Universidad Pontificia de Comillas

Transcription

1 Universidad Pontificia de Comillas Ingeniería Industrial Proyecto Fin de Carrera PERFORMANCE ASSESSMENT OF THE SCANDINAVIAN MEDITERRANEAN CORRIDOR ON THE BASIS OF THE RELEVANT TRANSPORT MARKET STUDY Autor: Herrero Pinilla, Iñigo José Supervisor: Psaraftis, Harilaos N., Professor Co-supervisor: Panagakos, George P., Ph.D. Student Madrid, julio 2015

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5 AUTORIZACIÓN PARA LA DIGITALIZACIÓN, DEPÓSITO Y DIVULGACIÓN EN ACCESO ABIERTO ( RESTRINGIDO) DE DOCUMENTACIÓN 1º. Declaración de la autoría y acreditación de la misma. El autor D., como de la UNIVERSIDAD PONTIFICIA COMILLAS (COMILLAS), DECLARA que es el titular de los derechos de propiedad intelectual, objeto de la presente cesión, en relación con la obra 1, que ésta es una obra original, y que ostenta la condición de autor en el sentido que otorga la Ley de Propiedad Intelectual como titular único o cotitular de la obra. En caso de ser cotitular, el autor (firmante) declara asimismo que cuenta con el consentimiento de los restantes titulares para hacer la presente cesión. En caso de previa cesión a terceros de derechos de explotación de la obra, el autor declara que tiene la oportuna autorización de dichos titulares de derechos a los fines de esta cesión o bien que retiene la facultad de ceder estos derechos en la forma prevista en la presente cesión y así lo acredita. 2º. Objeto y fines de la cesión. Con el fin de dar la máxima difusión a la obra citada a través del Repositorio institucional de la Universidad y hacer posible su utilización de forma libre y gratuita ( con las limitaciones que más adelante se detallan) por todos los usuarios del repositorio y del portal e-ciencia, el autor CEDE a la Universidad Pontificia Comillas de forma gratuita y no exclusiva, por el máximo plazo legal y con ámbito universal, los derechos de digitalización, de archivo, de reproducción, de distribución, de comunicación pública, incluido el derecho de puesta a disposición electrónica, tal y como se describen en la Ley de Propiedad Intelectual. El derecho de transformación se cede a los únicos efectos de lo dispuesto en la letra (a) del apartado siguiente. 1 Especificar si es una tesis doctoral, proyecto fin de carrera, proyecto fin de Máster o cualquier otro trabajo que deba ser objeto de evaluación académica

6 3º. Condiciones de la cesión. Sin perjuicio de la titularidad de la obra, que sigue correspondiendo a su autor, la cesión de derechos contemplada en esta licencia, el repositorio institucional podrá: (a) Transformarla para adaptarla a cualquier tecnología susceptible de incorporarla a internet; realizar adaptaciones para hacer posible la utilización de la obra en formatos electrónicos, así como incorporar metadatos para realizar el registro de la obra e incorporar marcas de agua o cualquier otro sistema de seguridad o de protección. (b) Reproducirla en un soporte digital para su incorporación a una base de datos electrónica, incluyendo el derecho de reproducir y almacenar la obra en servidores, a los efectos de garantizar su seguridad, conservación y preservar el formato.. (c) Comunicarla y ponerla a disposición del público a través de un archivo abierto institucional, accesible de modo libre y gratuito a través de internet. 2 (d) Distribuir copias electrónicas de la obra a los usuarios en un soporte digital. 3 4º. Derechos del autor. El autor, en tanto que titular de una obra que cede con carácter no exclusivo a la Universidad por medio de su registro en el Repositorio Institucional tiene derecho a: a) A que la Universidad identifique claramente su nombre como el autor o propietario de los derechos del documento. b) Comunicar y dar publicidad a la obra en la versión que ceda y en otras posteriores a través de cualquier medio. c) Solicitar la retirada de la obra del repositorio por causa justificada. A tal fin deberá ponerse en contacto con el vicerrector/a de investigación (curiarte@rec.upcomillas.es). 2 En el supuesto de que el autor opte por el acceso restringido, este apartado quedaría redactado en los siguientes términos: (c) Comunicarla y ponerla a disposición del público a través de un archivo institucional, accesible de modo restringido, en los términos previstos en el Reglamento del Repositorio Institucional 3 En el supuesto de que el autor opte por el acceso restringido, este apartado quedaría eliminado.

7 d) Autorizar expresamente a COMILLAS para, en su caso, realizar los trámites necesarios para la obtención del ISBN. d) Recibir notificación fehaciente de cualquier reclamación que puedan formular terceras personas en relación con la obra y, en particular, de reclamaciones relativas a los derechos de propiedad intelectual sobre ella. 5º. Deberes del autor. El autor se compromete a: a) Garantizar que el compromiso que adquiere mediante el presente escrito no infringe ningún derecho de terceros, ya sean de propiedad industrial, intelectual o cualquier otro. b) Garantizar que el contenido de las obras no atenta contra los derechos al honor, a la intimidad y a la imagen de terceros. c) Asumir toda reclamación o responsabilidad, incluyendo las indemnizaciones por daños, que pudieran ejercitarse contra la Universidad por terceros que vieran infringidos sus derechos e intereses a causa de la cesión. d) Asumir la responsabilidad en el caso de que las instituciones fueran condenadas por infracción de derechos derivada de las obras objeto de la cesión. 6º. Fines y funcionamiento del Repositorio Institucional. La obra se pondrá a disposición de los usuarios para que hagan de ella un uso justo y respetuoso con los derechos del autor, según lo permitido por la legislación aplicable, y con fines de estudio, investigación, o cualquier otro fin lícito. Con dicha finalidad, la Universidad asume los siguientes deberes y se reserva las siguientes facultades: a) Deberes del repositorio Institucional: - La Universidad informará a los usuarios del archivo sobre los usos permitidos, y no garantiza ni asume responsabilidad alguna por otras formas en que los usuarios hagan un uso posterior de las obras no conforme con la legislación vigente. El uso posterior, más allá de la copia privada, requerirá que se cite la fuente y se reconozca la autoría, que no se obtenga beneficio comercial, y que no se realicen obras derivadas.

