4 Oil & Hydrocarbon Spills, Modelling, Analysis & Control...Oil & Hydrocarbon Spills, Modelling,...

Quantifying environmental implications of

alternative oil spill contingency and response

plans

M. Reed & N. Ekrol

SINTEF Applied Chemistry

Environmental Engineering

Trondheim, Norway

mark. reed@chem. sintef.no

Abstract

This paper suggests some simple and robust physical, chemical, andtoxicological measures of mitigation success. More in-depth measures andanalyses for unusually sensitive environmental issues can then support thesefirst-order measures. Example applications are carried out with the SINTEF OilSpill Contingency and Response (OSCAR1 model system. The methodologysupplies an objective basis for net environmental analysis of planned responsestrategies.

Introduction

The purpose of spill response actions is to mitigate potentialenvironmental effects of oil spills. Given the uncertainty associated withdetailed prognostics of biological dynamic processes, it is desirable toestablish some robust measures of environmental consequence, whichrely on some broad assumptions of animal behaviour. More in-depthmeasures and analyses for unusually sensitive environmental issues canthen support these first-order measures. A set of such measures is givenhere, with example applications carried out with the SINTEF Oil SpillContingency and Response (OSCAR) 3-dimensional model system. The

Transactions on Ecology and the Environment vol 20, © 1998 WIT Press, www.witpress.com, ISSN 1743-3541

4 Oil & Hydrocarbon Spills, Modelling, Analysis & Control

analysis supplies an objective basis for net environmental analysis ofplanned response strategies.The measures of potential environmental impact presently used inOSCAR are listed in Table 1. The user identifies the natural resourceareas of interest from local experts, biological atlases, or natural resourcedatabases. Such natural resource areas may include beaches, bird andmarine mammal habitats, and fishing and spawning areas. OSCAR canthen summarise, for each area, the exposure to surface and / or subsurfacehydrocarbons for each alternate response strategy to be analysed. Resultsare produced graphically as time series:• fractional or areal surface coverage of resource area (oil exceeding a

specified thickness)

• volumes over specified concentrations of hydrocarbons (dissolved or

total).

OSCAR also includes models to compute exposure of fish, fish eggs, andlarvae to hydrocarbons in the water column. Here the swimmingbehaviour of adult fish and the passive drift of eggs and larvae fromspawning areas are used to compute and record:• time series of exposures (above a specified minimum concentration)

• cumulative exposures.

For even more detailed analysis, the marine mammal and bird migrationmodel MIGMOD (Downing and Reed, 1996) evaluates individual animalexposures. Thus OSCAR can be used for Net Environmental BenefitAnalysis (NEBA) of alternate spill response strategies, comparing forexample the net change in environmental impact with and without the useof dispersants. Reed et al (1998) and Ekrol (1998a, b) demonstrates theapplication of some of these capabilities.

1 Model Description

The OSCAR model system (Reed et al, 1995a; Aamo et al, 1996) hasbeen developed to supply a tool for objective analysis of alternative spillresponse strategies. OSCAR is intended to help achieve a balancebetween the cost of preparedness on the one hand, and potentialenvironmental impacts on the other. Although it is always theoreticallypossible to purchase more equipment, or a higher level of preparedness,the marginal value, in terms of reduced environmental impacts, of eachadditional purchase tends to decrease. OSCAR is a tool that directly andobjectively addresses this trade-off.


Oil & Hydrocarbon Spills, Modelling, Analysis & Control 5

Key components of the system are shown schematically in Figure 1.

SINTEF's data-based oil weathering model (Aamo et al, 1993; Baling etal, 1990, 1997) is linked to a three-dimensional oil trajectory andchemical fates model (Reed et al, 1995b), and an oil spill combat model(Aamo et al, 1995, 1996). Biological exposure models for fish andichthyoplankton (Reed et al, 1995a, 1998), and birds, and marinemammals (Downing and Reed, 1996) are also included in the system.

