IChemE SYMPOSIUM SERIES NO. 153 # 2007 IChemE

ANALYSIS OF RISKS TO THE AUSTRALIAN MARINE ENVIRONMENT FROM SPILLSOF BULK NOXIOUS LIQUID SUBSTANCES

Philip Skinner and Robert Hutchison

Lloyd’s Register; e-mail: philip.skinner@lr.org, robert.hutchison@lr.org

The Protocol on Preparedness, Response and Co-operation to Pollution Incidents by Hazardous

and Noxious Substances (HNS Protocol) was ratified on 14 June 2006, and will come into force

on 14 June 2007. The pre-positioning of spill response equipment, which is commensurate with

the risk, is a requirement of this Protocol.

In 2006, Lloyd’s Register (LR):

. Obtained/collated information on the type and quantity of pollution category A, B and C

noxious liquid substances (A/B/C-NLSs) transported in bulk tankers within Australian

waters/ports; and

. Undertook an analysis of the risks to the marine environment due to spills/releases of bulk

A/B/C-NLSs in Australian waters / ports.

The information required for the risk analysis was not available from any single source. Therefore,

information on the type and quantity of A/B/C-NLSs imported / exported through Australian ports

was firstly obtained from the relevant port authorities. This information was then matched to data in

AMSA’s AUSREP system to build-up a map of the bulk tankers that carried A/B/C-NLSs within

Australian waters / ports during January 2004 to December 2005.

Sixty-five different A/B/C-NLSs were transported in bulk tankers within Australian waters /

ports during January 2004 to December 2005. Of these, 6 were pollution category A-NLSs, 27

were pollution category B-NLSs and 32 were pollution category C-NLSs.

A risk index (RI) based model was developed for the risk analysis. This required additional data

acquisition and analysis so as to determine the likelihood of bulk NLS spills (based on historical

data) and to map areas of varying environmental sensitivity.

Maps showing the cumulative risk index scores for spills/releases of A-NLSs, B-NLSs, C-NLSs

and A/B/C-NLSs to the marine environment were created using a geographic information system

(GIS). The specific A/B/C-NLSs that contribute to the risk index score within each grid square can

be determined from the GIS model.

The RI model is consistent with the data and will be used by the Australian Maritime Safety

Authority to pre-position spill response equipment in Australia, as required by the HNS Protocol.

KEYWORDS: risk analysis, noxious liquid substances, chemical tanker, GIS, marine environment,

marine pollution

INTRODUCTIONThe latest version of the Australian National MarineChemical Spill Contingency Plan (Chemplan) was adoptedin 2001. Since then, it was identified that information onthe types, volumes and transport modes of materials (princi-pally chemicals) transported by ship in Australian watersand ports would be needed before an analysis of the risksto the environment could be completed.

The risk analysis was undertaken by Lloyd’s Regis-ter and ultimately will assist with pre-positioning spillresponse equipment and other resources in Australia,which is a requirement of the Protocol on Preparedness,Response and Co-operation to Pollution Incidents byHazardous and Noxious Substances (HNS Protocol,2000). This protocol was ratified by Australia in March2005 and will enter into force internationally in July2007.

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Lloyd’s Register collected the required shippinginformation and undertook an analysis of the risks to theenvironment due to spills/releases of bulk chemicals inAustralian waters/ports. Packaged goods were excludedfrom this initial work because the magnitude of the data col-lection and analysis task would have been much greater forpackaged goods compared to bulk materials. It is possiblethat packaged goods and category D NLSs will be includedin a later study.

The geographical study area included all waters withinthe Australian Exclusive Economic Zone (AEEZ) andincluded the waters surrounding all islands within this zone.

The principal objective of the project was to deter-mine the relative risks associated with spills/releases ofpollution category A, B and C bulk noxious liquid sub-stances (A/B/C-NLSs) from ships in Australian watersand ports.

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APPROACHThe approach taken for the risk analysis involved twomajor steps:

The most time consuming step involved acquiring andanalysing information on chemical tanker movementsthrough the AEEZ. This included determining the typesand quantities of bulk NLSs carried on these vessels.

