Status of risk analysis
in the Dutch part of
the North Sea
Henk Offringa
Rijkswaterstaat
National Institute for Coastal and Marine Management
Note ‘To protect vulnerable marine and
estuarine areas’
‘Capacity note 2006 –
2010’ (issued 2006)
Indicates the extent of resources
needed to combat pollution due to
calamities at sea
 Based on risk analysis
Risk analyses
Pollution sources
Risk = chance * effect
Prevention
Required resources for incidents
Sources of pollution
•• Incidental
from:installations,
shipping, under
Shipping discharges
>>>>> offshore
offshore
installations,
under
water pipelines,
water pipelines,
harbour
activities,
aeroplane
harbour
activities,
aeroplaneonaccidents
accidents
and installations
shore; and
installations on shore;
• Crude oil >>>>> Heavy Fuel Oil (HFO) and
chemical substances
Top 10 of crude oils unloaded in
Rotterdam
Name
Origin
Volume (Mton) 2000
Arabian Light
Saudi Arabia
9,22
4,41
Russian Export Blend
Russia
6,59
11,45
Oseberg
Norway
5,87
3,1
Kuwait Export
Kuwait
5,33
1,32
Kirkük
Iraq
4,23
Gullfaks
Norway
3,80
1,58
Forties
Great Britain
3,70
1,4
Arabian Extra Light
Saudi Arabia
2,84
0,9
Arabian Medium
Saudi Arabia
2,67
Alba
Great Britain
2,25
Σ ~ 100 Mton
2004
Risk = chance  effect
Traffic density, routes and
transport of substances
Risk on incidents
~ frequency
and nature
Risk on spills ~
frequency and
nature
Human health
Logistic and practical
aspects
Economical valuable
objects and areas
Ecological
vulnerability
finances
Transport routes, approach
Cargo data
Lloyds database
Port A
Arrival date
IMO-number
Type of oil
Amount of oil
Type of activity
Arrival port A
Arrival date
Previous/next port (B)
IMO-number
Ship type/size
Example: result Rotterdam (crude)
• Almost all import
• Main origin:
– 40% Dover strait
– 30% Northern part of the North Sea
– 24% Baltic
Amount of
crude oil to
Rotterdam
<500 kton
500 – 1000 kton
1000 – 2500 kton
2500 – 5000 kton
5000 – 7500 kton
7500 – 10000 kton
> 10000 kton
Amount of
HFO
to Rotterdam
<50 kton
50 – 100 kton
100 – 250 kton
250 – 500 kton
500 – 750 kton
750 – 1000 kton
> 1000 kton
Estimated passing
ships with
dangerous goods
Conclusion transport
• Quality is reasonable acceptable, but little is known
on the exact routes
• Passing ships is not discernible with this method
• Preliminary: shift in transport routes through Baltic
Further work: chance on collision
and spills
• Created traffic databases are used within the
SAMSON-model (Safety Assessment Model for
Shipping and Offshore on the North Sea). Samson
is run by MARIN
• Determine the frequency of an oil spill and the
expected size of the oil spill.
• Report 2004, data 2000, update not available yet
Potential number of collisions between ships
(regardless their cargo, year 2000)
Aanvaringen tussen schepen (niet-routegebonden en/of routegebonden verkeer) ongeacht de lading.
