275
1 INTRODUCTION
Theaimofthispaperistoinvestigatetheimpactof
bunker prices in the compliance decisions related to
theMARPOLAnnexVIRegulations,andspecifically
of Regulation 14, which deals with the sulfur
emissions (SOx). The set limits apply to all vessels
that fly the flag of
a country, which has ratified the
convention.Additionally,itappliestovesselsthatfly
the flag of a nonsignatory state while operating
within waters under the jurisdiction of a country
adhering to MARPOL’s Annex VI Reg. 14. On
October 10
th
2008 more stringent amendments were
adoptedtoAnnexVI,whichenteredintoforceonJuly
1
st
2010. Regulation 14 specifies the sulfur limit in
marine fuel for global maritime trade. The highest
sulfur content allowed in ship fuel will reduce
globallyasof1January2012from4.5%to3.5%andas
of 1 January 2020 to 0.5%, depending on the
availabilityoflowsulfurfuel,
asthiswillbediscussed
andreviewedbytheIMOin2018.Evenstrictervalues
applyfortheEmissionControlAreas(ECA).TheECA
includes Baltic Sea, North Sea and the English
Channel,aswellastheoceaniccoastlineoftheUnited
StatesandCanada.WithintheECA’sthesulfurlimit
was1.5%untilJuly2010.AsofJuly2010theallowed
sulfurcontentwasreducedto1.0%.In2015thelimit
willfurtherbedecreasedto0.1%.
TheissueofcompliancewithRegulation14iswell
known in the related business and academic
literature.ThestudyofEMSA(2010)and
thereportof
Miola et al. (2010), as well as the studies on green
housegases(GHG)andairpollutionofBuhaugetal.
(2009)amongothers,havepavedthewayforfurther
research,regulatoryactionandvividdebates.Tothis
discussion, the authors have also contributed with
advanced methodologies estimating
the cost of
operatinginmixedECAandnonECAareas(Schinas,
et. al. 2012a) as well as with policy support
documents,suchasinSchinasetal.(2012b).Inallthe
relatedstudies,thefocusiseithermicroeconomic,i.e.
a focus on the impact from the operation and
the
related expenses of burning fuels of diverse quality,
namely either HighSulfur (HS) or LowSulfur (LS)
heavy fuel oil (HFO) or intermediated fuel oil (IFO)
The Cost of SOx Limits to Marine Operators; Results
from Exploring Marine Fuel Prices
O.Schinas
HamburgSchoolofBusinessAdministration,Hamburg,Germany
Ch.Stefanakos
TechnologicalandEducationalInstituteofAthens,Athens,Greece
ABSTRACT:Marineoperatorsareconfrontedwiththenewairemissionsregulationsthatdeterminethelimits
ofsulfurcontentinmarinefuels.Thelowsulfur(LS)marinefuelshaveahigherprice,andtheirfluctuationis
almostsimilartothefluctuationofhigh
sulfur(HS)fuels.ThepricedifferencebetweenHSandLSmightalso
determinethedecisionofoperatorsforalternativetechnicalmeans,suchasscrubbers,inordertocomplywith
thenewlimits.ThispaperaimstoprovideathoroughstatisticalanalysisofthecurrentlyavailableLSandHS
marinefuelstime
series,aswellastopresenttheanalysisofthedifferentialoftheHSandLSfuelprices.The
paperconcludeswithsuggestionsforfurtherresearch.
http://www.transnav.eu
the International Journal
on Marine Navigation
and Safety of Sea Transportation
Volume 7
Number 2
June 2013
DOI:10.12716/1001.07.02.15
276
marine diesel oil (MDO), or macroeconomic, i.e.
approaches dealing with the global fleet and total
effectofmarinefuelconsumptiontotheenvironment.
However, there is no study, to the best of the
knowledgeoftheauthors,examiningthetimeseries
ofthepricesoftherelatedfuels.Alizadeh
et.al.(2004)
examinedthecorrelationofRotterdam,Houstonand
Singapore bunker prices timeseries visàvis the
prices of future contracts traded at the New York
MercantileExchange(NYMEX)andtheInternational
PetroleumExchange(IPE)inLondon;furtherworkon
this subject is not reported. Should the statistical
characteristicsofthetimeseriesbeknownthenbetter
forecasting and explanatory models can be derived.
This paper aims to offer some basic analysis of the
time series of HSHFO and LSHFO in Rotterdam,
discusstheresultsoftheanalysisandfinallydiscuss
some possible steps for further research.
It is out of
the scope of this paper to analyze the political and
economic factors that determine the prices, but
scientificallyanalyzetherelatedtimeseries.