OSCAR has been applied to the analysis of alternative oil spill responsestrategies for both offshore platforms (Aamo et al, 1995; Reed et al,1995a; Ekrol 1998a, b) and coastal terminals (Reed et al, 1997). OSCARprovides, for alternate spill response strategies, a basis forcomprehensive, quantitative environmental impact assessments in themarine environment. The model calculates and records the dynamicdistribution in three physical dimensions plus time of a contaminant onthe water surface, along shorelines, in the water column, and in thesediments. The model is embedded within a graphical user interface inWINDOWS NT, which facilitates linkages to a variety of standard andcustomised databases and tools. These tools allow the user to create orimport wind time series, current fields, and grids of arbitrary spatialresolution, and to map and graph model output.

1.1 Oil weathering database

Oil and chemical databases supply chemical and toxicological parametersrequired by the model. A unique strength of the OSCAR model is itsfoundation on an observational database of oil weathering properties. Thelaboratory and field methods developed at SINTEF for weathering ofcrude oils and petroleum products are described in Dating et al. (1990,1997). Numerous field tests have verified the reliability of weatheringpredictions based on this methodology, avoiding unrealistic results thatare common with other computational approaches.


Table 1. Measures of potential environmental impact used in OSCAR for comparison of alternative oil spill responsestrategies. Each measure is available as a snapshot or time series.

ImpSurfaceWater

Act

0nExP0Sure

act MeasureMaximumArea

Potential SurfaceExposureSwept Area

Maximum Volume

Potential Exposure inWater ColumnSwept Volume

Mass Ashore

Mass Recovered

Mass Dispersed

Fish

Fish Eggs and Larvae

Birds and MarineMammals

Meaning / InterpretationMaximum instantaneous surface area covered with oil over a specified threshold thickness (e.g. 100 jim)

Surface area covered with oil over the threshold thickness integrated over time, a measure of the potential forexposure of birds and marine mammalsTotal surface area affected by oil over the threshold thickness

Max. instantaneous volume in the water column affected by concentrations of WSF over a specified threshold (e.g.lOppb)Total volume over concentration threshold, integrated over time, a measure of potential exposure for ichthyoplanktonand fishTotal volume affected by WSF above the threshold concentration

Total mass of oil ashore

Total oil removed from the environment via skimming operations

Mass of oil dispersed into the water column due to chemical dispersants

Histogram showing fraction of fish in the area which are exposed to WSF concentrations, by exposure interval,computed with active swimming behaviour

Exposure histogram for eggs/larvae, computed as for fish, but assuming passive drift

Oil-animal interaction statistics for individuals and populations

Units

km^

knr - days

km^

km^

knr - days

km^

tonnes

tonnes

tonnes

ppb - hours

ppb - hours

oo

o

CO

2o

OQ

ppoo«—»3



1.2 Physical-chemical fates processes

Processes governing the behaviour of spilled hydrocarbons in OSCARare presented in Figure 2. OSCAR employs surface spreading, advection,entrapment, emulsification, and volatilisation algorithms to determinetransport and fate at the surface. In the water column, horizontal andvertical advection and dispersion of entrained and dissolvedhydrocarbons are simulated by random walk procedures. Verticalturbulence is a function of wind speed (wave height) and depth;horizontal turbulence is a function of the age of a pollutant 'cloud'.Partitioning between particulate-adsorbed and dissolved states iscalculated based on linear equilibrium theory. The contaminant fractionthat is adsorbed to suspended particulate matter settles with the particles.Contaminants at the bottom are mixed into the underlying sediments, andmay dissolve back into the water. Degradation in water and sediments isrepresented as a first order decay process. The algorithms used tosimulate these processes controlling physical fates of substances aredescribed in Aamo et al (1993) and Reed et al (1994, 1995a, b).

Results of model simulations are stored at discrete time-steps in computerfiles, which are then available as input to one or more biological exposuremodels.