8 - La Universidad no revisará el contenido de las obras, que en todo caso permanecerá bajo la responsabilidad exclusiva del autor y no estará obligada a ejercitar acciones legales en nombre del autor en el supuesto de infracciones a derechos de propiedad intelectual derivados del depósito y archivo de las obras. El autor renuncia a cualquier reclamación frente a la Universidad por las formas no ajustadas a la legislación vigente en que los usuarios hagan uso de las obras. - La Universidad adoptará las medidas necesarias para la preservación de la obra en un futuro. b) Derechos que se reserva el Repositorio institucional respecto de las obras en él registradas: - retirar la obra, previa notificación al autor, en supuestos suficientemente justificados, o en caso de reclamaciones de terceros. Madrid, a.. de... de. ACEPTA Fdo

9 Universidad Pontificia de Comillas Ingeniería Industrial Proyecto Fin de Carrera PERFORMANCE ASSESSMENT OF THE SCANDINAVIAN MEDITERRANEAN CORRIDOR ON THE BASIS OF THE RELEVANT TRANSPORT MARKET STUDY Autor: Herrero Pinilla, Iñigo José Supervisor: Psaraftis, Harilaos N., Professor Co-supervisor: Panagakos, George P., Ph.D. Student Madrid, julio 2015

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11 PERFORMANCE ASSESSMENT OF THE SCANDINAVIAN MEDITERRANEAN CORRIDOR ON THE BASIS OF THE RELEVANT TRANSPORT MARKET STUDY Autor: Iñigo José Herrero Pinilla Supervisor: Psaraftis, Harilaos N., Professor Co-supervisor: Panagakos, George P., Ph.D. Student Project summary Introduction There is an increasing interest from the EC in implementing measures for the improvement of the trans-european transport network (TEN-T). The establishment of the TEN-T core network corridors plays a central role in this effort. The longest of these corridors is the so-called Scandinavian-Mediterranean corridor or simply ScanMed. The present thesis attempts to apply a methodology for assessing the performance of ScanMed in relation to a number of sustainability indicators. The methodology was first suggested by the EU-financed research project SuperGreen for assessing green freight corridors through a set of Key Performance Indicators (KPIs). It is for this reason that the first part of this thesis is devoted to the definition of a green corridor and the comparison of a TEN-T core network corridor with the green corridor concept. The conclusion that all characteristics of a green corridor are displayed by the freight dimension of the TEN-T core network corridors, makes the application of this methodology suitable for assessing the TEN-T corridors, too. The aim of the thesis is to prove that the benchmarking methodology developed by SuperGreen can be used in order to do a proper corridor assessment. Page 3

12 Methodology The assessment involves the construction of a sample of representative transport chains along the corridor, the estimation of KPI values for each chain in the sample and the aggregation of these chain-level indicators to corridor-level ones. The main source of information for both the selection of the chains to be examined and the KPI calculations is the transport market studies of the ScanMed itself and the corresponding rail freight corridor, which focuses on the operational characteristics of transporting freight by rail. A presentation of these studies, then, precedes the actual analysis of the corridor. The performance results are discussed and compared among the three transport modes examined (rail, road, maritime transport), while the sample results are also viewed in comparison to the original corridor. Results The values of the different transport modes are presented below: Transport Mode Costs ( /T-Km) Time (Km/h) Frequency Reliability CO2-eq emissions (g/t-km) SO X emissions(g/t-km) Rail 0, No data 12,11 0,03 Road 0, No data 75,43 0,10 Short-sea Shipping No data No data 6,02 0,09 Breaking down the table above, it is important to remark several interesting appreciations. Firstly, road transportation is the least environmental friendly among all transport modes, having the highest CO2 and SOx emissions. Secondly, it has been proved that road transportation is the most expensive mode of transportation, when talking about carrying largo cargo volumes over long distances. Even though, finding figures for short-sea shipping (SSS) was not possible, the cost of SSS on /T-Km will follow the line of rail costs, giving the huge amount of cargo volume that these ships are able to carry. Thirdly, although time (average speed) figures have been found, the values obtained are not what it was expected. The figures found only describe the speed while running the links of the corridor, but, they don t take into account the time Page 4

