uras
Marine Incidents Management Cluster (MIMAC):
technical and organizational measures related to
marine incidents in the North Sea
Member of (f ARCADIS
Í E J ECOLAS
Arijs K.1, Volckaert A.2, Versonnen B.1, Vanhoorne B.3, Vangheluwe M.1, Le Roy D.2, Maes F.4,
Calewaert J.B.4, Mees J.3, Fockedey N.3, Claus S.3, Janssen C.5
1EURAS - m em ber o f A R C A D IS , 2ECOLAS, 3Flanders Marine Institute (VLIZ), 4Maritim e Institute - G hent University, 5R esearch G roup Environm ental
Toxicology - G hent University
Introduction and aims
Several shipping accidents in Belgian territorial w aters made the various governm ent agencies involved aware o f the need to
develop integrated tools to assess the risks & environm ental im pact o f accidental spills o f hazardous com pounds. The MIMAC
project, funded by the Belgian Science Policy, aimed to integrate the results o f 2 projects related to marine incidents
m anagem ent: DIMAS (D evelopm ent o ta n Integrated Database for the M anagem ent o f Accidental Spills) & RAM A (Risk Analysis
o f Marine A ctivities in the Belgian part o f the North Sea).
DIMAS data collection: 250 compounds
Physico-chem ical properties
Risk assessment (RAMA)
Identification o f hazardous activities in the Belgian part o f the North Sea
Ecotoxicology
/ W a te r/s e d im e n t
/ S altw ater / freshw ater
/ # trophic levels (fish, algae, plants,
invertebrates, m icroorganism s, ...)
/ A cute / chronic effects
/ # endpoints (mortality, growth, reproduction,
■/Total 57.791 voyages
(or ± 320.000 ship mov.)
■/ 40% da ngerous goods (DG)
■/ 60% o f DG in packaged form;
40% in bulk
Human effects
/
R isk & safety phrases
/ 7 4 % w ith oil tankers, RoR o/
c a r carriers, containers
#
G ESA M P hazard profiles
Legend
SJMpromnenu (*Am»)
Quality
check
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951 - in o
Relational database & modelling
U I I «393
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Exposure modelling
)» «
23 »! - 'MII
Environm ental partitioning modelling in m arine specific environm ent,
based on M acKay level I model
R elease assessm ent
£ > Aerosols
■/ Marine A ccident Risk A ssessm ent S ystem (M ARCS)
■/ A ccident frequency (accidents / year)
Suspended sedim ent
W ater
■/ A ccident spill frequency (accidents with
environm ental spill / year)
■/ Spatial cargo spill risk (tonnes spilled / year) —
Fish
Description o f effects of incidents
Sediment
■/ S ensitivity analysis
■/ Effect analysis
Effect modelling
Expressed as potentially affected fraction (PAF), based on SSD (species
sensitivity distribution) approach
o W orst case sim ulation o f HNS spill near coast
o 75 sim ulation days
o M aximum concentration
o Ecological im pact area, based on 5% effect from PAF
/■
■
/
m /
fa
/ ■
.
.
/
/
/
■/
■/
m
■
Q B rugge
■7
leuw poort
1,0000 mg/I
C o n c e n tra tio n (LC50ÆC50 mg/1)
2 .0 8
- iLow risk
2 .3 3
to ta l m a 55 =
2 .5 8
2 .8 3
724.41 kg
3 .5 8
10 km
5% PAF)
Conclusion
Attention (5-25% PAF)
e
M ajor risk (> 25% PAF)
Both the results o f RAM A and DIMAS as well as the outcom e o f the M IMAC sym posium o f O ctober 2006 are
ready to be used in contingency planning. The risk analysis o f RAMA form s a basis for the evaluation o f the
degree o f preparedness (products, equipment, response) w hile the database developed within the DIMAS
project form s an operational tool that can be readily used during pollution com bating operations at sea.
T his project was supported by the Belgian Federal Science Office
http://w ww .vliz.be/projects/m im ac
katrien.arijs@ euras.be