editorial jems

UCTEA - The Chamber of Marine Engineers

JEMS

Volume : 8Issue : 4Year : 2020ISSN:2147-2955UCTEA - The Chamber of Marine Engineers

JOURNAL OF ETA MARITIME SCIENCE

Journal of ETA Maritime Science

Volume 8, Issue 4, (2020)Contents

(ED) EditorialSelçuk NAS

213

(RE) Dimensions of the Port Performance: A Review of Literature.Umur BUCAK, İbrahim Müjdat BAŞARAN, Soner ESMER

214

(AR) Risk-based Analysis of Pressurized Vessel on LNG Carriers in Harbor.Thaddeus Chidiebere NWAOHA, Sidum ADUMENE

242

(AR) Weighting Key Factors for Port Congestion by AHP Method.Pelin BOLAT, Gizem KAYISOGLU, Emine GÜNEŞ, Furkan Eyup KIZILAY, Soysal ÖZSÖĞÜT

252

(AR) Simulation-Based Optimization of the Sea Trial on Ships.Yusuf GENÇ, Murat ÖZKÖK

274

(AR) Measurement and Modelling of Particulate Matter Emissions from Harbor Activities at a Port Area: A Case Study of Trabzon, Turkey.Süleyman KÖSE

286

(RP) Is Existing Maintenance System Adequate for Sulphur 2020 Amendments?A. Yaşar CANCA, Görkem KÖKKÜLÜNK

302

YAVUZ, B. R. (2020) The Hard Times of Maritime Pilots in Pandemic. Istanbul Strait, Turkey

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JOURNAL INFO

Publisher : Feramuz AŞKIN The Chamber of Marine Engineers Chairman of the Board

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ii

EXECUTIVE BOARD:

Editor-in-ChiefProf. Dr. Selçuk NASDokuz Eylül University, Maritime Faculty

Deputy EditorRes. Asst. Dr. Remzi FIŞKINOrdu University, Fatsa Faculty of Marine Sciences

Associate EditorsRes. Asst. Dr. Emin Deniz ÖZKANDokuz Eylül University, Maritime FacultyRes. Asst. Burak KUNDAKÇIİskenderun Technical University, Maritime FacultyRes. Asst. Coşkan SEVGİLİZonguldak Bülent Ecevit University, Maritime FacultyRes. Asst. Elif ARSLANDokuz Eylül University, Maritime FacultyRes. Asst. Gizem KAYİŞOĞLUİstanbul Technical University, Maritime FacultyRes. Asst. Merve GÜL ÇIVGINİstanbul Technical University, Maritime FacultyRes. Asst. Ömer ARSLANDokuz Eylül University, Maritime FacultyRes. Asst. Pelin ERDEMPiri Reis University, Maritime Faculty

Foreign Language EditorsAsst. Prof. Dr. Aydın ŞIHMANTEPEPiri Reis UniversityAsst. Prof. Dr. Seçil GÜLMEZIskenderun Technical UniversityLec. Seda ALTUNTAŞRecep Tayyip Erdoğan UniversityCpt. Yücel YILDIZ

Guest EditorAssoc. Prof. Charif MABROUKIUniversité Hassan 1er-settat, Morocco

BOARD OF SECTION EDITORS:

Maritime Transportation Eng. Section EditorsProf. Dr. Ender ASYALIMaine Maritime AcademyProf. Dr. Selçuk ÇEBİYıldız Technical Uni., Fac. of Mechanical EngineeringAssoc. Prof. Dr. Emre AKYÜZ İstanbul Technical University, Maritime FacultyAssoc. Prof. Dr. Momoko KITADAWorld Maritime UniversityAssoc. Prof. Dr. Özkan UĞURLUOrdu University, Fatsa Faculty of Marine Sciences

Naval Architecture Section EditorsProf. Dr. Dimitrios KONOVESSIS Singapore Institute of TechnologyProf. Dr. Ercan KÖSE Karadeniz Tech. Uni, Sürmene Fac. of Mar. SciencesDr. Rafet Emek KURTUniversity of Strathclyde, Ocean and Marine EngineeringDr. Sefer Anıl GÜNBEYAZUniversity of Stratchlyde, Ocean and Marine Engineering

Marine Engineering Section EditorsAssoc. Prof. Dr. Alper KILIÇBandırma Onyedi Eylül University, Maritime FacultyAssoc. Prof. Dr. Görkem KÖKKÜLÜNKYıldız Technical Uni., Fac. of Nav. Arch. and MaritimeAsst. Prof. Dr. Fırat BOLAT Istanbul Technical University, Maritime FacultyDr. Jing YUDalian Maritime UniversityDr. José A. OROSA University of A Coruña

Maritime Business Admin. Section EditorsProf. Dr. Soner ESMERIskenderun Technical University, Maritime FacultyAssoc. Prof. Dr. Çimen KARATAŞ ÇETİNDokuz Eylül University, Maritime FacultyCoastal and Port Engineering Section EditorAssoc. Prof. Dr. Kubilay CİHANKırıkkale University, Engineering Faculty

Logistic and Supply Chain Man. Section EditorAssoc. Prof. Dr. Ceren ALTUNTAŞ VURAL Chalmers University of Technology, Technology Management and Economics

EDITORIAL BOARD

iii

MEMBERS OF EDITORIAL BOARD:

Prof. Dr. Ersan BAŞARKaradeniz Technical University, Sürmene Faculty of Marine Sciences, TURKEY

Prof. Dr. Masao FURUSHOKobe University, Faculty, Graduate School of Maritime Sciences, JAPAN

Prof. Dr. Metin ÇELİKİstanbul Technical University, Maritime Faculty, TURKEY

Prof. Dr. Nikitas NIKITAKOSUniversity of the Aegean, Dept. of Shipping Trade and Transport, GREECE

Prof. Dr. Selçuk NASDokuz Eylül University, Maritime Faculty, TURKEY

Assoc. Prof. Dr. Feiza MEMETConstanta Maritime University, ROMANIA

Assoc. Prof. Dr. Ghiorghe BATRINCAConstanta Maritime University, ROMANIA

Assoc. Prof. Dr. Marcel.la Castells i SANABRAPolytechnic University of Catalonia, Nautical Science and Engineering Department, SPAIN

Dr. Angelica M. BAYLONMaritime Academy of Asia and the Pacific, PHILIPPINES

Dr. Iraklis LAZAKISUniversity of Strathclyde, Naval Arch. Ocean and Marine Engineering, UNITED KINGDOM

Heikki KOIVISTOSatakunta University of Applied Sciences, FINLAND

EDITORIAL BOARD

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MEMBERS OF ADVISORY BOARD

Prof. Dr. Durmuş Ali DEVECİ Dokuz Eylül University, Maritime Faculty, TURKEY

Prof. Dr. Irakli SHARABIDZE(President)Batumi State Maritime Academy, GEORGIA

Prof. Dr. Latif KELEBEKLİ Ordu University, Fatsa Faculty of Marine Sciences, TURKEY

Prof. Dr. Mehmet BİLGİN İstanbul University, Faculty of Engineering, TURKEY

Prof. Dr. Ali Muzaffer FEYZİOĞLUKaradeniz Technical University, Sürmene Faculty of Marine Sciences, TURKEY

Prof. Dr. Oğuz Salim SÖĞÜT İstanbul Technical University, Maritime Faculty, TURKEY

Prof. Dr. Oral ERDOĞAN (President)Piri Reis University, TURKEY

Prof. Osman TURANUniversity of Strathclyde, Naval Arch. Ocean and Marine Engineering, UNITED KINGDOM

Prof. Dr. Ferhat KALAYCI Recep Tayyip Erdoğan University, Turgut Kıran Maritime School, TURKEY

EDITORIAL BOARD

v

1. Submission of an article implies that the manuscript described has not been publishedpreviouslyinanyjournalsorasaconferencepaperwithDOInumber.

2. Submissionsshouldbeoriginalresearchpapersaboutanymaritimeapplications.

3. Itwillnotbepublishedelsewhereincludingelectronicinthesameform,inEnglish,inTurkishorinanyotherlanguage,withoutthewrittenconsentofthecopyright-holder.

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9. JEMS operates the article evaluation processwith “double blind” peer reviewpolicy. Thismeansthatthereviewersofthepaperwillnotgettoknowtheidentityoftheauthor(s),andtheauthor(s)willnotgettoknowtheidentityofthereviewer.

10. Accordingtoreviewers’reports,editor(s)willdecidewhetherthesubmissionsareeligibleforpublication.

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12. JEMSispublishedquarterlyperiod(March,June,September,December).

13. JEMSdoesnotchargeanyarticlesubmission,processingandpublicationfees.

JEMS SUBMISSION POLICY

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213

(RE) DimensionsofthePortPerformance:AReviewofLiteratureUmur BUCAK, İbrahim Müjdat BAŞARAN, Soner ESMER

214

(AR) Risk-basedAnalysisofPressurizedVesselonLNGCarriersinHarborThaddeus Chidiebere NWAOHA, Sidum ADUMENE

242

(AR) Weighting Key Factors for Port Congestion by AHP MethodPelin BOLAT, Gizem KAYISOGLU, Emine GÜNEŞ, Furkan Eyup KIZILAY, Soysal ÖZSÖĞÜT

252

(AR) Simulation-BasedOptimizationoftheSeaTrialonShipsYusuf GENÇ, Murat ÖZKÖK

274

(AR) MeasurementandModellingofParticulateMatterEmissionsfromHarborActivitiesataPortArea:ACaseStudyofTrabzon,TurkeySüleyman KÖSE

286

(RP) IsExistingMaintenanceSystemAdequateforSulphur2020Amendments?A. Yaşar CANCA, Görkem KÖKKÜLÜNK

302

ReviewerListofVolume8Issue4(2020) IIndexing II

CONTENTS

213

WearepleasedtointroduceJEMS8(4)toourvaluablefollowers.Therearevaluableandendeavoredstudiesinthisissueofthejournal.Wehopethatthesestudieswillcontributetothemaritimeindustry.Iwouldliketomentionmygratitudetoauthorswhosenttheirvaluable studies for this issue, to our reviewers, to our editorial board, to our sectioneditors, to our foreign language editors who provide quality publications by followingourpublicationpoliciesdiligentlyandalsotolayouteditorswhospentgreateffortsinthepreparationofthisissue.

YourSincerely.

JournalofETAMaritimeScienceNas/JEMS,2020;8(4):21310.5505/jems.2020.020.53254EDITORIAL(ED)

Editorial

Prof. Dr. Selçuk NASEditor-in-Chief

214

JournalofETAMaritimeScienceBucaketal./JEMS, 2020;8(4):214-240

10.5505/jems.2020.76598

Dimensions of the Port Performance: A Review of Literature

Umur BUCAK1, İbrahim Müjdat BAŞARAN2, Soner ESMER3,4

1ZonguldakBulentEcevitUniversity,MaritimeFaculty,Turkey2ZonguldakBulentEcevitUniversity,FacultyofEconomicsandAdministrativeSciences,Turkey3IskenderunTechnicalUniversity,BarbarosHayrettinNavalArchitectureandMaritime

Faculty,Turkey4DokuzEylülUniversity,MaritimeFaculty,Turkey

[email protected];ORCIDID:https://orcid.org/[email protected];ORCIDID:https://orcid.org/[email protected];ORCIDID:https://orcid.org/0000-0002-0614-7818

CorrespondingAuthor:UmurBUCAK

ABSTRACT

The port performance has frequently been studied in the academic literature, and thefirststudiesonthesubjectarefocusedonfinancialoroperationaldimensions.However,today,portperformancehasbecomemulti-dimensionalduetothechangingrolesoftheportstoitsstakeholders,andthefactthatlocalcompetitionhasbeenreplacedbyglobalcompetitionthroughcontinuouslydevelopingroutes,etc.Withinthisstudy,itisaimedtodetermineeachdimensionoftheportperformanceconceptwhichhadbeenhandledasamulti-dimensionalprocessinrecentyearsinliterature.Forthispurpose,portperformanceliteratureisreviewedandfrequencyanalysisoftherelatedstudieswasmade.Asaresultof the analysis, dimensional perspectivewas brought to the port performance conceptand the indicatorsofeachdimensionused inempirical studiesweregathered together.So, theconceptofportperformancehadbeendividedintofourbasicdimensionswhichare operational, financial, sustainable, and logistics. Finally, dimensional gaps in portperformanceliteraturewererevealedandsomesuggestionsweregivenforfurtherstudies.

Keywords

PortPerformance,PerformanceDimensions,PerformanceMeasurement,OperationalPerformance,SustainablePerformance.

REVIEW(RE)Received: 25 August 2020 Accepted: 17 December 2020

To cite this article:Bucak, U.,Başaran,İ.M.&Esmer,S.(2020).DimensionsofthePortPerformance:AReviewofLiterature.Journal of ETA Maritime Science,8(4),214-240.To link to this article: https://dx.doi.org/10.5505/jems.2020.76598

1. IntroductionDevelopmentssuchastheexpansionary

force of globalization, the transfer of theseat of efficient units to the countrieswith low input costs, the adaptation ofmarket economies by more countries,the mounting pressure on decreasing

transportationcosts,themarketforagilityintransportation,thepoliticandstructuralchanges including more autonomy inport management, the inclusion of stateof the art technology in loading anddischarging process, etc. require ports tobe more efficient and advantageous [1].

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© UCTEA The Chamber of Marine Engineers Journal of ETA Maritime Science

These developments also increased theperformance of the competition betweenports [2]. While high port competitionand increased carrying capacities of shipsdemand a better port performance, thisperformance largely depends on portcharacteristics such as infrastructure,expertise in cargo handling, shippingservices, and the level of integration intofreight networks [3]. In short, in today'ssupply chain era, both the demands ofcustomersandthenecessitiesoftheglobalcompetitiveenvironmentforcetheportstocontinuously improve their performance[4]. Therefore, ports need to measuretheir performance at regular intervals toimprove their performance. In general,ports need performance measurementto measure their efficiency, effectiveness,howtheyhavebeencomparedtopreviousyears,whethertheyhavemettheirtargets,their situationagainst competitors,and togain new customers by promoting theirbusiness[5].

Ports are the hubs of the shipping,so, the performance of a port has directand indirect effects. Therefore, themeasurement and the monitoring of theports' performance are very important tomaintain the development and economicsuccess of the countries [6]. Performancemeasurement results are the mostimportant data input for regional portplanningandoperations[7][8].Inthisagewhen creditworthiness is difficult, one ofthe most important challenges for portmanagement is defining and prioritizinginvestments[9].Inresponsetothis,regularperformance measurement is one of themostimportanttoolstomeetthischallenge.Thus, the investments can be easilymanaged according to the demands andtrends of themarket tracked by regularlymonitoredportperformance.

Whileportshadbeenashelterforshipsor a facility that carried out the loadingand unloading operations of the ships in

the past, they have turned into a livingspace for all foreign trade stakeholdersand a business unit that serve a largenumber of customers and produce value-added businesses covering almost alllogisticsservices.Therefore,itwillbemoreappropriate to consider the dimensionsof port performance as interdependentcomponents, considering today's complexport management [4]. For example, whiletraditionalmeasurementsfocusonlyontheseawardoftheport,thereisalsoaneedtomeasuretheconnectionleveloftheonshore[10].Manyofthestudiestakeintoaccountoperational and financial indicators whenevaluatingportperformance[11].However,evaluating the port performance only inthese twodimensionswill not be suitablefor the complex structure of the ports intermsoftheservicestheyprovidetoships,cargoes, and other transportation modes[12]. Studies in recent years show thatperformance measurement has evolvedtowards focusing on a large number ofindicators rather than only financialmeasurements and focusing on macro-level (national) performance rather thanmicro-level(organization)orregional-level(industry)performance[13].Basedonthis,Onwuegbuchunam [14] argued that newport performance indicators should bedevelopedbecauseofthechangingrolesoftheports.Objectivecriteriaarerequiredtomakeameaningfulperformanceassessmentoftheworld'sleadingcontainerports[15].Accordingly, UNCTAD [16] revealed thatport performance has a financial, market(customer) based, human resources, andoperationaldimensions.

This study aims to review portperformance literature and exhibit alldimensions of port performance andits indicators. For this purpose, thewhole reached articles that measuredports’ performance or reviewed relatedmeasurement tools were researchedthoroughly.

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Accordingly, in the second section, themethodology of this study and reviewprocesswerepresented,andthereviewoftheliteraturemadeinthescopeof‘performancemeasurement’, ‘internalandexternalfactorsthataffectportperformance’, ‘milestones inportperformancemeasurement’andresultsobtained from the detailed review wasexpressed.Inthethirdsection,eachindicatorofeachperformancedimensionusedintheport performance literature was detected.Finally,similarstudiestakenpart inrelatedliteraturewereevaluatedand theresultsoftheresearchwerediscussed.

2. MethodologyIn this study, port performance-related

literature was presented by reviewingacademicarticlesissuedinacademicjournalswhich are available at the ‘Google Scholar’.'Google Scholar' database was selected forreview because no different studies werefound inotheracademicdatabases. So, thesearchwasmade by combining thewords'port' and 'performance' in the 'GoogleScholar'database consideringarticles aftertheyear2000.However,anexemptionwasmadetoTongzon[17]andMartinez-Budriaetal.[18],becausetheywereapproachedasbasicarticles intermsof itscontents.Afterreadingabstractsectionsofthestudies,124articleswereseemedtoberelevantforourresearch.A frequencyanalysismethodwasemployed to examine relevant literature.First, a literature table that contains themethods of the accessed articles and theperformance dimensions they assessedwere revealed, and thus, the articles wereclassified. Then, homogeneous informationobtained after the classification of thearticlesbydimensionswasbroughttogether.Inthelightofsuchinformation,dimensionsof the port performance and its indicatorswere revealed. Besides statistical datarelated to the contentsof the studieswereanalysedwiththehelpofMicrosoftExcel.

2.1. Literature ReviewBichou[19]classified themethodsused

in port performance assessment into threegroups: performance measurements andindexmethods,economicimpactstudies,andefficient frontier approaches. Traditionally,port and terminal performance have beenassessed by way of calculation of whetheroptimizing the efficiency of handlingoperationsattheberthsandterminalareas[20][21]. However, port performance canalso be evaluated via calculation of itstechnical effectivenessor cost-effectiveness,or comparison of the port's actual outputwith the targeted output [22]. Herein, themeasurement of the desired or expectedperformance dimension is critical becauseport performance measurement is animportant tool in terms of managingrelations with stakeholders and achievinga sustainable competitive position [23].A performance measurement or metric,however,ispresentednumericallytoquantifyoneormoreattributesofanobject,product,process, or any related factor, and shouldallowcomparisonandevaluationincontrastwith objectives, criteria, and/or historicaldata[19].

Until the 1980s, performancemeasurementwasmostlylimitedtofinancialmeasurements. Performance measurementtechniques emerged through the use of adouble-entry accounting system [13]. Overtime, operational performance dimensionssuch as effectiveness, productivity,utilization, and effectiveness, which willenablemeasurementonanoperationalscale,have been added to these techniques [24].However, today, performancemeasurementtechniquesaremorecomplexconsideringthefactors such as themore complex businessenvironment,ever-changingglobalcustomerbehaviour, and developing companystructures. In the literature, there are twotypes of port performance measurementapproaches, which are descriptive andempirical. Descriptive approaches provide

Bucaketal./JEMS, 2020;8(4):214-240

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informationtobeusedtoobservelong-termdatabehaviour.Ontheotherhand,empiricalmodels thatmeasureportperformanceareusedtoobtaintime-seriesgraphs,horizontalsectiongraphs,scatterdiagramstorevealtherelationshipsbetweentwoormorevariablesandtherelationshipsbetweenitstrends[25].Atthispoint,Somensietal.[26]revealedthatDataEnvelopmentAnalysis(DEA)andMulti-Criteria DecisionMaking (MCDM)methodsarefrequentlyemployedinportperformancemeasurement studies. In addition to this,from the port selection perspective, therearetwobasicapproachestotheevaluationofportperformance.Thetraditionalapproachis based on directmeasurements involvingobservations, interviews, surveys,while thebehavioural approach focuses on the portusers'decisionsandmeasures[27].

However, due to the unique nature oftheportswhicharehighlyaffectedby localdynamics, an internationally acceptedstandard port performance measurementtool has not been developed yet. Althoughat the macro level, such performancemeasurement tools have been developedfor the logistics industry. For example, thelogistics performance index which is aninterchangeablecomparisontool,generatedto help countries identify the challengesand opportunities in trade logistics, is ameasurement tool developed by theWorldBank and recognized in the internationallogisticsworld [28].On theotherhand, theproject called 'PPRISM' put forward by theEuropeanCommission is themostconcretestudythattriedtosettheportperformancemeasurement to a standard. After all, thisprojectcannotfullymeettheneedsduetoitsproblemsintermsofdigitisingperformancedimensions[78].

Althoughportperformanceisoneofthemost popular topics in the literature, thereisnoconsensusonwhichfactorsaffectportperformance.Whilesomeresearchersthinkthat administrative factors have an impacton port performance, some researchers

relate between the port performance andmanagement structure, geographic factors,the port's socio-economic environment, orthe local supply chain system [29]. Studiesthatpointedouttheimportanceofthelocation[30][31][32] emphasized that the ports indifferentregionsperformdifferently.Oneofthemostimportantelementsintheexternalenvironment of the port is the politicalenvironment. Some studies [33][34][35]suggestedthatpoliticaldecisionsdetermineport performance to some extent. Somestudies[31][36]defendedthatportsshouldobtaineconomiesofscalebyincreasingthecapacity to improve their performance. Atthispoint,itwouldnotbecorrecttoconfinethe capacity concept to physical capacity.While expressing the linear relationship ofthe capacity with port performance, someauthors [37][38][39]brought theeconomiccapacity of the port environment into theforefront,someofthem[6][40]emphasizedinformationandtechnologycapacity,andoneof them [41]pointedout theport's servicecapacity. Accordingly, many authors thinkthatthefactorsthatdeterminethequalityofthe port infrastructure and superstructure,such as length, design, and maintenanceof the infrastructure and superstructure,availability, seaside accessibility, etc. affectthe performance [33][42][43][44]. On thecontrary,Paketal.[45]advocatedtheexactopposite and stated that the intangibleresources such as recognition, technologyknowledge, effective process, and qualifiedpersonnel fundamentally affect the portperformance.

Performance perceptions of ports havechanged as well as the evolution of portsover the years. In this sense, there aremilestone articles in the literature thanksto their contributions to the concept ofport performance. Tongzon [17] was thefirst to reveal the determinants of theport performance. Bichou and Gray [10]discussed that exclusively financial andproduction-based evaluations on port

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performanceremainincapabletodeterminecustomer satisfaction levels. Cullinane etal. [7] had one of the unique studies thatprocessed performance inputs and outputslong term and evaluated with panel dataanalysis.Darbraetal.[53]werefirst-timersto inject sustainability concerns in theport performance concept. Woo et al. [68]expressedthatportperformanceisversatile,cannotbelimitedtointernalprocesses,andislinkedtoexternalserviceaspectssuchasservicequalityandlogisticsaspects.Madeiraet al. [71] presented the first known studythatemployedoneoftheMCDMmethodstoevaluatetheperformanceofports.DeLangenand Sharypova [78] became the initialresearcherswho used the ‘intermodal link-level’ asoneof theperformance indicators.LiandJiang[91]presentedthe firstknownstudy that handled the collaborationperformance of the ports with its dryports. Antao et al. [100] approached safetyperformanceasaseparateportperformanceitem.MussoandSciomachen[121]proposedsolutionsforalleviatingmegavessels’effectsonportperformance.

Today'sportsoperateaslogisticscentresand even trade centres as a result of theincreasing volume of cargo transportedwith the spread of trade to all countries.Thissituationbringscompetitionamongtheportsinitswake.Ontheonehand,Cullinaneand Wang [46] believed that inter-portcompetitionwillencourageportstoimproveitsperformancewithintheframeworkoftheOrthodoxeconomictheory.Ontheotherhand,Cheon et al. [47] argued that competitionincreases performance at first, but overtime this pressure will exceed a certainthresholdandwilldowngradeperformance.As a result of competitiveness pressuressuch as the increase in ship sizes and thevarietyofcargoesthatcanbecontainerizedin recent years, dry ports have been usedin container terminals' hinterland. Dryports,withitsadditionalareasandfacilities,shortenwaiting times at the port, regulate

cargo traffic, provide container segregationand transportation options, so increase thecapacity of theport, approximate theportstoitshinterland,ensurethattheportsofferservices diversity, and enhance the foreigntradecapacityoftheregionbybringingtheports closer to the manufacturer [48]. Forthisreason,itisexpectedthatdryportshavea positive impact on port performance byincreasingtheirefficiency,thenumberofshipcalls, reliability, and berth productivity. Asanotherwayofdealingwiththiscompetitivepressure, Han [49] proposed that portsshouldcooperatewithsupplychainpartnersto provide value-added services to theircustomers.However,portsshouldcooperatewithnotonlysupplychainserviceproviders.Withintheportarea,customers(consignors,consignees), regulatory groups (freightforwarders, logistics service providers),physical groups (terminal operators),authoriser groups, and financial groups(insurancecompanies)needtointeractwitheachotherhorizontallyandvertically[50].Inthissense,themanagementoftheserelationscan directly affect port performance. Forthis reason, Hervas-Peralta et al. [51] whopointed out the right planning stated thatport performance will be increased if thefocus is on terminal area optimization. Insupport of this, Esmer [5] highlighted theinternal factors such as handled emptycontainers, inefficientcontainermovements(displacement movements within thebay), the automation level of the ship toshore cranes, container weight, and thenecessities forspecial requirementsaswellascommercialconstraints.

2.2. ResultsAs a result of the frequency analysis,

informationsuchastheyearandthejournalinwhichthearticleswerepublished,themethodsinwhich thearticleswereemployed, and theperformancedimensionsinwhichthearticlesrevealedwhilemeasuringtheportperformancewereclassifiedandshowninTable1.

Bucaketal./JEMS, 2020;8(4):214-240

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Year Reference Journal Method(s) Approached Performance Dimension

1995 [17] TransportationResearchPartA Mathematicalmodel

infrastructureandsuperstructure,operation,

financial

1999 [18] InternationalJournalofTransportEconomics DEA financial,operation

2001 [33] TransportationResearchPartA DEA

operation,financial,infrastructureandsuperstructure

2002 [42]ReviewofUrban&

RegionalDevelopmentStudies

DEA operation,infrastructureandsuperstructure

2004 [10] MaritimePolicy&Management StructuredInterview operation,financial,customer

satisfaction

2004 [41] MaritimeEconomics&Logistics DEA

operation,infrastructureandsuperstructure,financial,customersatisfaction

2004 [7] TheReviewofNetworkEconomics

DEAandPaneldataanalysis

operation,infrastructureandsuperstructure

2004 [52] JournalofMarineScienceandTechnology

Hierarchicscoremethod,Grey

relationalanalysis,


2004 [53] MarinePollutionBulletin Literaturereview sustainability

2005 [54] TransportationResearchPartA

stochasticfrontieranalysis

operation,financial,customersatisfaction,infrastructureand

superstructure,

2006 [55]InternationalJournalofLogistics:Researchand

ApplicationsDEA operation,infrastructureand

superstructure

2006 [20] TransportationResearch stochasticfrontieranalysisandDEA

infrastructureandsuperstructure,operation

2006 [22]Researchin

TransportationEconomics

Literaturereview financial,operation,safety

2006 [19]Researchin


Literaturereview financial,operation,customersatisfaction

2007 [56] AppliedMathematicsandComputation FuzzyMCDM


financial

2007 [57]Researchin


Literaturereviewoperation,infrastructureandsuperstructure,financial,

customersatisfaction,safety

2007 [15] MaritimePolicy&Management DEA operation

Table 1. Literature Table

./..