13 spend at the nodes. Therefore, the KPI s vales of time, is the average speed of the vehicle running the corridor not the total average speed. Finally, it was impossible to find data related with reliability. In order to gather the data necessary to calculate this KPI value, it would be necessary make an interview to all the stakeholders, and even though, the final data could not be accurate enough. Looking at the values obtained, it is easier to understand why the EU is pushing all their policies and measures to move cargo away from roads to other more environmental friendly modes of transportation. Final KPI s values of the sample corridor: Costs: Speed: Frequency of service: CO2-eq emissions: SOx emissions: 0,04 /T-Km 45 Km/h services per year (one every 11 min) 13,8 g/t-km 0,68 g/ T-Km Conclusions Albeit, the values of the KPI s depend on the sources of information, specially their availability, the final values are satisfactory. In addition, it has proved that the methodology developed by SuperGreen is valid for assessing green corridors. Page 5

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15 PERFORMANCE ASSESSMENT OF THE SCANDINAVIAN MEDITERRANEAN CORRIDOR ON THE BASIS OF THE RELEVANT TRANSPORT MARKET STUDY Autor: Iñigo José Herrero Pinilla Supervisor: Psaraftis, Harilaos N., Professor Co-supervisor: Panagakos, George P., Ph.D. Student Resumen del proyecto Introducción Existe un creciente interés tanto de la Unión Europea (UE), como de organizaciones independientes, en el establecimiento de la conocida como "Trans- European Tranport Network" (TEN-T). Se aplica una metodología basada en unos indicadores de sostenibilidad denominados Key Performance Indicators (KPI s), para analizar el Corredor más largo de esta red. Este Corredor se denomina "Scandinavian-Mediterranean Corridor" o simplemente "ScanMed Corridor". La metodología fue sugerida por primera vez, por el proyecto de investigación financiado por la Unión Europea "SuperGreen", para desarrollar un método de estudio para los denominados como Corredores Verdes. La primera parte de este proyecto está dedicado a la definición de un Corredores Verdes y la comparación de la red TEN-T con la red propuesta por SuperGreen, buscando además las similitudes entre ellas. El hecho de que la TEN-T cumpla los requisitos demandados por SuperGreen, hace que su método sea aplicable a la red europea de transporte. El objetivo de este proyecto es comprobar que el método desarrollado por SuperGreen es válido para analizar el comportamiento de distintas redes de transporte, y como en el caso de este proyecto, de redes de la UE. Page 7

16 Metodología Consiste en: primero, la búsqueda de los datos necesarios para poder hallar los mencionados KPI s del ScanMed Corridor, segundo, la selección de las conexiones (Origen/Destino) más importantes encontradas en los datos, para construir así un Corredor ejemplo, a partir del cual se van a calcular los indicadores; tercero, el cálculo de los valores de los KPI s para cada modo de transporte a partir del segundo paso, y por último hallar un valor para el conjunto del Corredor. Este valor final será el utilizado para analizar el rendimiento y prestaciones del Corredor de Transporte. Los datos del rendimiento del Corredor son analizados y comparados entre modos de transporte, desglosando los pros y los contras de cada uno. Además se hará una comparación con el Corredor original para comprobar las similitudes entre ellos y analizar si es una buena aproximación. La principal fuente de información fueron los estudios de mercado del "ScanMed Rail Freight Corridor" y el del "ScanMed TEN-T Corridor", además de diferentes bases de datos de la UE como EuroStat, ETIS-Plus o TenTec. Resultados A continuación se presentan los resultados de todos los modos de transporte y los del propio Corredor. Valores de los tres modos de transporte: Modo de Transporte Costes ( /T-Km) Tiempo (Km/h) Frecuencia Confiabilidad Emisiones de CO2-eq (g/t-km) Emisiones de SO X (g/t-km) Ferrocaril 0, No data 12,11 0,03 Carretera 0, No data 75,43 0,10 Maritimo No data No data 6,02 0,09 Observando los valores finales obtenidos para cada modo de transporte se pueden obtener varias apreciaciones. Primero, el transporte por carretera es el más contaminante, dado que tanto las emisiones de CO 2 como de SO X son las más elevadas de los tres modos de transporte. Segundo, para grandes volúmenes de Page 8

17 carga y largas distancias, queda probado que el transporte por carretera es el más caro. A pesar de no haber podido obtener, datos para el cálculo de los costes de transporte marítimo, el hecho de la gran cantidad de toneladas que mueven y las largas distancias que recorren, su precio en /Km-T sería similar al del tren. Tercero, a pesar de haber obtenido valores de velocidad media, este dato no es un valor real. Los datos encontrados solo describían la velocidad media del medio de transporte una vez esta en circulación, pero no tenían en cuenta el tiempo de espera en los nudos de transporte debido a operaciones básicas como mantenimiento, carga y descarga, etc... Finalmente, no se han podido obtener datos sobre la confiabilidad en ningún modo de transporte. La obtención de estos valores se antoja imposible, ya que habría que hacer entrevistas a todos los "stakeholders" (grupos de interés) relacionados con el propio Corredor para obtener unos datos aceptables, algo que casi no pueden ni conseguir los Directores de los Corredores. Analizando los datos, en especial costes y emisiones, queda demostrado el motivo por el que la UE está promoviendo la sustitución parcial del transporte por carretera por otros menos contaminantes como el tren o el transporte marítimo. Los valores obtenidos para el conjunto del Corredor: Costes Velocidad: Frecuencia del servicio: CO2-eq emissions: SOx emissions: Conclusiones 0,04 /T-Km 45 Km/h services per year (one every 11 min) 13,8 g/t-km 0,68 g/ T-Km A pesar de que los valores de los KPI s dependen mucho de las fuentes de información, y sobre todo de la disponibilidad de los mismo, los valores finalmente obtenidos son más que satisfactorios. Además se ha conseguido demostrar que el método desarrollado por SuperGreen es válido, algo que no se había probado hasta ahora. Page 9

