderate evaporation Persistent High adherence Lower water column impacts (fish kill and water quality), moderate-term shoreline impacts, bird/mammal coating Lower toxicity Low dissolution Low evaporation Very high adherence Very high persistent Low water column impacts (fish kill and water quality), longer-term shoreline impacts, bird/mammal coating Fish sensitive to toxicity Wildlife sensitive to toxicity and adherence Cultural sensitive to adherence and toxicity Temperature Cleanup response Proximity of water intakes and fish larvae (seasonal) Cleanup response Proximity to sensitive shorelines and wildlife Cleanup response Proximity to sensitive shorelines and wildlife Cleanup response Season Higher temperatures increase evaporation rate Cleanup response not usually possible Proximity to water intakes and presence of fish larvae can increase impacts Cleanup response and preventive booming of sensitive areas can mitigate some impacts High presence of sensitive resources and wildlife will increase impacts through coating and some toxicity Cleanup response and preventive booming of sensitive areas can mitigate some impacts High presence of sensitive resources and wildlife will increase impacts through coating Cleanup response and preventive booming of sensitive areas can mitigate some impacts Season may affect degree of sensitivity of resources 32 Dissolution means dissolving into the water column. Persistence means the degree to which the components of the oil, particularly polycyclic aromatic hydrocarbons (PAHs) remain in the environment after spillage. Adherence means the propensity for sticking to and coating surfaces, including bird feathers, mammal fur, and shoreline features. 25 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

32 Table 27: Interrelated Factors that Affect Oil Spill Impacts Factor Varied Values Spill Impacts 32 Interrelated Factor(s) Affect on Spill Impact With wind and currents in Wind/current Winds Puget Sound most spills Season Winds and currents differ by location direction and Currents will impact shoreline and Location and somewhat by season velocity spread Cleanup Response Diversion Containment Recovery Protective/diversion and containment booming can mitigate some impacts Recovery reduces oil amount that can impact resources Current velocity Oil type 26 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills Currents > 1 knot will hamper protective/diversion and containment booming Mechanical recovery is dependent on booming effectiveness Volatile distillates/light fuels cannot effectively be recovered to any extent Washington Department of Ecology developed a methodology for assigning a relative environmental impact score to different oil types as shown in Table 28. Table 28: Relative Environmental Impact Scores by Oil Type 33 Oil Type Acute Toxicity Mechanical Injury (Coating) Persistence 34 Crude Heavy oils Light oils Gasoline Jet fuel In a study conducted for the Washington State Legislative Audit and Review Committee, 35 the relative sensitivity to oiling by different oil types (as in Table 26) in different seasons was coupled with the relative sensitivity of various subregions in the state s waters to derive a season-specific and oil-type specific sensitivity on a regional basis. Table 29 shows these scores for the regions in the GPT study area. Note that throughout the state, the impact risk scores varied from a low of 6.15, as in the Strait of Juan de Fuca West during the winter with a spill of jet fuel, to a high of 32.82, as in the Strait of Juan de Fuca East, with a spill of heavy oil in the spring. These risk scores provide a measure of relative sensitivity of the environment to oiling by different oil types by season. The actual impacts will depend on the quantity of oil spilled, the exact location with regard to the proximity to specific sensitive resources, wind and currents (velocity and direction) at the time of the spill and in its aftermath, and the degree to which a spill response can mitigate the impacts. Table 29: Impact Risk by Oil Type/Season for GPT Study Area Zones 36 Zone Oil Type Spring Summer Fall Winter Crude Heavy oils Strait of Juan de Fuca 37 Light oils Gasoline Jet fuel WAC Score of 5 = 5-10 years or more persistence; 4 = 2-5 years; 3 = 1-2 years; 2 = 1 month -1 year; 1 = days to weeks. 35 French-McCay et al. 2008; Etkin et al. 2009; French-McCay et al French-McCay et al. 2008; Etkin et al. 2009; French-McCay et al Corresponds to Juan de Fuca West subarea in GPT study.

33 Table 29: Impact Risk by Oil Type/Season for GPT Study Area Zones 36 Zone Oil Type Spring Summer Fall Winter Crude Heavy oils Inner Straits 38 Light oils Gasoline Jet fuel Crude Heavy oils Rosario Strait and Vicinity 39 Light oils Gasoline Jet fuel Note that the impacts of any oil spill can be mitigated to some degree with a prompt and effective spill response. The factors that affect the efficacy of spill response measures are complex and depend on the response strategy. In general, the effectiveness of mechanical containment and recovery operations (booms and skimmers or vacuum pumping) is rarely more effective than 5 25% on open water. For transfer operation spills, however, the response effectiveness can be greatly enhanced for a number of reasons: Most transfer operations in the GPT study area will be conducted with pre-booming around the vessel; Transfer operations conducted at a dockside facility will have response equipment at the dock or in the near vicinity, and onboard the vessel or in the near vicinity at an anchorage; Mechanical recovery (vacuum pumping and skimming) will be highly effective (50% to as high as 90% or more) when conducted under conditions of calm water, well-contained oil (with boom) to increase the thickness of the oil on the water surface), and within a short time-frame after spillage so that oil will not spread; Transfer operations are conducted by skilled personnel with spill response preparedness training. Impacts of oil spills in the GPT study area have been studied extensively 40 and it is beyond the scope of this project to do spill trajectory, fate, and effects modeling and analyses on potential spill scenarios of transfer errors. Brief synopses of the key findings for spill impacts as specifically relevant to the expected spills of bunker fuel, oil cargo, and dry cargo from transfer errors in the GPT study area are presented in this report. Typical Dockside or Vessel-Side (At-Anchor) Spills Most transfer-related spills would be expected to be relatively small. For all transfer-related spills (bunkering and cargo transfer) in the US, the 95 th percentile spill involved 500 gallons, the 99 th percentile spill 41 involved 10,000 gallons. In GPT study area, during , the largest transfer-related spill was one of 21, Corresponds to Juan de Fuca East subarea in GPT study. 39 Corresponds to Rosario Strait, Haro Strait-Boundary Bay, Cherry Point, Guemes Channel, and Saddlebag subareas in GPT study in addition to San Juan Islands, which is excluded from the GPT study area. 40 For example, Etkin 2005; Etkin et al. 2005, 2009; French-McCay et al. 2005a, 2005b, 2005c, 2006a, 2006b, A percentile spill is that spill volume at which n% of spills are smaller and only 1-n% are larger. For the 99 th percentile spill, only 1% are larger. 27 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