The following section presents the value of
accurateoratleastreliableandtrustworthystatistical
attributesoffueloilpricetimeseriesfor
thesupport
oftechnical,operationalandfinancialdecisionsatthe
microlevel. In the next session, the analyses of the
HS‐andLSHFOpricesinRotterdamaswellasofthe
derivedtimeseriesofthedifferencebetweenHS‐and
LSHFO are presented. In the last section the
conclusions
are summarized and suggestions for
furtherresearcharepresented.
2 THEIMPACTOFFUELPRICES
Although different ship types and propulsion plant
configurations suggest different cost structures, it is
commonknowledgethatfuelcostsdeterminealarge
percentage of the overall cost, and therefore the
financial performance of this asset.
The compliance
withreducedsulfurlimitscanbeachievedviavarious
instruments, however two major and most feasible
instruments are practically available to operators: a
dualfuelsystemandanexhaustgascleaningsystem
(EGCS),i.e.ascrubberorsimilartechnology.Thedual
fuelsystemimpliesa switchfromregularfuel
toLS
fueloilinECAs.Withtheinstallationofscrubbersitis
notnecessarytooperatewithmorethanonefuel:HS
fueloilscanbeused,theexhaustsarethencleanedby
thescrubbersinordertoreducetheemissionofsulfur
into the air. Other sulfur abatement
instruments are
also in discussion, but do not seem to be
implementable within the next couple of years, as
there are many unsolved questions regarding their
usage.
Oneofthosealternativesisthevesselpropulsion
via liquefied natural gas (LNG). Implementing this
technology makes costly retrofitting of the vessel
necessary.A
furtheraspect,whichhastobetakeninto
account,istheavailabilityofLNGbunkeringfacilities
inports.Recentpolicyinitiatives,includeaproposed
European Directive, where the Commission
introduces an obligation for all the major European
seaports to be equipped by 2020 with publicly
accessible LNG refueling points for
both maritime
andinlandwaterwaytransport(EC,2013).Addingto
thepolicycontroversyoverairemissionissues,ESPO
doubts, whether imposing LNG refueling
infrastructure in all the major European would be
appropriate,sincetheremaynotbeamarketforitin
allofthoseports,whereastherecouldbea
marketin
other,noncoreports,aswellasalternativesolutions
to the development of LNG are and will become
increasinglyavailableinthenearfuture(ESPO,2013).
Generallyspeaking,intheshorttermtheavailability
of LNG bunkering facilities globally cannot be
guaranteed and thus this option is intentionally
neglectedinthisanalysis.
Thusthissectionwillcover
two alternatives that seem to be available in short
termin detail: the dualfuel system and the exhaust
gasscrubbertechnology.
Assuming the following data for a typical
containervessel:
1 OperatingSpeeds
ECOSpeed:16.5kn
DesignSpeed:18.5kn
MaximumSpeed:21kn
2 FuelTypesconsumed
IFO380
MDO
3 OperationalData
Steaming@ECOSpeed16.5kn(days/year):50
Steaming @DesignSpeed 18.5 kn(days/year):
140
Steaming@MaximumSpeed21kn(days/year):
20
Port/IdleTime(days/year): 150
Timenotusedforoperation(days/year):5
Estimated Annual Operation in ECAs
(days/year):80
4 MainEngine
MCR(kW):16,000
TypeofFuel:IFO380
FuelConsumption(t/yr):7,939
5 AuxiliaryEngine
No.ofMachineryofthisType:4
MCR(kW):1,600
TotalkWAuxiliaryEngine:6,400
SpecificFuelOilConsumption(g/kWh):180
TypeofFuel:MDO
FuelConsumption(t/yr):1,459
6 Boiler
No.ofMachineryofthisType:1
FuelOilConsumption(t/day):25
TypeofFuel:MDO
FuelConsumption(t/yr):1,664
Obviouslythe consumptiondata canbe
thoroughly evaluated, and the calculations above
yieldtheproductofthedailyconsumptiontimesthe
timeofoperationatvarious‘expected’levelsofload.
Giventhat the consumptiondataaboveare accurate
enough to support further estimation of the cost,
operators face the following dilemma: they should
either install a scrubber (generally a EGCS) or to
install/useadualfuelsystem.Thecriticalparameters
that determine the decision are the price of HSHFO
and LSHFO, the time (days/year) of expected
operationinanECAandtherequiredinvestmentfor
EGCS. In
few words, operators have the option to
installanEGCSandconsumethecheaperHSHFOin
all operating cases or to use HSHFO and LSHFO
whereverpermittedorrequired.Thedifferenceofthe
discountedcoststreamswilldetermine,whichoption
277
is from a financial point of view more appropriate.