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19 Preface The thesis was prepared at the Department of Transport of the Technical University of Denmark in fulfilment of the requirements for acquiring a M.Sc. Degree. Harilaos N. Psaraftis and George Panagakos were the supervisors of this project. Copenhague, 26-June-2015 Iñigo José Herrero Pinilla Page 11

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21 Acknowledgment First of all, I would like to thank my family for giving me the opportunity to study at ICAI and always support me. Then, to my hometown university, ICAI, for all these years of both academic and personal education. Finally, I would like to thank DTU and especially my supervisors, Professor Harilaos N. Psaraftis and Ph.D. Student George Panagakos, for their patience, knowledge and advice during the whole thesis. Page 13

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23 Table of Contents 1. Introduction Motivation Objectives Thesis Organization and methods used The Green Corridor Concept The Characteristics of Transport Corridors The green corridor concept Green Corridor projects in Europe Legal Framework Freight Transport Logistics Action Plan (2007) Rail Freight Corridors (2010) The White Paper (2011) The New TEN-T Policy (2013) The TMS of the ScanMed Rail Freight Corridor Objectives of the TMS Catchment area Analysis of current freight market Expected future market developments Conclusions and Recommendations The TMS of the ScanMed TEN-T Core Network Corridor Corridor Alignment Objectives and Methodology of the MTMS Corridor Infrastructure and Traffic Volume Page 15

24 5.4 KPIs and Compliance Analysis Capacity Constraints and List of Projects ScanMed CNC vs. ScanMed RFC Monitoring the Performance of the Corridor Benchmarking Goal Corridor Description KPI s Selection Methodological Principles Sample Construction Data Collection Emissions Estimation KPI Aggregation Benchmarking Frequency Sample Construction and Estimation Selection and Estimation of Rail Chains Cost Calculations Emissions Rail Freight KPI s values Selection and Estimation of Road Chains Cost Calculation Frequency Emissions Road Freight KPI s values Selection and Estimation of Short-sea Shipping Chains Frequency Emissions Page 16

25 8. Performance Assessment Costs Calculations Time Frequency Reliability Emissions Conclusions References ANNEX I Criteria for choice of transport mode ANNEX II Conclusions and recommendations ANNEX III Page 17

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27 Table of Figures Figure 1: CO2 emissions per sector. Source: IEA Statistics (2014) Figure 2: CO2 emissions per transport mode. Source: IEA Statistics (2014) Figure 3: Three dimensions of sustainable development.source: The Sustainable Leader (2014) Figure 4: Blue Banana Corridor or Corridor A. Source: Panagakos (2012) Figure 5: The three pillars of green corridors.source: Engström (2011) Figure 6: The nine TEN-T corridors. Source: EC (2013) Figure 7: The East-West Transport Corridor. Source: EWTC Association Figure 8: Rail Freight Corridor Network. Source: INFRABEL Figure 9: Implementation Plan Rail Freight Corridor Network Source: Panagakos (2012) Figure 10: The nine TEN-T corridors. Source: EC (2013) Figure 11: Catchment area and routing in Norway, Sweden, and Denmark. Source: ETC (2014) Figure 12: Catchment area and routing in Germany and Austria. Source: ETC (2014) Figure 13: Catchment area and routing in Italy. Source: ETC (2014) Figure 14: Corridor train traffic composition (both directions, 2012). Source: ETC (2014) Figure 15: General alignment of the ScanMed CNC. Source: EC, Figure 16: Definition of system boundaries. Source: Swahn (2010) Figure 17: Map of rail freight sample chains. Source: Own compilation Figure 18: Map of Road Freight Transport Chains. Source: Own compilation Figure 19: Map of Short-sea Shipping Transport Chains (Table Figure 20: Corridor-level CO 2 -eq emissions (Chart) Figure 21: Corridor-level SO X emissions (Chart) Figure 22: Sample composition Page 19

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29 Table of Tables Table 1: The nine SuperGreen Corridors. Source: Panagakos (2015) Table 2: Rail freight transport matrix for Source: ETC (2014) Table 3: Road freight transport matrix for Source: ETC (2014) Table 4: Short-sea shipping matrix for Source: ETC (2014) Table 5: Modal split for country-to-country transports (2012). Source: ETC (2014) Table 6: Main sections of ScanMed CNC. Source: EC, Table 7: Basic characteristics of the ScanMed CNC. Source: EC, Table 8: International rail freight volume (1.000 tonnes). Source: EC, Table 9: International road freight volume (1.000 tonnes). Source: EC, Table 10: International sea freight volume (1.000 tonnes). Source: EC, Table 11: The objectives of the ScanMed CNC. Source: EC, Table 12: Number of projects by mode and country. Source: EC, Table 13: Differences between ScanMed CNC and RFC. Source: EC, Table 14: Corridor trains on ScanMed (both directions, 2012) Source: ETC (2014) Table 15: Train utilization ratio Table 16: Rail freight sample chains Table 17: KPI values extracted from databases Table 18: Fixed and variable costs for train operations ( ) Source: DTU Transport Table 19: Price of kwh ( ) Source: Eurostat Table 20: Fixed and Variable Costs Values ( ) Table 21: Chain and Mode level Costs ( /T-Km) Table 22: EcoTransIT default train characteristics Table 23: Total emissions per chain. Source: EcoTransIT Table 24: Chain-level emissions and Mode-level related emissions (g/t-km) Table 25: Rail Freight KPI values Table 26: NUTS 3 Areas. Source: Own Compilation Table 27: Representative transport chains (2012) Source: ETC (2014) Table 28: Costs of Road Freight Traffic. Sources: TMS RFC3, ETIS-Plus Table 29: EcoTransIT Truck Model Table 30: Emissions of Road Freight Traffic Table 31: Road Freight KPI values Page 21