1.3 Spill response capabilities

Parameters defining the response capabilities are outlined in Table 2 formechanical recovery systems, and Table 3 for dispersant applicationsystems. Recovery efficiency is assumed dependent on significant waveheight (Figure 3), which in OSCAR is computed as a function of windspeed, fetch, water depth, and duration. Under ideal conditions, amaximum percentage of the oil entering the boom can be recovered, withthe remaining leaking under the boom. Effectiveness is reduced as waveheight increases, and goes to zero at a user-supplied threshold waveheight. The user can also specify whether operations cease at night (i.e.whether infrared-monitoring equipment is available). OSCAR computessunrise and sunset from latitude and longitude and calendar day.


Oil1 Characteristics

1 1

SINTEF-OWMOil Weathering

Model

Biok• Pas• Act• Migmar

Measui•Mass•Reduc- ashc- wate- wate

Oil & Hydrocarbon Spills, Modelling, Analysis & Control 9Recovery

Efficiency (%

o£8SSS§c!§g!

//

Re

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co\mm

X

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ery

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-3. 22>

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IcU

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x

m.5mwlr

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"*V

X

thmlthid

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yof

reshnresspe"

Relationship of Wave Height toBoom-Skimmer Systems (Left Axis) and Wind Speed (Right Axis)

*̂%\

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hojshho>ed

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\D.1 0.3 0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9

Wave Height (m)

S/LU) peads PUIMCM

OT-

T- 00

CO -̂

CM O

Figure 3. Example relationship of wave height to recovery efficiency (%of maximum) of boom-skimmer systems (left axis) and wind speed (right

axis), for a fully developed sea.

1.4 Oil spill response strategies

OSCAR allows the assignment of specific operational strategies to eachboom-skimmer or dispersant application system being simulated. Astandard strategy for blowout situations is to position mechanicalrecovery equipment as near the source as possible to reduce surfacespreading and increase the potential encounter rate between booms andoil. If all units follow this strategy, then oil that escapes this initialresponse action will continue to drift unhindered. Unless dispersednaturally or by a directed dispersant action, this oil can later threatennatural resource areas 'down-stream' of the source. The oil responsescenarios sometimes therefore employ a mixed strategy, wherein someskimmers work near the source, and others collect oil threateningidentified natural resource areas.


Table 2. Descriptive parameters describing mechanicalresponse activities in OSCAR.

Table 3. Example parameters governing dispersantapplication for three application systems in OSCAR.

o

O

Parameter

System NameStorage Location

Onboard VesselStorage CapacityRecovered OilCruising SpeedBoom Swath Widthin OperationOperational SpeedWave Thresholdfor OperationMaximumSkimming RateMobilisation Time

Max. Effectiveness(daylight)

Max. Effectiveness(night)

Units

XXXLat,Long.bblornT3

knotsm

knotsm

bbl/hr orm/3/hr

hr

%

%

ExampleValues:NOFO

ResponseTransrec

Kristiansund

1500 m̂ 3

12250

12

200 m*3/hr

24 hr systeml;48hrsystem 2

80%@5m/swind; 60%@ lOm/s50% ofdaylightvalue

Example Values:First Line Response

DiversePlatform

1000 m̂ 3

860

12

60 m/3/hr

1 timer system 1 ; 60for system 2

80% @ 5 m/s wind;60%@10m/s

50% of daylight value

Parameter

Application rate(1/min)Mobilisation time(hr)Dispersant tankage(m3)Operational windthreshold (kts)Operational speed(kts)Endurance (hr)Spray width (m)ExampleapplicationstrategyNo. of trips pr. dayMaximumEffectivenessCruise speed (w/bucket; kts)Turnaround timefor refilling (hr)

Small bucket(Rotortech-TC-

3)

150

1

0.9

30

58

825

Oil NearestResource Area

1180

80

0.5

Large bucket(Disp 3000)