The method of net present value (NPV) could be
considered, although with some cautiousness as
manyassumptionscanjeopardizethevalidityof the
outcome. The NPV analysis pinpoints the economic
lifeoftheasset(theageoftheship),thebunker
prices
andthediscountrateasthecriticalparametersofthe
decision.Thisdoesnotcontradictwiththepraxis,and
impliesthattheonlyparameternotdeterminedbythe
ownerorthefleetstatusisthepriceofbunkers,which
drawsalsotheattentionasthemainriskparameter.
Having
saidthat,itisobviousthatitisofcritical
importance to consider rational scenarios of future
fuel price values, as the amortization of the
investmentwillbeconcludedinsomefutureyears.In
ordertodealwiththeseissues,atypicalspreadsheet
modelerwouldconsiderscenariosthatarestructured
as
follows:
CurrentFuelPriceUSD/t:610
PriceDifferencetoSulfurContentof1%USD/t:40
PriceDifferencetoSulfurContent of 0.5% USD/t:
140
PriceDifferencetoSulfurContent of 0.1% USD/t:
225
Considering the above data and an investment
horizonof25yearsfortheship,discountrates(forthe
DCF Analysis) of 1.0% (low), 5.0% (medium) and
10.0%(high), as wellas the assumptions of tables X
and Y below, the accumulated
consumption is
depictedinthefollowinggraphs:
Table1.CurrentPricesandPriceDifferences(Scenarios)
_______________________________________________
USD/tBase 50% 75%
_______________________________________________
CurrentFuelPrice610 610 610
PriceDifference1%406070
PriceDifference0.5% 140 210 245
PriceDifference0.1% 225 340 390
_______________________________________________
Table2.Growthrates(Scenarios)
_______________________________________________
ScenarioLow MediumHigh
_______________________________________________
EstimatedFuelPrice 1%5%10%
IncreasesperYearin%
EstimatedFuelPrice 1%10%15%
Increaseasof2015(ontop
oftheaboveincrease)
EstimatedFuelPrice 1%10%20%
Increaseafter2020/25(on
topoftheaboveincrease)
_______________________________________________
Figure1.Lifecyclecostofbunkersas perthescenarios
ThebunkeringhubofRotterdamistakenasabase
case,aspricesofallmajorbunkeringhubsfollowthe
samefluctuationpattern,asdepictedinFigure2(see
alsosection4aboutthisissue.)
Figure2.Pricesinvariousbunkeringhubs
Obviously the difference of the prices among HS
and LS fuels is determining at large the financial
exposure for bunkers. Having a closer look at the
results of this given and indicative example the
difference of 50% from the base scenario implies an
annualgrowthrateof1.9%visàvis
1.5%forthelow
costscenariothatsuggestanincreaseofcloseto5.8%
(ca.600,000USD)oftheannualbunkercosts.Forthe
highscenario, the annual growth rate is 11.9% and
the annual increase close to 7% (close to 3.2millions
USD).Consideringthedataofthe75%scenario,then
thefiguresdramaticallychangeforthelowandhigh
scenarios,asanannualgrowthof2.0%and12.1%of
the expenses is envisaged, an increase of minimum
8.6%andmaximumof9.9%isexpectedintheaverage
annualbunkercost,implyinghigherexpensescloseto
minimum900kUSDandmaximum4.7mUSD.
In conclusion, operators can neither ignore the
evolutionoftheHSandLSprices,nordisregardthe
influence of the difference of the HS and LS prices
anditisimperativeforthemtodrafttheappropriate
scenarios,i.e.tohaveabetterinsightofthedynamics
of the statistical
attributes, in order to support their
decisions.
3 PROBABILITYANALYSIS
The data source used in the present study is the
weekly time series of the HS, LSHFO (380cSt) in
Rotterdam, as published by Shipping Intelligence
NetworkofClarksons.AlthoughdatafortheHSHFO
278
areavailablesince 1990, wedecided to useonly the
subsetofdatawherebothvalues(HS ‐ andLSHFO)
arepresent.Thus,theanalyzeddatacoversthetime
period from 2007 till 2012. The total amount of the
analyzed data (256 values) is not statistically
significant.However,itis
theonlyreliabledatasetup
tonow.
Along with the analysis of basic statistics,
probability analysis is also necessary. Probability
analysisisaversatiletoolfortheanalysisofhistorical
data. For each dry index, the empirical histogram is
calculatedasfollows(Spanos2003).
First,aparticularpartitionisdefined
oftheform
12 1
,,,,,
iI


(1)
in order to appropriately segment the range of
possiblevaluesoftheindex.Then,thetableofrelative