Following collection of the data, a risk model wasdeveloped to calculate and present the risk results using ageographical information system (GIS). This requiredadditional data acquisition and analysis to determine thelikelihood of bulk NLS spills (based on historical data)and to map areas of environmental sensitivity.

DETERMINATION OF CHEMICAL

TANKER MOVEMENTSThe Australian Ship Reporting (AUSREP) system is oper-ated by AMSA through the Rescue Coordination Centre(RCC) in Canberra. Although designed for identifying andlocating missing commercial vessels, it is also relevant tothe risk assessment since it provides an indication of thelocations of chemical tankers that may be carrying A/B/C-NLSs.

FLEET CHARACTERISTICS – ALL CHEMICAL

TANKERSAn analysis of the chemical tanker fleet characteristics wasundertaken using the AUSREP (2004) data and the tankerswere categorised by size (DWT) into five categories: C1,1500 tonnes; C2 – 1500–5000 tonnes; C3 – 5000–15000tonnes; C4 – 15000–40000 tonnes; C5 .40000 tonnes.

The total number of tankers and tanker voyages foreach of the five chemical tanker (DWT) categories weredetermined using the AUSREP (2004) data. Chemicaltankers in the C3 category (5–15 kdwt) were by far themost common, representing approximately 50% and 65%of the tanker numbers and voyages, respectively.

BULK CARGOES OF NOXIOUS

LIQUID SUBSTANCESTo undertake the risk analysis, it was essential to obtaininformation on the type and quantity of each A/B/C-NLSon each vessel. Initial consultation highlighted that were anumber of potential challenges to obtaining the required,very specific, cargo information, including:

. Commercial sensitivities (i.e. concern that competitorsmight benefit from being able to track individual chemi-cal cargoes) - To manage this issue, specific chemicaldata was only presented in the report if it was alreadyavailable in the public domain. If not available in thepublic domain, the information provided by the portauthority was only presented when grouped by pollutioncategory.

. The relevant stakeholders may not provide the requestedchemical shipping data, or may not provide this

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information in a timely manner, as there was no clearregulatory requirement, or a perceived incentive, to doso. To manage this issue the port authorities were usedas the primary point of contact for import/export datawhich was then cross-checked against information pro-vided by AMSA (e.g. SHIPSYS database) and anydata that was available in the public domain.

DATA ACQUISITIONA two-page data request letter was initially sent, via theAustralian Association of Ports and Marine Authorities(AAPMA), to 12 port authorities. These 12 were selectedas they had the largest number of tanker visits for theperiod July 2004 to June 2005. The letter was generally fol-lowed up by phone calls and/or emails and was progress-ively distributed to other port authorities. Eight portauthorities, which represented 17 individual ports, wereidentified as only handling materials that are excludedfrom the scope of the risk analysis (e.g. petroleum products,vegetable oils, caustic soda, etc.) and these bodies were notcontacted.

Most data was available electronically. However,some customised database searches needed to be developed.It was also necessary to make repeated contact with someport authorities, either to provide a reminder to providethe data or to clarify some aspects of the data already pro-vided. The Australian Association of Ports and MarineAuthorities also sent reminders to the port authorities andwas particularly helpful in facilitating this process. Thedata required for the risk analysis was eventually providedby 16 port authorities, representing a total of 27 individualports.

DATA ANALYSIS AND VALIDATIONMost of the information received from the port auth-orities was straightforward to analyse and validate as itcovered only a relatively small number of NLSs andtanker movements. However, some of the data requireda considerable time to review, particularly to identifythe A/B/C NLSs. For example, data for approximately1,600 cargoes (including in-transit cargo) was providedfor the port of Melbourne and data on a similarnumber of cargoes (including in-transit cargo) was pro-vided for Port Botany.

It was necessary to cross-check the information on thelisted vessels (e.g. call sign, IMO number, DWT, etc.)against available classification details (e.g. using LR’sClassDirect Live database). Many of the listed cargoes atMelbourne and Port Botany included trade-named materialsthat were not easily identified as A/B/C-NLSs. A MarineEnvironment Protection Committee (MEPC) circular wasused to assist with identification of the category A/B/C-NLSs, but not all of the trade-named substances are listedin this circular and a few materials could still not be ident-ified. In some cases, this was due to the use of non-specificacronyms.