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2008 [58] MaritimePolicy&Management Literaturereview


2008 [59] MaritimePolicy&Management Mathematicalmodel operation

2008 [43] EuropeanJournalofScientificResearch

DEA,CorrelationAnalysis,Regression

Analysis


2008 [60] TransportationResearchPartA FactorAnalysis

operation,financial,infrastructureand

superstructure,customersatisfaction,logistics

2008 [5]DokuzEylülÜniversitesiSosyalBilimlerEnstitüsü

DergisiLiteraturereview operation,infrastructureand

superstructure,financial

2009 [8] IUPJournalofInfrastructure

CorrelationAnalysis,PrincipalComponent

Analysis


2009 [61] JournalofCleanerProduction Literaturereview sustainability

2009 [32] MaritimePolicy&Management DEA operation,infrastructureand

superstructure

2010 [34] JournalofEconomicStudies

DEA,Paneldataanalysis


2010 [62] MaritimeEconomics&Logistics DEA infrastructureand

superstructure,operation

2010 [63]InternationalJournalofComputational

IntelligenceSystemsDEA operation

2010 [64] TransportationPlanningandTechnology

FreeDisposalHull,DEA financial

2010 [46] OperationsResearchSpectrum DEA,ANOVA operation,infrastructureand

superstructure

2011 [65]AnaleleUniversitatii"EftimieMurgu"ResitaFascicoladeInginerie

Literaturereview operation

2011 [66] ScientificResearchandEssays FuzzyMCDM


financial

2011 [67] Resources,ConservationandRecycling

Mathematicalmodel,DEA

operation,financial,sustainability

2011 [68] MaritimeEconomics&Logistics

ConfirmatoryFactorAnalysis

operation,safety,customersatisfaction,logistics,financial

2011 [69] TransportPolicy FuzzyANPoperation,financial,infrastructureandsuperstructure

Table 1. Literature Table (Cont')

./..

Bucaketal./JEMS, 2020;8(4):214-240

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2012 [30]InternationalJournalofPhysicalDistributionandLogisticsManagement

TTest operation,logistics,financial,safety

2012 [70] JournalofManagement&Economics Depthinterview,tTest safety,operation

2012 [71] InternationalJournalofProductionEconomics

Factoranalysis,MACBETH financial,operation

2012 [72] SimulationModellingPracticeandTheory SimulationModel operation,infrastructureand

superstructure

2012 [73] TheAsianJournalofShippingandLogistics

Factoranalysis,Fuzzylogic sustainability

2012 [74]InternationalJournalofBusinessPerformance

ManagementDEA


superstructure,customersatisfaction,logistics

2012 [75] TransportPolicy Literaturereview operation

2013 [76]InternationalJournalofPhysicalDistributionandLogisticsManagement

AHPandFuzzyMCDM sustainability

2013 [77]Researchin

TransportationBusinessandManagement

Mathematicalmodel sustainability,financial

2013 [78]Researchin


Mathematicalmodel

logistics,operation,sustainability,financial,infrastructureandsuperstructure

2013 [79]Researchin


CorrelationAnalysis operation,safety,logistics

2013 [35]Researchin


Mathematicalmodel infrastructureandsuperstructure,operation

2013 [80]Researchin


Stochasticfrontieranalysis,DEA


2013 [81] GirişimcilikveKalkınmaDergisi Descriptiveanalysis financial,customersatisfaction

2013 [82]SupplyChain

Management:AnInternationalJournal

Structuralequationmodel

operation,financial,customersatisfaction,logistics

2013 [83] MaritimePolicy&Management DEA

sustainability,financial,infrastructureand


2013 [21] TransportPolicy DEA operation,infrastructureandsuperstructure

2013 [84] PolishMaritimeResearch Interview financial,operation,logistics


./..

222


2013 [85] MaritimeEconomics&Logistics DEA infrastructureand


2014 [12] VerimlilikDergisi DEA infrastructureandsuperstructure,operation

2014 [86] TransportReviews Literaturereview operation

2014 [87] İstanbulÜniversitesiİşletmeFakültesiDergisi DEA financial,operation

2014 [88] TransportationResearchPartE Mathematicalmodel operation,financial,logistics,

safety

2014 [3] MaritimePolicyandManagement Factoranalysis operation,financial

2014 [89] DecisionSupportSystems Mathematicalmodel operation,financial


Hierarchicalclusteranalysis

operation,infrastructureandsuperstructure,financial

2014 [91]InternationalJournalofe-NavigationandMaritimeEconomy

GreyRelationsAnalysis,AHP

customersatisfaction,financial,operation

2014 [92] MarinePollutionBulletin Delphi sustainability,operation

2014 [9] MaritimePolicy&Management

Importance-PerformanceAnalysis

operation,safety,financial,customersatisfaction

2014 [93]

InternationalJournalofResearchinApplied,NaturalandSocial

Sciences

Literaturereviewinfrastructureand

superstructure,logistics,operation,financial

2015 [94] TransportationResearchPartC SimulationModel infrastructureand


2015 [95] TransportationResearchProcedia

MultipleRegressionAnalysis operation

2015 [96] AlphanumericJournal DEAinfrastructureand

superstructure,operation,financial

2015 [45] TheAsianJournalofShippingandLogistics FuzzyTOPSIS operation,safety,customer

satisfaction

2015 [13]InternationalJournalofLogisticsResearchand

ApplicationsLiteraturereview operation,financial,customer

satisfaction,sustainability

2015 [1]

InternationalJournalofProductivityandPerformanceManagement

Literaturereview operation,sustainability,financial,customersatisfaction

2015 [97] TransportationResearch DEA infrastructureandsuperstructure,operation


./..

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2015 [98]InternationalJournalofOperationsandLogistics

ManagementELECTRE


2016 [2] Benchmarking:AnInternationalJournal DEA operation,financial

2016 [99]IEEETransactionsonIntelligent

TransportationSystemsMathematicalModel operation

2016 [100] SafetyScience Literaturereview safety,sustainability

2016 [101]InternationalJournalofLogisticsResearchand

Applications

Structuralequationmodel logistics,operation,financial


Stochasticfrontieranalysis,DEA



Factoranalysis,Structuralequation

model,sustainability,financial

2017 [26] IntangibleCapitalLiteraturereview,Bibliographicalportfolioanalysis

logistics,operation,financial

2017 [102] MaritimePolicyandManagement Delphianalysis sustainability

2017 [103] TheAsianJournalofShippingandLogistics AHPandFuzzyTOPSIS operation,customer

satisfaction

2017 [4] TransportationResearchPartA AHP,DEMATEL,ANP

operation,financial,customersatisfaction,logistics,

sustainability

2017 [104] JournalofManagement,MarketingandLogistics DEA operation,infrastructureand

superstructure

2017 [11] EconomicsandFinanceinIndonesia

HybridLeastsquaremethods operation,financial

2017 [105] MaritimeEconomicsandLogistics

MathematicalmodelandDEA

operation,safety,infrastructureandsuperstructure

2017 [38] ForumScientiaeOeconomia Literaturereview financial,operation

2017 [31] MaritimeEconomicsandLogistics

NetworkanalysisandPanelRegression


2017 [25] ComputerSciencePortEfficiency

Performance(PEP)Model

operation

2017 [106]InternationalColloquiumonLogisticsandSupplyChainManagement

Principalcomponentanalysis

financial,operation,infrastructureandsuperstructure

2017 [107] MATECWebofConferences

StochasticSimulationModel operation


./..

224


2017 [23] TransportationResearchPartE

DEMATEL,ANP,FuzzyER

operation,financial,customersatisfaction,logistics,sustainability,safety

2017 [108] JournalofManagement,MarketingandLogistics TOPSIS infrastructureand


2017 [109] JournalofBusinessManagement operation,financial

2017 [110] MarinePollutionBulletin Semi-structuredinterview sustainability,financial

2017 [47] MaritimePolicy&Management DEA

sustainability,operation,infrastructureandsuperstructure

2018 [111]InternationalJournalofQualityandReliability

Management

SigmaValue(SV),theProcessCapability

indices(PCIs),andtheCostofPoorQuality

(COPQ)

operation,financial,safety

2018 [112] JournalofETAMaritimeScience DEA infrastructureand


2018 [113] TheIUPJournalofSupplyChainManagement

ImportancePerformanceAnalysis(IPA),QualityFunctionDeployment(QFD)andInterpretiveStructural

Model(ISM)

operation,customersatisfaction

2018 [14] Logistics QueueAnalysisoperation,logistics,infrastructureandsuperstructure


Metafrontieranalysis,DEA,stochasticfrontieranalysis


2018 [114]JournalofIntegrated

CoastalZoneManagement

DuncanTest sustainability

2018 [50]Productionand

OperationsManagementSociety

Mathematicalmodel operation

2018 [28] JurnalTeknikIndustri AHP financial,infrastructureandsuperstructure,operation

2018 [49] TheAsianJournalofShippingandLogistics

Factoranalysis,RegressionAnalysis

financial,operation,customersatisfaction

2018 [40] JournalofShippingandTrade CorrelationAnalysis logistics,operation,financial

2019 [44] CogentBusiness&Management

Structuralequationmodel

infrastructureandsuperstructure,financial,

operation


./..

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2019 [115] InternationalJournalofInformationManagement

CorrelationAnalysis,RegressionAnalysis logistics,operation

2019 [116] TransportationResearchPartD Literaturereview sustainability

2019 [117]InternationalConferenceonEngineering,AppliedSciencesandTechnology

RegressionAnalysis operation,infrastructureandsuperstructure

2019 [118] ScientificBulletinofNavalAcademy Literaturereview operation,customer

satisfaction,logistics

2019 [119] Sustainability Literaturereview sustainability

2019 [51] Sustainability AHP operation,financial,customersatisfaction,sustainability

2019 [120] CogentBusiness&Management

ExploratoryFactoranalysis,One-Way

ANOVA

sustainability,safety,financial,operation

2019 [6] Complexity Mathematicalmodel


superstructure,logistics,sustainability

2019 [122] TransportPolicy Importance-Performanceanalysis

operation,infrastructureandsuperstructure,customer

satisfaction,financial,logistics

2019 [123] AVRASYAUluslararasıAraştırmalarDergisi DEMATEL sustainability


PanelRegressionAnalysis financial

2019 [125] JournalofYaşarUniversity

AHP-TOPSIShybridmethod

financial,infrastructureandsuperstructure,operation,

safety

2019 [27] ManagementDecision Best-Worstmethodfinancial,infrastructureandsuperstructure,operation,

customersatisfaction,logistics


ExploratoryFactoranalysis


superstructure,logistics

2020 [39] ISHJournalofHydraulicEngineering CorrelationAnalysis operation


Discreteeventsimulationmodel operation,financial

2020 [29] TransportPolicyTtest,Multiple

RegressionAnalysis,DEA

operation,customersatisfaction,infrastructureand

superstructure


226

As a result of the frequency analysis,it is seen that 25 articles were publishedbetween the years of 1995-2009, 40articlesbetweentheyearsof2010-2014,59articlesbetweentheyearsof2015-2020.Inthelightofthisinformation,79.8percentofthesearticleswerepublishedaftertheyear2010. This situation shows that recently,port performance studies have becomea trend again in academic literature andthere has been much more attention toit.When looking at the journals in whicharticles were published, 'TransportationResearch'drawsattentionwith14articlespublished on the subject, ‘MaritimePolicy & Management' accompanied with12 articles and 'Maritime Economics &Logistics'followedupthemwith9articles.Besides, these three journals are followedby 'Research in Transportation Businessand Management' with 5 articles, 'TheAsianJournalofShippingandLogistics'and'TransportPolicy'with4articles.

Whenwelookatthestatisticaldataonthemostpreferredmethodsinthearticles(shown in Figure 1), it is seen that DEAcomes to the forefront. Accordingly,whilethenumberofarticlesemployingDEAis33,thisnumbercorrespondstoapproximately27percentofallarticles.While16percent

Figure 1. Employed Methods

of the authors contribute to the portperformance literature by producingreviewpapersthrougha literaturereview,the number of articles that employed oneoftheMCDMmethodsis15.Besides,while12studiesmeasuredtheportperformanceby proposing a newmathematical model,9articlestriedtodevelopadatacollectiontoolrelatedtoportperformance.The firststudyemployedMCDMmethodspublishedin 2012. So, it is detected that the mostfrequently used method was MCDMmethods after the year 2012. Studies thatemployed MCDM methods and DEA hadmadeasignificantcontributiontotheportperformanceconceptintermsofmonitoringthe evolution of port performanceindicatorsovertheyears.Itisverydifficulttodevelopastandarddatacollectiontooltomeasure port performancedue to variousreasonssuchastheuniquenatureofeachport type and constantly changing andevolving customer expectations. Perhaps,forthisreason,thenumberofstudiestryingto combine all port performance criteriausingfactoranalysiswaslimitedto9.

Finally, the operational performanceof the ports has been determined as themost discussed performance dimensionin the articles. The operational dimension

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of port performance was approached in105 different articles, which indicatesthat this dimension is examined in 86.78percent of all articles. The financial(economic)dimensionofportperformancewas discussed in 62 studies, and thesustainability dimension, which wastrendingespeciallyaftertheyear2010,washandled in 39 studies. Lastly, the logisticsdimension of port performance wasexamined in 22 studies. In the followingsection, the content of the studies ondimensionsoftheportperformancewillbeanalysedindetail.

3. Dimensions of the Port PerformanceInthisstudycontentsofthe124articles

were analysed and port performancedimensions discussed in the articleswereevaluated. As a result of the frequencyanalysisemployedinthisstudy,itwasseenthat port performance has operational,financial, sustainability, and logisticsdimensions. In this section, indicators ofeachdimensiontoprovideameasurementtoolwerepresented.

3.1. Operational IndicatorsAccordingtoDucruet[126]andMangan

et al. [30], if the parameters of the portperformance are constantly monitored, itbecomesthestandardizedparametersoftheportoperationsandtheseparametervaluesbecome the standard of the port [118].Consideringthisthought,almostallstudiesonportperformanceintheliteratureeitherused the operation performance insteadof the port performance or integratedan operational indicator into the portperformance.

One of the most important indicatorsof operational performance is the speedconcept, especially from a customerperspective. In this sense, Tongzon andHeng[54]andKavakebetal.[94]expressedtheoperationalspeedlevel intheportsasan importantperformance indicator, since

thenavigationalcostsoftheshipsaremuchlower than the costsduring the time theyareintheports.Studiesonimprovingportperformance especially emphasize theconcepts of efficiency and effectivenesssothatportoperationscanbeaccelerated[106]. Herein, while traditional portperformance indicators focus on specificefficiency criteria, what is expected fromcontemporary indicators is inclusiveof allaspects of the operation and is consistentwith the organization's strategies [68].As almost all the studies analysing theoperational performance of ports withDEA did, Lin and Tseng [15] and Ursavaş[89]used thenumberof calling shipsandtheloadedandunloadedcontainervolumeas outputs, in other words, performanceindicatorsoftheDEAmodel.Esmer[5], inaddition to these indicators, approachedsuch the indicators as the rate of thecontainer loaded and unloaded, craneproductivity, the automation level of thecranes, average container weight, shipturnaround time, total working time,stored container movement, labour forceproductivity, area utilization efficiency,equipment usage efficiency, cost-effectiveness. Apart from these, Paingand Prabnasak [117] emphasized thatsuch criteria as 'average waiting timewhile anchoring', 'average handling cargotonnage per ship’, 'berth occupancy rate','container dwell time', 'truck turnaroundtime'areusedasperformanceindicatorsinliterature.Finally,inthereportpublishedbyUNCTAD [16], the operation performanceof the portswas handled in two differentways: shipoperationandcargooperation.Accordingly,whilethereporthandledshipoperation indicators with such criteria as"average waiting time (hours), averageship length (meters), average ship draft(meters), average ship gross tonnage";cargooperationperformancewasanalysedusing such indicators as "average tonnageper ship call, cargo tonnage handled per

228

working hour, the number of containershandled per hour, container dwell time(days), handled cargo per area (ton/hectare), handled cargo ton per berthlength".

3.2. Financial IndicatorsLandlord ports can be influenced by

three main factors: competition pressurefor infrastructure investment, competitionfor landuse, and financialpressure [109].To eliminate or at least alleviate financialpressure, ports need tomeasure financialperformance and check compliance withitstargets.Fromashareholderperspective,portauthoritiesneedto increasetheirnetprofitability, increase their overall marketshare,investinnewdevelopmentprojects,andinotherwordsincreasetheirfinancialperformance [109]. The United Nationshas accepted financial performanceindicators, which measure the extent towhich port authority converts capital andfunds intoperformance,asoneof the twomost important criteria in measuringport performance [11]. The financial andoperationalperformanceofportauthoritiesemerges as a result of managerial skills,and the financialperformanceof aport isofgreatimportancetoprotectinvestmentsandtoplannewprojectsinthefuture[109].

Thefinancialperformanceofaportcangenerally be explainedby theprofitabilityof thatport.Aguiar-Diazetal. [124]whilemeasuring the financial performance ofSpanish ports, addressed the return ofassets (ROA)of theports as a criterionofperformance.Ontheotherhand,Wiegmansand Dekker [2] emphasized that twomain indicators determine the financialperformanceoftheportsandthattheyaresales and profitability. While Muangpanand Suthiwartnarueput [120] consideredthe unconsolidated financial situationof the port as a financial performanceindicator, Roos and Neto [110] took intoaccount financial investment requirement,

Bolevics [109] handled net profit, totalmarket share, operating income, totaldebts, investment intangible fixedassets, Earnings Before Interest TaxesDepreciation and Amortization (EBITDA),Mickiene and Valioniene [38] addressedfinancialefficiencyandfinancialautonomy,Aqmarina and Achjar [11] approachedthe rate of return andoperating expensesas indicators of financial performance.Brooks and Pallis [58], who handled thefinancial performance of ports muchmore comprehensively, included financialindicators such as return on capitalemployed (ROCE), service revenues,service profitability, trade receivables,interest coverage ratio, terminal charges,shipcharges,andtheseindicators'shareingrossincomeandnetprofit.

3.3. Sustainable IndicatorsWhilemostofthestudiesrelatedtoport

management are on the competitivenessor efficiency of the ports, undesirablevariablessuchasCO2emissionshavebeenignored in studies on port efficiency [83].Portshavebecomeacomplexsystemduetofactorssuchas thevarietyofcargowithinthem, their location close to the society,and responsibilities for the benefits oftheir stakeholders. For these reasons andconsidering today's climate conditions[76],propermanagementmentalityagainstsecurityandenvironmentalriskswithintheportareahasbecomeveryimportant[100].To establish harmonious environmentalprotectionandsustainabledevelopment,aneffective environmental portmanagementstrategy needs to consider environmentalhazards, mitigation options, forecastingmethods,informationaboutenvironmentalindicators, and laws [92]. There arethree critical processes to implementenvironmental management practicesat the ports: cooperation with supplychain partners, environmentally friendlyoperations, and internal management

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support [67]. Air quality, greenhouse gasemissions, soil and ground resources,rubble,lightandsoundproblems,water,andclimatechangecanbecountedamongthosethatneedtobe improvedenvironmentallyto ensure port sustainability. For theeconomicdimension,indicatorssuchasthebenefitsoftheportusers,faircompetition,employment, economic development, andtourism and port investment should betaken into account [37]. Environmentalperformanceindicatorshavetaskssuchasprovidinginformationaboutenvironmentalproblems,supportingdevelopmentpoliciesanddeterminingpriorities,monitoringtheeffectsofpolicies,pursuingenvironmentaltargets, comparing environmentalperformanceover time, and attracting theattention of the society [61]. The socialdimension, especially human resources,had been seen as independent variablesor input elements. The safety aspect ofsocial sustainability came to the forefrontof the literature. The issue of ensuring asafe operation has gained currency latelyin the literature and studies concludethat appropriate working conditions haveincreased labour efficiency and thus theoperationalperformanceoftheport[100].Forthisreason,thesafetyoftheportareahasstartedtobeassociatedwiththeconceptsof effectiveness and competitiveness [68].Other important results of ensuring safeoperationintheportareaarethehiringofqualified workers, employing them long-term, and minimizing the economic andsocial losses of accidents. Recognition ofaport as a safeporthas ameaningmuchmore for the related unit than businessunits serving in other industries [45].Because of the port becomes inoperabledue to emerging unsafe situations in theport area, it will have negative resultsboth socially and economically. To takeprecautions against unsafe situations,it is very important to know what thesesituations are. Darbra and Casal [127]

stated that accidents in ports are mostlyoccurred during the manoeuvring of theships,whileYip[128]revealedthatmostoftheaccidentsintheportareaoccurreddueto the ships crashing into the dock [100].Unlike, Mollaoğlu et al. [129] groupedthe factors that caused the accident inthe port area as labour induced, vehicleand equipment induced, facility induced,lack of coordination induced. Accordingly,overconfidence and disengagementbehaviour, which are among the labourinducedfactors,havebeenidentifiedasthemostleadingreasonfortheaccidentsintheports.

Lim et al. [116] had not encounteredin the literature any studies that areconcernedonlywiththesocialoreconomicdimension of sustainability. The generaltrend in the related literature is that theconcepts of sustainable port performanceand environmental port performance areinterwoven.Thefirsttime,Darbraetal.[53]introduced the project, which expressesenvironmentally friendly practices in theports,namedasthe'SelfDiagnosisMethod'carriedoutbyESPO.Inthisproject,criteriasuch as “air quality, dredging activities,dust management, energy usage, loss ofhabitat, health and safety management,noise management, soil pollution, wastemanagement and water quality” wereused as indicators of sustainable portperformance. Saengsupavanich et al. [61]addressedbothcountableanduncountablecriteria such as the number of ISO 14001Environmental Management Systemcertifiedfacilitiesandterminals,thenumberof environmental complaints, the numberof fuel/chemical leakage incidents, waterqualityaroundtheport,penaltiesimposedon non-observant operators, number ofenvironmental department employees,number of ships inspected annually inthe port, environmental expenditures,taxes and allowances, accessibility to theemergency plan, frequency of training,

230

knowledge level of employeeson theportstatecontrols,protectionofenvironmentalpolicies, as an indicator of environmentalperformance. Apart from these, Parkand Yeo [73] analysed such indicatorsas "alternative fuel usage, incentives toreducepollution, renewableenergyusage,development of the breakwater system torevive the dock, resource recycling in theport area, mode change to prevent trafficcongestion,artificialsandpileandwetlandcreation", while they were evaluating theenvironmental performance of Koreanports.Manynewcriteriahavebeenaddedtothesesustainableperformanceindicatorsovertheyears:coldironing(onshorepowersupplytoships)[76],CO2emissioncontrol[83], odour management [92], waterconsumption level, and tariff discount togreen ships [100], green material usageintheportbuildingprocessandattendingrelated conferences [37], environmentalcosts [110],areaconsumption level [119].Ontheotherhand,inthesocialdimension,Antao et al. [100] used such indicators as"the number of off days due to accident,the accident frequency rate, the numberof fatal work accidents, the total numberof work accidents, the degree of accidentseverity,thenumberofabsenteeismduetoaccidentorillness,thenumberofseawardaccidents, the number of ships crashesintothedock,thenumberofnear-miss,thenumber of leakage incidents, the numberof fires or explosions" to measure thesafety performance of the ports. Brooks[57] handled frequency of accidents,Wooet al. [68] approached compliance withregulations, the number of accidents andthenumberofpreventedaccidents,Brooksand Schellinck [79] focusedonprejudicialto cargo incidents,Ha et al. [23] used thedetermination of restricted areas, formalsafety training practices, number ofadequateobservationandthreatawarenessasindicatorsthatdeterminewhetherportsaresafeornot.

3.4. Logistics IndicatorsFor the logistics world, ports are an

importantnodalpointsothattheyprovideintermodalandmultimodaltransportationservices and operate as logistics centresfor cargo and passengers [10]. Today,almostalltheservicesprovidedbylogisticscompaniesareexpectedfromtheportsbyitscustomers.Forthatreasonalone,portsshouldcooperatewithsupplychainpartnersto provide value-added services to theirstakeholders [49]. Among the advantagesthataportcooperateswithlogisticsserviceproviders, not only does it increase thevalue of the relevant port supply chain,but alsodecreases thevalueof competingforportsupplychains[101].Throughthis,many companies are involved in logisticsand supply chain integration throughouttheportandaroundtheports[10].Duetothe changing logistics environment, portsshould carefully monitor changes andproducestrategiesaccordingly[68].

The logistics performance of theports is often based on efficiency andutility measurements. Bichou [130]stated that since ports have used theirfacilities for logistics, production, andeconomicactivities,newportperformanceindicators are needed [14]. Accordingly,many indicators determine the logisticsperformanceoftheports.Theseindicatorswereprocessedintheacademicliteratureinawaythatwilldifferaccordingtotheyears,inotherwords,theywereshapedaccordingtothemarketsituation.BichouandGray[10]have identifiedprocesses such as logisticsintegration, benchmarking, logisticschannel design, value-added services,customer service as indicators of a port'slogisticsperformance.Wooetal.[68]addedindicatorssuchasservicequality,customerorientation level, auxiliary service prices,intermodal cargoes' waiting and workingtimes, to the literature. Seo et al. [101]used the logistics performance indicatorsof the ports such as convenience to the

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portusers,safety,andsecuritythroughoutthe hinterland, and reliability. Han [49]considered performance dimensions suchas costperformance,qualityperformance,and responsiveness as indicators of thelogisticsperformanceof theports. Finally,Haetal.[122]havetakenintoaccountthelevelofintermodaltransportationsystemsandvalue-addedservicesasanindicatoroflogisticsintegrationsofcontainerterminals.

4. DiscussionWhentheliteratureisanalysed,itisseen

that some studies have made a literaturereview regarding the port performanceand as a result of their analysis, theybrought different perspectives to the portperformance concept. These studies wereanalysed in detail and detached aspectsof these studies from our study wererevealed.Thus,theoriginalityofthisstudyand its contribution to the literature wastriedtoberevealed.LangenusandDooms[13] evaluated 74 articles in literatureand drew attention to the gap that isless concern on industry specific ports’performance. And the authors proposedthat new developments such as thecontainer revolution, big data analytics,knowledgetransparency,whichaffectportperformance, should be assessed. Lim etal. [116] reviewed 21 articles focused onthe sustainability performance of portsand proposed that social indicators ofport performance should be revealed. Inourresearch,itisdeterminedthat8socialindicators revealed in that study usedgenerallyasinputorindependentvariableto assess ports’ overall performance.Somensi et al. [26] analysed 37 articlesin literature and suggested that it shouldbe evaluated whether port managementactivities contribute to port performance.Similarly, Vieira et al. [86] advocated thatthere is a researchgap in the relationshipbetweenportgovernanceandperformance.Ontheotherhand,ourresearchsuggested

amoredescriptiveapproachforcollectingdata and measuring port performance.Dutra et al. [1] handled 23 articles andremarked thatmostof thestudiesareoutof interactingwith portmanagers. Unlike,wethinkthatstakeholdersofportsshouldevaluate service quality they receive andthus,portperformancewouldshowup.