200 / 900

1

2.5

30

58

825

FreshestEmulsified Oil

1080

60

0.5

Addspack

(Southampton)2100

24

21

30

140

850

ThickestOil

350

280

2

0.3O&3-O

00

O8-

OQ

22.C/2*

Oo

3



Example 1: Spill of 150 m of marine diesel fuel

offshore Namibia

Marine diesel fuel is a low-viscosity substance, does not form a stablewater-in-oil emulsion, spreads rapidly, and therefor tends to have a shortlifetime on the sea surface. A release of 150 m^ of diesel fuel will incuronly local effects, within 100 km of the exploratory site. A stochasticanalysis (Reed et al, 1998) demonstrated that surface effects would belimited to within 40 km of the source 80% of the time. Figures 4 and 5delineate the natural resource areas of primary concern in the area.

Figure 4. Spawning areas "downstream" of the spill site. Hake, pilchard,sole, and pelagic goby use spawning area #1. Anchovy, pilchard, andmackerel use spawning area #2.66.



300 km

)amara -Terns

Daniarn Terns, Seals

ICPOO'E

Figure 5. Major bird and marine mammal locations within the potentialimpact area.

Figure 6 gives both a bird's-eye view and a vertical section of thehydrocarbon concentration field 3.5 days after the spill of marine diesel.Despite very quiet weather, vertical and horizontal turbulence, combinedwith evaporation from the water column and from the surface, havebrought the concentrations down to 1-3 ppb, well into normal backgroundlevels. The vertical cross-section in Figure 6 is drawn from north-east tosouth-west. Despite winds under 5 m/s during this scenario, less than 5%of the oil remains on the sea surface at this time Figure 7 shows thevolume over the 2 ppb threshold as a function of time for this release.



13°45'E 14°00'E

1-33-1010-3030-100100-300300-WOO> 1000

Figure 6. Concentration field of dissolved hydrocarbons about 3.5 days after thediesel spill.

J

Figure 7. Volume of water exceeding a potential no-effect (PNEC) concentrationof 2 ppb. This total volume represents less than 0.03% of the total spawningvolume, assuming spawning to occur in the top 50 m of the water column.



Example 2: Surface blowout scenario offshore

Namibia

A blowout of 11,000 bbl/day (1450 tonnes/day) is simulated to allowcomparison of response actions (Tables 4 and 5) with and withoutdispersant application. The scenario brings over 20% of the oil ashore(Figures 8 and 9a) with maximum average linear loading at about 20kg/m occurring south of Walvis Bay. The planned mechanical recoveryoperation results in the recovery of over 23% of the spilled oil, andreduction of oil ashore to a maximum of about 16% (Figure 9b). Additionof the fixed wing areal dispersant capability changes the overall massbalance significantly (Figure 9c), with much more oil being naturallydispersed into the water column. This in turn reduces the mass of oil thatis recovered by the surface skimmers systems. The mass of oil comingashore is also reduced, to about 5%. Potential biological effects in thedesignated natural resource areas are reduced by the mechanical responseoperation (Figures 10 a and b), and virtually eliminated by the addition ofthe dispersant action (Figure lOc).

Table 4. Descriptive parameters for mechanical response activities.System

First Boom-SkimmerSystems (2)SecondBoom-SkimmerSystems (2)

Mobilisation

(hours)

48

96

Cruis-ing

Speed

(knots)

12

12

Operat-ionalSpeed

(knots)

1

1

BoomOpen-ing

(m)

100

100

NominalSkimm-

erCapac-

ity(m*/h)150

150

StorageCapa-city

(m')

1200

1200

MaximumOperational WaveHeight(m)

2.5

2.5

Table 5. Parameters governing dispersant application offshore Namibia.Parameter

Application rate (m'Vmin)Mobilisation time (hr)Dispersant tankage (m**)Operational wind threshold (knots)Cruise speed (knots)Operational speed (knots)Endurance (hr)Spray width (m)No. of trips pr. dayTotal available dispersant (m')Effectiveness (%)Turnaround time for refilling (hr)

System: Hercules Fixed-Wing Aircraft w/Dispersant Pack

2.14821302801408502100702



Figure 8, Distribution of surface oil 18 days after the beginning of thehypothetical release beginning 880201. In this scenario, with no responseaction, over 20% of the oil, (22000 barrels, or 2900 tonnes) eventuallycomes ashore.