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Once the A/B/C-NLSs had been identified, an initialvalidation check was undertaken to ensure the data providedby the port authorities/corporations (or equivalent) wasconsistent with:

. AMSA’s SHIPSYS database (January to December2004 and January to December 2005) – This databaseincludes a record of vessel inspections made byAMSA’s inspectors at each port.

. Other data provided on the port authorities’/corpor-ation’s web sites (including the AAPMA’s) and intheir annual reports.

DISTRIBUTION WITHIN THE AEEZTo determine the distribution of A/B/C-NLS tanker move-ments through the AEEZ, it was necessary to consolidate thedata on chemical tanker movements with the bulk cargoimport/export/transit data. This was a difficult and timeconsuming process and involved:

1. Consolidating the chemical tanker movement data fromAUSREP with the bulk cargo import/export/transitdata provided by the port authorities. A program waswritten to consolidate the quarter of a million rows ofdata. The program was used to delete irrelevantrecords (i.e. where there was no match between thetwo data sets) and to automatically calculate the in-transit quantities for each tanker voyage from theimport/export data for each port.

2. Mapping each A/B/C-NLS tanker voyage (using aGIS). This required an extensive review and amend-ment of the tanker voyage identification number fromthe AUSREP data. In some cases, the same voyageidentification number was found to have been incor-rectly entered into the AUSREP database despite thevessel having arrived/departed multiple ports (andhaving submitted multiple sail plans and final reports).

Figure 1 shows the results of the initial mapping ofthe consolidated chemical tanker movement data fromAUSREP with the bulk cargo import/export/transit

Figure 1. Initial map of A/B/C-NLS tanker voyages showing

“cross-country” routes

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data provided by the port authorities / corporations (orequivalent). As the reporting interval for data in AUSREPis typically 12–24 hours (but can vary from minutes toweeks), joining each of the reported vessel positions foreach voyage identification number produced a largenumber of invalid tanker movements (i.e. tanker voyagesthat appear to cross overland). In some cases, only a smallsection of land is crossed (e.g. at the point of entry to aport), but in others it is very significant, particularly alongthe east coast of NSW and Victoria, the south coast ofVictoria, Tasmania and the south-west of WA. When a ship-ping route appeared to cross overland, the route wasadjusted using the GIS to conform to the coastline. Althoughthis would not map the exact route, it was a conservativeapproach as it brought those ship routes closer to the sensi-tive environmental locations.

RISK ANALYSISA ‘Risk Index’ (RI) approach was used to analyse the poten-tial risk to the marine environment from bulk spills orreleases of A/B/C-NLSs in the AEEZ. RI approaches areideally suited to the analysis of large amounts of data andprovide an appropriate and ‘fit-for-purpose’ methodologyfor making risk-based decisions on the pre-positioning ofspill response equipment. A RI approach was used in 2000to determine relative risk scores for pollution from oilspills in Australian waters. The previous approach wasadapted to estimate a risk score for pollution from bulkNLS spills/releases. The most significant difference wasthat the RI was estimated for approximately 6,000 (30minute � 30 minute) individual grid squares, rather thanthe 97 regions considered previously.

The RI, which was calculated for each pre-defined30-minute (c. 50 km � 50 km) grid square, is defined asfollows:

Risk Index ¼ Consequence Score � Likelihood

Score

Where:

Consequence Score ¼ A function of the effect

area (which is dependent on the toxicity/dis-

persion characteristics of the NLS and the

amount spilled/released), material factor (e.g.

persistence) and the environmental sensitivity

of the receptor/s (e.g. coral reef, mangroves,

etc.) within the effect area.

Likelihood Score ¼ The likelihood of a spill/release of a NLS impacting upon a particular

receptor (e.g. environmentally sensitive area).