No other study focusing on thedimensions of port performance wasfound among the descriptive studiesin the literature. On the other hand, itwas observed that the empirical studiesdid not analyse cases by combining thedimensionsof theportperformanceorbyseparating the related dimensions. Sinceperformance dimensions were thought tohaveanaturalrelationshipwitheachotherornomeasurementmodelseemstoallowthis separation. For instance, Brooks andSchellinck[79]askedcustomersofUSandCanadian ports to evaluate the five-yearperformance of the most frequent porttheyworkwith.Whiletheywereevaluatingthese ports’ performance, they didmeasure operational, safety, and logisticsperformance,butdidnottakeintoaccountfinancial and sustainable dimensions. Onthe other hand,most of studies had usedoperational indicators to evaluate overallperformance of ports [42][7][55][15][43][8][32][72][35][80][21][85][94][95][99][24][25][107][108][36][39][50]. However,theoriginalityofthisstudycomesfromthispoint.Ourresearchsuggests thatanalyseson port performance should be made byseparatingitsdimensionsfromeachother.After this separation, an analysis of thepreferred dimension(s) should be carriedout.

5. ConclusionPortsaremorethanjustameetingpoint

forcarriersandshipperstodaybutarethenodes of global trade and produce value-added services for many stakeholders.So, the concept of port performance has

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changed greatly over the years and theperformance perception of each portstakeholder has differed from each other.For example, while operational quality inthe terminal area is perceived as a highperformancebyshippersorcarriers,ontheother hand, the legislative bodies or localcommunityperceiveefficientsustainabilityapplications as high performance orlogistics service providers care abouthinterlandconnectionqualitymore.Atthispoint, the perception of the shippers, theport authority, the company that providestowageandpilotageservice,etc.candifferfromeachother.For thisreason, it isverydifficulttoestablishastandardperformancemeasurement. Besides, considering thecompetition between the ports outsidetheportarea, it isalso importanttoknowwhichperformancedimensionisdesiredtomeasure.

In order to overcome the challengesof standardising port performancemeasurement, different perceptions ofthe stakeholders should be gathered andobtained an overall score or should beexactly separated fromeachother.Soasacontributionofthisstudy,dimensionsoftheportperformancewererevealedtobringanew perception to the port performanceconcept. Moreover, indicators of eachdimension were developed for empiricalanalyses. Thus, different aspects of portperformance will be determined and alsoassessed. Maybe the contribution level ofeachaspect tooverallperformancecanbeevaluated.

For further studies, it would beappropriate to develop a measurementon in which dimension of the portperformance is desired to be examined.Although corporate social responsibility(CSR)inportshadbeenstudiedmanytimesbefore,theeffectivenessorefficiencyofCSRactivitieswasnotanalysedintheliterature.Thus,performancecriteriaregardingports'CSR practices can be developed. Most

of the studies assessed the operationalperformanceof theportshadseenhumanresources as an independent variable orinput factor to achieve high performance.However,factorsthataffecthumanresourcequalitycanbestudied.Inthisway,in-depthanalysisofoperationalperformancecanbepresented.

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JournalofETAMaritimeScienceNwaoha&Adumene/JEMS, 2020;8(4):242-251

10.5505/jems.2020.89266

Risk-based Analysis of Pressurized Vessel on Risk-based Analysis of Pressurized Vessel on LNG Carriers in HarborLNG Carriers in Harbor

Thaddeus Chidiebere NWAOHA Thaddeus Chidiebere NWAOHA1, Sidum ADUMENE, Sidum ADUMENE2

1FederalUniversityofPetroleumResources,NigeriaFederalUniversityofPetroleumResources,Nigeria 2RiversStateUniversity,NigeriaRiversStateUniversity,Nigeria

[email protected]; [email protected]; ORCIDID:ORCIDID:https://orcid.org/0000-0002-8687-5558https://orcid.org/[email protected];ORCIDID:[email protected];ORCIDID:https://orcid.org/0000-0003-4095-467Xhttps://orcid.org/0000-0003-4095-467X

CorrespondingAuthor:ThaddeusChidiebereNWAOHACorrespondingAuthor:ThaddeusChidiebereNWAOHA

ABSTRACTABSTRACT

TheneedtounderstandtheassociatedrisksofpressurizedvesselsandtheirconsequencesTheneedtounderstandtheassociatedrisksofpressurizedvesselsandtheirconsequencesonboard ship is imperative. The handling and storage of Liquefied Natural Gas (LNG)onboard ship is imperative. The handling and storage of Liquefied Natural Gas (LNG)mostly result in catastrophic accidentwith associated consequences. To quantify thesemostly result in catastrophic accidentwith associated consequences. To quantify theseconsequencesintermsofdeathanddegreeofburndependsonthetankstructuresandconsequencesintermsofdeathanddegreeofburndependsonthetankstructuresandpressurecontrolmechanismonboardLNGcarriersinaharbor.Inthisresearch,theresultpressurecontrolmechanismonboardLNGcarriersinaharbor.Inthisresearch,theresultofthepotentialrisksanddamageconsequencesoftheLNGfireaccidentintermsoftheofthepotentialrisksanddamageconsequencesoftheLNGfireaccidentintermsofthedegreeofburnsandfatalityispresented.Theprobabilityofdeath,firstandseconddegreedegreeofburnsandfatalityispresented.Theprobabilityofdeath,firstandseconddegreeofburninjuriesareassessedusingconsequencemodellingtechnique,whilethepoolfireofburninjuriesareassessedusingconsequencemodellingtechnique,whilethepoolfirewasmodelledusing theBoilingLiquidExpandingVapourExplosion (BLEVE)approach.wasmodelledusing theBoilingLiquidExpandingVapourExplosion (BLEVE)approach.Theresultshowsthatat30metersfromtheflameradius,theprobabilitiesforfirst-degreeTheresultshowsthatat30metersfromtheflameradius,theprobabilitiesforfirst-degreeburn,second-degreeburn,anddeathdecrease,respectively.Asensitivityanalysisrevealedburn,second-degreeburn,anddeathdecrease,respectively.Asensitivityanalysisrevealedthat at the initial heat flux and closer distance of 5m to 10m from the flame radius atthat at the initial heat flux and closer distance of 5m to 10m from the flame radius atthepointof theaccident, thedeathrate, firstdegree,andsecond-degreeburns increasethepointof theaccident, thedeathrate, firstdegree,andsecond-degreeburns increasesignificantly.Therefore,installingasafetysystemandbestpracticesthatwillmitigatethesesignificantly.Therefore,installingasafetysystemandbestpracticesthatwillmitigatetheseriskstoaslowasreasonablypossibleshouldbeincorporatedintothesystemdesign.riskstoaslowasreasonablypossibleshouldbeincorporatedintothesystemdesign.

KeywordsKeywords

LNGCarriers,Risk,Harbor,Fire,Explosion,Accidents.LNGCarriers,Risk,Harbor,Fire,Explosion,Accidents.

ORIGINALRESEARCH(AR)Received: 08 October 202008 October 2020 Accepted: 17 November 202017 November 2020

To cite this article:Nwaoha,T.C.&Adumene,S.(2020).Risk-basedAnalysisofPressurizedVesselonLNGCarriersinHarbor.Journal of ETA Maritime Science,8(4),242-251.To link to this article: https://dx.doi.org/10.5505/jems.2020.89266

1. IntroductionThe oil and gas industries store largeThe oil and gas industries store large

volumes of flammable and hazardousvolumes of flammable and hazardouschemicals in tanks, including LNG.chemicals in tanks, including LNG.Hydrocarbon products are highly volatile.Hydrocarbon products are highly volatile.Once there is any fuel-air mixture in orOnce there is any fuel-air mixture in oraround the storage tank, ignition occurs,around the storage tank, ignition occurs,which results in a fire and explosionwhich results in a fire and explosionaccident.Researchhasshownthatmostofaccident.Researchhasshownthatmostof

these accidents occurred during cleaning,these accidents occurred during cleaning,storage, maintenance, anti-rusting, spray-storage, maintenance, anti-rusting, spray-painting,welding,loading,unloadingwork,painting,welding,loading,unloadingwork,etc., [1]. Such exercises have resulted inetc., [1]. Such exercises have resulted insevere fire and explosion accidents withsevere fire and explosion accidents withseveral global consequences [2, 3]. Otherseveral global consequences [2, 3]. Otherexamples where such activities resultedexamples where such activities resultedin fire and explosion accidents are thein fire and explosion accidents are theBayamonoil storage facility fire in PuertoBayamonoil storage facility fire in Puerto

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Rico [4], and the Indian Oil CorporationRico [4], and the Indian Oil CorporationLtd explosion accident [5]. SevereLtd explosion accident [5]. Severeenvironmental pollutions, casualties andenvironmental pollutions, casualties andeconomic losses have resulted from fireeconomic losses have resulted from fireandexplosionofstoredhydrocarbon.Thisandexplosionofstoredhydrocarbon.Thispoints to how safety-critical hydrocarbonpoints to how safety-critical hydrocarbonstoragesare.storagesare.

Hydrocarbon products, especially theHydrocarbon products, especially theLNG, have a high level of risk of fire andLNG, have a high level of risk of fire andexplosion. Therefore, it is imperative toexplosion. Therefore, it is imperative tostudyandanalyzetheriskandconsequencesstudyandanalyzetheriskandconsequencesof fire and explosion accidents in LNGof fire and explosion accidents in LNGstored vessels. This research's mainstored vessels. This research's mainobjective is to analyze the risk associatedobjective is to analyze the risk associatedwithLNGstoredinapressurizedtankinawithLNGstoredinapressurizedtankinaharbor and evaluate the consequences onharbor and evaluate the consequences onthepeopleandenvironment.Afireaccidentthepeopleandenvironment.Afireaccidentscenariowas considered in the study.Thescenariowas considered in the study.Theresearch analysis examined a pool fireresearch analysis examined a pool firecase study.Riskandconsequenceanalysiscase study.Riskandconsequenceanalysismodels were adopted to demonstrate themodels were adopted to demonstrate thecase study to assess the degree of impactcase study to assess the degree of impactor damage of the pressurized vessel's fireor damage of the pressurized vessel's fireandexplosion.Thisenablesthepredictionandexplosion.Thisenablesthepredictionofthefrequenciesofpossibleaccidentsandofthefrequenciesofpossibleaccidentsandthequantitativeassessmentofbothsocietalthequantitativeassessmentofbothsocietalriskandindividualrisk.riskandindividualrisk.

2. Review of Relevant Literature2.1. Risk Assessment and Methodology

Risk is a phenomenon that measuresRisk is a phenomenon that measuresthe impact of a hazardous event on thethe impact of a hazardous event on theenvironment, human or economic loss inenvironment, human or economic loss interms of the incident likelihood and theterms of the incident likelihood and themagnitude of the injury, damage, or lossmagnitude of the injury, damage, or loss[6].Similarly, riskcanbedefined in terms[6].Similarly, riskcanbedefined in termsof the combination of the probability ofof the combination of the probability ofa hazardous event and the consequencesa hazardous event and the consequencesof occurrence [7]. Risk analysis involvesof occurrence [7]. Risk analysis involvesrisk estimation, information integrationrisk estimation, information integrationabout scenarios from the estimatedabout scenarios from the estimatedrisk, frequencies of occurrence, andrisk, frequencies of occurrence, andconsequences[7].consequences[7].

Risk indices are being used byRisk indices are being used byresearchers to correlate the magnituderesearchers to correlate the magnitudeof the risk on people and facilities. Forof the risk on people and facilities. Forexample, a risk ranking matrix has beenexample, a risk ranking matrix has been

usedtoassessvariousrisklevelsregardingusedtoassessvariousrisklevelsregardingharm probability and severity categories.harm probability and severity categories.This is presented in the two-dimensionalThis is presented in the two-dimensionalframeworkforlikelihoodandconsequencesframeworkforlikelihoodandconsequences[8]. Based on this approach, the risk is[8]. Based on this approach, the risk ischaracterizedbycategorizingprobabilitiescharacterizedbycategorizingprobabilitiesandconsequencesonthematrixaxes.Riskandconsequencesonthematrixaxes.Riskeffectcategorizationmaybeindividualizedeffectcategorizationmaybeindividualizedorsocietal.Individualriskischaracterizedorsocietal.Individualriskischaracterizedbythelikelihoodofanindividualdeathperbythelikelihoodofanindividualdeathperyearfromanexposeddistancetothesourceyearfromanexposeddistancetothesourceofhazard[6].Itisalsoessentialtoevaluateofhazard[6].Itisalsoessentialtoevaluatethesocietalriskofpressurizedtankfireandthesocietalriskofpressurizedtankfireandexplosion, which defined the probabilityexplosion, which defined the probabilityof death of a group of people exposed toof death of a group of people exposed tohazardousevents[9].Itisquantifiedbasedhazardousevents[9].Itisquantifiedbasedon the number of persons involved inon the number of persons involved inthe accident. In multiple causality eventsthe accident. In multiple causality events(accidents), the frequency distribution is(accidents), the frequency distribution iscommonly represented on the cumulativecommonly represented on the cumulativefrequencyversusnumberof fatalitiesplotfrequencyversusnumberof fatalitiesplot(i.e.,theF-Ncurve)[9].(i.e.,theF-Ncurve)[9].

Societal risk effects are mostlySocietal risk effects are mostlypresentedusingaquantitativeapproachforpresentedusingaquantitativeapproachforthe hydrocarbon industries. Vulnerabilitythe hydrocarbon industries. Vulnerabilityrate describes the degree of exposedrate describes the degree of exposedthreat, the capability to suffer harm, andthreat, the capability to suffer harm, andthe extent to which various social groupsthe extent to which various social groupsare at risk [10]. In their research, Li et al.are at risk [10]. In their research, Li et al.[11] estimated the individual risk of a[11] estimated the individual risk of anaturalgaspipelinefailureunderpressure.naturalgaspipelinefailureunderpressure.The authors proposed the “exposure-The authors proposed the “exposure-sensitivity-resilience” framework tosensitivity-resilience” framework tocapture the social-ecological indicators ofcapture the social-ecological indicators ofthe associated risk of natural gas pipelinethe associated risk of natural gas pipelinehazards. However, to adequately capturehazards. However, to adequately capturethe risk indicators, CPS/AICHE [12]the risk indicators, CPS/AICHE [12]provides criteria for individual risk andprovides criteria for individual risk andsocietalriskestimationduetoexposuretosocietalriskestimationduetoexposuretoadverse/major accidents in the chemical,adverse/major accidents in the chemical,oil and gas industries. Fire and explosionoil and gas industries. Fire and explosionaccident analysis was presented by [1]accident analysis was presented by [1]for oil depots, and the result of the studyfor oil depots, and the result of the studyshowsthatmostof thecommonaccidentsshowsthatmostof thecommonaccidentsareduetothevaporcloudexplosion.Thisareduetothevaporcloudexplosion.Thisaccident type and itsmanagement shouldaccident type and itsmanagement shouldbe targeted by minimizing/controllingbe targeted by minimizing/controlling

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the predisposing causes. Rigas andthe predisposing causes. Rigas andSklavounos [13] investigated variousSklavounos [13] investigated variousaccident scenarios based on real data,accident scenarios based on real data,using quantitative statistical estimation.using quantitative statistical estimation.JianhuaandZhenghua [14]analyzed fireJianhuaandZhenghua [14]analyzed fireand explosion onboard LNG ships. Theyand explosion onboard LNG ships. Theyused the DOWChemical Exposure Indexused the DOWChemical Exposure Index(CEI) criteria, BLEVE model, and Vapor(CEI) criteria, BLEVE model, and VaporCloud Explosion (VCE) model to predictCloud Explosion (VCE) model to predictthe consequences of fireball withoutthe consequences of fireball withoutconsidering theprobability of impact onconsidering theprobability of impact ontheenvironment.Also,in[15],theauthorstheenvironment.Also,in[15],theauthorspresent a review of LNG application forpresent a review of LNG application forshipandlandtransportation,respectively.shipandlandtransportation,respectively.TheyfurtherexamineddifferentmethodsTheyfurtherexamineddifferentmethodsfor LNG based analysis, likely accident-for LNG based analysis, likely accident-prone operations, and the necessaryprone operations, and the necessaryprecaution during operation. To furtherprecaution during operation. To furtherexaminedtheeffectofLNGoperation,[16]examinedtheeffectofLNGoperation,[16]

considered the overpressure against theconsidered the overpressure against theaccident'sdistanceofimpactandthermalaccident'sdistanceofimpactandthermalintensity. Therefore, this work seeks tointensity. Therefore, this work seeks toanalyze pool fire explosion consequenceanalyze pool fire explosion consequenceusingtheBLEVEmodel,thermalradiationusingtheBLEVEmodel,thermalradiationmodel,andprobabilistic function(probitmodel,andprobabilistic function(probitfunction) for an LNG carrier at harbor.function) for an LNG carrier at harbor.This will help to reliably evaluate theThis will help to reliably evaluate theconsequences in terms of burns andconsequences in terms of burns anddeath.death.

3. MethodologyThe common modeling algorithm forThe common modeling algorithm for

consequenceanalysisisshowninFigure1consequenceanalysisisshowninFigure1[12].Themodelestimatestheimpactsof[12].Themodelestimatestheimpactsofflammableexplosionandreleaseof toxicflammableexplosionandreleaseof toxicmaterial due to the loss of containmentmaterial due to the loss of containmentor system failure on the environment,or system failure on the environment,human,andassetsnumerically.human,andassetsnumerically.

Figure 1. Logic Diagram for Consequence Models due to Releases of Volatile Hazardous Substances [12]

Nwaoha&Adumene/JEMS, 2020;8(4):242-251

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3.1. Individual and Societal Risk Analysis To model the individual risk, theTo model the individual risk, the

likelihoodofinjurytotheindividualatthelikelihoodofinjurytotheindividualattheperiod overwhich the injurymight occurperiod overwhich the injurymight occurneedtobeestimated[3].Thisisexpressedneedtobeestimated[3].Thisisexpressedintermsoftheexposedlikelihood,suchasintermsoftheexposedlikelihood,suchasdeathandisusuallyquantifiedasariskperdeathandisusuallyquantifiedasariskperyear[9],asshownbyequation(1).year[9],asshownbyequation(1).

For a geographical location definedby x,y within a period, t, the individualexposed risk can be estimated usingequation(2)[12]: n

IRx,y = ∑ IRx,y,i (2) i=1

where IRx,y describe the total numberof persons at risk (fatality) due tothe exposure for a given geographiclocation, while IRx,y,i is for an individualrisk of exposure (fatality) based on thecharacterized x, y geographical locationduetoahazardevent, i.Theupperboundndescribesthetotalnumberofindividualsexposedbasedontheaccidentalrelease.

The risk of individual exposure(fatality)due to ahazardevent, i, IRx,y,i, ismodeledusingequation(3)

IRx,y,i = fi Pfi(3)

wherefi describestherateofhazardeventi, outcome, Pfi indicates the likelihoodthat thehazard event i, the outcomewillbefatalfortheoperatingx, ycharacterizesgeographicallocation.

The rate fi of ahazardeventoutcomecanbeestimatedbyequation(4)

fi = Fi Poi,Poci (4)

where Fi describes the rate of occurrenceofthehazardousevent,withanassociated

outcome case i, while Poi, indicates thelikelihood that the hazard event occurswith the associated outcome case, i. Poci defines the likelihood of the hazardouseventoutcomecaseioccurrencedependingonthepriorcircumstanceoftheprecursorincident i and its corresponding outcomecase.

For societal risk analysis, therelationship that describes the rate ofhazardous exposures and the numberof people exposed due to the accidentalrelease need to be established [9]. Thesetwo measures are essential for a well-informedriskmitigation/reductioncriteriaadapted for facility operation assessingthebenefitsofriskreductionmeasuresoracceptabilitycriteriaforriskcriticalfacility.Equation(5)isusedtopredictsocietalrisk[9]:

Ni=∑Px,y Pf,i (5) x,y

where Ni describes the outcome of thehazardous event, i, (that is the numberof fatalities as a result of the hazardevent),Px,y indicatesthepopulationat thegeographical location that the hazardousevent occurs, and Pfi indicates thelikelihood that thehazardousevent i, theoutcomewill be fatal for the operating x, ycharacterizesthegeographicallocation.

3.2. Hazard Impact AssessmentThe complete risk assessment due toThe complete risk assessment due to

hazardous events involves predicting thehazardous events involves predicting thefatality likelihood at a given exposure.fatality likelihood at a given exposure.The fatality likelihood as a result of theThe fatality likelihood as a result of theexposuredeath is calculatedusingProbitexposuredeath is calculatedusingProbitFunction (see equation (6)) [17]. EffectFunction (see equation (6)) [17]. Effectassessmentmodelsareadoptedtomeasureassessmentmodelsareadoptedtomeasurethedegreeofimpactoftheexposure.Thethedegreeofimpactoftheexposure.Thehazard incident outcome can be due tohazard incident outcome can be due todifferentfactors,asreportedby[13].differentfactors,asreportedby[13].

(1)

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Pr = c1 + c2 InD(6)

where Pr represents the probit, C1 is amodel constant that is dependent on thetype of injury, C2 is also constant, whichdependsontheloadtype.D istheload.Aconversiontablefromprobittopercentagewas provided by [12]. For differenthydrocarbons,themodelingconstantsc1 , c2 areprovided[12].

3.3. Consequence Assessment This involves an analytical modelingThis involves an analytical modeling

tool to assess the hazard potential andtool to assess the hazard potential andsubsequently translate into potentialsubsequently translate into potentialconsequences(e.g.,harmtopeople,pollutionconsequences(e.g.,harmtopeople,pollutiontotheenvironment,ordamagetotheasset).totheenvironment,ordamagetotheasset).To calculate the number of burns due toTo calculate the number of burns due toexposureorfatality,thethermaldoseoughtexposureorfatality,thethermaldoseoughttobequantified.Mathematically,thethermaltobequantified.Mathematically,thethermaldose is expressed in term of the exposuredose is expressed in term of the exposuretime and the heat flux as presented bytime and the heat flux as presented byequation(7)[18]:equation(7)[18]:

D = teff (q')4/3 (7)

q'=calculatedheatfluxinW/m²

teff = the effective exposure time of apersontoheatfluxin(seconds)

Forafirepooldevelopedinanareawherethepopulationishigh,thatisabout1personper20m²(inthewholearea),theprobabilityofinjury(firstorsecond-degreeburns)anddeath in 30m from the flame’s surface intermsofthenumberofthepersonswithfirstandsecond-degreeburns,andfatalitywillbecalculatedbyequation(10).

For thecase study, theheat fluxwillbecalculated as q'=26.964e-⁰⁰²³⁸x³⁰= 13.2KW/m²for30m.ForU=4m/s,Xo=138.42m(at138.4m,q'=1kW/m²)andr=30m.Theexposuretimewascalculatedas:

(8)

where;tr =person'sresponsetimein(s)Xo = is the distance between the flame'ssurfaceandthepositionwheretheintensityof theheat flux is lower than1kW/m² in(m)r = the distance of the person from thesurfaceoftheflamein(m)u=theescapevelocityin(m/s)

Thethermalradiationdosewascalculated“as” D = 32.11×(13.204)4/3 = 10.02×106 W4/3sm-8/3

3.3.1. The Probability of Death or InjuryThe number of fatalities or injuredThe number of fatalities or injured

personsduetoexposurecouldbepredictedpersonsduetoexposurecouldbepredictedbased on the Probit function. The Probitbased on the Probit function. The Probitfunctioniswidelyemployedduetoitsbroadfunctioniswidelyemployedduetoitsbroadapplicability in assessing the risk involvedapplicability in assessing the risk involvedinfireaccidents.Theprobabilityofdeathorinfireaccidents.Theprobabilityofdeathorinjury(P),becauseofaspecificthermaldoseinjury(P),becauseofaspecificthermaldoseisgivenbyequation(9):isgivenbyequation(9):

(9)

4. Results and DiscussionThisresearchassessestherisk involvedThisresearchassessestherisk involved

ifapoolfireshouldoccurinanLNGstorageifapoolfireshouldoccurinanLNGstoragetankonanLNGcarrierinharbor.AcasestudytankonanLNGcarrierinharbor.Acasestudydataas recorded in [18]wasadoptedwithdataas recorded in [18]wasadoptedwiththefollowingasinputparameters:“Boilingthefollowingasinputparameters:“Boilingtemperature,Ttemperature,Tbb=423k;HeatofCombustion,=423k;HeatofCombustion,∆Hc = 45,000KJ/Kg; Heat of Vaporization,∆Hc = 45,000KJ/Kg; Heat of Vaporization,∆Hv=370KJ/Kg;Specificheatcapacity,C�=∆Hv=370KJ/Kg;Specificheatcapacity,C�=2.21KJ/Kgk.Ambienttemperature,T2.21KJ/Kgk.Ambienttemperature,Taa=298=298k;Sootsurface-emittingpower,SEPsoot=20k;Sootsurface-emittingpower,SEPsoot=20KW/m²;Windvelocity,uw=5m/s;Densityofair,KW/m²;Windvelocity,uw=5m/s;Densityofair,ƿƿairair=1.21Kg/m³;Viscosityofair,=1.21Kg/m³;Viscosityofair,ηηairair=16.7μPas,=16.7μPas,


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Saturationwatervapourpressure,PSaturationwatervapourpressure,Pww=2320=2320PPaa;Relativehumidity,RH=0.7”;Relativehumidity,RH=0.7”

For this research,For this research, Fk value of 0.40was value of 0.40waschosen to account for its influence in thechosen to account for its influence in theprobability estimation. The coefficientsprobability estimation. The coefficientsC1andandC2havevaluesdependingonthedeathhavevaluesdependingonthedeathand degree of burn. The values of theseand degree of burn. The values of thesecoefficientscanbeobtainedfromTable1.coefficientscanbeobtainedfromTable1.

Table 1. Coefficients c1 and c2 [12]

Effect c1 c2

1st degree burn -39.83 3.0186

2nd degree burn -43.14 3.0186

Deaths -36.38 2.56

The probit function for the 1st degreeburnisgivenasfollows: Pr =-39.83+3.0186ln(10.02×10⁶) Pr =8.83

Theprobabilityof1stdegreeburnsatr=30miscalculatedas:

The probit function for the 2nddegreeburnisgivenasfollows: Pr =-43.14+3.0186ln(10.02×10⁶) Pr =5.5212

Theprobabilityof2nddegreeburnsatr=30miscalculatedas:

Theprobitfunctionfordeathsisgivenas: Pr =-36.38+2.56ln(10.02×10⁶) Pr =4.887

Theprobabilityofdeathsatr=30miscalculatedas:

The probabilities of 1st, 2nd degreeburns,anddeathsare0.3999,0.2794,and0.1822. The predicted impact at varyingdistance from the center of the flame isshowninTable2andFigure2.

Figure 2. Predicted Impact at Varying Distance from Center of Flame

The result shown in Figure 2, givesThe result shown in Figure 2, givesthe probability of impactwith respect tothe probability of impactwith respect tothetimeofexposuretothermalradiationthetimeofexposuretothermalradiationdoseduringfireaccident.Itshowsthatthedoseduringfireaccident.Itshowsthattheprobabilityofburnordeathincreasewithprobabilityofburnordeathincreasewiththe time of exposure. This indicates thatthe time of exposure. This indicates thatas the person’s duration of exposure toas the person’s duration of exposure tothe thermal radiation dose increases, thethe thermal radiation dose increases, thelikelihoodofimpactincreasesaccordingly.likelihoodofimpactincreasesaccordingly.However,forthe1stdegreeburn,thereisHowever,forthe1stdegreeburn,thereisanasymptoticcharacteristicasthetimeofanasymptoticcharacteristicasthetimeofexposureincreases,asshown.exposureincreases,asshown.