30 Table 32: Road Freight KPI S total values Table 33: Road Freight KPI S corridor-level values Table 34: Ports of the corridor sample. Source: TMS RFC Table 35: NUTS assumptions Table 36: Representative short-sea shipping chains (2010.) Source: TRANS-TOOLS Table 37: EcoTransIT Ship Characteristics Table 38: Emissions and frequency of shipping sample chains Table 39: Mode-level values (all transport modes) Table 40: Corridor-level costs Table 41: Corridor-level average speed Table 42: Corridor-level average frequency Table 43: Corridor-level CO 2 -eq emissions Table 44: Corridor-level SO X emissions Table 45: Sample suitability Page 22

31 Nomenclature - : Euro - BGLC: Bothnian Green Logistic Corridor - CEF: Connecting Europe Facility - CNC: Core Network Corridor - CO 2 : Carbon Dioxide - CO 2 eq: Carbon Dioxide Equivalent - DTU: DanmarksTeckniskeUniversitet - Dkk: Danish Krone - DWT: Deadweight Tonnage - EC: European Commission - ECT: European Transport Conference - EP: European Parliament - ERTMS: European Rail Traffic Management System - EU: European Union - EWTC: East-West Transport Corridor - FTLAP: Freight Transport Logistics Action Plan - g: Grams - GDP: Gross Domestic Product - GHG: Green House Gases - h: Hours - ICT: Information and Communication Technology - IEA: International Energy Agency - IMO: International Maritime Organization - INFRAS: Institute of Energy and Environmental Research - Km: Kilometres - KPI: Key Performance Indicator - KWh: Kilowatts per hour - LCA: Life Cycle Assessment - MARPOL: International Convention for the Prevention of Pollution from Ships Page 23

32 - MOU: Memorandum of Understanding - NUTS: Nomenclature of Territorial Units for Statistics - O/D: Origin/Destination - PESTL: Political, Economic, Socio-Cultural, Technological and Logistic - PP: Priority Projects - RFC: Rail Freight Corridor - RRT: Rail Road Terminals - SCGI: Swedish Green Corridors Initiative - SO 2 : Sulphur Dioxide - SSS: Short-sea Shipping - SWOT: Strengths, Weaknesses, Opportunities and Threats. - T: Tonnes - TEN-T: Trans-European Transport Network - TMS: Transport Market Study - WtW: Well-to-Wheel Page 24

33 1. Introduction 1.1 Motivation With a share of 22,6%, the transport sector is the highest producer of worldwide CO 2 emissions after electricity generation, which accounts for an impressive 40,8% (IEA Statistics, 2014). Not all transport modes are equally responsible for this infamous distinction. The vast majority of this share (16,8 out of 22,6%) is attributed to road transport. Even after excluding passenger transportation, which is the major source of CO 2 emissions but lies outside the scope of this thesis, road freight is the front runner in greenhouse gas (GHG) production. Figure 1: CO2 emissions per sector. Source: IEA Statistics (2014) Figure 2: CO2 emissions per transport mode. Source: IEA Statistics (2014) Page 25

34 For decades the European Commission (EC) has been pushing for shifting cargoes away from road towards rail and maritime transport, basically to address the sometimes severe congestion problem of the European road network. The increasing public awareness of environmental issues has recently intensified this drive as long as trains and ships are considered much friendlier to the environment than trucks. A major drawback in this endeavour stems from the fact that trains and, to a larger extent, ships require large quantities of cargo to run in an economically efficient and environmentally sustainable manner. In order to ensure the necessary scale economies, the EC has introduced, since mid-2000s, the corridor approach,which involves the consolidation of large quantities of cargo for shipment over long distances. In less than 10 years from its inception, the concept has found important applications in the European transport policy like the ERTMS (European Rail Traffic Management System) corridors, the green corridors, the Rail Freight Corridors (RFCs), and more recently the TEN-T core network corridors (CNCs), which constitute the backbone of the European transport infrastructure policy. In addition, numerous corridor initiatives have appeared at a lower level, in most cases seen by local/regional authorities as a functional tool fostering economic development through trade growth. All these initiatives, which are now in their implementation phase, require a formalised performance monitoring mechanism. A corridor assessment methodology involving a set of Key performance indicators (KPIs) was proposed by the EU-funded project SuperGreen, which run in the period This methodology, however, has never been really applied due to lack of data. The introduction of the RFCs and CNCs has been accompanied by the formal requirement for a Transport Market Study (TMS), which analyses the status quo of the corridor, produces demand forecasts, considers the user needs and identifies potential gaps that have to be addressed by the corridor management. Page 26