9(a)

9(b)

0 2 4 6

0 2 4

9(c)

Figure 9. Mass balance time series for simulated blowout beginning880201. (a) without response; (b) with 4 boom-skimmer systems inoperation, and (c) with 4 boom-skimmer systems and the Hercules-Addspack dispersant aircraft in operation.



10(a)

10(b)

0.007

0.006

0.005

. 0.004

J Dama,a Terns LSeaBrdsi Seals I

TIME (DAYS)

, CZTDal̂J_0ama,aI Sea Bird-I—Seal.

10(c)

Figure 10. Potential for exposure to surface oil in designated naturalresource areas, (a) no response; (b) with 4 boom-skimmer systems inoperation, and (c) with 4 boom-skimmer systems and the fixed wingdispersant plane in operation. In the latter case potential effects of oil inthe designated seal area are virtually eliminated. (Fractional exposure isthe fraction of each resource area in Figure 5 that is covered with oil at aparticular time.)



Dissolved or WAF Concentrations

00 7? 23 9

Figure 11. Snapshot of the geographical surface and subsurfacedistribution of hydrocarbons during the simulated blowout starting880201. The maximum concentration of dissolved or WAF of the oil isabout 60 ppb, and occurs in the top 4 meters of the water column. Themaximum total hydrocarbon concentration (not shown) is nearly 400 ppb,and extends down to 8 meters.



It is also logical to ask what the effects are in the water column of thedispersed oil. A snapshot of the subsurface concentration followingcompletion of the dispersant application operation is shown in Figure 11.

The volume of water in which dissolved hydrocarbonconcentrations exceed 10, 50, and 100 ppb concentrations is displayed asa time series in Figure 12 for (a) no response, and (b) response with 4skimmers and a fixed wing dispersant aircraft coming into action after 48hours. The affected volume clearly increases with the use of dispersant.However, the wind-driven currents, under the influence of the earth'srotation, carry the subsurface oil offshore (Figure 11) and away from thelocal spawning area shown in Figure 4. It is also worth noting that themaximum volume affected by concentrations over 10 ppb is less than0.1% of the total volume identified as being used for spawning. Thepatchiness of spawning activity should also be considered in evaluatingpotential impacts.

Summary and Conclusions

The work reported here encompasses analyses of specific potential spillscenarios for oil exploration activity planned offshore of Namibia. Theanalyses are carried out with the SINTEF Oil Spill Contingency andResponse (OSCAR) 3-dimensional model system.

A spill scenario using 150 m^ of marine diesel demonstrates therapidity with which such a spill will dissipate naturally, even in lightwinds. Vertical and horizontal mixing bring subsurface hydrocarbonconcentrations to background levels within a few days. The analysisdemonstrates that the volume of water exceeding a potential no-effect(PNEC) concentration of 2 ppb represents less than 0.03% of the totalspawning volume, assuming spawning to occur in the top 50 m of thewater column.

A hypothetical 10-day blowout scenario releasing 11,000 bbl perday of light crude oil is investigated in terms of the potential fordelivering oil to selected bird and marine mammal areas along theNamibian coast. Worst case scenarios are selected to investigate thepotential mitigating effects of planned oil spill response actions.Mechanical recovery significantly reduces, and in some cases eliminates,potential environmental consequences of these worst case scenarios.Dispersant application from fixed wing aircraft further reduces thepotential surface effects.