P=0.3999

P=0.2794

P=0.1822

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Figure 3. Thermal Radiation Dose-effect Against Flame Radius Distance

Table 2. Predicted Probability of Burns and Death at Varying Distances from the Flame and Exposed Hours

Distance from

Flame (m)

Exposed Time (s)

Thermal Radiation

Dose(W4/3 sm-8/3)

Probit 1st

degree burn

Probit 2nd

degree burn

Probit Death

Probability 1st

Degree Burn

Probability 2nd Degree

Burn

Probability of Death

15.00 35.85 11183757.33 9.16180 5.85180 5.16873 0.39999 0.32113 0.22680

30.00 32.10 10013908.24 8.82828 5.51828 4.88588 0.39997 0.27915 0.18183

45.00 28.35 8844059.14 8.45328 5.14328 4.56786 0.39989 0.22279 0.13313

60.00 24.60 7674210.05 8.02500 4.71500 4.20464 0.39950 0.15513 0.08528

79.00 19.85 6192401.19 7.37738 4.06738 3.65541 0.39651 0.07020 0.03575

90.00 17.10 5334511.86 6.92723 3.61723 3.27365 0.38921 0.03335 0.01686

105.00 13.35 4164662.77 6.17994 2.86994 2.63989 0.35240 0.00663 0.00365

120.00 9.60 2994813.68 5.18455 1.87455 1.79572 0.22928 0.00036 0.00027

The result shows that the probabilityof burn and death increases with therateofexposuretofireorexplosion.Thisimplies that an increase in the exposuretime increases the degree of burn on theindividual. Also, as the distance from theflame center increases, the probabilityof impact gradually decreases, as shownin Table 2. Figure 3 shows that thethermal radiation dose-effect decreasescorrespondingly at the farther distancefrom the radius of the flame. Hence,critical firework or accident causative

factors should be monitored in case ofmaintenancework.

4.1. The Total Number of Victims in the Pool Fire Accident

Having calculated the probabilitiesHaving calculated the probabilitiesof burns (whether 1st or 2nd degrees),of burns (whether 1st or 2nd degrees),equation (10) is used to calculate theequation (10) is used to calculate thenumber of victims who died and/ornumber of victims who died and/orsustained the two degrees of burns, assustained the two degrees of burns, asmentioned.mentioned.

∞∞N=(NoπR²)+∫P No 2πrdr(10) R

No -thenumberofpersons/m²R-radiusofthefire

Thefirsttermintheexpressionusedtopredict the number of fatalitywithin thefireradius,andthesecondterm(includingthe corresponding probit function fordeath) is used to estimate the numberof deaths outside the fire flame radius.Calculations of the number of victimswho suffered1st or 2nd degree burns arecalculated using the second term (withtheirappropriateprobitfunctions).


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Giventhatthepopulationdensityattheterminal is 1 person per 30m², implyingthatNois0.033persons/m²andtheradiusofthepetrolpoolcalculatedas21.22m,thenumber of deaths inside the radius of thefireiscalculatedas:

N = NoπR²=0.033×3.142×(21.22)²N=46.69≈47workers

Calculating the number of deathsoutside the fire radius and victims with1st and 2nd degrees of injury requires aprobability relation expressed in termsofr, thedistancefromtheflame’ssurfaceto the farthest point in the area underconsideration (30m). Thus, a generalexpressionforthermaldoseDisobtainedasfollows:

D=(3202.4603+20.215r)e-⁰.⁰³¹⁷³³r(11)

Appropriate probability expressionsare then obtained that incorporatecorresponding probit function expressionswith appropriate C1 andand C2 values. Theintegralsbasedonequation(10) isusedtopredictthenumberofdeathasshown:

Thenumberofdeathsis: ∞∞

N=0.04147∫r[1+erf(-29.26+1.810ln 21.22

((3202.4603+20.215r) e-⁰.⁰³¹⁷³³r))]dr

The number of victims who sustained1stdegreeburnsis:

∞∞N=0.04147∫r[1+erf(-31.70+2.134ln

21.22

((3202.4603+20.215r) e-⁰.⁰³¹⁷³³r))]dr

The number of victims who sustained2nddegreeburnsis:

∞∞N=0.04147∫r[1+erf(-34.04+2.134ln

21.22

((3202.4603+20.215r) e-⁰.⁰³¹⁷³³r))]dr

The approximate solutions of theintegrals as shown above for the accidentscenario,revealsthefollowing:

•66personnelwillsuffer1stdegreeburns•14personnelwillsuffer2nddegreeburns•85deaths (within fire radius,1st and2nddegreeburnsinclusive)

4.2. Risk EstimationThe risk associatedwith the pool fireThe risk associatedwith the pool fire

accidentiscalculatedastheproductoftheaccidentiscalculatedastheproductoftherateofoccurrenceofthepoolfireandtherateofoccurrenceofthepoolfireandtheconsequenceofthefireonworkersattheconsequenceofthefireonworkersattheterminal. Thus, the risk associated withterminal. Thus, the risk associated witheachfireconsequenceisshownbelow:eachfireconsequenceisshownbelow:

•Riskofvictimswhosustained1st degreeburn=1.9×10-⁶×66=1.254*10-⁴=0.0001254victims/kmyears•Riskofvictimswhosustained2nddegreeburn=1.9×10-⁶×14=2.66*10-⁵=2.66×10-⁵victims/kmyears•Riskofdeaths=1.9×10-⁶×85=1.615*10-⁴=0.0001615victims/kmyears

5. ConclusionThe adopted methodology for poolThe adopted methodology for pool

fire analysis is advantageous due to itsfire analysis is advantageous due to itsability to evaluate the probability of theability to evaluate the probability of thetop event (release rate of LNG in thetop event (release rate of LNG in thestoragetankbasedonthiscasestudy).Thestoragetankbasedonthiscasestudy).Thecombination of several root causes, suchcombination of several root causes, suchasleaks,overpressure,ignition,spark,andasleaks,overpressure,ignition,spark,andthepossibleconsequencesofthisrelease,thepossibleconsequencesofthisrelease,suchasnumbersofburnsanddeath,weresuchasnumbersofburnsanddeath,wereevaluated. The LNG release ratemay beevaluated. The LNG release ratemay beduetodifferentrootcausessinceeveryoneduetodifferentrootcausessinceeveryonecanleadtothereleaseofLNG.TheresearchcanleadtothereleaseofLNG.Theresearchconclusivelyshowsthat:conclusivelyshowsthat:

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• The release rate of 1.712E-02 per1000kmyearsfortheleakwasobserved.

• The probabilities evaluated for 1st and2nd degree burns and fatality at 30mfrom the flame radiusweredefinedbythefiresphereforthecasestudy.

• Forthesameheatflux,thefire'simpactdecreases accordingly based on thedistancefromthefireflameradius.

• The sensitivity analysis (Table 2)shows the predicted save zone fromthe incident's point by varying theflame radius and the exposure time.This provides a technical guide onthe appropriate safety barrier/actionneededforsafemaintenanceoperations.

• The number of deaths, first-degreeburn, and second-degree burn at theflame radius range of 5-10m decreaserespectivelywithrespecttothethermaldose. This indicated that the workerin theharborwithin the spherewouldsuffer the greatest damage (mostlydeath).

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[10] DeSouzaPorto,M.F.andDeFreitas,C. M. (2003). Vulnerability andindustrialhazardsinindustrializingcountries: An integrative approach.Futures, 35(7), 717–736. https://d o i . o r g / 1 0 . 1 0 1 6 / S 0 0 1 6 -3287(03)00024-7.


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[11] Li,Y.,Zhang,X.,Zhao,X.,Ma,S.,Cao,H. and Cao, J. (2016). Assessingspatial vulnerability from rapidurbanization to inform coastalurban regional planning. Ocean and Coastal Management. 123,53–65. https://doi.org/10.1016/j.ocecoaman.2016.01.010.

[12] CPS/AIChE. (1995). Center for Chemical Process Safety. Retrievedfrom https://www.aiche.org/ccps/resources/glossary/process-safety-glossary

[13] Rigas, F. and Sklavounos, S.(2004). Major hazards analysis forpopulations adjacent to chemicalstorage facilities.Process Safety and Environmental Protection, 82(5 B),341–351. https://doi.org/10.1205/psep.82.5.341.44189.

[14] Jianhua,L.andZhenghua,H.(2012).Fireandexplosion riskanalysisandevaluation for LNG ships. Procedia Engineering, 45, 70–76. https://doi.org/10.1016/j.proeng.2012.08.123.

[15] Banaszkiewicz, et.al. (2020).Liquefied Natural Gas in MobileApplications—Opportunities andChallenges.Energies,13,5673.https://doi.org/10.3390/en13215673.h t t p s : / / d o i . o r g / 1 0 . 3 3 9 0 /en13215673.

[16]Malviya,K.R.andRushaid,M.(2018).ConsequenceanalysisofLPGstoragetank.Materials Today: Proceedings, 5(2), 4359–4367. https://doi.org/10.1016/j.matpr.2017.12.003.

[17] Crowl,D.A.andLouvar, J.A.(2002).Chemical process safety: fundamentals with applications. PearsonEducation.

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JournalofETAMaritimeScienceBolatet.al /JEMS, 2020;8(4):252-273

10.5505/jems.2020.64426

Weighting Key Factors for Port Congestion by AHP Method

Pelin BOLAT1, Gizem KAYİŞOĞLU2, Emine GÜNEŞ3, Furkan Eyüp KIZILAY4, Soysal ÖZSÖĞÜT5

1,2,5IstanbulTechnicalUniversity,MaritimeFaculty,Turkey3BandirmaOnyediEylulUniversity,MaritimeFaculty,Turkey

4PiriReisVocationalandTechnicalAnatolianHighSchool,MaritimeArea,[email protected];ORCIDID:https://orcid.org/[email protected];ORCIDID:https://orcid.org/0000-0003-2730-9780

[email protected];ORCIDID:https://orcid.org/[email protected];ORCIDID:https://orcid.org/0000-0002-0576-534X

[email protected];ORCIDID:https://orcid.org/0000-0002-2553-125XCorrespondingAuthor:EmineGÜNEŞ

ABSTRACT

Portcongestionisoneofthemostimportantfactorsformeasuringportperformanceanda critical problem that affects seaports' performance, productivity and efficiency levelsaswell. Determining themost important factors affecting the port congestion in detailcontributestotheeconomicandsocialgrowthoftheports.Thispapermakesanefforttocontributetotheexistingliteraturebydeterminingimportanceweightsoffactorsleadingtoportcongestionastheuniquestudyonthematter.Therefore,itisaimedtoidentifythemostimportantfactorsonportcongestionaccordingtotheportstatecontrol, flagstatecontrolandindependentsurveyors’pointsofviews.Forthispurpose,aliteratureresearchwas conducted on the factors causing port congestion and experts on the field wereconsulted.ThenthecollecteddatawereclassifiedinalistandthedeterminedfactorshavebeenorderedwithAnalyticHierarchyProcessmethodbyexperts.Theimportanceweightsofthefactorshavebeenidentifiedandthemostsignificantfactorsforportcongestionhavebeenobtainedwiththepairwisecomparisonofthecriteria.Accordingtotheresults,itcanbeargued that themost importantmain factors forport congestionaredocumentationprocedures,portoperationandmanagement,shiptrafficinputs,portstructureandstrategyandgovernmentrelations,respectively.

Keywords

PortCongestion,AHP,CriteriaforPortCongestion

ORIGINALRESEARCH(AR)Received: 08 Seprember 2020 Accepted: 01 December 2020

To cite this article:Bolat,P.,Kayişoğlu,G.,Güneş,E.,Kızılay,F.E.,&Özsöğüt,S. (2020).WeightingKeyFactorsforPortCongestionbyAHPMethod.Journal of ETA Maritime Science,8(4),252-273.To link to this article: https://dx.doi.org/10.5505/jems.2020.64426

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1. IntroductionCommercial shipping is a key factor

in international goods transportation,therefore international trade depends onshippingbymeansofmovingcargofromoneregion to another. For international trade,new shipping demands to accommodatedifferent types of cargoes and new shipdesigns for a faster long distance freighttransport, ensuring a minimum cost perlong tonnage. [1]. It is also compatiblewith the development of seaports forincreased rate of international trade andtransportation, for efficient loading andunloadingofcargofromships.Atthispoint,ports must be operated efficiently, withenoughspacetoaccommodateberths,withmoderntechnologicaltransportequipmentand ships, sufficient skilled manpower,efficient handling of documentationprocess and, storage facilities and goodinfrastructure[2].Forinstance,Tongozo[3]statesthattheefficiencyofaportiscrucialforachievingcompetitiveadvantagesanditisexpressedthroughtheprovisionofgoodservices that areexpectedby shipownersandcustomers.AccordingtoNilsson[4],oneof themost important factors to considerformeasuringportperformanceisalsoportcongestion.

Fromthispointofview,itcanbesaidthatportcongestionisacriticalproblem,whichaffectsseaports'performance,productivityand efficiency levels. It is a fact that shipscreate congestionat theport entrancesbyusingalotoftimeinthechannelorduringberthing. The ships wait in the anchoragearea and line up for berthing to the port.The waiting time is calculated using theservicetimeoftheships.Ships'servicetimeisawaytomeasuretheefficiencyofports.Thecongestionisafactthatbecauseofthecargoesreachuptoquantitiesthataremuchmore than theport'shandlingandstoragecapacityaswellascapacityoftheallocatedspacetheycanbemoved.

Various factors that may cause port

congestion have been specified by moststudies.Thesearelistedingeneralheadingsas follows [5]: inefficient and old portinfrastructure, inconsistent governments'policies, failure to meet technologicaltrends in globalization and manpowerproblemsofsomeports,excessivedemandfor supply of port services. When thefactors that cause port congestion areexamined in detail, the following itemsare encountered[6]:reserving the port orterminal beyond its capacity, industrialactions or strikes, pandemics such asCOVID-19, lack of allocated space orstockpile, delays due to bad weatherresulting in ships lining up outside, war,limited port access, lack of port handlingequipment, slow productivity, hinterlandconnections and location of the port. Portcongestion, caused by a variety of factorsmayalsoaddsomeextracoststothesupplychain,suchasinventorycostsandexorbitantdemurragecosts.JanssonandShneerson[7]stated that the effect of port congestionon economic as follows: 'Congestion costsexist if the other short-run costs of portoperations, per unit of throughput, are anincreasing function of the actual capacityutilization. When actual demand exceedscapacity, extreme congestion costs arise,whichwecallqueuingcosts.Whenaportissaidtobecongested,itiscommonlymeantthatshipsarequeuing,waiting toobtainaberth'.

Considering the effects of the portcongestionproblemonaportasmentionedabove,inordertoanyportnottoencounterwiththisproblem,modernportsmustfocuson investing in modern equipment andotherinfrastructurestodevelopandexpandthe port area for compensating increasedcargo volume of ships. On the other hand,bydeterminingthemostimportantfactorsvia considering the factors affecting thecongestionoftheportindetail,contributesto the economic and social growth of theports.

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In this context, it is aimed to identifymost important factorsoncongestionofaport,accordingtotheportstatecontrol,flagstate control, and independent surveyors’points of views. For this purpose, firstfactors causing port congestion wereresearched from the literature, expertswereconsultedandthecollecteddatawereclassified in a list. Then, the determinedfactors have been ordered by experts,in accordance with Analytic HierarchyProcess(AHP)method.Aspartofthescopeofthisstudy,expertshavebeendesignatedas independent, port state and flag statesurveyors who have been empowered tocarryoutvariousinspectionsinaccordancewithnationalandinternationalconventionsand rules for ships approaching ports. Bythe pairwise comparison of criteria, theimportance weights of the factors havebeenidentifiedviatheAHPmethodandthemostsignificantfactorsforportcongestionhavebeenobtained.

For this purpose, factors causing portcongestion were researched from theliterature, experts were consulted andthe collected data were classified in alist. Therefore, the ports that have portcongestion problems gain an insight intowhichareatheyshouldimproveandaportinvestorcanalsorefertothesefactorswhencreatingaportproject.

2. Literature ReviewCongestionofports,asoneofthemajor

reasonofdisruptionstomaritimetransportoperation networks, results infertility andincreasethecostsof logisticsandtrade[2][8].

Although port congestion is definedas “waiting for berthing” in literature,additional concerns are possible whenmentioned port congestion by separatingas“majorcategoriesofcongestion”. Theseare; ship berth congestion, ship workcongestion,vehiclegatecongestion,vehiclework congestion, ship entry/exit route

congestion, and additionally cargo stackcongestion[5][9].

Considering port selection, both portcongestion and distance of navigation aremajordeterminantsforshippers[10].Ontheotherhand,Nilsson[4]statesthatnotonlydistanceofnavigationandportcongestionbutalsodistanceoftheshipperfromport,distancefromoriginandtodestinationandshipping line’s fleet size affects shippers’port choice. In another study, Lirn et al[11] examines the transshipment portselectionbyglobalcarriesbyAHPmethodto explore factors affect port selectioncriteriaandadvicesinstrategicperspectivetotransshipmentmarket.

In the sense of the containerports, continuous growth in containertransportation by vessels which putsindustry under pressure results withcongestions at port land entries andthat situation affects port productivitynegatively [6][12]. Port productivity incontainer terminals has direct influenceonportefficiencyandnotonlydependsonpsychical factors but also organizationalfactors[13].

Ontheotherhand,consideringtheissueofportcongestion,theuniquenatureoftheport,whichdiffersfromporttoport,shouldbe taken into account [9]. Several studieshavebeenmaderegardingportcongestionboth for optimization to increase portefficiency and analysis of policies aboutincrease of psychical structures, capacityand modernization. Oyatoye et al [14]highlight the importance of queuingtheory to the port congestion problem toincrease the sustainable development ofNigerianports.The studydetermines thatthenumberofberthsintheportofNigeriawassufficient for the trafficdensityof theships, includes the content analysis of theinterview with the stakeholders at theport and other factors that caused portcongestion. Also, policy recommendationsare made for a cost-effective and more

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attractive solution that also includes therapid return of ships in Nigerian port.Maneno [2] evaluates factors affectingportcongestionforPortofDaresSalaam/Tanzania.Forthatpurpose,Manenomakesaliteraturereviewandlistthefactorsofportcongestion, prepares a questionnaire andmakes a survey with stakeholders. In theresult, Maneno makes recommendationsboth psychical and organizational forsolutionofportcongestionprobleminPortof Dar es Salaam. In another study, landsidecongestionoftrafficforTheConsorzioNapoletano Terminal Containers (CO.NA.TE.CO.), located in the Port of Naples/ Italy analyzedwith Queuing theory andaccording to results offer solutions [15].As an alternative truck chassis exchangeterminaltoincreasetruckflowincontainerterminals[16].Anotheroptimizationstudyby Jin et al [17] puts another solutionalternative to berth congestion problemby column generation based approach tooptimizecontainerflowbyberthandyarddesign.

Even if several studiesmade regardingmitigate port congestion and it’s factorsbyoptimizationormathematicalmethods,thebestwayforremovingportcongestionis using modern equipment, expandingterminal size and capacities, which isinevitableforsomecountriestokeeptheirrole upright in maritime transportation,such as Canada [2][18][19]. Besides, forseveral countries, port congestion is amajorproblemandneeds tobeorganizedboth by governments and private sectorfor best results. Cullinane and Song [20]evaluateTheRepublicofKoreaandshowingas an example to developing countries instrategic planning. Potgieter [21] focuseson Cape Town Container Terminal anduses both qualitative and quantitativemethods for identification, analyzeevaluation and recommendations formitigation of port congestion factors. Fanet al [22] investigates congestionproblem

in container terminalsofUSAwith spatialcompetition and explores the negativeresults of the consequences. Emecen[23]comparessupplyanddemand inMarmaraportsbyqueuingtheory.Thestudyresultsthe current capacity is enough to handleship flow and gives recommendations incase of increase on demand. Zorlu [24]examinesportclutter inTurkey,highlightsthe importance and magnitude of TheGulf of İzmit area ports and recommendsbuildingabig transitport to thearea.Yeoetal[25]analyzetheeffectsofvesseltrafficconditions in 2011 for Busan and assessthepotential formarine traffic congestionusing the AWE-SIM simulation program.According to the results, enlarging of thesuperstructure of the container terminals,the reallocation of terminal functions innumber two pier, and the eliminationof anchorage are the emergent tasks tominimize possible congestion for Busan.AbuAlhaoletal[26]presentthreemaritimeport congestion indicators mined usingstaticanddynamicmessagesofAutomaticIdentification System. The consideredindicators are time of service criticality,spatial density, and, spatial complexity.They proposed that these indicators canbe used by port authorities and othermaritimestakeholderstopredictforfuturecongestion levels that can be correlatedto high demand, weather, or a suddencollapseincapacityduetosabotage,strike,orotherdisruptiveevents.Saeedetal[27]explain governance strategies that severalplayers in themaritime field can adopt todecrease port congestion by developinga conceptual model. For examining portcongestion decrease from a governanceperspective, they use frequency, anduncertainty,assetspecificity,andprevailinthemaritimesectorasthreecharacteristicsof transaction cost analysis. Accordingto their study, the main reasons for portcongestionarecausedbyothermembersoftheportsupplychain.Thesefactorscanbe

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frequencyofcargo(megavessels),and/orenvironmental uncertainty (for example,trucker strikes, bad weather). Neagoe etal [28] present a paper that highlights“howasupplychainperspectivedeployinginformation systems can improve portcongestion management by stimulatingcollaboration amongst multiple transportandterminaloperators”.Theystatethatoneof the reasonsof congestionmanagementsystems’ low solutionacceptancebecauseof the trucking industry. This is causedby lack of engagement from the port orterminal operators, inflexible systems totransporters’businessdemands,andone-sided benefits derived by the terminalfromthecongestionmanagementsystems.Li et al [29] present “a hybrid simulationmodelthatcombinestraffic-flowmodelingand discrete-event simulation for land-side port planning and evaluation oftraffic conditions for a number of what-if scenarios”. They show that problem ofport congestion is resulted from externalvehicles traveling in spaces with verylimited traffic regulation and complexityof heterogeneous closed-looped internalvehicles and the traffic interactionswith port operations such as loadingand unloading cargoes. Pruyn et al [30]introduce a study to predict port waitingtimes for Mormugoa, New Mangalore,Shanghai,andEsperanceportsbecauseofcongestion by using historical data from2012to2015intheMarkovchainanalysis.Theystatethatforecastingthewaitingtimein a port can enhance the planning andefficiencyofthetransportationofcargoes.

For summarizing the literature reviewregarding port congestion, Table 1 isintroduced.

The distinctive feature of this paperfrom theother studies in the literature isthe effort to gather all the studies on theport congestion and its factors in detail,specifically to prove which factors aremost important on port congestion. In

the literature there aren’t many studiesavailable that themost important factorson port congestion present via scientificanalysisclearly.

3. Methodology3.1. Analytic Hierarchy Process (AHP)

Analytic Hierarchy Process (AHP)represents the hierarchical structureof a system and is developed at first formilitary by Thomas Saaty in 1980 [31].Thehierarchy,whichisformedbyvariouslevels including decomposition of maingoaltoasetofclassandsubclass,andfinallevel,summarizesthefactorsaccordingtothegoalof thesystemas inFigure1.Theclassofthehierarchicalstructureisnamedas criteria or attribute and the sub classofthestructureiscalledassubcriteriaorsub attribute. If a multi criteria decisionmaking (MCDM) is the point in question,thealternativestakepartinthefinallevelof the hierarchical structure. AHP is thepopular method as the methodologicalproceduresinceitcanbeeasilyperformedwith multiple, objective programmingformulations via the interactive solutionprocess.Thebasisof themethodisbasedon pairwise comparison of criteria andalternativesbytheexperts[32].

Figure 1. Sample Hierarchical Structure for AHP

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Author Title of Study Methodology The Aim of The Study Findings or Suggestion

FadhiliHarubuManeno(2019)

Assessmentoffactorscausingportcongestion:acaseoftheportDaresSalaam

QuestionnairesandquantitativemethodsindatacollectionsPraxeologydesign

ThemainpurposeofthestudyistorevealthefactorscausingcongestioninDaresSalaamharborthroughasurveyforinvestigatingthechallengesfacedbyportstakeholdersandprovidingsolutionstothisproblem.

ThefindingsofthisstudyshowedthatDaresSalaamisfacedwithvariouschallengessuchasdocumentationprocedures,unskilledmanpower,poorpolicy,useofinformation,communicationandinformationsystems,inadequateequipment,bureaucracy,portinfrastructure,poormanagementplanning.

IbeawuchiC.Nze&ChinedumOnyemechi(2018)

PortcongestiondeterminantsandimpactsonlogisticsandsupplychainnetworkoffiveAfricanports

Thisanalyticaltooldiffersslightlyfromthecommonlyusedqueuingtheorymodel,whichmostlyaimstotakeintoaccountthearrivalandservicetimeofshipsandcargoesatports.

ThemainpurposeofthisstudyisdeterminetheeffectsofportcongestiononLogisticsandSupplychainaccordingtosomeSub-SaharanAfricanports.

ThefindingsoftheregressionanalysisrevealthatcongestioninAfricanportsisentirelyduetoplanning,regulation,capacity,efficiency,oracombinationofthese.

UsmanGidado(2015)

ConsequencesofPortCongestiononLogisticsandSupplyChaininAfricanPorts

Thisarticleexaminescommonportcongestionscenarios,theirextent,andthevariousfactorsthattriggercongestioninLagos,Durban,Mombasaports.

Thisarticleexaminesthecommonportcongestionscenarios,sizes,andvariousfactorsthattriggercongestionintheportsofLagos,Durban,MombasaandthecollectionportsoftheSuezCanal.

TheDurbanandPortSaidfacilitieshaveprovedtobethemostcongestion-resistantportsinAfrica,largelyduetotherobuststrategiesadoptedintheoperationaldistributionofportsandcargomanagement.

FıratBolat&NilGüler(2015)

HubportpotentialofMarmararegioninTurkeybynetwork-basedmodelling

Inthisstudy,network-basedhubportassessment(NHPA)modelisused.

ThemainpurposeofthisstudyistoevaluatewhethertheportregionsofAmbarlı,Gemlik,İstanbul,İzmitandTekirdağhavethepotentialtobecomeamainportusingtheNHPAmodel.

Asaresultoftheincreaseincontainerhandling,increasesinactivityandeconomiesofscalewerereflectedintheconnectivityindex.Asaresultoftheinstantandactiveuseofthisport,theconnectivityindexhasincreasedandthecollaborativeindexhasdecreased.

TCLirn,HAThanopoulou,MJBeynon&AKCBeresford(2004)

AnApplicationofAHPonTranshipmentPortSelection:AGlobalPerspective

ApproachAnAnalyticHierarchyProcess(AHP)

Thisstudyexaminesthedominantfactorsinfluencingshippers'portselectiondecisionsusingAnalyticalHierarchyProcess(AHP).

TheresultsoftheAHPanalysisrevealedthatbothglobalcontainercarriersandportserviceprovidershavesimilarperceptionoftheservicefeaturesarethemostimportantfortransferportselection.

HarieshManaadiar(2020)

PortCongestion–causes,consequencesandimpactonglobaltrade

- Inthisstudy,itisaimedtoexaminethePortCongestion-itscauses,consequencesanditsimpactonglobaltrade.

Globalizationhasledtocontainerization,leadingtoanincreaseinglobalcontainertrade,whichhasgrownbyanaverageof9.5%sincethe1980s.Between2000-2018,theglobalcontainerportbusinessvolumeincreasedby254%.