35 It is hoped that the TMSs that meanwhile have been published provide the data that the SuperGreen methodology needs for a proper corridor assessment. This is what this thesis will try to explore. 1.2 Objectives The aim of this thesis is to assess the performance of the Scandinavian- Mediterranean (ScanMed) corridor, on the basis of the information contained in the transport market studies of the relevant rail freight and TEN-T multimodal corridors. The specific objectives of the thesis have been defined as follows: Formulating the thesis problem. Finding and describing the relevant literature within the scope of the problem. Defining and describing a green corridor. Comparing green corridors with other transport corridors. Arguing in favour of the choice of theory and method selected for addressing the problem. Identifying and discussing indicators used for assessing the performance of a corridor. Selecting a set of indicators to be used for monitoring the performance of the ScanMed corridor on the basis of the objectives pursued by the corridor management. Constructing a sample of representative transport chains along the corridor. Collecting and evaluating data pertaining to the selected transport chains in connection with the indicators to be assessed. Proposing a method for transforming chain-level indicators to corridor KPIs. Discussing and putting the results into perspective in relation to the theory and the empirical data. Page 27

36 Reporting the obtained results in a structured, comprehensive, brief, clear, critically, evaluating/concluding way, and in accordance with good practice for a written presentation. 1.3 Thesis Organization and methods used This thesis has been divided into four major blocks, ensuring that: its objectives are adequately met, and it is as friendly to the reader as possible. The first block aims at setting the scene and familiarizing the reader with the basic concepts. It consists of two chapters, one on green corridors (Chapter 2) and one on the European legal framework (Chapter 3). Chapter 2 starts with the description of the more general transport corridor and narrows it down to the more specific green corridor concept, emphasizing on the characteristics that distinguish a green from any other efficient corridor. It further refers to the most important green corridor projects in Europe and discusses the basic benefits derived from this approach. Chapter 3 briefly presents, in chronological order, the basic corridor-related policy documents in the EU: the Freight Logistics Action Plan, which introduced green corridors in 2007, the Rail Freight Corridor regulation of 2010, the White Paper on Transport of 2011, that set the European strategy for the next decade, and the new transport infrastructure policy of 2013 that introduced the core network corridors as an implementation instrument for the most important segments of all transport networks in the EU. The method used for this first block is literature search. The second block seeks to explore the two basic sources of information for this thesis: the transport market study of the ScanMed RFC (Chapter 4) and the multimodal transport market study of the ScanMed TEN-T core network corridor (Chapter 5). The two chapters summarize the basic findings of these two studies, Page 28

37 as resulting from their detailed review. The main differences between them have also been identified and briefly presented in Chapter 5. The third block presents in detail the methodology to be followed in assessing the corridor. In its sole chapter (Chapter 6) it discusses the most critical issues concerning the assessment of a corridor as identified in the extended SuperGreen literature. Emphasis is placed on the methodological principles and the selection of KPIs to be used for monitoring the performance of the corridor. Practical matters pertaining to the particular application of the methodology and its necessary adjustment to conform to the available data are also contained in Chapter 6. The last block is devoted to the application of the method. It consists of two chapters. Chapter 7 presents: the decomposition of the corridor into transport chains for the three modes examined (rail, road and maritime transport), for each mode, the construction of a sample of representative chains on the basis of certain criteria, the collection of information needed for calculating the KPI values for each selected chain, and the estimation of KPI values for each chain, as well as the aggregation of these values at the modal level. Information extracted from the two TMSs of the second block is used for the construction of the three samples. Data gaps in relation to the sample construction and the calculation of the corresponding KPI values are covered to the extent possible from a number of other databases and internal information used in the extensive modelling work of DTU Transport. The final chapter of the thesis, Chapter 8, aggregates the KPIs at corridor level, discusses the results and presents the conclusions. Page 29

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39 2. The Green Corridor Concept The purpose of this chapter is to introduce the concept of Green Corridor, as used in the European transport policy document in the area of freight logistics. The basis of this material presented here is based on work performed in the context of the EU SuperGreen project. The chapter draws on the various SuperGreen project reportsamong which the Green CorridorsHandbook Vol II (Panagakos, 2012) was of particular use. A good summary of the SuperGreen results can also be formed in the bookgreen Transport Logistics in Search of Win-Win Solutions (Psaraftis, 2015) supplemented by additional material on green logistics. Before starting to explain what a corridor is, it is necessary to explain what the term green means. It is very common to use the term green to refer to environmental protection features. In this thesis, by green it is meant sustainable, adding economic and social dimensions to the usual environmental ones when used in the context of freight transportation logistics. Figure 3: Three dimensions of sustainable development.source: The Sustainable Leader (2014) The chapter is structured as follows: Section 2.1 introduces transportation corridors. Section 2.2 discusses the different definitions of green corridors and the relation to transportation corridors. Section 2.3 present a number of greencorridor projects in Europe. Page 31