Whether the trade-off of potential effects in the water columnagainst reduced effects for birds and marine mammals justifies use of adispersant application strategy is an issue that should be resolved by



experts. The OSCAR analysis is intended to supply an objective basis fora net environmental benefit analysis of planned response strategies.

% 0.08

0.04

_ A

12(a)

10 15 20Time (days)

[—VOLUME>I—VOLUME>I V O L U M E >

10.PPB(KM3) 150PPB(KM3)100.PPB(KM3)

o 0.1|"S 0.08

O 0.04>

0 .0 15

Time (days)25

: VOLUMEVOLUMEVOLUME

• 10PPB(KM3) I• 50.PPB(KM3)• 100.PPB(KM3)

12(b)

Figure 12. Volume of water exceeding 10, 50, and 100 ppbconcentrations of dissolved hydrocarbons, (a) with no response, and (b)during and following a dispersant application operation on the 10-dayblowout scenario starting on date 880201.



References

AAMO, O. M, REED, ML, BALING, P. S, JOHANSEN, 0. (1993): ALaboratory-based weathering model: PC version for coupling to transportmodels. Proceedings of the 1993 Arctic and Marine Oil Spill Program(AMOP) Technical Seminar, pp.617-626.

AAMO, O. M., REED, M., DALING, P. S. (1995): Evaluation ofenvironmental consequences and effectiveness of oil spill responseoperations with a possible change in first line response at the Veslefrikkfield. (In Norwegian). SINTEF Report No. 95.006, SINTEF PetroleumResearch 1995.

AAMO, O. M., M. REED, AND K. DOWNING (1996): Calibration,verification, and sensitivity analysis of the SINTEF oil spill contingencyand response (OSCAR) model system (in Norwegian). Report No.

42.4048.00/01/96. 87 p.

DALING, P. S., BRANDVIK, P. J., MACKAY, D., JOHANSEN, 0.(1990): Characterisation of crude oils for environmental purposes. Oil &Chemical Pollution 7, 1990, pp. 199-224.

DALING, P. S., O. M. AAMO, A. LEWIS, AND T. STROM-KRISTIANSEN, 1997: 67Ar7E/v7K(7 O/Y-)%afWmg MxM. f/Wz'cfmgOil Properties at Sea. Proceedings 1997 Oil Spill Conference. APIpublication No. 4651, Washington D. C., pp 297 - 307.

DOWNING, K. AND M. REED (1996): Object-oriented migrationmodelling for biological impact assessment. Ecological modelling 93

(1996): 203-219.

EKROL, N. 1998a. Computation of the effectiveness of oil spill responsestrategies for oil well blowouts at the Nome oil field. SINTEF rapportSTF66F98051 to Statoil.

EKROL, N. 1998b. Analysis of oil spill response strategies for the Trolloil field. SINTEF rapport STF66 F98053 for Norsk Hydro.

REED, M., C. TURNER, AND A. ODULO (1994): The role of wind andemulsification in modelling oil spill and surface drifter trajectories. SpillScience and Technology, Pergamon Press (2): .143-157.

REED, M., O. M. AAMO, AND P. S. DALING (1995a): Quantitativeanalysis of alternate oil spill response strategies using OSCAR. SpillScience and Technology, Pergamon Press 2(1): 67-74.



REED, M., FRENCH, D., RINES, H., and RYE, H. (1995b): A three-dimensional oil and chemical spill model for environmental impactassessment. Proceedings of the 1995 International Oil Spill Conference,pp.61-66.

Reed, M, O. M. Aamo, P. J. Brandvik, P. S. Dating, P. E. Nilsen, G.Fumes, 1997. Development of a dispersant use plan for a coastal oilterminal. Proc. 1997 International Oil Spill Conference, Ft. Lauderdale,Fl, pp. 643 - 654.

REED, M. , RYE, H, and EKROL, N., 1998. Norsk Hydro Namibia:Support for Environmental Impact Analysis. Report to Norsk Hydra AS,Bergen, Norway, pp. 41


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