Table 1. Summary of Literature Review

./..

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ChangQianGuan(2009)

Analysisofmarinecontainerterminalgatecongestion,truckwaitingcost,andsystemoptimization

1)dataanalysis2)fieldobservations,3)developmentofthequeuingmodel,4)modelvalidationandverification,5)syntheticanalysis,6)sensitivityanalysis,and7)gatecongestionmitigationalternatives.

TheaimofthisthesisistoanalyzetheMCTdoorsystemstudytomeasuretheeconomiccostsofthegatecongestionanddevelopamodeltomeasure,providealternativestooptimizedooroperationandreducethegatecongestioninNewYorkHarboristoinvestigatethealternatives.

Thisstudyprovidesacomprehensiveanalysisofthisissue,includingmeasuringthecostofcongestionandoffersseveralalternativestoreducecongestion.

E.OOyatoyeS.O.Adebiyi,J.COkoyeeB.BAmole,(2011)

ApplicationofqueueingtheorytoportcongestionprobleminNigeria

Thequeuemodelhasbeenappliedtothearrivalandservicemodelthatcausescongestionproblemsandprovidessolutionstoproblemareas.

ThisarticleaimstoexaminetheproblemofportcongestionwithqueuingtheoryinordertoincreasethesustainabledevelopmentofNigerianports.

Itisrecommendedthatconcessionairesattheportsbeauthorizedtostartextensiveinfrastructuredevelopmentandcapacitybuilding.

I.M.Veloqui,M.M.Turias,M.J.Cerbán,G.GonzálezBuiza,andJ.Beltrán(2014)

SimulatingtheLandsideCongestioninaContainerTerminal.TheExperienceofthePortofNaples(Italy)

Aqueuingmodelhasbeendevelopedtoanalyzethecongestionproblem.

ThisstudyaimstoexaminethereasonswhyConsorzioNapoletanoTerminalContainers(CO.NA.TE.CO.)inthePortofNaplesareconstantlysubjecttotrafficcongestion.

Thestudyshowsthatthesolutionmusttakeintoaccountthereductioninservicetimeattheaccessgateandinthefieldsimultaneously.

SamuelMondayNyema(2014)

Factorsinfluencingcontainerterminalsefficiency:acasestudyofmombasaentryport

DataEnvelopmentAnalysis(DEA)applicationhasbeenusedintheportindustrytomeasureportefficiencyandperformance.

ThemainpurposeofthestudyistoevaluatethefactorsaffectingtheefficiencyofcontainerterminalsintheMaritimeindustrywiththecasestudyofMombasaPortofEntryintheRepublicofKenya.

Moreresearchshouldbedoneinthefollowingareas:MaritimeFreightTransportLogisticsContainerTerminalsContainerSecurityPolicyImplementationandRoleofGlobalSupplyChainSecurity.

R.Dekker,S.VanDerHeide,E.VanAsperen,andP.Ypsilantis(2013)

Achassisexchangeterminaltoreducetruckcongestionatcontainerterminals

ThetypicaloperationofacontainerterminalandtheCET@solutionareoutlined,andtheireffectsaremeasuredintermsofbothcost,environmentalandefficiency.

Inthisarticle,achassisexchangesterminalconcepttoreducecongestionispresentedandanalyzed.

Becausethereisnorealhandlingbottleneck,italsoremovestheuncertaintyofretrievingcontainers,allowingtruckingcompaniestoschedulemultipletripsfromcustomerstoCETeachday.

R.Dekker,S.VanDerHeide,E.VanAsperen,andP.Ypsilantis(2013)

Achassisexchangeterminaltoreducetruckcongestionatcontainerterminals

ThetypicaloperationofacontainerterminalandtheCET@solutionareoutlined,andtheireffectsaremeasuredintermsofbothcost,environmentalandefficiency.

Inthisarticle,achassisexchangesterminalconcepttoreducecongestionispresentedandanalyzed.

Becausethereisnorealhandlingbottleneck,italsoremovestheuncertaintyofretrievingcontainers,allowingtruckingcompaniestoschedulemultipletripsfromcustomerstoCETeachday.

Table 1. Summary of Literature Review (Cont')

./..

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J.G.Jin,D.H.Lee,andH.Hu(2015)

Tacticalberthandyardtemplatedesignatcontainertransshipmentterminals:Acolumngeneration-basedapproach

Asetspanningformulationhasbeendevelopedfortheberthandyardtemplatedesignproblem.Column-basedheuristicsaredevelopedandevaluatedwithcomputationalexperiments.

Thisarticleaddressestheproblemofberthingcongestionbypresentingaproactivemanagementstrategyfromaterminalperspectivethatadjustsships'callingschedulesothatitcanbalancethedistributionofworkloadonthedockside.

Computationalexperimentsonreal-worldtestsampleshavedemonstratedtheefficiencyandeffectivenessoftheproposedapproach.

G.Y.Ke,K.W.Li,andK.W.Hipel(2012)

AnintegratedmultiplecriteriapreferencerankingapproachtotheCanadianwestcoastportcongestionconflict

Inthestudy,aholisticconflictanalysisapproachthatincludestheAnalyticalHierarchyProcess(AHP)basedpreferencerankingmethodintheConflictResolutionGraphModel(GMCR)wasused.

ThisarticleexplorestheportcongestiondisputeonCanada'swestcoast.

ThestrategicanalysiscarriedoutinthisresearchsuggestspossibledecisionsthatCanadawillexpanditsportfacilitiesinvariouslocationsandencouragetraderstocontinuechoosingCanada'swestcoastasoneofthetradinggatewaystoNorthAmerica.

M.Mollaoğlu,U.Bucak,andH.Demirel(2019)

AQuantitativeAnalysisoftheFactorsThatMayCauseOccupationalAccidentsatPorts

TheFuzzyAnalyticalHierarchyProcess(FAHP)method

ThepurposeofthisstudyistodeterminetherisksthatcauseOccupationalHealthandSafety(OHS)violationsintheportareaandtorevealtheprominentrisksasaresultofexpertexaminations.

Thisstudyisthebasisforfurtherstudiestobecarriedouttounifytheprocessofseeingworkaccidentsintheportarea.

K.CullinaneandD.W.Song(2006)

ContainerterminalsinSouthKorea:problemsandpanaceas

DataEnvelopmentAnalysisorFrontierProductionmodels.

ThisarticleexaminestheextentofthecongestioninKoreanports,particularlyPusan,thecountry'slargestport;andnewportdevelopmentprogramsaimedatattractingprivateandforeignfunding.

Fromthisanalysis,astrategyforportdevelopmentindevelopingcountriescanbedrawn.

L.Potgieter(2016) Riskprofileofportcongestion:capetowncontainerterminalcasestudy

Thebowtiemethod,whichisthemostcommonmethod,isusedforthisstudy.

Inthisstudy,thetimingeffectandfrequencyoftheseasideandlandsideportcongestionexperiencedattheCapeTownContainerTerminaltodevelopthebasicriskprofilesofcurrentandfutureportcongestion.

Porttailbacksoutsidethelandsidecongestionandin2015proposedtoincludetheeffectoffurtherresearchshouldbedoneabouttruckban.

L.Fan,W.W.Wilson,andB.Dahl(2012)

Congestion,portexpansionandspatialcompetitionforUScontainerimports

Anintermodalnetworkflowmodelwasdevelopedandusedtoanalyzecongestioninthelogisticssystemforcontainerimport.

Thepurposeofthisarticle,spatialcompetitionofcontainerimportstotheUnitedStates,istoanalyzethecongestionandflow.

ThefindingsandresultsofthisstudyledtorecommendationsforfurtherresearchandrecommendationsforthePortofCapeTown,theshippingindustryasawhole.

Table 1. Summary of Literature Review (Cont')

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The purpose of the AHP is aimed toassign weights to tested factors withassessment of experts. Through thismethod,weightsareassignedtofactorstoserve two important purposes. First, thefactorsareprioritizedorrankedbywayofAHP, hence the key factors are identified.Ithelpstodevelopkeymeasuresorientedthegoal,especiallyintermsofcommercialenterprises. Second, by focusing on keymeasures, the business decision is givenmore accurate, the key information forcommercial operations is determinedmorecorrect,orthealternativemarketingstrategies are evaluated more accurate[33].

The steps of AHP that is used for this

Figure 2. Flow Diagram for AHP

paperareshownintheflowdiagramasinFigure2[34].

3.2. AHP Method for Port Congestion In this study, the AHP method is

used for determining key elements thataffect the port congestion, for taking theprecaution toward this problem, and fordeveloping new strategies in the matterof port congestion for port investment.In order to identify the most importantfactors for port congestion, the AHP ismost appropriate method. Since, it canassigntheweightstothefactorsthatcauseport congestion via pairwise comparisonbetweenthembytheexperts.ThefunctionofAHPispracticalforthesegoals.

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Relative Intensity Definition Explanation

1 EqualvalueTworequirementsareofequalvalue

3 Slightlymorevalue

Experienceslightlyfavorsonerequirementoveranother

5 Essentialorstrongvalue

Experiencestronglyfavorsonerequirementoveranother

7 Verystrongvalue

Arequirementisstronglyfavoredanditsdominanceisdemonstratedinpractice

9 Extremevalue

Theevidencefavoringoneoveranotherisofthehighestpossibleorderofaffirmation

2,4,6,8

Intermediatevaluesbetweentwoadjacentjudgments

Whencompromiseisneeded

1/3,1/5,1/7,1/9 Reciprocals

Reciprocalsforinversecomparison

Table 2. Saaty’s Scale for Pairwise Comparisons [31]

Size of matrix

(n)1 2 3 4 5 6 7 8 9 10 11 12

RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.58

Table 3. Random Index for AHP

3.2.1. Data CollectionAccording toAHP, formakingpairwise

comparison, first, experts should beidentifiedclearly.Inthisstudy,tenexpertsincludingportstatecontrolsurveyors,flagstate control surveyors and independentsurveyorsareconsultedinordertoobtainascoringthecriteriaaccordingtothescaleof AHP. The inspection of foreign ships innational ports is carried out by port statecontrolsurveyors.Theyverifytheconditionoftheship,itsequipmentandmannedandoperated the shipappropriately accordingto the requirements of internationalregulations [35]. The flag state controlsurveyors inspect the vessels registeredunder its flag, due to their responsibilityand authority on the topic of issuance ofsafety and pollution prevention documentand certification. The independentsurveyors take part in almost every stageof cargo operation of ship in port such asdraft survey, on-off hire condition survey,preloading-dischargingsurvey,supercargo,tallysurvey,bunkersurveyandhavetobeinports throughouttheentireprocess.Allexperts have several experiences to carryoutvariousinspectionsinaccordancewithnationalandinternationalconventionsandrules forshipsapproachingports.For thisreason,portstatecontrol,flagstatecontrolsurveyors, and independent surveyors arethemostsuitableexpertstoconsulttogetthemostaccuratedatatoidentifythemostimportantfactorsaffectingportcongestion.

Secondly,anAHPsurveyispreparedfordetermining the most important factorson port congestion. The survey for portcongestion includes pairwise comparisonbetweencriteriaandsub-criteriastatedinTable4.

262

Criteria Number Sub criteria

DocumentationProcedures

D1 LackofinformationandcommunicationtechnologiesD2 CustomsandportoperationsD3 LackofinfluenceofownerorchartererD4 Deficienciesinthesupplyprogram

ShipTrafficInputs

G1 Waitingforothershipswithshipdockoccupation

G2 Thedelaysinmultimodaltransportation

G3 RegionalintensityG4 AccidentsG5 Delaysinarrival-departure

PortStructure

L1 InadequateloadcapacityoftheportL2 InadequatenumberofdocksattheportL3 InadequatecapacityandtypeofcargohandlingequipmentL4 Insufficientdry-dockcapacityL5 Insufficientdockdepthsandtidaleffect

PortOperationandManagement

Y1 WeaknessintheportadministrationY2 Inadequateportpersonnel/notqualifiedY3 InadequatenumberofportstaffandsubcontractorworkersY4 Lowportdependency-cooperationindexY5 Inefficientworkingtimeoftheportandpooroperatingspeed

StrategyandGovernmentPolicies

S1 Inadequatepublic-privatecollaborationandplanning

S2 War-embargosituations

S3 InadequateimmigrationpoliceprocedureandsecuritypolicyS4 Strike-lockoutstatusS5 Inadequatefightagainstpandemic

S6 Inadequateportmodernizationandnotconstructionofnewports

Table 4. Criteria and Sub Criteria for Port Congestion

3.2.2. Application of AHP Step 1 – Defining the problemTheresearchquestionortheproblemis

determiningwhicharethemostsignificantfactorsforportcongestion.Asmentionedinthe literatureandintroductionsection,some studies indicated the factors thatcause port congestion, but there is nostudythatrevealstheorderofimportanceamong these factors.For this reason, thisstudy aimed determining key elements

that affect the port congestion, takingthe precaution toward this problem, anddevelopingnewstrategiesinthematterofportcongestionforportinvestment.

Step 2 – Hierarchical structureThe hierarchical structure in Figure 3

isestablishedtodeterminewhatthemostimportantfactorsforportcongestionare.The criteria and sub-criteria in Figure 3isobtainedfrompreviousstudiesonportcongestionmentionedintheintroduction

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andliteraturesections.Step 3 – Pairwise comparison matrixBy comparing the sub-criteria

belonging to the same group and main

Figure 3. Hierarchical Structure for Port Congestion

Criteria Compared Factors EXP 1 EXP 2 EXP 3 EXP 4 EXP 5 EXP 6 EXP 7 EXP 8 EXP

9 EXP 10 Average

documentationprocedures(Dmatrix)

D1/D2 0,25 0,14 5,00 0,50 0,13 0,20 0,20 0,17 0,14 0,33 0,71

D1/D3 1,00 0,20 0,50 3,00 0,33 0,17 0,25 2,00 0,14 5,00 1,26

D1/D4 5,00 0,33 4,00 3,00 0,20 0,50 0,33 0,33 2,00 3,00 1,87

D2/D3 0,20 7,00 3,00 4,00 0,33 2,00 5,00 4,00 0,20 4,00 2,97

D2/D4 6,00 5,00 0,50 0,25 0,20 2,00 6,00 0,50 1,00 6,00 2,75

D3/D4 6,00 5,00 4,00 0,25 3,00 5,00 3,00 0,25 0,17 0,20 2,69

Table 5. Pairwise Comparison Matrix and Data from Experts

criteria,dataisobtainedfromtheexpertsasinTable5andaggregatedwitharithmeticmeantoseethecommonidea.

./..

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Criteria Compared Factors EXP 1 EXP 2 EXP 3 EXP 4 EXP 5 EXP 6 EXP 7 EXP 8 EXP 9 EXP 10 Average

shiptrafficinputs

(Gmatrix)

G1/G2 0,20 5,00 3,00 0,33 0,13 1,00 0,17 4,00 0,25 3,00 1,71

G1/G3 3,00 3,00 2,00 0,20 0,14 0,20 0,17 0,20 5,00 1,00 1,49

G1/G4 1,00 0,33 1,00 1,00 0,50 4,00 2,00 0,25 1,00 8,00 1,91

G1/G5 0,33 0,33 2,00 0,33 0,50 4,00 0,50 0,33 8,00 1,00 1,73

G2/G3 0,33 0,20 2,00 0,33 0,14 0,14 0,33 3,00 6,00 1,00 1,35

G2/G4 1,00 0,20 0,33 0,33 0,50 0,50 0,25 3,00 1,00 8,00 1,51

G2/G5 6,00 0,33 0,33 0,25 0,50 0,33 0,25 0,33 7,00 0,25 1,56

G3/G4 1,00 0,20 0,50 1,00 7,00 6,00 5,00 3,00 6,00 8,00 3,77

G3/G5 0,50 0,20 3,00 1,00 7,00 6,00 6,00 3,00 5,00 1,00 3,27

G4/G5 0,50 5,00 5,00 3,00 2,00 2,00 3,00 0,33 7,00 0,13 2,80

portstructure(Lmatrix)

L1/L2 0,25 0,33 4,00 1,00 0,13 1,00 3,00 0,33 1,00 0,50 1,15

L1/L3 6,00 1,00 0,20 0,50 0,13 5,00 3,00 =1/4 1,00 2,00 2,09

L1/L4 1,00 9,00 3,00 2,00 0,13 1,00 0,33 2,00 8,00 1,00 2,75

L1/L5 5,00 0,20 2,00 0,33 0,13 7,00 4,00 3,00 7,00 5,00 3,37

L2/L3 5,00 3,00 0,33 1,00 0,25 0,33 4 0,33 6,00 3,00 2,14

L2/L4 2,00 9,00 2,00 2,00 0,33 4,00 =1/4 3,00 7,00 3,00 3,59

L2/L5 7,00 1,00 0,17 0,33 1,00 4,00 5,00 0,50 7,00 5,00 3,10

L3/L4 0,25 9,00 4,00 1,00 4,00 3 0,25 3,00 7,00 4,00 3,61

L3/L5 1,00 0,33 0,20 0,50 4,00 6,00 5,00 2,00 6,00 5,00 3,00

L4/L5 4,00 0,11 3,00 0,50 3,00 2,00 5,00 1,00 8,00 1,00 2,76

portoperation

andmanagement(Ymatrix)

Y1/Y2 1,00 0,14 0,25 2,00 5,00 0,13 0,33 0,33 6,00 2,00 1,72

Y1/Y3 2,00 0,14 3,00 2,00 0,11 0,17 4 0,20 7,00 3,00 1,96

Y1/Y4 0,50 0,14 0,33 1,00 3,00 1,00 4 3,00 5,00 3,00 1,89

Y1/Y5 0,25 0,14 0,50 0,33 0,14 0,25 5,00 3 6,00 2,00 1,62

Y2/Y3 2,00 1,00 0,33 1,00 2,00 4,00 0,20 3,00 0,20 1,00 1,47

Y2/Y4 3,00 1,00 0,25 1,00 2,00 4,00 0,20 3,00 0,20 3,00 1,77

Y2/Y5 0,50 1,00 0,25 0,33 2,00 6,00 0,20 0,33 0,17 3,00 1,38

Y3/Y4 0,33 1,00 0,20 3,00 0,33 1 0,25 3,00 5,00 4,00 1,90

Y3/Y5 0,25 1,00 0,17 1,00 0,14 0,50 3,00 0,33 6,00 3,00 1,54

Y4/Y5 0,20 1,00 0,25 1,00 3,00 0,50 3,00 2,00 0,13 1,00 1,21

Table 5. Pairwise Comparison Matrix and Data from Experts (Cont')

./..

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Criteria Compared Factors EXP 1 EXP 2 EXP 3 EXP 4 EXP 5 EXP 6 EXP 7 EXP 8 EXP 9 EXP 10 Average

strategyandgovernmentpolicies(Smatrix)

S1/S2 2,00 0,11 0,50 2,00 1,00 0,11 5,00 4,00 0,14 1,00 1,59

S1/S3 4,00 0,14 0,25 2,00 0,33 0,33 6,00 4,00 0,17 4,00 2,12

S1/S4 9,00 0,14 0,33 1,00 1,00 0,33 5,00 4,00 0,14 4,00 2,50

S1/S5 5,00 0,14 0,33 1,00 1,00 0,33 6,00 3,00 0,17 8,00 2,50

S1/S6 0,33 0,14 0,50 1,00 0,17 0,25 5,00 4,00 0,14 1,00 1,25

S2/S3 0,20 9,00 0,33 2,00 0,33 9,00 0,50 1,00 5,00 0,50 2,79

S2/S4 1,00 9,00 0,17 2,00 1,00 9,00 1,00 1,00 6,00 0,50 3,07

S2/S5 0,50 9,00 0,33 2,00 1,00 9,00 0,25 0,25 6,00 0,33 2,87

S2/S6 0,20 9,00 3,00 2,00 1,00 9,00 0,25 0,33 6,00 0,20 3,10

S3/S4 1,00 0,20 0,25 0,50 3,00 1,00 2,00 1,00 5,00 4,00 1,80

S3/S5 0,50 0,20 1,00 0,50 3,00 1,00 1,00 1,00 0,20 4,00 1,24

S3/S6 0,17 0,20 2,00 0,50 3,00 0,25 0,33 1,00 0,17 1,00 0,86

S4/S5 1,00 5,00 0,20 2,00 1,00 1,00 0,20 0,33 5,00 0,33 1,61

S4/S6 0,17 5,00 0,33 2,00 1,00 0,25 0,25 1,00 0,20 0,17 1,04

S5/S6 0,50 0,14 0,25 1,00 1,00 0,25 0,25 3,00 5,00 0,17 1,16

mainfactors(Amatrix)

A1/A2 1,00 0,33 0,20 0,50 3,00 2,00 6,00 4,00 0,17 5,00 2,22

A1/A3 5,00 0,33 0,17 1,00 0,25 3,00 5 5,00 0,14 3,00 1,99

A1/A4 4,00 0,33 0,25 0,50 0,17 0,25 7,00 5,00 0,14 1,00 1,86

A1/A5 4,00 0,33 0,50 0,50 3,00 1,00 0,14 5,00 0,17 1,00 1,56

A2/A3 2,00 0,14 2,00 0,50 5,00 0,50 5,00 0,25 0,14 0,33 1,59

A2/A4 5,00 0,14 0,25 0,50 5,00 0,14 0,20 0,25 0,14 0,25 1,19

A2/A5 5,00 0,14 0,14 2,00 0,25 0,50 0,14 0,33 0,13 0,25 0,89

A3/A4 1,00 0,20 1,00 0,50 0,17 0,33 0,17 4,00 0,17 1,00 0,85

A3/A5 3,00 3,00 0,33 2,00 4,00 5,00 0,17 0,33 0,13 0,50 1,85

A4/A5 3,00 5,00 2,00 2,00 6,00 6,00 0,14 3,00 0,17 1,00 2,83

Table 5. Pairwise Comparison Matrix and Data from Experts (Cont')

Step 4 – Performing judgment of pairwise comparison

Pairwise comparisons of entire sub-criteriaareasinTable6,andthevaluesinthesamecolumnaresummeduptoprepareforthenormalizationprocessinstep5andindicatedonthebottomline.

Step 5 – Weights of criteriaToobtainweightsofcriteria,firstly,allvaluesinpairwisecomparisonmatrixbelongingtosubcriteriaandmaincriteriaarenormalized.Fornormalizingthevalues,eachvalueinthesame column is divided by the sum of thevalues in that column as shown in Step 5intheflowdiagram.Then,Criteriaweights

266

(wi)ofthesubcriteriaandmaincriteriaareobtainedbyusingequationinStep5intheflowdiagram.Finally, tomakeconsistencyanalysis in Step 6, Di and Ei values are

D matrix D1 D2 D3 D4D1 1,00 0,71 1,26 1,87D2 1,41 1,00 2,97 2,75D3 0,79 0,34 1,00 2,69D4 0,53 0,36 0,37 1,00SUM 3,736860856 2,410337 5,6017472 8,31

G matrix G1 G2 G3 G4 G5G1 1,00 1,71 1,49 1,91 1,73G2 0,58 1,00 1,35 1,51 1,56G3 0,67 0,74 1,00 3,77 3,27G4 0,52 0,66 0,27 1,00 2,80G5 0,58 0,64 0,31 0,36 1,00SUM 3,357531153 4,754018 4,4110624 8,547143 10,36

L matrix L1 L2 L3 L4 L5L1 1,00 1,15 2,09 2,75 3,37L2 0,87 1,00 2,14 3,59 3,10L3 0,48 0,47 1,00 3,61 3,00L4 0,36 0,28 0,28 1,00 2,76L5 0,30 0,32 0,33 0,36 1,00SUM 3,008406386 3,218422 5,8403416 11,31232 13,23

Y matrix Y1 Y2 Y3 Y4 Y5Y1 1,00 1,72 1,96 1,89 1,62Y2 0,58 1,00 1,47 1,77 1,38Y3 0,51 0,68 1,00 1,90 1,54Y4 0,53 0,56 0,53 1,00 1,21Y5 0,62 0,72 0,65 0,83 1,00SUM 3,23798391 4,689882 5,6056664 7,386446 6,75

S matrix S1 S2 S3 S4 S5 S6S1 1,00 1,59 2,12 2,50 2,50 1,25S2 0,63 1,00 2,79 3,07 2,87 3,10S3 0,47 0,36 1,00 1,80 1,24 0,86

Table 6. Pairwise Comparisons of Entire Sub-Criteria and Main Criteria

./..

foundaccordingtoequationinStep6intheflowdiagram.TheresultsofallthesestepsforeachcriteriaandsubcriteriaaregivenintheTable7.

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S matrix S1 S2 S3 S4 S5 S6S4 0,40 0,33 0,56 1,00 1,61 1,04S5 0,40 0,35 0,81 0,62 1,00 1,16S6 0,80 0,32 1,16 0,96 0,86 1,00SUM 3,70 3,945169 8,4347979 9,952656 10,08207 8,41

A matrix A1 A2 A3 A4 A5A1 1,00 2,22 1,99 1,86 1,56A2 0,45 1,00 1,59 1,19 0,89A3 0,50 0,63 1,00 0,85 1,85A4 0,54 0,84 1,18 1,00 2,83A5 0,64 1,12 0,54 0,35 1,00

SUM 3,13 5,81 6,30 5,25 8,13

Table 6. Pairwise Comparisons of Entire Sub-Criteria and Main Criteria (Cont')

Table 7. Normalized Pairwise Comparisons and Criteria Weights of the Entire Sub-Criteria and Main Criteria

D matrix D1 D2 D3 D4Criteria Weights

(wi)Dİ=⅀wi*aij Ei=wi/Dİ

D1 0,27 0,29 0,22 0,23 0,25 1,04 4,11D2 0,38 0,41 0,53 0,33 0,41 1,73 4,20D3 0,21 0,14 0,18 0,32 0,21 0,88 4,11D4 0,14 0,15 0,07 0,12 0,12 0,49 4,04SUM 1 1 1 1

G matrix G1 G2 G3 G4 G5

Criteria Weights

(wi)Dİ=⅀wi*aij Ei=wi /

Dİ

G1 0,30 0,36 0,34 0,22 0,17 0,28 1,49 5,36G2 0,17 0,21 0,31 0,18 0,15 0,20 1,11 5,46G3 0,20 0,16 0,23 0,44 0,32 0,27 1,50 5,60G4 0,16 0,14 0,06 0,12 0,27 0,15 0,79 5,30G5 0,17 0,13 0,07 0,04 0,10 0,10 0,53 5,14SUM 1 1 1 1 1

./..