40 2.1 The Characteristics of Transport Corridors Although, used for years as a concept, there is not yet a precise definition for transport corridor. The definition that fits better the way the term is used here, is the World Bank publication Best Practices in Management of International Trade Corridors (Arnold, 2006). According to this definition, transport corridors have both physical and functional elements. Physical dimension: 1. Transport corridors include one or more routes which connect centers of economic activity. 2. These routes have different alignments but share common transfer points and common end points. 3. The end points are gateways that allow traffic to enter or exit the corridors. 4. The routes are composed of the links over the transportation services travel and the nodes interconnecting the transportation services. 5. Some corridors are uni-modal, but most corridors are multi-modal. 6. Some corridors are very short and defined by a principal gateway like a port; others are defined by the regions they serve; still others are defined as part of a network serving a larger region. Functional dimension: 1. Transportation corridors provide transportation and other logistics services that promote trade among the cities and countries along the corridor. In fact, most transportation corridors are developed to support regional economic growth. This is the reason that many transportation corridors are associated with corresponding trade and economic corridors. 2. Transportation corridors can be domestic or international. 3. A domestic corridor is a designated set of routes within the national transportation network that is used to distribute goods within the country. It includes links and nodes for the various modes as well as nodes that connect different modes and different service areas. Page 32

41 4. An international transportation corridor may serve the foreign trade of a single country or several neighbouring countries. It may also connect countries that are separated by one or more transit countries or provide a landlocked country with access to the sea. In relation with the last point it is necessary to mention that the international corridors consist of a number of national ones. Due to this relation, there are very often conflicts between international and national objectives, such as, competing functions or different funding regulations for their development and maintenance. Corridor A, it is a good example of an international transport corridor. This corridor covers the area from Rotterdam (Netherlands) to Genoa (Italy). This area is the most heavily industrialized North-South route in Europe connecting some of the main economic centers of Europe, such as Rotterdam, Amsterdam, Duisburg, Cologne, Frankfurt, Mannheim, Basle, Zurich, Milan and Genoa. Other cities indirectly connected are London and Brussels. Corridor A, also called the Blue Banana is shown in Figure (4) below: Figure 4: Blue Banana Corridor or Corridor A. Source: Panagakos (2012) The Blue Banana is the pioneer for international rail freight traffic in Europe being the corridor that carries the greatest transport volume in Europe. Page 33

42 2.2 The green corridor concept It was mentioned above that transport corridors do not have a precise definition. Neither green corridors are defined in a strict sense. Actually, one of the goals of ongoing research in this area is to develop an explicit and workable definition for the term. The concept appeared for the first time in 2007 by the Freight Transport Logistics Action Plan of the European Commission (EC, 2007). The definition given by the document was:... [green] transport corridors are marked by a concentration of freight traffic between major hubs and by relatively long distances Industry will be encouraged along these corridors to rely on co-modality and on advanced technology in order to accommodate rising traffic volumes, while promoting environmental sustainability and energy efficiency Green transport corridors will be equipped with adequate transhipment facilities at strategic locations and with supply points initially for bio-fuels and, later, for other forms of green propulsion Green corridors could be used to experiment with environmentally-friendly, innovative transport units, and with advanced Intelligent Transport Systems (ITS) applications... Fair and non-discriminatory access to corridors and transhipment facilities should be ensured in accordance with the rules of the Treaty. Further to the above, the Swedish Logistics Forum made a more structured definition (Swedish Logistics Forum s, 2011). According to them: Green Corridors aim at reducing environmental and climate impact while increasing safety and efficiency. Characteristics of a green corridor include: 1. sustainable logistics solutions with documented reductions of environmental and climate impact, high safety, high quality and strong efficiency, 2. integrated logistics concepts with optimal utilization of all transport modes, so called co-modality, 3. harmonized regulations with openness for all actors, Page 34

43 4. a concentration of national and international freight traffic on relatively long transport routes, 5. efficient and strategically placed transhipment points, as well as an adapted, supportive infrastructure, and 6. a platform for development and demonstration of innovative logistics solutions, including information systems, collaborative models and technology. The two definitions share an important aspect of green corridors: they are both economically efficient and environmentally sustainable. However, there are differences between them: The Swedish definition includes high safety, an element referring to social acceptance, the third pillar of sustainability. On the other hand, the EU definition just mentioned two dimensions, economic and environmental efficiency. The Swedish definition notes the importance of harmonizing regulations as a necessary feature of a green corridor. Only the EU definition makes direct reference to alternative fuel and green propulsion. An interesting exercise would be to identify the characteristics that distinguish a green corridor from an otherwiseefficient one. In order to do that, it is necessary to merge the two lists described above into a single one, and subtract the characteristics that pertain to all efficient corridors. What remains are the characteristics that you always find in green corridors but not necessarily in the other transport corridors. These green characteristics are summarized below: 1. Reliance on co-modality Green corridors are multimodal by definition. The term co-modality is used by the EU policy documents to refer to the use of different transport modes on their own or in combination in the aim of obtaining an optimal and sustainable Page 35

44 utilization of resources. The actual use of different modes depends on their efficiency and performance in the logistic chain. There are different factors affecting in the modal choice, including geographical barriers and infrastructuralcapacities. Nevertheless, a green corridor exploits the existing networks in an optimal way providing superior services overall. 2. Reliance on advanced technologies Allowing use of alternative and clean fuels and promoting the development and demonstration of innovative logistics solutions. 3. Advanced telematics applications Advanced ICT applications will enhance the performance of existing infrastructure while minimizing congestion, accidents and travel time, i.e. they will improve the efficiency of the corridor. They are considered a green characteristic to the extent that they can enhance co-modality and integrated logistics. 4. Collaborative business models They might not be considered a green characteristic because they can be found in most efficient transport corridors. However, they fit perfectly with the concept of integrated logistics of the green corridors and as such have been added to the list of green features (Panagakos, 2012) The Swedish Transport Administration offers holistic perspective of green corridor projects that promote integrated services and seek for increasing efficiency while reducing ecologic impact(engström, 2011).They are divided into the following three major categories (Figure 5). 1. Corridors:Refers to the needs of an efficient transportation network and infrastructure in a physical aspect. Corridor projects aim at Page 36