34 gallons 42 that occurred dockside at Cherry Point refinery in 1972 (T/V World Bond) at a time before many of the current spill prevention measures and regulatory practices were in place. The spill volume is important in that it determines the degree of potential spread of the oil, as shown in Table 30. This table shows dockside transfer spills in Puget Sound during the years Table 30: Oil Volumes and Slick Spread Expected for Transfer-Related Spills Percentile Spill Gallons Fresh Slick 44 Square Miles Coverage 43 Rainbow Sheen 45 Silver Sheen th th th th th 1, Worst-Case (actual) 21, ,300 Figure 7 shows the dimensions of fresh slicks of 0.06 and 0.3 square miles at a hypothetical spill at the BP Cherry Point dock. Figure 8 shows a three-square-mile slick from a 21,000-gallon spill. The oil would spread out into sheen with evaporation and natural dispersion, depending on oil type. Figure 7: Theoretical Fresh Slick Size for 95 th and 99 th Percentile Dock Spills 42 ERC Spill Databases. 43 Assuming 25% evaporation for sheen mm thickness mm thickness mm thickness 28 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

35 Figure 8: Theoretical Fresh Slick Size for 21,000-Gallon Dock Spill With mandatory pre-booming of vessels during oil transfer operations, as discussed in another section of this report, it is highly likely that in the case of a dockside spill, the majority of oil spilled would be contained by boom, especially under calm weather conditions. Pre-positioned oil recovery equipment (e.g., vacuum pumps) would recover oil within the containment area. In the event that oil escaped the containment boom, the oil would spread, with its trajectory dependent on winds and currents in the hours after the spill occurred. If the oil escaped containment booming at dockside, the oil would eventually form a thin sheen as it spread. The degree of spreading and the behavior of the oil with regard to evaporation rates, emulsification, dispersion, and dissolution are dependent on the oil type, as well as temperature conditions at the time of the spill. Impacts of Dockside or At-Anchor Spills of Crude Oil 47 The trajectory of spills in the San Juan Islands area has been studied extensively for much larger spills than would be expected for a transfer-related dockside spill. Modeling studies conducted by ERC with its colleagues at Applied Science Associates, Inc. (ASA) for Washington Department of Ecology 48 on spill scenarios of 2.73 million gallon spill of crude oil spilled in the San Juan Islands area provide data on the fate and effects of this amount of spillage in this location. The spread and trajectory of the oil, as well as its impacts, vary with the particular conditions of season, timing with currents, and wind direction and velocity. The studies including stochastic modeling of hundreds of outcomes of spillage based on these environmental variables. The results for the 50 th (median) and 95 th percentile 49 (worst-case) 50 damage scenarios were analyzed. Note that the percentile damage cases are not the same as the percentile volume cases. The former 47 Crude oil is presented as a typical oil cargo. Other oil cargos would include diesel and heavier oils (discussed under bunker spills below.) 48 French-McCay et al. 2005, 2006a, 2006b. 49 The n th percentile case is that particular set of environmental circumstances for the spill for which n% of the cases have lesser impacts and 100 n% of the spills have greater impacts. 50 The 95 th percentile case was used rather than the 99 th or 100 th percentile case with the assumption that the 96 th 100 th cases would represent statistical outliers. 29 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills

36 ranks the spill scenarios of the same volume by damage caused depending on the particular circumstances of season, winds, and currents at the time of the spill. The latter ranks spills by volume alone. Figures 9 and 10 show two potential scenarios of oil spread (including sheen) of a 2.73 million-gallon spill of Alaska North Slope Crude oil in the San Juan Islands area. This hypothetical spill is 130 times larger than the most-likely largest spill for any dockside- or vessel-side, for that matter, spill scenario. This degree of spill spread would occur only with an extremely large dockside spill, an event that is highly unlikely, but is presented here to demonstrate the extreme case. Figure 9: 50 th Percentile Scenario Surface Water Oiling Figure 10: 95 th Percentile Scenario Surface Water Oiling 30 ERC Report: GPT Characterization of Bunker and Oil and Dry Cargo Transfer Spills