268

L matrix L1 L2 L3 L4 L5Criteria Weights

(wi)Dİ=⅀wi*aij Ei=wi /Dİ

L1 0,33 0,36 0,36 0,24 0,25 0,31 1,63 5,29L2 0,29 0,31 0,37 0,32 0,23 0,30 1,63 5,37L3 0,16 0,15 0,17 0,32 0,23 0,20 1,11 5,44L4 0,12 0,09 0,05 0,09 0,21 0,11 0,56 5,12L5 0,10 0,10 0,06 0,03 0,08 0,07 0,37 5,09SUM 1 1 1 1 1

Y matrix Y1 Y2 Y3 Y4 Y5Criteria Weights

(wi)Dİ=⅀wi*aij Ei=wi /Dİ

Y1 0,31 0,37 0,35 0,26 0,24 0,30 1,56 5,12Y2 0,18 0,21 0,26 0,24 0,20 0,22 1,12 5,12Y3 0,16 0,15 0,18 0,26 0,23 0,19 0,98 5,09Y4 0,16 0,12 0,09 0,14 0,18 0,14 0,70 5,05Y5 0,19 0,15 0,12 0,11 0,15 0,14 0,73 5,07SUM 1 1 1 1 1

Table 7. Normalized Pairwise Comparisons and Criteria Weights of the Entire Sub-Criteria and Main Criteria (Cont')

S matrix S1 S2 S3 S4 S5 S6

Criteria Weights

(wi)Dİ=⅀wi*aij Ei=wi /

Dİ

S1 0,27 0,40 0,25 0,25 0,25 0,15 0,26 1,65 6,28S2 0,17 0,25 0,33 0,31 0,28 0,37 0,29 1,79 6,25S3 0,13 0,09 0,12 0,18 0,12 0,10 0,12 0,77 6,22S4 0,11 0,08 0,07 0,10 0,16 0,12 0,11 0,66 6,18S5 0,11 0,09 0,10 0,06 0,10 0,14 0,10 0,61 6,20S6 0,22 0,08 0,14 0,10 0,09 0,12 0,12 0,76 6,16SUM 1 1 1 1 1 1

A matrix A1 A2 A3 A4 A5 Criteria Weights (wi) Dİ=⅀wi*aij Ei=wi /Dİ

A1 0,32 0,38 0,32 0,35 0,19 0,31 1,64 5,24

A2 0,14 0,17 0,25 0,23 0,11 0,18 0,95 5,25

A3 0,16 0,11 0,16 0,16 0,23 0,16 0,86 5,27

A4 0,17 0,14 0,19 0,19 0,35 0,21 1,10 5,29

A5 0,20 0,19 0,09 0,07 0,12 0,13 0,70 5,19

SUM 1 1 1 1 1

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Step 6 – Consistency verification Inordertoidentifythemostimportant

factors for port congestion, after the datais received from the experts, it is checkedwhether these data are consistent or not.Forthispurpose,intheconsistencyanalysis,the values ofmax, consistency index (CI),consistency ratio (CR) and random index(RI) are calculatedaccording to equationsinstep6intheflowdiagram.Theresultsoftheconsistencyanalysisforeachmatrixareshown inTable8.According toanalysis, ifCR<0,10,theresultisconsistent.

Matrices λmax CI RI CR

Dmatrix 4,11 0,04 0,9 0,04

Gmatrix 5,37 0,09 1,12 0,08

Lmatrix 5,36 0,07 1,12 0,06

Ymatrix 5,09 0,02 1,12 0,02

Smatrix 6,22 0,04 1,24 0,03

Amatrix 5,25 0,06 1,12 0,06

Table 8. Results of Consistency Analysis

3.2.3. FindingsAccording to consistency analysis,

the results of all pair wise comparisonsare consistent and from the result of theconsistency, it is understood to valid tospecifytheorderofimportanceoffactorsfor port congestion. Examining the Table7, it is seen that the most importantmain factor for port congestions isdocumentation procedures (A1). Theorder of important main factor for portcongestion is as port operation andmanagement (A4), ship traffic inputs(A2),portstructure(A3)andstrategyandgovernmentrelations(A5),respectively.

In the Table 7, it is understood thatthe most important factor among thesub-factors of documentation proceduresfor port congestion is the procedures inport and customs operations (D2). Thisis followed by the lack of informationand communication technologies (D1),

thelackof influenceoftheshipownerorcharterer(D3)andthedeficienciesinthesupplyprogram(D4).

According to results, the weakness inthe port administration (Y1) is the mostimportantfactoramongthesub-factorsofport operation andmanagement for portcongestion.Then,thelackofqualifiedportpersonnel (Y2) and insufficient numberofportpersonnel(Y3)followit,whilethelow port loyalty cooperation index (Y4)and the inefficient working time of theportandinadequateoperatingspeed(Y5)areinthelastrankwiththesamecriteriaweights.

Inaddition, themost important factoramong the sub-factors of ship trafficinputs for port congestion is the waitingforothershipswithshipdockoccupation(G1). Regional density (G3), delays inconnectionsinmulti-modeltransportation(G2),accidents(G4)anddelaysinarrival-departure(G5)comeafterit.

When Table 7 is examined, it isunderstoodthatthemostimportantfactoramong the port structure sub-factors forport congestion is the inadequate loadcapacityoftheport(L1).This is followedbyinsufficientnumberofdocks(L2)attheport, insufficient capacity and type (L3)of cargo handling equipment, insufficientdry-dock capacity (L4) and insufficientdockdepthsandtidaleffect(L5).

Finally, the most important factorsamong the sub-factors of strategy andstate policy for port congestion are warand embargo situations (S2). This isfollowed by insufficient public-privatecooperation and planning (S1), whileinsufficient immigrationpoliceprocedureand insufficient security policy (S3), andinsufficient port modernization and newconstructions (S6) share third order.The strike-lockout situation (S4) andinsufficient outbreak (S5) are in the lasttwoplaces,respectively.

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4. ConslusionInthisstudy,itisaimedtoidentifymost

important factors on congestion of a portaccordingtopointofviewoftheportstatecontrolsurveyors,flagstatesurveyors,andindependent surveyors. For this purpose,the factors affecting the port congestionobtained from the literature are orderedaccordingtocriteriaweightsusingtheAHPmethod.

According to results, it is observedthat the main factors for port congestionwith the highest importance aredocumentationprocedures,portoperationandmanagement, ship traffic inputs, portstructure and strategy and governmentrelations,respectively.Themostimportantsubfactorsaretheproceduresinportandcustoms operations,weakness in the portadministration,thewaitingforothershipswithshipdockoccupation,inadequateloadcapacityoftheport,andWarandembargosituations.Whenthewaitingforothershipswithshipdockoccupationandinadequateloadcapacityoftheportareconsideredasone of the important sub factors for portcongestion,inthiscontext,bybuildingnewhubandsubportsregionaldensitycanbereduced, with both port dependency andintegrity dock occupation and inadequatecapacityofnumberofdocksproblemscanbesolvedorasmuchaspossibleminimized.Examining the port operation andmanagement indetail,which isoneof theimportantmainfactorforportcongestion,the research findings indicated that theweaknessintheportadministrationismostimportantsubfactorinthiscategory.Takingthisfactorintoaccount,byinvestigatingtheforeign ports’ best management practicesin terms of operation and management,qualified and sufficiently quantifiedpersonnelinportforbothmanagementandoperational departments can be obtainedby a combination of sufficient salary, taxrelief and encouragement. In this way,can make an action for the topic of port

congestion in the sense of port operationand management. On the other hand,via strategy and governmental relationstake place in the end point to affect portcongestion,withpublic-privatepartnership,a strategic planning can be developed forpreventingportcongestionefficiently.Andfinally,newtechnologies(radio-label-scan)canbeintegratedtothesystemtoestablishdigital customization systems (e-manifest,e-bl,etc.)tominimizehumanfactorsintheofficial part of the sector, minimize timespendandtominimizeerrors,bymeansofautomation.

Thispapermakesanefforttocontributeto the existing literature by determiningimportance weights of factors leading toportcongestionastheuniquestudyonthematter.Therefore,theportsthathaveportcongestion problemsmay gain an insightintowhichareastheyshoulddevelopandaportinvestorcanalsorefertothesefactorswhen creating a new port project. Forfurther studies, it is considered that greyrelational analysis can be practiced forrankingorderof someports takingplacein the specific area in accordance withport congestion. For example, five portscanbeanalyzed in the İstanbulportareaorinanyotherportareaandtheycanbeusedasalternative for thegreyrelationalanalysis. Since, the weighting of thefactorseffectingportcongestionhasbeenobtainedfromthisresearch,inthefurtherstudy,realdataregardingthesefactorsofthe determined ports is obtained. Aftergreyanalysis,determinedportsarerankedaccording to the level of port congestionwhich they have. In thisway, themap ofport congestion fordeterminedportareamaybeobtained.

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Simulation-Based Optimization of the Sea Trial on Ships

Yusuf GENÇ1, Murat ÖZKÖK2

1Ordu University, Fatsa Vocational Higher School, Turkey2Karadeniz Technical University, Surmene Faculty of Marine Sciences, [email protected]; ORCIDID:https://orcid.org/0000-0002-4903-5015

[email protected]; ORCIDID:https://orcid.org/0000-0002-1782-8694CorrespondingAuthor:YusufGENÇ

ABSTRACT

Aswellknown,shipswhichhavecomplexproductionprocessesaresubjecttovarioustestsmadeoneverystageinmanyfieldsfromthebeginningtotheendoftheproduction.Afterthetestsarecompletedsuccessfully,theshipisdeliveredtotheship-owner.“Seatrial”beingthelaststageofthesetests,isexaminedindetailinthisstudy.Thepurposeofthisstudyistoplanthetestsperformedintheseatrialbythemeansofcomputerprogramsandtosuggestshortercompletionperiodforthetests.Thus,reducingthetotalcostofthecruising.Moreover,shorteningthedurationofthecruisewillbeafactorthatcanspeedupthedeliveryoftheship.Forthispurpose,thetestsandprocessesperformedduringtheseatrialarelisted.Acruiseprocessflowdiagramincludingallthetestsappliedundernormalconditionswascreated,andthedatawereenteredintotheSIMIOsimulationprogram.Asaresult,itwasdeterminedthatthetotalcruisingtimewas28,0989hours.Afterthat,anewflowdiagramwascreatedbymakingsomeimprovementsinthecurrenttestingprocess,andanewsimulationmodelwasbuiltup.Inthenewsimulationmodel,totaltimespenttocompletethetestswere25,3567hours,sothetestingtimewasshortenedby2.75(9,76%)hours.

Keywords

SeaTrial,Shipbuilding,SIMIO,Simulation,Optimization.

1. IntroductionShips are marine vehicles that are

manufactured at very high costs inshipyards and have complex productionprocesses. A shipyard must manage thecomplexprocessessuccessfullyanddelivertheshiptotheship-ownerontime.Duringthe construction phase of a ship in theshipyard, many variables consisting ofdifferent main topics, such as the correct

ORIGINALRESEARCH(AR)Received: 12 August 2020 Accepted: 08 December 2020

JournalofETAMaritimeScienceGenç&Özkök /JEMS, 2020;8(4):274-285

10.5505/jems.2020.93898

To cite this article:Genç,Y.&Özkök,M. (2020).Simulation-BasedOptimizationof theSeaTrialonShips. Journal of ETA Maritime Science,8(4),274-285.To link to this article: https://dx.doi.org/10.5505/jems.2020.93898

placementofproductionlines,theselectionof the right equipment, the qualificationsof the workers, the experience of theengineering staff, and the selection of anappropriate subcontractors, directly affectthe performance and the efficiency of theshipyard, and therefore thepunctualityofthe delivery. The shipbuilding contractsmust be made consciously and freely bytheparties, as ineverycontract [1]. Since

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thedeliverytimeoftheshipdependsontheagreementbetweentheshipownerandtheshipyard, therewill be financial losses onbothparties in theeventof anydelaysonthe delivery dates. Moreover, delay of theship’s delivery due to shipyardmay causenegative business consequences for thefutureoftheshipyard.

Given the quality standards anddelivery times of themanufactured ships,the general situation of shipyards hasparamount importance. With the rapiddevelopmentsincomputertechnologyandthe successful use of these developmentsin ship engineering, computer simulationmethods based on mathematical modelshave become effective [2]. Depending onthe progress of these methods, it is alsopossibletoshortenthedeliverytimesoftheshipbecauseshipproductionconsiderablyvaries technologically. Thus, the use ofsimulation programs in the shipyardsallowsustoforeseethepossibleproblems,do planning in different scenarios forproductionandtests.

Shipproduction is aprocess thatmustbecontinuouslymonitoredandsupervisedfrom the beginning of the project phase.In this process, beginning with the testsdone on the equipment manufactured infactories,varioustestsmustbecarriedoutwithincertainrulesduringeachproductionphaseintheshipyards.Thesetestsneedtobepassed incrementally. It isnecessary tocheck if the ship formed through variousstagesduringtheconstructionperiodmeetsthenecessaryrequirementsinseveralpointssuchassafety,maneuverability,equipment,andsufficiency.Forthispurpose,however,experiences differ throughout the cruise.The International Maritime Organization(IMO)statesthatitisimperativetoperformrotational, zigzag, and stop maneuversto determine if 100-meter large shipshave sufficient maneuverability [3]. Sincethese tests and experiments conductedintheshipyardsarecarriedoutunderthe

supervisionoftheshiprepresentativesandtheclass,theyassistfuturecrewmembersoftheshiptogetfamiliarised.

2. Literature ResearchThankstotoday’stechnology,simulation

programs are used in every field of theindustrytoseethepossibleproblemsthatmayemergeinthesystemorworkingorderandtomovetheproductiontobetterlevels.Simulationiswidelyused,especiallyintheareaswhereproduction iscontinuousandautomation-related,suchastransportation,medicalservices,andsupplychain.

Ponsignon and Mönch [4] studiedfactories thathadcomplexmanufacturing.By creating production planning basedon simulation, they evaluated them witha scenario. It was found out that thesimulation could produce stable plans.Medeiros et al. [5] developed models ofplate processing operations in terms ofthemodernizationof theplateproductionline bymaking simulation-basedwork onship-building yardmanufacturingprocess.Caprace et al. [6] developed a simulationonmanufacturingprocessessuchasblockerectionintheshipyardusingoptimizationtechniques.Itwasobservedthatthechoiceof a correct mounting sequence had apositive contribution on the productionlead time. Another simulation study wascarried out by Roh and Lee [7]. In thisstudy,usingthe3DCADmethod,asuitablesimulationmethodwasdevelopedforblockmounting for thewhole-body structure ofthe ship.Byusing the3DCAMmodel, theblock division method was created, andit was seen that the block mounting wassimulatedappropriatelyintheinitialdesignphase. Yuguang [8] proposed the Petrinetwork to make a good block assemblymodelinshipbuildingindustry.HeshowedthathecouldcontributetonormalplanningprocessesbydevelopingalgorithmsduringassemblywiththePetrinetmodelheused.Lamb et al. [9] investigated the validity

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of theoretical approaches and modelsusing international competitive shipyardproduction data in theirwork to improvetheshipbuildingprocess.Theydefinedtheshipbuilding process as a result of longstudies and modellings. In their work,ChengandHongxiang [10] concluded thatby simulating the anchorage operation ofthe shipwith the help of Visual C ++, theresultsobtainedcanhelpthestaffworkingonthedeckasanexercise.

Abdel-atif et al. [2], by using Simulinksoftware, made use of hydrodynamicforces and moments based on modularmathematics to simulate the maneuverbehavior of the Esso Osaka tanker classship.Theyalsotestedtherotationandzig-zagmotionandachievedsuccessfulresults.Chaetal.[11]appliedthesimulationstudythattheyproposedintheshipandoffshorestructures to the block assembly processin their study. As a result, they concludedthat the simulationworkwould be usefulin this framework, and the developmentarea could be provided. Nam et al. [12]have emphasized the importance of usingthe simulation at the shipyard in theirstudy.Theyalso tried tocreateacommonstructure that would facilitate simulationat shipyards, claiming that it would be acustomized simulation for each shipyard.Chaetal.[13],inanotherstudy,simulatedthe block assembly process, which wascarriedoutwithafloatingcrane,bytakingthe6degreesof freedommovements intoconsideration.Thus,itcanbededucedthatthe resonance frequency canbe predictedby simulation, and the situation thatmaycausedanger canbedetected in the earlystage. Shin and Sohn [14] developed anautomated production system for productflow control at a workplace by usingobjective information technologies suchasmodelingandnetworking, emphasizingthe importance of the automatedshipbuilding process. In thisway, productflow simulation was carried out and the

problems on the process were evaluated.Ljubenkov et al. [15], have emphasizedthe importance of using simulation in theshipbuilding production process in theirwork.Ithasbeenseenthattheshipbuildingwithacomplicatedproductionprocesscanbe identifiedwith the simulationmethod,andthepartswhichmaycreatebottlenecksand problems can be determined. Kimet al. [16] analyzed the simulation of themanufacturing systems in the shipyardin their study. By designing the blockerection simulation, they produced amodel.Leeetal.[17]dwelledonthepanelship, which was an important part of theshipbuilding production process in theirstudy. The simulation model was verifiedusing a real manufacturing scenario, andthe relationship between the model andthe panel linewas accepted. Hadjina [18]conducted a simulation-based study ontheprofilecuttinglinefortheshipbuildingprocess.Viketal.[19]aimedtogetthebestproductionlinebyusingdifferentscenariosinthedesignphaseofacementplantwithSIMIO program. Mandalaki and Manesis[20] made 3D simulations of vessels,vehicles,andhumanactivitiesforthePatrascityport theycreated in threedimensionswiththehelpoftheAutoCADprogram.The3D simulation done with SIMIO aims toexamine the changes planned in advanceandlookforwaystoworkmoreeffectivelyintheportwithdifferentscenarios.Özkök[21] studied with SIMIO program in hisstudy, and hemade the simulationmodelby making the process analysis of theprofile processing unit in the shipyard,and he applied different scenarios toincreasetheamountofprofileproduction.He concluded that the improvementsthat can bemade onmarking and cuttingactivities can contribute to increasingthe amount of profile production. Jeonget al. [22] developed a process-orientedsimulationmodeltosimulatethebehaviorof shipyard logistics.With this simulation,

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thephysicalmovementofeachtransactionwas analyzed, and a logistic indicatorwasused for theprocess.Duetal. [23], inanotherstudy,proposedanewsimulation-based spatial planning program to avoidthespatiallayoutproblemoftheblocks.Inthisway,visualresultsfortheblocklayoutandprocessdiagramwereeasilyobtained.Lee at al. [24], parallel to new productiontechnologies,workedonasimulation-basedshipbuilding planning case. They used aprocess-oriented simulation techniquewith the help of a new scheduling systemfor shipbuilding planning processes. Byapplying the proposed simulation-basedplanning system to a real shipbuildingprocess, it was proven that the quality ofproduction planning could be increased.Ju et al. [25] investigated the mid-termproductionplanningprocessintheshipyardin detail. Later, they developed a systemthat can simulate a new discrete event byapplying a backward process-centeredsimulationtothisprocess.Theverificationof the system was carried out with the

productiondataoffourdifferentships.

3. Material and MethodSimulation technology is used inmany

production areas. It shouldbeknown thatin today's world, where the competitiveenvironment is constantly increasing,businessesthataimtosurviveandachievecontinuity in production should improvethemselves with the help of simulationand similar techniques. Timely delivery ofprojectsandcustomersatisfactionareveryimportantforthecontinuityofthebusiness.Inthisstudy,whichwethinkwillcontributetothedeliveryprocessoftheship,theteststobecarriedoutduringthetrialcourseofashipwhosefactoryacceptanceandharboracceptance tests have been completedare examined with the help of the SIMIOprogram,whichisbasedonbottleneckandqueue theory, and it is foreseen to reducethe total time spent on the cruise. In thiscontext,the7-stepprocessshowninFigure1hasbeenfollowed.

Figure 1. The Process of Obtaining the Simulation Models of the Tests

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• In stage 1, all the test activities to becarriedoutonthecruiseare identifiedandlistedinatabularform.

• In stage 2, the durations of the teststo be entered into the SIMIO programare indicated in accordance with thetriangulardistribution.

• In stage 3, a simulation model of thecruisingprogram,whichisavailableandusedinseatrials,hasbeenformed.

• Instage4,thesimulationmodelhasbeenrun,andhowlongthetotaldurationofthecruisewouldbeunderthespecifiedconditionshasbeenstated.

• In stage 5, improvements have beenmadeontheorderandsequenceoftheteststobedoneonthecruise,andanewsimulationmodelhasbeenformed.

• In stage 6, a new simulation modelhas been run, and how long the totaldurationof thecruisewouldbe in thiscasehasbeenobserved.

• In the 7th stage, the simulationmodelobtained from the existing cruise testprogramandthenewsimulationmodel

Test no “Tests and controls Periods (minute)Optimistic Expected Pessimistic

1 Goingabroadofrelevantpersons(shipyard,service,classetc.)

45 60 90

2 Startupmeeting(shipyard,ship-owner,class)

20 30 45

3 Measurementofshipdrafts(fore,stern,midship)

15 20 30

4 Gyrocompasssettings 45 60 755 Boilercontrolsandalarmtests 30 45 606 Bowthrustertest–starboardside 20 30 407 Bowthrustertest–portside 20 30 408 TransitionfromMDOtoHFO 15 20 309 Boostermoduletestsanditsalarms 20 30 4510 Separatortestanditsalarms 20 30 4511 Navigationequipmenttest 20 30 4512 Mainenginesettings 45 60 90

Table 1. Tests and Controls to be Carried Out During the Sea Trial

obtained after the improvements arecompared.

3.1. Cruise Acceptance Tests and Determination of Duration

Theshipisreadyforcruiseacceptancetests after the completion of harboracceptance tests (HAT) and preparationsmadebeforetheseatrial.Forthisstudy,acruising program of 8400 DWT chemicaltanker was used. Tests and controlsplannedtobemadeduringtheseatrialaregiven in Table 1. Besides, the applicationtimesofthetestsandcontrolscorrespondsto the data recorded during the sea trialof the 8400 DWT chemical tanker. WhilepreparingTable1, noorderof testinghasbeenapplied.Then,usingthedatainTable1, a normal workflow diagram of the seatrial has been composed. Afterwards, intermsofshorteningthetotalspendtimeintheseatrial,anewdiagramisobtainedbyperforming the improvementworkon thecruiseworkflowdiagramformedbefore.

./..

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Test no Tests and controls Periods (minute)

Optimistic Expected Pessimistic13 Freshwatergeneratortest 30 45 60

14 Anchorandwindlassteststarboardside 20 30 4015 Anchorandwindlasstestportside 20 30 4016 Doublebumpssteeringtest 10 15 2017 Singlebumpsteeringtest 10 15 2518 Singlebumpsteeringtest 10 15 2519 Portsideturningcircletest 20 30 4520 Starboardturningcircletest 20 30 4521 Zig-zagmaneuveringtest(10°/10°) 20 30 4522 Zig-zagmaneuveringtest(20°/20°) 20 30 4523 Speedtest 30 45 6024 Stoppingtest 20 30 4525 Noisemeasurementtest 45 60 9026 Asterntrial 20 30 4527 Crashstoptest 20 30 4528 Automaticslowdownalarms/shutdown

test30 45 60

29 Blackouttest 20 30 4530 Mainengineendurancetest 240 270 30031 Smokedetectiontest 45 60 7532 Automationtest(AUT-UMS) 360 400 46033 ShaftgeneratorcontrolbeforeAVM-APS 15 20 3034 Alternativedrivesystemtest(AVM-APS) 60 75 9035 Resultmeeting(shipyard,ship-owner,

class)20 30 45

36 TransitionfromHFOtoMDO 15 20 3037 Gettingbacktotheshipyardbuilding 45 60 90

Table 1. Tests and Controls to be Carried Out During the Sea Trial (Cont')

The following can be stated regardingtheseatrialandTable1:• While the duration of each test to be

performed in the sea trial was beingdetermined,thepreparationphasepriortothetestwasincludedtotheduration.

• Air and sea conditions are suitable forcruising.

• Itisassumedthatthereisnobreakdownontheshipfromthestarttotheendoftheseatrial.

• InTable1,theperiodsoftheteststobeentered into the SIMIO program havebeendeterminedasappropriate to thetriangulardistribution.

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3.2. Creating the Simulation Model of the Sea Trial

InTable1,aseatrialworkflowdiagramhas been created to use in the SIMIOprogramfor thesea trialprogram,which

iscomposedof37items(Figure2).Whilethis flow diagram was being formed, noimprovement work was done on the seatrialprogramwhichwasperformedundernormalconditions.

Figure 2. Current Status of the Cruising Program Flow Diagram (Simulation Model)

Figure 3. New Status of the Cruising Program Flow Diagram (Simulation Model)

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3.3. Improvement of the Sea Trial Simulation Model

Inordertoconductthecruisingprogrammore efficiently,which is composed of 37itemsshowninTable1,thetestflowcreatedtobeusedintheSIMIOprogramhasbeenrearrangedtoprovidebetterresults(Figure3).Whilepreparingthisflowdiagram,teststhatcouldbedoneinthesametimeframeand that will not affect each other werecarriedoutwiththehelpoftheexperiencesgainedinthepreviousseatrialtests.Hence,acertainsequencewasfollowedduringthetests, taking factors, such as the positionandthespeedoftheship,andthedifficultyofthetestintoconsideration.

The intendedpurposehere is to finishthe sea trial as soon as possible. Enteringthe test flowdiagramcreatedunder theseconditions into the SIMIO simulationprogram,theresultswereexamined,andbycomparingthetwomodels,thedifferencesduringtheseatrialhavebeenobserved.

4. Results and Discussions4.1. Current Status of the Sea Trial Simulation Model

Figure 4 shows a 3D image of the

Figure 4. The Cruising Flow Diagram Provided from the Program

simulation model entered the SIMIOprogramforthecurrentsituation.Thetestsand controls shown in Table 1 have beenentered to the program as activities 1, 2,etc. with the sequence numbers specifiedin accordance with the current statesimulationmodel(Figure2).

After creating the cruising programsimulation model in the program undernormal conditions, the program has beenrun to find out how long the testswill becompleted,and the total cruisingdurationhasbeenobservedas28,0989hours(Table2).

4.2. After the Improvement of the Sea Trial Simulation Model

Followingthefindingsobtainedforthecurrent situation, anewsimulationmodelprogramhasbeenenteredintotheprogrambymakingaseriesofimprovements.Figure5 shows the 3D model of the simulationmodel. The tests and controls shown intable1havebeenenteredintotheprogramas activities 1, 2, etc. with the sequencenumbers specified in accordance withthe simulation model after improvements(Figure3).

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TimeInsystem-Average

Object Name Data Source Category Value

Ship [Population] FlowTime 28,0989

Sink1 [DestroyedEntities] FlowTime 28,0989

TimeInSystem-Maximum




TimeInSystem-Minimum




Table 2. The Result of Current Status of Simulation Model

Figure 5. The Cruising Flow Diagram After the Improvement

After creating the new model in theprogram under normal conditions, theprogramhasbeenruntofindouthowlongthe testswill be completed, and the totalduration has been recorded as 25,3567hours shortened by 2,75 hours for thenew situation (Table 3). This amount ofshortening corresponds to 9,76% of the

total cruising time calculated before theimprovement.

Inthetestscarriedoutontheprogram,it was accepted that there was nobreakdown of the ship during the periodfromthebeginningtotheendofthetestsand that the weather and sea conditionsweresuitableforcruising.

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Table 3. The Result of the New Status of Simulation Model

TimeInsystem-Average




TimeInSystem-Maximum




TimeInSystem-Minimum




Examplestothedifferencesbetweenthefirstcruisingmodelandthesecondcruisingmodel:• Tests number 5 (boiler controls and

alarms) and 6 (bow thruster STBS),which are planned to be carried outsequentiallyinthefirstcruisingmodel,weredeterminedasparalleltestsinthesecondmodelwithdifferentpersonnelinthesametimezone.

• Likewise, the tests number 10(separator test and its alarms) and15 (anchor windlass PS), which areplanned to be carried out sequentiallyin the first cruising model, have beenshownparallelinthesecondmodel.

• Inaddition,thesequenceofthetestshasbeenchangedingeneral.