56.0
minder dan eens in de 1000 jaar
100 en 1000 jaar
55.5
50 en 100 jaar
10 en 50 jaar
5 en 10 jaar
55.0
vaker dan eens in de 5 jaar
kustlijn
VSS
54.5
NEEZ
54.0
53.5
53.0
52.5
52.0
51.5
51.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
Reported collisions 2000-2003
Potential frequency of an oil spill as a
result of any accident at sea (year 2000)
Eens in de ... jaar een uitstroom van ladingolie (olieklasse 1 t/m 7) als gevolg van een ongeval op zee
(alle type ongevallen)
56.0
meer dan 5000 jaar
tussen 1000 en 5000 jaar
tussen 500 en 1000 jaar
tussen 250 en 500 jaar
tussen 100 en 250 jaar
minder dan 100 jaar
kustlijn
NEEZ
VSS
55.5
55.0
54.5
54.0
53.5
53.0
52.5
52.0
51.5
51.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
Maximum amount of spilled oil that is expected to
occur at least once every 10,000 year
(based on traffic data year 2000)
Finally:
ecological
vulnerability
maps
Doggersbank
49
Centrale Oestergronden
(-40-50 NAP)
50
Klaverbank
55
Friese front
60
81
81
Rest NCP
82
Waddenzee
33
Kustzone
81
65
Kust
56
Belangrijke
ecologische
gebieden 81
81
Voordelta
65
81
83 Oosterschelde
67 Westerschelde
Ecological advice in operational contingency
planning
dimension
time
advice
1 minute
Immediate
½ hour
Look up
1 hour
Discuss with
colleagues
3 hours
Call external
experts
3 days
3 weeks/months
Monitoring /
evaluation
Method
Acidification/basification
Vulnerability class
Reduced transperancy
Substance Vulnerability Index (SVI)
Oxygen depletion
Bio Accumulation
Toxicity
Species Recoverability Index
(SpecRI)
Heating
10
91 1
105 5
35 5
35 1
35 5
31 5
95 1
3 510
31 5
3 10
3105
3 5
3 5
3 5
9 10
10 10 10 10 10 10
Status
10
Trend of population
FE
39
FE
59
FE
44
FE
60
FE
76
FE
24
FE
30
FE
16
FE
24
FE
16
63
FE
44
63
20
61
Recruitment
Smouthering/Constipation
of cavities
Mobility
mT/year max
class
11,451 heavy crude oil
3 4,419
5 light
4 5crude
4 oil
5 10
3 3,108
5 medium
6 2 10
5 oil
10
crude
7 1,986
5 10
0 1crude
0 oil
0
medium
7 1,669
5 10
0 6crude
0 oil
0
medium
10 1,58
5 10
0 8crude
0 oil
0
medium
2 1,466
5 light
6 0crude
1 oil
0 0
4 1,324
5 medium
6 0 1crude
0 oil
0
2 943
5 medium
2 0 0crude
0 oil
0
2 935
5 light
6 0crude
1 oil
0 0
2
5 2 0 0 0 0
10 5 10 0 4 fill0 in:0
7
5 10 0 1 0 0
10 5 10 0 4 0 0
2
5 6 0 0 0 0
3
5 6 5 10 5 10
Sensitivity
Index (SI)
behaviour
Acidification/basification
Oxygen depletion
Reduced transperancy
Heating
Bio Accumulation
Toxiciticy
examples:
R.E.B.C.O
Allis shad Arabian light
MP
1
Anglerfish Oseberg MB
1
Arctic skua Arabian heavy
BF
6
Arctic tern Foroozan BN
7
auks
9
Gullfaks BS
Avocet
2
Forties BC
Bank vole Kuwait export
RS
5
Barnacle goose
BC light
2
Arabian extra
Bar-tailed godwit
2
Asgård BC
Bewick's swan
BC
2
Black throated diver BN
7
Black-headed gull BN
7
Blacknecked grebe BN
7
Black-tailed godwit BC
2
Blue whiting
MP
1
Smouthering/Constipation of
cavities
substance
Exposure factor (EF)
Habitat of the species
effect