CONSEQUENCE ANALYSIS

EFFECT DISTANCEThe effect distance (i.e. the distance at which at an observa-ble adverse effect occurs to the biophysical environment) isdependent on the amount of NLS spilled / released, its tox-icity and/or its dispersion behaviour.

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Up to five effect distances were estimated for each A/B/C-NLS on each vessel based on representative spill sizesselected to comply with the categories defined for the like-lihood analysis (see below). The toxicity was categorisedbased on the NLS pollution category.

Dispersion behaviour is the most complex consider-ation in estimating the effect distance. Depending on itsproperties (solubility, density and vapour pressure), a NLSreleased into the marine environment may float on thewater surface, it may be diluted and dispersed throughoutthe water column, it may evaporate (and disperse throughthe air) and/or it may sink to the sea floor. Environmentalconditions (e.g. wind speed, water current speed, etc.) alsoaffect the extent of dispersion.

There is very little information (either experimentalor from previous accidents) available to validate the effectdistance estimates. For this risk analysis, the objective wasto estimate a reasonably conservative effect distance (km),and for this to be within one order of magnitude of the dis-tance at which at an observable adverse effect would occurto the marine environment.

FLOATERSThe model used to estimate the effect distance for all ‘floa-ters’ assumes the effect distance is dependent on the massreleased and a nominal maximum film thickness, ratherthan on the pollution category of the NLS. However, foran equal spill size (i.e. an equivalent effect distance), theaffect on the environment would be expected to be moresevere for a pollution category A NLS than a pollution cat-egory B or C NLS – This is addressed in the RI calculationby the material factor.

Figure 2. Maximum sensitivity rating (colour

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DISSOLVERSUnlike the floaters, the effect distance for the A/B/C-NLSdissolvers (miscible liquids) is a function of the pollutioncategory since an environmental impact will occur untilthe spill is diluted to a sufficiently low concentration. Inthis case, the median tolerance limit concentrations foreach pollution category were used as a representative endpoint.

SINKERSThe effect distance for the A/B/C-NLS sinkers is the mostdifficult to estimate since even more parameters that mayaffect the dispersion (e.g. the density, surface tension andsolubility of the NLS; water currents at the surface and atthe bottom of the water column; water depth; sediment per-meability). There are fewer A/B/CNLS sinkers than A/B/C-NLS floaters or dissolvers. The effect distance for A/B/C-NLS sinkers was assumed to be half the estimatedeffect distance for a pollution category C NLS.

ENVIRONMENTAL SENSITIVITY ANALYSISThe risk index model takes account of the environmentalsensitivity of the fauna and flora potentially affected by aspill/release of A/B/C-NLSs by using a relative sensi-tivity rating, which ranges from 1 (lowest sensitivity forcliffs and open water) to 25 (highest sensitivity for WorldHeritage Areas). The location of these areas was determinedusing AMSA’s Oil Spill Response Atlas (OSRA). Similarrating schemes are used by the National Oceanic andAtmospheric Administration (NOAA) in the US and havebeen used in earlier risk analyses undertaken for AMSA.The sensitivity ratings are shown in Figure 2.

coded by category) per 30-minute grid square

Table 1. Likelihood of spill (per tanker.km) in open water

Spill Size (tonnes)

Likelihood of Spill (per tanker.km) by Tanker Size (DWT) Category (C1–C5)

C1 C2 C3 C4 C5

0–1,500 1,500–5,000 5,000–15,000 15,000–40,000 . 40,000

, ¼ 100 7.0 � 1028 3.6 � 1028 3.0 � 1028 2.4 � 1028 7.8 � 1029

.100 and , ¼ 1,000 7.6 � 1029 4.0 � 1029 2.6 � 1029 3.6 � 1029 1.2 � 1029

.1,000 and , ¼ 10,000 0 5.2 � 10210 3.2 � 1029 2.8 � 1029 8.6 � 10210

.10,000 and , ¼ 50,000 0 0 2.6 � 10211 1.8 � 10210 8.9 � 10210

.50,000 0 0 0 0 2.7 � 10211

Total 7.8 � 1028 4.1 � 1028 3.6 � 1028 3.0 � 1028 1.1 � 1028

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FREQUENCY AND LIKELIHOOD ANALYSISHistorical accident data was used to estimate, within anorder of magnitude, the relative likelihood of spills ofvarious sizes from tankers of various capacities (seeTable 1)