5. ConclusionsIn this study, it is emphasized that the

seatrialcanbecompletedinashortertime.Forthispurpose,theteststobecarriedoutinthecruiseareshownintheformofitemswith their periods, and the periods of theteststobeenteredintotheSIMIOprogramhavebeendetermined in accordancewiththetriangulardistribution.

Theflowdiagramofthetestplanformed

undernormalconditionshasbeenpreparedandentered to theprogram.Theprogramhas been run afterwards, and it has beenunderstoodthatthetotaltimespentonthetestsduringtheseatrialis28,0989hours.Then, the new flow diagram created as aconsequence of the improvements madeon the test plan has been entered to theprogramagain.Asaresultofthisprocess,itisseenthatthetotaltimespentonthetestsis25,3567hours.Asaresult,whentheflowchart is formed after the improvement isapplied,thecruiseiscompletedinlessthan2.75hours.Inthiscase,thetotalspenttimefor the cruise tests decreased by a 9,76%ratio compared to the first case. Thus, itcanbededuced that the testprocedure inthe second cruise flow diagram is moreuseful.Whatisimportanthereistoensurethat the necessary arrangements in thetests are carried out in parallel (in thesameprocess)withthecruiseandthatthepersonnelcomplywiththeworkplan.Thiswillshortenthetotaltimespentontests.

Insubsequentstudiesrelatedtotheseatrial,betterresultscanbeshownintermsofreducingthetotalspenttimeonthetestsbydesigningdifferentscenariosonthecruiseflowdiagramsformedforthetests.Similar

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simulationstudiescanalsobeconductedonmilitaryshipsthathavemoresophisticatedsea trial procedures thanmerchant ships.It isunderstood that itwouldbeuseful tousetheseandsimilarsimulationprogramseffectively in the shipbuilding industry tobeabletoproducehighqualityshipsin ashorterperiodandtoimprovetheon-timedeliveryperformanceofshipyards.

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JournalofETAMaritimeScienceKöse/JEMS, 2020;8(4):286-301

10.5505/jems.2020.49389

Measurement and Modelling of Particulate Matter Emissions from Harbor Activities at a Port Area: A Case Study of Trabzon, Turkey

Süleyman KÖSE

KaradenizTechnicalUniversity,AbdullahKancaVocationalSchool,[email protected]; ORCIDID:https://orcid.org/0000-0003-2940-7042

CorrespondingAuthor:SüleymanKÖSE

ABSTRACT

Duetotheversatileactivitiescausedbytheservicesprovidedattheharbor,alargeamountofparticulatematterisemanated.Thehealthoflivingthingsisseriouslythreatenedbythespreadofthesesubstancesintheairduetotheeffectofmanyenvironmentalfactors.Thesizeofthisthreatmayreachmuchhigherlevels,especiallyatports locatedclosetocitycenters.Inthisstudy,attheTrabzonPortarea,PM10andPM(depositeddust)measurementsfromtheharboractivitieswerecarriedoutat9differentpointsbetweenFebruary2019and April 2019 and the dispersion of these particulatematter into the environment isanalyzedutilizingtheISCST3(IndustrialSourceComplex-ShortTerm)modelprogram.ItisdetectedthatthehighestamountofmeasuredPM10(suspendedparticulatematter)isatthedock3with1.84mg/Nm3andthehighestamountofPM(depositeddust)isinthedockloadingareawith203mg/m2-day.Inthemodellingstudy,itisdeterminedthattheparticulatematterdispersearoundanareaof25km2inthesouthdirectionoftheport,anditisconcludedthatportairqualitymanagementwillfocusonprecautionsfordockswhereintensiveloading-unloadingactivitiestakeplace.

Keywords

HarborActivities,ParticulateMatter,EmissionModelling,AirPollution.

ORIGINALRESEARCH(AR)Received: 05 September 2020 Accepted: 27 November 2020

To cite this article:Köse,S. (2020).MeasurementandModellingofParticulateMatterEmissionsfromHarborActivitiesataPortArea:ACaseStudyofTrabzon,Turkey.Journal of ETA Maritime Science,8(4),286-301.To link to this article: https://dx.doi.org/10.5505/jems.2020.49389

1. IntroductionTheglobalizationoftheworldeconomy,

theliberalizationoftradeandtheformationof the international transportationmarkethavecontributedgreatlytothedevelopmentoflogisticsandthusportshavebecomethekeypointofworldtrade[1]. Inourworld,where global trade is rapidly developingand 90% of its trade is carried out via

sea transportation, the demand for portservices has also increased significantly[2]. It is possible to divide port servicesintotwomaingroupsasrenderedservicestocargosandships[3].Servicesunderthetwomaingroupsinquestioncanbestatedas unloading, loading, pilotage, towage,storage, temporary storage, sheltering,loading-unloading in container, weighing,

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water-electricity, waste and passengerservices [4]. Ports, generally establishedat close regions of urban areas, have asignificant impact on the air pollution oftheir regions [5]. Particularly, loading,unloading, transport and storage of loadssuchascement,coal,minerals,soybeanandflourcausesignificantincreasesinairborneparticulateconcentrations[6].

Given the fact that more than 50%of the world's population live in coastalcities [7], emissions from port activitiesmayhaveastrongimpactonthehealthofcoastal communities and the environment[8]. For this reason, in the recent years,manystudieshavebeenconductedon theassessmentoftheimpactofportemissionsonairqualityatalocalscaleandclimateataregionalscale[9][10][11][12][13].

In the case when granule size of thesubstances (particulates) which is in asolid-state in the atmosphere is less than300micronsinsize,theyarecalledasdust.50microns is the limit of visionwith thenaked eye while the particulates that canreachourlungsarethosewithasizeof10microns or less (PM10) [14]. Some studiesin the literature [15][16][17] indicate thatatmospheric particulate matter (PM) inurbanareasislinkedtothenumberofdailymortalityandhospitalizationsasaresultoflungandheartdiseases.

In2000,itwascalculatedthatthehumanlifespan in Europe has been shortenedapproximately 8.6 months due to PMexposure. Resulting from this particulateexposure, acute upper respiratory tractinfectionssuchassorethroatandcoughingcould be experienced, furthermore ithas been concluded that diseases likebronchitis, chronic obstructive pulmonarydisease (COPD) and asthma are closelyrelatedtohighlevelsofPM10[18][19].

It has also been reported that theincrease in seeking medical advice withcardiovascular system diseases suchas vascular occlusion is linked with PM

concentration level. Additionally, thisexposure to PM is reported as causingcardiacarrhythmia[20].

TheresultsofacohortstudyconductedinUSArevealedthatthe10μg/m3increasein PM concentration is associated with arise in mortality rates by 13%. AnothercohortstudybyAmericanHeartAssociationhas also demonstrated that 6% increaseinmortality ratesdependingon10μg/m3 increaseinPMconcentration[21].

ManydiseasescaughtinTrabzonaredueto particulate matter-based air pollutionand some of them even resulted in death.About200peoplediedintheprovinceduetodiseasescausedbyairpollutionbetween2005-2007, while approximately 9000people received inpatient treatment athospital[22].

When the pollutant amounts fromport activities in European harbors wereexamined, it has been determined thattheamountofparticulatematterobtainedconstitutes 40% of all pollutant amounts[10]. In the literaturereviewconducted inline with this information, many studieshavebeenfoundonPM10(particulatemattersuspended in the air) emissions resultingfrom port activities [23][24][25][26][27][28][29][30], however, it is observed thatthere has not been anymodelling carriedout related to the dispersion of emissionsto the environment. In addition, whengoing through the studies examining theemissions of PM10 and PM (depositeddust; includingparticulates larger than10microns) together, although studies havebeenconductedonPM10andPM(depositeddust) measurements in the facilities suchas cement plant [31][32], thermal powerplant [33],mines [34]. Additionally,manystudiesmeasuringandmodellingPM10andPM (deposited dust) emissions togetherfromportactivities[35][36]couldbefoundin the literature, however the number ofstudies which integrate modelling, real-time measurement and dispersion is

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scarce. Therefore, in this study, PM10 andPM (deposited dust) measurements werecarried out at Trabzon Port by selectingthe city of Trabzon, which is located inthe centre rather than having the portareaclose to thecity centre, and itseffecton the environment is investigated bymodelling study. Thanks to this study, itis tried tobe findoutwhich regionof theporttheemissionsfromporttheemissionsoriginatingfromportactivitiesweremoreintense.Inaddition,thankstothemodellingstudy,revealingthedispersionandimpactareas of these emissions is aimed. It isestimated that the study will be effectivebothintermsofhelpingportauthoritiesindeterminingemissionsourcesandguidingthestudiestobecarriedoutatotherports.

2. Methodology2.1. Measurement Site and Instruments Used

PM10 and PM (deposited dust)measurement area is the port of Trabzon(shown in Figure 1), which is the most

active harbour of the Eastern Black Sea,(between 40 57' 30" North - 41 06' 36"Northlatitudeand4002'30"East-3925'00" East longitudes) in the north east ofTurkey.Attheport,threeseparatedaily(24hours)measurementsweremadeforPM10(suspended particulate matter) and twoseparatedailymeasurementsweremadeforPM(depositeddust) forpermonth.Threedifferentmeasurementsweremadeforpermonthat theportat5differentpoints forPM10andtwoseparatemeasurementsat4different points for PM (deposited dust).The firstperiodmeasurements tookplacebetween February 3rd 2019 – March 4th2019,andthesecondperiodmeasurementstookplacebetweenMarch4th2019–April4th2019.

Consisting of 9 docks, the port has anannualcapacityof10milliontonsofcargohandling and 2500 ships reception peryear. In 2019, a total of 1,869,725 tons ofunloading operations were performedand 568,950 tons of cargos were loaded.Thereareannually5milliontonsofcargo

Figure 1. Demonstration of the City Where the Port Chosen as the Study Area on the World Map and Satellite View of the Trabzon Port

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storageareaand250tonsofbilgestoragearea at the indoor and outdoor storageareaswithintheport.Inaddition,24-hourpilotageandtowageservicesareprovidedatthe port, which has 350,000 TEU containerhandlingand300,000TEUcontainerstoragearea annually. Apart from these, there isa passenger terminal in the port whereapproximately 50,000 passengers enter andexit annually. In addition to these indicatedareas,thefreezoneofTrabzonprovinceisalsolocated within the port boundaries. In thisregion there are two covered storage spacewithacapacityof11,000m2andanopenarea

Code Name of Emission SourceParameters

PM10 PM (deposited dust)

1 StockArea(warehousearea) x -

2 Dock3(loading-unloading) x -

3 Dock4(loading-unloading) x -

4 BesideWeighbridge x -

5 TruckCrossingRoad(smallport) x -

6 BesideGuestParkingArea - x

7 FrontofDock3 - x

8 NexttoLoadingArea4-5 - x

9 BilgeArea - x

withastoragecapacityof20,000m2.The names of the codes of all

emission sources detected, measured andevaluated in this study as a result of on-site inspections within the port and theparametersmeasuredinthesesourcesaregiven in Table 1. Moreover, the locationswherePM10measurement areas located intheport'sgeneralsettlementareshowninFigure2withsatellitephotographs,andthelocations where the PM (deposited dust)measurement sites were located in thegeneral location of the port are shown inFigure3withsatellitephotographs.

Table 1. Measured Emission Sources

Figure 2. PM10 Measuring Points Figure 3. PM (deposited dust) Measuring Points

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Official permissions for performingnecessary measurements were grantedfromportauthoritypriortothestudyandthe researcher also contacted with portmanagement company and guaranteedtheirsupportforthestudy.

2.1.1. PM10 Sampling MethodEPA 40 CFR PART 50, one of the

gravimetric measurement methods, is awidelyusedmethod for themeasurementof particulates called PM10, which exist inoutdoor air as suspended in solid state.The sampling process was carried out bydeterminingthemostsuitabledistancesfortheemissionsourcesspecified inFigure4(1)-(2)-(3)-(4)-(5).

The PM10 absorption nozzle of theZambelliIsoPlus6000dustsamplingdevicewas located at a certain height and thedevicewasoperated.Theairsampletaken

atconstantflowrateatappropriatepointsaround ambient dust sources was passedthrough the appropriately conditionedfilter.ItheldontothesuspendedPM10filterintheenvironment.Afterthemeasurementwasconcluded,themeasurementdatawastakenfromthedeviceandrecordedonthemeasurement form. The filter used in themeasurementwascarefullyremoved,placedinapetridishandbroughttothelaboratorybylabelling.Thefiltersusedinthesamplingwere weighed by waiting 24 hours underweighing room conditions (20 °C ± 1 °Ctemperatureand50%±5%humidity).Dustconcentration was calculated as mg/Nm3 byproportioningweighingresults intothevolume of air drawn. PM10 measurementresults were obtained by performing thisprocess between February and April 20193timesforeachmeasurementpointand15timesintotal.

Figure 4. PM10 Measuring Points, (1) Stock Area, (2) Dock 3, (3) Dock 4, (4) beside Weighbridge, (5) Truck Crossing Road

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2.1.2. PM (Deposited dust) Sampling Method

TS2341standard,whichisagravimetricmeasurementmethod,hasbeentakenasbasisin collecting PM (deposited dust) samples.This standard comprises methods for theconstruction, installation and operation ofthesedimentcollectiondevice,whichisusedtocollectandmeasuredepositeddustintheatmosphere, that collapse with their ownweightorrain,andsoon.

Thedepositeddustunitusedinsampling,whichisplacedatpointsinFigure5(6)-(7)-(8)-(9),generallyconsistsof:stand,sumpcase,collecting bottle and connecting pipes. Thestandwas approximately 1350mm tall andtheprotectivecageagainstbirdswasselectedwithanaperturesizeofapproximately0.7mm.Thestandwas fixedwithasuitable fastenertoprevent the collectionbottles from fallingofftheshelveswheretheywerelocated.Thesumpcasewasselectedfromasuitableplasticmaterial thatwasresistant tochemicalsandnotchargedwithstaticelectricity.

Eachsumpcasewasmarkedwithaserialnumber,withgettingaconversion factor(F)foreachcontainer,andthecalculationsweremadeoverthisFfactor.Theconversionfactorwas calculated from the average effectivediameter of the sump case. The average ofthese 24 measurements was taken at 12points around the container by measuringthe inner and outer diameters. Thus, the Ddiameter required for the conversion factorwasobtained.Thedimensionswereroundeduptothenearestmillimetreandfactor(F)wascalculatedas1/m2withthefollowingformula.Whentheweight(milligrams)ofthecollectedsedimentwasmultipliedby this factor, theresult was milligrams per square meter(mg/m2).

(1)

Figure 5. PM (deposited dust) Measuring Points, (6) beside Guest Parking Area, (7) front of Dock 3, (8) next to Loading Area 4-5, (9) Bilge Area

The measurement period was 2 (two)measurements per month at the pointsspecifiedinFigure5andatspecifiedperiods,and a total of 2 (two)months. The average

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2.2. Air Quality ModellingThe air quality modelling process is

prepared using the ISCST3 (IndustrialSource Complex– Short Term) modelprogramapprovedbytheU.S.EnvironmentalProtection Agency. The ISCST3 model isan internationally recognised modellingprogram used worldwide by manyresearchers, supervisory and authoritybodies to predict pollutant concentrations.GaussianDistribution[37]formsthebasisofthemodel.With thismodel,many emissionsources can be modelled simultaneously orseparately.ISCST3calculatesthedistributionofemissionsfromsourcesaroundthesegroupof resources, long-term concentrations atgroundleveloratdesiredheight,andground-levelprecipitation.

In order to use the modelling program,source,emissiondataandmeteorologicalandtopographical data were inputted into theprogram.Themeteorologicaldatawerehourlywind blowing directions and frequencies,hourly wind speeds, average hourlytemperatures, daily average mixture heightand stability class values. The evaluation ofstability classes is made according to thestabilitycategoriesofPasquill[38].Inaddition,inaccordancewithmeteorologicaldata,wind

rosewascreatedbasedonthedirectionofwindand thenumberofblows.For topographicaldataentered in themodel, topographicmapof the regionwas used. Cartesian and polarcoordinate systems were inputted into themodellingprogram.Theexaminedregionwasdividedinto500m.intervals(x-yaxes)intherangeof0-2kmandtheaverageconcentrationvalues were determined at the designatedreceivingpoints. Inordertoseetheeffectofthe buildings around the port to dispersion,theheightsof thebuildings around theportaswellastopographywerealsotypedintothemodel.

The concentration areas were calculatedfor each source and thrown into a commonpolarandCartesiancoordinatesystem.Finally,emissions from all sources were collected.The model also could take emissions fromvolume and surface area into account. As aresult of operating the model, monthly andannual average PM concentrations amountswere obtained at the port and the annualdistributionof thesePM concentrationswasdetermined.

3. Results and Discussion3.1. Particulate Matter Measurement Results

The first, second and third measurementresultsobtainedfrom5sources,andthemeanandlimitvalueofthesevaluesareshowninTable2fortheemissionofPM10withintwomonths.

Code Name of the SourceMeasurements (mg / Nm3) Average

Value(mg / Nm3)

Limit Value (mg

/ Nm3)1st

measurement2nd

measurement3rd

measurement

1 StockArea(warehousearea) 1.50 1.36 1.44 1.43 3.0

2 DockNo3(loading-unloading) 1.56 1.84 1.70 1.70 3.0

3 DockNo4(loading-unloading) 1.84 1.36 1.50 1.57 3.0

4 BesideWeighbridge 1.78 1.48 1.58 1.61 3.0

5 TruckCrossingRoad(smallport) 0.90 1.08 0.78 0.92 3.0

Table 2. PM10 Measurements Results

amount of dust settled in one day wascalculatedbydividingthemonthlyvaluesbythenumberofdays.

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In the examination, it is detected thatthehighestvalueforthefirstmeasurementwasatdockno.4with1.84mg/Nm3. It isseen that the lowest PM10 concentrationwas on the truck crossing roadwith 0.90mg/Nm3. When checking the other twomeasurementresults,itisdeterminedthatthelowestvaluesobtainedwereinthesamedirectionwiththefirstmeasurements,butthehighestvalueswereduetothedock3.Whenexaminingthelengthsanddepthsofdocks3and4;itisdeterminedthatthedocknumber3was580meters long and10mdeepandthedockno.4was290m.longand12m.deep.Whereasthedockwascapableofacceptingmoreshipsthanthedock4atonce,theshipswithmoredraftcouldberthto the dock 4. These two conditions arefactorsthataffect the increaseofhandlingactivitiesandaccordingly increaseofPM10emissions. As it can be seen from theseresults while the first measurement wascarried out, more ships were loaded andunloadedatdock4;dock3,whichhadthecapacitytoacceptmoreshipswasworkingmore actively during the period of theothertwomeasurements.Asaresultoftheresults obtained, we can clearly say thatthe dock length and dock depth directlyaffected thePM10 concentration formed intheport.Whentheaveragevaluesaretakenintoconsideration,itisunderstoodthatthelengthofthedockismoreeffectivethanthedepthofthedockintermsoftheeffectontheemissionamount.

Considering the wind direction in

the port, it is determined that theseconcentrationsdidnotexceed theTurkishair quality limit value of 3.0 mg/Nm3 as a result of the measurement valuesobtained at 5 points 3 meters awayfrom the dust source (PM10) (suspendedparticulatematter).Itisalsoobservedthatthe European PM10 concentration limitvalue,whichwas50μg/m3,hadnotbeenexceeded. Although the limit values hadnotbeenexceeded, ifweevaluatedtheairqualityoftheregionintermsofthelocationoftheport,thefactthataportlocatedinthecentreofthecitypollutedtheairthatmuchmightcauseproblemstobeconcernedwithhumanhealth.

The mean and limit values are showninTable3with the resultsof2periodsofPM (deposited dust) in 4 different pointsat the port. When the first and secondperiod measurements are examined, it isdetermined that the amount of depositeddustbesidethedock3andtheloadingarea4–5whichweretheactiveareasoftheport,wasmuchmorethanthebilgeareaandtheharbour’s guest car park which were inthescopeofharbour.ItisclearlyseenthatthehighestPM(depositeddust)valuewasin the 8-coded region in the 2nd periodmeasurements with 203 mg/m2-day andthelowestvaluewasinthe6-codedregionwiththe80mg/m2-day.Asitcanbeclearlyunderstood from these results, althoughtheamountofPM(depositeddust)causedby the port operations had affected theport'simpactarea,itisdeterminedthatthe

Code Name of the Source

1st Measurements (mg/m2-day)

2nd Measurements (mg/m2-day)

Average Value (mg/m2-day)

Limit Value (mg/m2-day)

6 BesideGuestParkingArea 80 82 81 450

7 FrontofDock3 191 185 188 450

8 NexttoLoadingArea4-5 185 203 199 450

9 BilgeArea 86 84 85 450

Table 3. PM (deposited dust) Measurement Results

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significantamountofitaccumulatedintheactiveareasoftheport.

It is determined that the limit valueof450mg/m2-daywasnotexceeded,whentheresultsofthedepositeddustmeasurementscarried out in the port are evaluated inaccordancewith theTurkishAir PollutionRegulation.

Loading, unloading and storingoperationsthatmightcausedustemissionarecarriedoutattheport.Emissionfactorsarecalculatedbasedonthemassflowrateof themeasurementsmade, based on thehourly production amount of 2,248 tons/hour. Emission factors are determined as0.005 kg/ton for loading and unloadingand2.9kgdust/haperday forstorage. Inaccordance with the specified processes,mass flow is found to be 11.24 kg/hourfor loading and unloading, and 0.15 kg/hourfor1.3-hectare(ha)storage.Thetotalamount of emissions discharged to theatmosphere from the places other thanthe chimney is determined as 22.63 kg/hour. This is approximately 23 times overthe limit valuedeterminedby theTurkishAirPollutionRegulationas1.0kg/hour.Asa consequence of this result, it is clearlyseen that the dust emissions caused bythe operation in the ports reached verydangerouslevels.

3.2. Air Quality Model ResultsAs a result of the researches, climate

and different factors related to climateand occupy an important portion ofthe amount of air pollution, along withsome other geographical factors such asgeographical location and topography. Itis possible to sort these climate-relatedfactors affecting air pollution in the formofwind,atmosphericstabilityandthermalinversions,topography[39].Inthisrespect,theportregionwindrosecreatedbyusingthe data obtained from the meteorologystationisshowninFigure6.

Asaresultofthemodelstudy,whenwe

examinethewindspeedanddirectionsthatwere effective in emission distributions;according to the specified measuringstationdata;theaveragewindspeedwasof1.8m/speryear.Windspeedsrangedfrom1.5m/sto1.9m/sindifferentmonths.Thefirst-degree prevailing wind direction intheregionwasthesouth-southwest(SSW)directionwithabreezenumberof3477.

Figure 6. Trabzon Port Region Wind Rose

Monthly emission values and theannualaverageemissionvalueobtainedasa result of the air qualitymodelling studyconductedtodeterminetheconcentrationsof dust emissions emitted from the portaroundtheportaregiveninTable4.Highervalueswereobtainedinmanypointsduetothe increase inPM10 concentrations in theair and dust emissions from the ground,especiallyinthesummerwiththedecreaseofprecipitationintheregion.However,itisthought that thehighvalues in thewintermonths such as December and January,which are determined from time to time,mightbeduetohouseholdheatingarousedfrom the samplingpoint in the settlementarea and also due to the increase in thenumberofshipsarrivingattheportduringtheseperiods.

In addition, when the monthly PMconcentrationsvaluesobtainedasa result

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of theairqualitymodellingstudygiven inTable4areexamined,itisclearlyseenthatthelowestvalueisthevalueinApril,whichisoneofthemostprecipitationmonthsoftheprovincewith9,2180mg/m2-day.Asaresult of these values, it can be predictedthat seasonal changes as well as thenumberofshipsaffect theamountofdustemission at the port. Although developed

Months Particulate Matter (mg/m2-day)

January 22,60

February 17,07

March 18,64

April 9,21

May 13,79

June 15,69

July 17,34

August 28,64

September 22,71

October 24,85

November 21,67

December 25,69

AnnualAverage 21,33

Table 4. Amounts of PM Deposition Obtained by Air Quality Modelling

Figure 7. Monthly and Annual Average Amount of PM Graph

countries have recently noticed the globaldamages of fossil fuels, the widespreaduseofthesefuelsstillcontinues.Coalfiringcauses the release of dust pollutants suchasparticulatematter(PM)intotheair[40].InTurkey,whichispoorintermsofoilandgas resources, the situation isprogressingwiththeuseoflow-qualityligniteinenergyproduction. China imports the world'slargest stone coal, and Turkey is the 7thlargest importer. Turkey is the countryplanning the most lignite and stone coal-firedthermalpowerplantsintheEuropeanRegion in terms of number and capacity[40]. Therefore, it is understood that theemission value, which had an averageannualvalueof21,3335mg/m2-day,isveryclosetothevaluesinSeptember,November,December and January, and emissionsfromhouseholdheatingintheregionhadasignificantimpactonportemissionvalues.

When the obtained results werecompared with the measurement resultsmade in a coal-fired thermalpowerplant,it was determined that the measurementresults obtained at the port were almosthalf lower than the measurement resultsat the thermalpowerplant (themeanPMmeasurementresultsbetween2013–2017

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for4pointswere69.41;30.32;30.97;and26.44mgm2dayrespectively[33]).

The distribution graph obtained as aresult of the air quality modelling studyconducted to determine the distributionof dust concentrations emitted from theport around the port is given in Figure 8.The wind rose prepared for annual blownumbers and directions where the windcame from and the distribution graphpreparedforannualaverageconcentrationsshows that the model consequences gaveresultsconsistentwiththewindrose.

Figure 8. The Particulate Matter Concentration Map

In the examination made on theparticulatematterconcentrationmap, it isdetermined that dust emissions affectedanareaofapproximately25km2.AsitcanbeseeninFigure9,theportsubjecttothestudyisoneoftherareportsinthecentreofthecitywhereit is locatedandsoclosetothecitycentre.The25km2impactareamentioned above threatens the regionwhere people live intensely and have thehighestaveragepopulationduringtheday.

Thereisaninternationalmainroadwithanaverageof50thousandvehiclespassingannually, just 100 meters from the southdirection of the port area subject to thestudy.PM10, PM (depositeddust) andVOC(Volatile Organic Compounds) emanating

Figure 9. The Satellite Image of the Closeness of the Port to the City Centre

from vehicles are important sources ofpollution in the urban air. According toTUIK (Turkish Statistical Institute) 2019data, the exhaust emissions of vehicleswhich are in traffic create a significantamount of air pollution in our countrywherethereareapproximately7.5millionvehiclesovertheageof16[41].Accordingto this information, whenwe think abouthow the emissions originating from thetrafficaredistributedinthesamedirectionby combining with the emissions flowingoutfromtheport,itisclearhowmuchtheportareaposesahumanhealthrisk.

Moreover, when the data obtained fromtheTrabzon-Meydan (Square)measurementstation,whichalsoincludesthePortregion,itisdeterminedthatin323-daymeasurementsfrom2019,PM10valuesarefoundtoexceedtheEUlimitvaluein94days[42].Whenthevaluesmeasuredinthespecifiedstationareanalysed,it is determined that approximately 32% ofthese values are emissions originating fromtheport. In ourworldwhere approximately7milliondeathsarecausedbybothoutdoorand indoor air pollution each year [43], thecontributionofportstothispollution isataconsiderablelevel.