English species name
Species
Recovery
Points
Stress Factors
Substance
(SpecRP)
per recovery
Species Sensitivity
Points (SpecSP) per
stress mechanism and
per species)
0
2 10 1
5 3
28
0 low
1 10
16 01
0,011
0 low
1 50,011
22 42 50
0
1 50,051 moderate
22 82 52
0
1 50,081 moderate
2 52
26 10
65
0high
1 50,101
2
26 10
0,011
0 low
1 10
14 41 42
0 low
1 50,031
24 62 45
0 low
1 50,001 very
2 82
26 10
0,011 very
0 low
1 10
16 81 58
4 8 72 0,00 very low
0,091 moderate
0
2 10
56 63 52
4 8 55 0,06 moderate
8 4 48 0,09 moderate
2 2 32 0,01
low
6 8 85 0,01 very low
Substance Vulnerability Index
Acidification/basification
Vulnerability class
Reduced transperancy
Substance Vulnerability Index (SVI)
Oxygen depletion
Bio Accumulation
Toxicity
Species Recoverability Index
(SpecRI)
Heating
10
91 1
105 5
35 5
35 1
35 5
31 5
95 1
3 510
31 5
3 10
3105
3 5
3 5
3 5
9 10
10 10 10 10 10 10
Status
10
Trend of population
FE
39
FE
59
FE
44
FE
60
FE
76
FE
24
FE
30
FE
16
FE
24
FE
16
63
FE
44
63
20
61
Recruitment
Smouthering/Constipation
of cavities
Mobility
mT/year max
class
11,451 heavy crude oil
3 4,419
5 light
4 5crude
4 oil
5 10
3 3,108
5 medium
6 2 10
5 oil
10
crude
7 1,986
5 10
0 1crude
0 oil
0
medium
7 1,669
5 10
0 6crude
0 oil
0
medium
10 1,58
5 10
0 8crude
0 oil
0
medium
2 1,466
5 light
6 0crude
1 oil
0 0
4 1,324
5 medium
6 0 1crude
0 oil
0
2 943
5 medium
2 0 0crude
0 oil
0
2 935
5 light
6 0crude
1 oil
0 0
2
5 2 0 0 0 0
10 5 10 0 4 fill0 in:0
7
5 10 0 1 0 0
10 5 10 0 4 0 0
2
5 6 0 0 0 0
3
5 6 5 10 5 10
Sensitivity
Index (SI)
behaviour
Acidification/basification
Oxygen depletion
Reduced transperancy
Heating
Bio Accumulation
Toxiciticy
examples:
R.E.B.C.O
Allis shad Arabian light
MP
1
Anglerfish Oseberg MB
1
Arctic skua Arabian heavy
BF
6
Arctic tern Foroozan BN
7
auks
9
Gullfaks BS
Avocet
2
Forties BC
Bank vole Kuwait export
RS
5
Barnacle goose
BC light
2
Arabian extra
Bar-tailed godwit
2
Asgård BC
Bewick's swan
BC
2
Black throated diver BN
7
Black-headed gull BN
7
Blacknecked grebe BN
7
Black-tailed godwit BC
2
Blue whiting
MP
1
Smouthering/Constipation of
cavities
substance
Exposure factor (EF)
Habitat of the species
effect
English species name
Species
Recovery
Points
Stress Factors
Substance
(SpecRP)
per recovery
Species Sensitivity
Points (SpecSP) per
stress mechanism and
per species)
0
2 10 1
5 3
28
0 low
1 10
16 01
0,011
0 low
1 50,011
22 42 50
0
1 50,051 moderate
22 82 52
0
1 50,081 moderate
2 52
26 10
65
0high
1 50,101
2
26 10
0,011
0 low
1 10
14 41 42
0 low
1 50,031
24 62 45
0 low
1 50,001 very
2 82
26 10
0,011 very
0 low
1 10
16 81 58
4 8 72 0,00 very low
0,091 moderate
0
2 10
56 63 52
4 8 55 0,06 moderate
8 4 48 0,09 moderate
2 2 32 0,01
low
6 8 85 0,01 very low
Scenario: medium crude oil (example)
Based on 34 species
Dilemma’s
• Do we need more
sophisticated and
detailed maps?
• How do we value
species in and outside
SPA’s and SACs
• Do we need
harmonisation of
existing maps?
Thank you