RISK RESULTSThe results of the analysis (See Figures 3 and 4) show that apollution category A-NLS spill/release could be expected tooccur in Australian waters/ports approximately once in 15to 17 years. In a particular 30-minute grid, the maximumlikelihood for a spill of A-NLS material is 1.2 � 1023 p.a.The majority of the potential spills/releases were deter-mined to occur along the southern and eastern coast ofAustralia from Port Pirie through to Gladstone. It is alsosignificant that A-NLSs were not transported along theQueensland coast to the north of Gladstone (i.e. within theGreat Barrier Reef World Heritage area). Vessels carrying

Figure 3. Cumulative risk index

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these NLSs appear to have deliberately travelled aroundthe southern extent of the Great Barrier Reef World HeritageArea before heading north into Asia.

The highest cumulative risk index category for pol-lution category A-NLS spills / releases occurred in 8 gridsquares:

. Near Newcastle (2 grid squares), Sydney (1 grid square)and Port Kembla (1 grid square) in NSW;

. Near Portland (1 grid square) and Wilsons Promontory(2 grid squares) in Victoria; and

. Near Kangaroo Island (1 grid square) in South Australia.

The risk of category B-NLS and category C-NLSspills have similar maximum risk values (6.9 � 1022) dueto the lower hazard being offset by the higher frequencyand quantities transported. However, the location of thelower risks is in different locations for the category B andC NLSs.

for pollution category a NLSs

Figure 4. Cumulative risk index for all pollution catagories

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CONCLUSIONSThe data collected by the Australian port authorities can becombined with AUSREP data and ship data to estimate thelocation of ships carrying particular cargoes.

The risk of such chemical cargoes on sensitive marineenvironments can be estimated using existing coastal andmarine resource sensitivity data.

The knowledge of the risk at various locations poten-tially will assist in contingency planning and enable moreappropriate locating of any emergency spill responseresources.

REFERENCES1. AAPMA, Trade Statistics 04/05 (www.aapma.org.au/

tradestats/).

2. AMSA, 6 October 1998, First Edition of Ship Reporting

Instructions, AUSREP and REEFREP ship reporting

systems.

3. AMSA, February 2000, Risk Assessment of Pollution from

Oil and Chemical Spills in Australian Ports and Waters,

Revision 1.

4. AMSA, AUSREP database (Jan 2004 to Dec 2005).

5. AMSA, Oil Spill Response Atlas (selected themes) and

Policy Management Guidelines.

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6. AMSA, SHIPSYS (2004 and 2005).

7. Helsinki Commission, Baltic Marine Environment Pro-

tection Commission, 2002, HELCOM Manual on Co-

operation in Response to Marine Pollution within the

framework of the Convention on the Protection of

the Marine Environment of the Baltic Sea Area, (Helsinki

Convention), Volume 2.

8. Environment Australia, 1998, Environmental Indicators

For National State of the Environment Reporting, Estuaries

and the Sea, State of the Environment Environmental Indi-

cator Report.

9. IMO, International Code for the Construction and Equip-

ment of Ships Carrying Dangerous Chemicals in Bulk

(IBC Code).

10. IMO, International Convention for the Prevention of Pol-

lution from Ships 1973/78.

11. IMO, 17 December 2005, Provisional Categorisation of

Liquid Substances, MEPC.2/Circ.11.

12. Lloyd’s Register, ClassDirect Live (www.cdlive.lr.org/).

13. Marine and Coastguard Agency (MCA), May 2001,

Chemical Spill Risk Assessment Report, Research

Project 447, Doc. No. ST-8604-RA-1-Rev 01.

14. NOAA, NOAA Ocean Service, March 2002, Environ-

mental Sensitivity Index Guidelines, NOAA Technical

Memorandum NOS OR&R 11, Version 3.0.