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4. ConclusionsAsaresultofoperationssuchasloading,

unloading and storage in Trabzon Portand other port activities that take placeoutside of these, a significant amount ofparticulate matter (PM) is emitted to theatmosphere. The loading and unloadingactivities carried out at the dock had themost profound effect on the PM10 valuesobtained at the port area. In addition,storageandtransportationactivitiesintheportcausedPM10tooccuralmostasmuchas loading and unloading activities. Theseactivities thatwementioned also affectedPM (deposited dust) emissions, anothertype of dust. It is determined that PM(depositeddust),whichoccurredasaresultof the activities taking place at the quay,mostlyaccumulatedinthecloseregionsofthequays.Itisseenthatthiseffectreducesby almost 50% in the car park and bilgearea,whicharetheimpactareaoftheport.

With the air quality distributionmodelling,whichistheresultofcombiningthe port region with meteorological andtopographicdata,itisdeterminedthatthedataobtainedfromthesourcesmentionedintheportisaffectedbydustemittedintotheatmosphereasaresultofportactivitiesof a region of 25 km2 including the port.While approximately 2 km2 of this areaconstituted the port area, the remainingpart is located in the central region ofthe city. Dust emissions, which can reachapproximately 3 km in the east and westdirections,canalsoreach5kminthesouthdirection according to the model results.Theregion,whichisstatedasthecitycentreand a high population zone, is locatedat a distance of 300 meters in the southdirectionoftheharbour,showingthattheseemissionsarehighly threatening the livinglife.Basedontheresultthatthedispersiondistances obtained at the selected portwillincreaseordecreasedependingonthechangeofloadamountsandwindspeedsatportsinotherregions,whenchoosingaport

establishment, we can make an apparentdeductionthatthedistanceoftheportfromthecitycentreisoneofthemostimportantfactorstobeconsidered.

As a result of the study, it ismade outthatthewindisthemost influential inthedispersion of the dust,which is causedbyport activities. At all ports and especiallyat ports like Trabzon Port,where loading-unloading, storage and transportation ofcargos such as coal, cement and grain arethemostfrequentbyships,theseactivitiesmayresultingeneratinghighlevelsofdust.Inordertoreducedustemission,measuressuchasplacingwindcuttingboardsat theportarea,coveringthematerialsstoredoutintheopen,keepingtheupperlayersofthematerialshumid,ensuringregularwateringandcleaningoftheportroadsarerequired.

Using cyclone separators in portbuildings with coal fired central heatingsystemsormakinguseofalternativeenergysourcessuchaselectricityornaturalgasforheatingwoulddecrease theamountofPMemissions. Achievingthermal insulation isalso essential for reducing PM emissions.In this way, fuel consumption could bedecreasedandlessairpollutantswouldbereleased into the atmosphere. Along withthese,greenwavecanbeappliedontheroadneartheportforacontinuoustrafficflowinordertoreducetheseemissionscausedbyvehicles, which are occurred generally onaccelerationandbraking.

In line with this study, estimation offutureemissionscanbecarriedoutbyusingthenumberofshipsarrivingtheportandthedata from cargo handling with regressionanalysis method. Accordingly, necessarypreventions could be taken for potentiallymoreseriousairpollutionthreats.

AcknowledgementFor the estimations on this study,

the authorized personnel certificate onemissionmeasurementhasbeentakenfromThe Turkish Ministry of Environment and

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Urbanization.WearealsothankfultoNEVALaboratoryemployeesfortheirgreateffortoneachmeasurement.

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JournalofETAMaritimeScienceCanca&Kökkülünk/JEMS, 2020;8(4):302-308

10.5505/jems.2020.89421

Is Existing Maintenance System Adequate for Sulphur 2020 Amendments?

A. Yaşar CANCA1, Görkem KÖKKÜLÜNK2

1İnceShippingandTrading,DPA&TechnicalManager,Turkey2YıldızTechnicalUniversity,NavalArchitectureandMaritimeFaculty,[email protected]; ORCIDID:https://orcid.org/0000-0002-0058-3969gö[email protected]; ORCIDID:https://orcid.org/0000-0001-6788-2982

CorrespondingAuthor:GörkemKÖKKÜLÜNK

ABSTRACT

Sulphur 2020 regulation as a reduction of sulphur emissions has been caused a bigchallengeviausingnewfuelsinthemaritimeindustry.Consistentchangesinthechemicalandphysicalpropertiesofthesenewfuelsmakeclassicalmaintenancemethodsasbrakedownorplannedinadequateandendangeroperationalandnavigationalsafetyonships.Withinthisframework,shipmaintenancesystemsneedtobereevaluatedinaccordancewiththenewmarinefuels.Inthisstudy,firstlyimpactsofnewmarinefuelsonshipshavebeenevaluatedbymeansofaliteraturereview.Furthermore,repairandmaintenancesystemshavebeenpresentedthatarecurrentlyusedonboardships.Subsequently,advantagesofapredictivemaintenancesystemthatwillreduceriskbyconstantlymonitoringthepotentialcriticalcharacteristicsof VLSFO over other maintenance systems have been discussed. Then, assessments ofcompliancefuelhavebeendoneinaccordancewithfuelproperties,problemsandcorrectiveactions.Lastly,discussionsandsuggestionshavebeenprovided to theshipownersandtechnicalmanagements.

Keywords

Sulphur2020,VLSFO,PredictiveMaintenance,MarineEngines.

TECHNICALREPORT(RP)

To cite this article:Canca,A.Y.,Kökkülünk,G. (2020).IsExistingMaintenanceSystemAdequateforSulphur2020Amendments?.Journal of ETA Maritime Science,8(4),302-308.To link to this article: https://dx.doi.org/10.5505/jems.2020.89421

1. IntroductionNowadays, ships have faced with

new technical problems via using verylow sulphur fuel oil as of Sulphur 2020Regulation which affect many parametersin themaritime industry. There are threemajor alternative solutions in order tocomply with new Sulphur regulationthat are firstly using of very low Sulphur

fuel oil (VLSFO) or marine diesel oil,secondly exhaust gas cleaning systemsuch as scrubber and thirdly the use ofnonpetroleum-based fuels as liquefiednaturalgas[1]-[3].

SOxemissionisnottheonlycomponenttobecontrolledonmarinedieselengines.Also,amethodthatreducesSOxemissionsshould not have an increasing effect on

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otherpollutingcomponents.While SOx emissions have been

significantly reduced with the scrubbersystemsasanexhaustgascleaningsystem,theadditionalenergyasafuelconsumptionfor the operation of the system and theneutralizationof theacidicwashingwaterinscrubberswillconsiderablyincreasetheCO2emissions[2][4].

In addition, the control of a verycomplexchemicalprocesscomplicates theoperationalprocessofscrubber.Moreover,usingofaseparate tank for thestorageofsludgegeneratedduringtheSOxbindingofNaOH using in decomposition of SOx andthedisposalofthesludgeformedatcertainintervalscausesadditionaloperatingcostsandincreasedpersonnelworkloads.

The effects of alternative fuels andexhaust gas cleaning systems which areused to reduce SOx emissions have beencompared on the initial investment cost,operating costs, storage requirementsandSOx,CO2emissions,inTable1[2][5][6].

1.1. New Marine Fuels and Impacts on Ships

Theapproximatenumberofshipswithscrubbersinoperationandonordercouldbe determined as 2702 and 2756 by theyear of 2020 and 2021, respectively [7].The rest of ships have been using a lowsulphurfueloilormarinedieseloilwitha

smallmodificationofengines.Asaninsidecomposition of marine fuels, there arekerosenetoreducetheviscosityofresiduesthrough blending, light and heavy gasoil,diesel, residue fractionwith fluid catalyticcracker and visbreaking process. Theseblends could be produced consideringmarine fuel standards with maximumdensity limit that affects ignition quality,maximum silicon and aluminum limits inorder to avoid abrasive corrosion insidefuel system; andmaximum total sedimentlimitsoastoreduceimpurities[2][8].

Hydrotreating, coking and crackingprocesses remove sulphur in the refineryprocess [9] which forms inside crudeoil from 0.03 to 7.89% [10] by weight.There are negative impacts on producingof large volumes of marine fuel suchas unsustainable reliability and lack ofexperience. For this reason, residues areblendedwithdistillates in refineries soastoobtainlowSulphurfueloil[2].Thisnewsituation could result with some negativeimpactsas;• Negative impacts on combustion

chamber of the substances remainingin the fuel as a result of the crackingmethodsusedinobtainingnewfuels,

• Negativeimpactofusingwrongcylinderoil with VLFSO on two stroke dieselengine,

• Filtrationandseparationprocesses

Capital Investments

Operating Costs Storage SOx CO2

HFO Low Low Unlimited High High

HFO/Scrubber High Medium SlightlyLimited Low High

MGO Low Veryhigh Unlimited Low High

Methanol Veryhigh High Limited VeryLow VeryLow

LNG Veryhigh VeryLow Limited VeryLow Low

Table 1. Comparing of Different Fuels According to Ecologic and Economic Factors [2][5][6]

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• Refineries have produced new fuelwith different specifications withinrequired Sulphur limits which causescompatibility, stability and waxingproblems.Since there are only chemical tests of

new very low Sulphur fuel oil not a testson marine diesel engines by refineries,the testing and evaluating of the resultswould be done on existing working shipsviatryandseemethod.Unfortunately,thissituationstrikesthefactthatexistingshipsare used as test tools. Furthermore, themalfunctions and failures that occurredduetoverylowSulphurfueloilcouldresultin detriment of navigational safety andcommerciallosses.

2. Necessity of New Maintenance System with New VLSFO

Maintenance for themaritime industryincludesmandatoryrequirementsthatareconcern with the maritime regulations.It also has to contribute effective andefficientshippingoperations.Furthermore,inspectiveprocedureshavebeenextendeddue to requirements of classificationsocietiesandrulemakers[11].

AplannedmaintenancesystemwhichiscompulsoryapplicationincompliancewithInternational Safety Management (ISM)Code involves schedule tasks. There arealsobrakedown,preventiveandpredictivemaintenance systems which are rarelyusedonboardships.Conventionally, thereare planned and unplanned maintenancesystems and also preventive or correctivein compliance with European standardEN 13306: 2017. Furthermore, preventivemaintenance can be expressed as timebasedplannedmaintenanceandconditionalmaintenance[12][13].

In maritime industry; scheduledreplacement, scheduled overhaul,corrective maintenance, continuous on-conditiontaskandscheduledon-conditiontask are utilized as the maintenance

systems[14,15,16].Essentially,preventive,correctivemaintenanceandconditionbasedas predictive maintenance approacheshave been expressed among the variousmaintenancesystems[14][17][18][19].

Among these, Predictive MaintenanceSystemhasbecomemuchmore importantfor the maritime industry with theintroductionofnewVLSFOfuels.Themainobjective of the predictivemaintenance isoriginatedfromthecurrentconditionoftheengines. Moreover, it can be expressed asmonitoringofthemachineryandabidedbyitscurrentcondition.Italsoinvolvessensorselection and betimes or continuous datameasurementwithdifferentmonitoringofperformance,lubrication,thermal,acousticandvibration[20].

Fromthedifferentviewpoint,predictivemaintenanceispolicywhichusesmonitoringdataofindirectconditionsoastoestimateforthcoming malfunctions. There are twokind of predictive maintenance modelwhich contains useful life prediction andmaintenance optimization. Thus, it can beexpressed as statistical, knowledge basedand data driven strategies with featureengineering,overfitting,andregularization[21]. As an example of statisticalmethod,speed and fuel consumption data of 14monthswereusedfortheshipperformanceevaluation[22].

In substance, predictive maintenancehave been predicated on early diagnosisof the engine failures which prevents thedegradation of engines. In this systems,machineriesarefittedwithasensorsanddataacquisitionsystemwhichensurebeforetimefailureprediction.Therefore,thiswillresultin firstly higher performance of engines,reduction of spare part usage, enhancedprofitanddecreasingofmaintenancecosts[23].Predictivemaintenancealsoprovidesadecreaseinfailurerisksandcosts,enhanceperformance in despite of higher initialinvestmentcosts[24][25][26].

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3. Results and Conclusion 3.1. Assessment of the New Compliant Fuels

Using of 0.5% sulphur marine fuelswithanincreasingnumberofdifferentfuelblend typeshave causeproblems suchasinstability incompatibility. Furthermore,fuel lines, filters and tanks have beenredesignedinordertodecreasetheriskofinstabilityandincompatibility[27].

There are some problems aboutusing compliant fuel as low viscosity,compatibilityproblems,stabilityandflashpoint which are about operational andsafetysubjects[28].Inthisrespects,Table2illustratesthefuelproperties,problemsandcorrectiveactionsofanewcompliantfuel.

3.2. Assessment of the Maintenance System with Compliant Fuels

When considered from the new lowsulphur fuel’s point of view, especiallydiesel engines have to be constantlyobserved while working even ifspecificationofthelatestreceivingfuelissuitable. This is because of compatibility,stabilityandothernegativeimpactsoflowsulphur fuel. Therefore, this will lead tochangesinconventionalmaintenanceandmonitoringstandardsonships.

Traditionally,breakdownmaintenance,planned maintenance and preventivemaintenance are insufficient as theunexpected impact of using new lowsulphur fuel oil. For instance, pistonrings,cylinderlinerandfuelpumpscouldbe broken after a few hundred hours ofoperation. Consequently, the plannedmaintenancesystemswhicharecurrentlyused on the ships could be revised byusing predictive maintenance in thecriticalequipmentintheshipengineroom.Particularly,itcouldbeappliedtothefuelsystems due to compulsory drydockingprocesses.

The new type of fuel has not been

tested on current marine diesel enginesby manufacturers. Hence, its effects aredifficult to predict. Furthermore, thecorrosivesubstances inside the fuelwerethrown with sulfur. However it sticksdirectly with the new fuel because oflow sulfur and bonding to themetal andbecomescorrosive.

In addition to the frequent analysisof fuels and oils for using of newly usedlow sulphur fuels, scavenge drain oil andflue gas analysis have also becomemoreimportant.Because,theeffectofadditivesinside the lubricating oils has a differentimpactonusingofnew fuelson ships. Inother words, the influence on enginesof using new fuel should be constantlymonitored such as temperatures,pressures, filters and exhaust gascomponents as required for predictivemaintenance.

3.3. Assessment for Ship Owners • Shipownersasfirstgeneration;moved

from other industries to maritimeindustry and became ship owner-operator. When considering of repairand maintenance on marine engines,generally, the first method of brakedown maintenance was utilized formaintenanceandspareparts.Plannedand preventive maintenance areperceivedasunnecessary.

• Shipowners as second generationwho are the children of the firstgeneration; although reluctant toplanned maintenance, internationalrules and regulations have beenobligatedtoimplementationofplannedmaintenance.

• Third generation shipowners as shipoperators; budgets and targets are socrucial however plannedmaintenancehave been implemented in theircompanies.In conclusion, shipping companies

shouldhaveapurchasingdepartmentwith

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Fuel Properties Problem Corrective Actions

High density [29] Difficultseparationduetounusualdensityofblendfuel.

TooperatetheseparatorsseriallyinPurifier+Clarifiermode,respectively.

High ash content [32]

Excessivecorrosioninthepistonringsandcylinders.Depositformationintheexhaustvalve,pistonringsocketandturbinewings.

Operatingtheseparatorwithhighefficiencyandputtingfilterwithlowporediameter(<50µm)intheoutletifnecessary.

High vanadium [29] Hightemperaturecorrosionanddepositformation

Tousetheadditiveswhichdeactivatethevanadiuminordertopreventhightemperaturecorrosion.

Sodium (sea water) [32]

Depositformationintheturbinewings.Excessivesludgeaccumulationintheexhaustvalves.Depositformationintheinjectornozzleandpistonrings.

Tooperatetheseparatorinlowflowrateandhighefficiencyandtodecomposemaximumwater.

High Al+Si [30] Highcorrosioninfuelpumps,cylinderjacketandpistonrings.

Forclassicalseparators,tooperatetheseparatorsinserialmodewithlowflowrate.

Fuel incompatibility [31]

Excessivesludgeoutletfromtheseparators,increaseofthecorrosioninthefuelpumps,depositformationintheinjectornozzle,exhaustvalveandturbine.

Toperformconformitytestsforfuels.Ifitisnotpossibletoperformcompatibilitytest,totransfertheoldfuelinthefueltankstootherfuelsbeforefueltank.

High CCAI [29] Knockingproblem Toactivatethepreheaterofthemainenginebeforestartingofmainenginetokeeptheenginehot.

Low flash point [31] Safetystorageproblembecauseoflowerflashpoints

Limitsto60°CaccordingtoSOLAS,Protectingfuelleakagesinfuellinesandventilationofserviceandsettlingtanksspaces.

Stability [29,30] Exhibitsthepotentialofparticleformation,sediment/gummingduringusingandstorageoffuelduetogravitationofasphaltenesresultinginsludgeformation

Notmixingofdifferentfuelblends.Suddentemperatureincreaseanddecreaseshouldbeavoidedduringchangeoverperiod.

Clouding /Pouring [31,32]

Itistheflowpropertyinlowtemperatureandaffectsfueltransfer.Highcloudpointcausespluggingoffilters.

Fuelshouldbeheatedadequatelyhigherthanpourpointandprobablewaxformationpoint.Thus,thetemperatureoffuelmustkeepabove10°CofcloudPointofVLSFO

Lubricating [30] Excessivewearonfuelpumpandinjectionvalvesduetolowersulfurcontent.

Additivescanbeused.Measuresmustbetakenthattheviscositywillnotdropbelow2cStespeciallyinthetransitiontolowviscosityfuels.

Table 2. Assessment of Fuel Properties, Problems and Corrective Actions in Accordance with Compliance Fuel


planning and reporting. Moreover, risksthatwill occurwhenplanningormakingdecisions should be well calculated. Riskassessment has been done. Technicalmanagements of shipping companies has

operatedshipyardprocesses,orders,sparepart management and engineer officersthat are working on ships. Therefore,predictive maintenance has becomemandatory in accordancewith new fuels

307


of maritime sectors. Knowledge, skillsand experience have become even moreimportantandshiptechnicalmanagementshouldbedoneinamoreprofessionalwaywithaseparatepurchasing,maintenance,educationandtrainingdepartment.

References[1] Solakivi, T., Laari, S., Kiiski, T., Töyli,

J., Ojala, L. (2019). How ShipownersHaveAdaptedtoSulphurRegulations– Evidence from Finnish SeaborneTrade. Case Studies on TransportPolicy,7(2),338–345.

[2] Chu-Van, T., Ramirez, J., Rainey, T.,Ristovski,Z.,Brown,R.J.(2019).GlobalImpactsOfRecentIMORegulationsonMarine Fuel Oil Refining Processesand Ship Emissions. TransportationResearch Part D: Transport andEnvironment,70,123–134.

[3] Zhu, M., Li, K. X., Lin, K.C., Shi, W.,Yang, J.(2020).HowCanShipownersComplywiththe2020GlobalSulphurLimit Economically?. TransportationResearch Part D: Transport andEnvironment,79,102234.

[4] Williams, P. J. l. B. (2010). TheNatural Oceanic Carbon and SulfurCycles:ImplicationsforSO2AndCO2Emissions from Marine Shipping.InternationalJournaloftheSocietyforUnderwaterTechnology,29(1),5–19.

[5] IMO. (2016a). Methanol as MarineFuel: Environmental Benefits,TechnologyReadiness,andEconomicFeasibility. IMO, London. http://www.methanol.org/wp-content/uploads/2016/07/IMO-Methanol-Marine-Fuel-21.01.2016.pdf

[6] IMO. (2016b). Studies on theFeasibilityandUseofLNGasaFuelforShipping.IMO,London.

[7] DNV-GL. (2019). Alternative FuelsInsight, Status on the Uptake ofScrubbers,UpdatedFebruary1,2019.https://www.dnvgl.com/services/

alternative-fuels-insight-128171[8] Vermeire, M. B., (2012). Everything

YouNeedtoKnowAboutMarineFuels.Chevron Global Marine Products.h t t p s : / / s i l o . t i p s / d own l o a d /everything-you-need-to-know-about-marine-fuels-4

[9] Elvers,B.(2008).HandbookofFuels:Energy Sources for Transportation.h t t p s : / / d o i . o r g / 1 0 . 1 0 0 2 /elsc.200890010

[10] Agarwal, P., Sharma, D. K. (2010).Comparative Studies on the Bio-Desulfurization of Crude Oil withOther Desulfurization Techniquesand Deep Desulfurization ThroughIntegrated Processes. Energy Fuels,24(1),518–524.

[11] Michala,A.L.,Lazakis,I.,Theotokatos,G., Varelas, T. (2015). PredictiveMaintenanceDecisionSupportSystemforEnhancedEnergyEfficiencyofShipMachinery. International Conferenceof Shipping in Changing Climates,Glasgow,UK.

[12] Ang,J.H.,Goh,C.,FloresSaldivar,A.A.,Li,Y.(2017).Energy-EfficientThrough-LifeSmartDesign,ManufacturingandOperation of Ships in an Industry4.0. Environment Energies, 10, 610.doi:10.3390/en10050610

[13] Simion, D., Purcărea, A., Cotorcea,A., Nicolae, F. (2020). MaintenanceOnboard Ships using ComputerMaintenance ManagementSystem. Scientific Bulletin of NavalAcademy, XXIII, 134-141. doi:10.21279/1454-864X-20-I1-017.

[14] Kimera, D., Nangolo, F. N. (2020).Predictive Maintenance for BallastPumps on Ship Repair Yards viaMachine Learning. TransportationEngineering,2,100020.

[15] Emovon, I. (2016). Ship SystemMaintenance Strategy Selectionbased on DELPHI-AHP-TOP- SISMethodology. World J. Eng. Technol.,

308

4,252–260.[16] Rausand,M.,Vatn,J.(1998).Reliability

Centered Maintenance. Risk andReliability in Marine Technology,Balkema,Holland.

[17] Dhillon, B. S. (2002). EngineeringMaintenance: A Modern Approach,CRCPress,Washing-ton,D.C.

[18] Waeyenbergh,G.,Pintelon,L. (2004).Maintenance Concept Development:A Case Study. Int. J. Prod. Econ., 89 ,395–405.

[19] Anil,R. (2016).OptimalMaintenanceLevel of Equipment with MultipleComponents.J.Qual-ityMaintenanceEng.,22(2),180–187.

[20] Alhouli, Y. (2011). Developmentof Ship Maintenance PerformanceMeasurement Framework to Assessthe Decision Making Process toOptimise in Ship MaintenancePlanning(PhDThesis).TheUniversityofManchester,FacultyofEngineeringand Physical Sciences, School ofMechanical, Aerospace and CivilEngineering.

[21] Dekker, K. J. (2020). MaintenanceOptimization Through RemainingUseful Life Prediction A Case StudyFor Damen Shipyards (MSc Thesis).University of Twente, Faculty ofIndustrial Engineering and BusinessInformationSystems.

[22] Bialystocki,N.,Konovessis,D.(2016).On the Estimation of Ship’s FuelConsumption and Speed Curve: AStatistical Approach. J. Ocean Eng.Sci.,1,157–166.

[23] Jimenez, V. J., Bouhmala, N.,Gausdal, A. H. (2020). Developing aPredictive Maintenance Model forVessel Machinery. Journal of OceanEngineering and Science, 5 (4), 358-386. https://doi.org/10.1016/j.joes.2020.03.003

[24] Sakib,N.,Wuest,T.(2018).ChallengesandOpportunitiesofCondition-based

Predictive Maintenance, A review.Procedia,78,267–272.

[25] Karabay, S., Uzman, I. (2009).Importance of Early Detection ofMaintenance Problems in RotatingMachines in Management of Plants:Case Studies From Wire And TyrePlants. J. Eng. Failure Anal., 16 (1),212–224.

[26] Lazakis, I., Raptodimos, Y., Varelas, T.(2018). Predicting Ship MachinerySystem Condition through AnalyticalReliabilityToolsandArtificialNeuralNetworks. J. Ocean Eng., 152, 404–415.

[27] Ubowska, A., Dobrzyńska, R. (2020).Low-Sulphur Marine Fuels—PanaceaoraNewThreat?.SustainableDesignandManufacturing,PartoftheSmartInnovation,SystemsandTechnologiesbookseries(SIST),200,415-424.

[28] Cuong, N. M., Hung, P. V. (2020). AnAnalysis of Available Solutions forCommercial Vessels to Comply withIMOStrategyonLowSulphur.Journalof International Maritime Safety,Environmental Affairs, and Shipping,4(2),40-47.

[29] Leyson, A. (2019). Getting theChemistryRight. Bunkerspot, 16 (3),64-69.

[30] ABS.(2019).MarineFuelOilAdvisory.Retrieved October 28, 2020, fromhttps://ww2.eagle.org/content/dam/eagle/advisories-and-debriefs/marine-fuel-oil-advisory.pdf

[31] MAN Energy Solutions. (2020).0.50% S fuel operation 2020.Retrieved October 28, 2020, fromhttps://marine.man-es.com/docs/librariesprovider6/test/0-50-s-fuel-operation.pdf

[32] The Alfa Laval Adaptive Fuel LineBlueBook.(2018).Technicalreferencebooklet.


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I

AbbasMAMUDU MemorialUniversityofNewfoundland CanadaAlper KILIÇ BandırmaOnyediEylülUniversity Turkey

AyferERGİN İstanbulUniversity-Cerrahpaşa Turkey

BadrTOUZI MohammedVUniversity MoroccoCharifMABROUKI UniversitéHassan1er MoroccoEmrahAKDAMAR BandırmaOnyediEylülUniversity TurkeyHasanÖLMEZ KaradenizTechnicalUniversity TurkeyKazımYENİ İskenderunTechnicalUniversity TurkeyLeventBİLGİLİ BandırmaOnyediEylülUniversity TurkeyNourhanIbrahimGHONEIM InternationalMaritimeCollegeOman OmanÖnderCANBULAT UniversityofStrathclyde UKÖzgürDEMİR YıldızTechnicalUniversity TurkeySunaryo UniversitasIndonesia IndonesiaZiemowitMALECHA WroclawUniversityofScienceand

TechnologyPoland

Reviewer List of Volume 8 Issue 4 (2020)

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Volume 8 Issue 4 (2020) is indexed in

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IV


UCTEA - The Chamber of Marine Engineers

JEMS

Volume : 8Issue : 4Year : 2020ISSN:2147-2955UCTEA - The Chamber of Marine Engineers

JOURNAL OF ETA MARITIME SCIENCE

Journal of ETA Maritime Science

Volume 8, Issue 4, (2020)Contents


213

(RE) Dimensions of the Port Performance: A Review of Literature.Umur BUCAK, İbrahim Müjdat BAŞARAN, Soner ESMER

214

(AR) Risk-based Analysis of Pressurized Vessel on LNG Carriers in Harbor.Thaddeus Chidiebere NWAOHA, Sidum ADUMENE

242

(AR) Weighting Key Factors for Port Congestion by AHP Method.Pelin BOLAT, Gizem KAYISOGLU, Emine GÜNEŞ, Furkan Eyup KIZILAY, Soysal ÖZSÖĞÜT

252

(AR) Simulation-Based Optimization of the Sea Trial on Ships.Yusuf GENÇ, Murat ÖZKÖK

274

(AR) Measurement and Modelling of Particulate Matter Emissions from Harbor Activities at a Port Area: A Case Study of Trabzon, Turkey.Süleyman KÖSE

286

(RP) Is Existing Maintenance System Adequate for Sulphur 2020 Amendments?A. Yaşar CANCA, Görkem KÖKKÜLÜNK

302

YAVUZ, B. R. (2020) The Hard Times of Maritime Pilots in Pandemic. Istanbul Strait, Turkey

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