45 integrating all transport at national or international context. 2. Transport techniques: The main objective is the development of the connections between modes enhancing the application of co-modality. 3. Logistic solutions: Refers to complete solutions that bring togetherdifferent stakeholders forming a business case, with the aim of promoting efficiency and lowering environmental impacts. Figure 5: The three pillars of green corridors.source: Engström (2011) Before closing this section, it is worth mentioning the benefits of the green corridor concept. Efficient freight transport in Europe is essential for the competitiveness of the European industry and the welfare of European citizens. Green corridors complement efficiency with environmental sustainability and social considerations. The basic principle is to consolidate a large volume of freight for transportation over long distances. This is necessary for improving the competitiveness of modes like rail or waterborne transport. These modes are environmentally friendlier than trucks and this shift will alleviate the serious congestion problems that trucks create. Page 37

46 In addition, the scale and length of freight corridors improve optimization possibilities in terms of energy use and emissions, resulting in further environmental and financial gains. The economies of scale created by a green corridor provide the necessary conditions for installing a network of refueling stations, which is needed, for the introduction of alternative clean fuels. Significant investments are required in order to reduce bottlenecks and improve the existing networks. Advanced ICT applications like automatic guidance systems improve the utilizations of existing infrastructure while integrating different modes of transportation. This bottleneck improves the capacity of the network reducing the expansion needs and saving scare funds. Another benefit stems from the international character of green corridors, which improves enhanced cooperation, not only among the countries involves but also among the numerous stakeholders that participate in the supply chains using the corridors. Page 38

47 2.3 Green Corridor projects in Europe As shown by the following milestones, the corridor concept gains more and more importance in the EU transport policy making: 1. In March 2005, the EC and the railway sector agreed on a MOU (Memorandum of Understanding) referring to the implementation of the European Rail Traffic Management Systems (ERTMS). Six new corridors were defined across Europe where ERTMS trend to be implemented as a priority. 2. In October 2007, the EC published the Freight Transport Logistics Action Plan. The concept of green corridors was introduced as a means to enhance the efficiency and sustainability of freight transportation. 3. In November 2010, the European Union adopted regulation No 913/2010 concerning a European rail network for competitive freight. This regulation defined nine initial corridors, where sufficient priority is given to international freight trains 4. In March 2011, the EC published the latest White Paper on transport that describes its vision of future transport and the corresponding strategy for the next decade. The document makes reference to multimodal freight corridors promoting projects related to innovative and efficient projects and the use of clean freight transport services. According to the paper: The EU needs specially developed freight corridors optimized in terms of energy use and emissions, minimizing environmental impacts, but also attractive for their reliability, limited congestion and low operating and administrative costs. Page 39

48 5. In December 2013, the EU Regulation No 1315/2013 was adopted. This regulation constitutes the new TEN-T (Trans-European Transport Network)Guidelinesproviding a new transport infrastructure policy which aims at closing existing gaps between the transport networks of the Member States and removing the relevant bottlenecks. The TEN-T Guidelines introduce nine core network corridors to facilitate the coordinated implementation of the core European network which network links the most important nodes (urban nodes, ports, airports) in Europe. Figure 6: The nine TEN-T corridors. Source: EC (2013) 6. During 2014, there were several meetings between the EU Transport Ministers to implement the TEN-T policy adopted in The objectives concerned planning and governance of the TEN-T core network corridors, as well as the necessary funding instruments. In December the Council adopted the Conclusions on Transport Infrastructure and the Trans- European Network, which reaffirm the policies adopted in the course of Page 40

49 the previous year, and underline the importance of promoting both public and private investments. Other corridor related initiatives in Europe, albeit at a lower than the EU level, include: 1. In December 2002, the Brenner Action Plan was adopted by Germany, Austria and Italy in the framework of the BRAVO project, aiming at achieving a significant increase of intermodal along the Brenner Corridor, transport which is one of the busiest international transit corridors. 2. In January 2003, the corridor from Rotterdam to Genoa was established by the collaboration of the Ministries of Transport of The Netherlands, Germany, Switzerland and Italy. Nowadays, this corridor is called Corridor Alater became the basis for the Rhine-Alpine TEN-T core network corridor. 3. In 2006, the East-West Transport Corridor was created by Denmark, Lithuania, Russia and Sweden. Their goal was to enhance transportation development through infrastructure improvements and greater cooperation between stakeholders and researchers. In 2012 the East-West Transport Corridor Association was founded. One of their main objectives was to turn EWTC into a green corridor in line with the new EU policy. Page 41

50 Figure 7: The East-West Transport Corridor. Source: EWTC Association 4. In 2008, one year after the publication of the Freight Transport Logistics Action Plan the Swedish Green Corridors Initiative (SGCI) was introduced. At the beginning the initiative involved a broad group of stakeholders interested in defining the green corridor concept. Two green corridors were established by this initiative: The Oslo-Randstad (GreCOR) and The Bothnian Green Logistic Corridor (BGLC). 5. In 2009, the Scandinavian-Adriatic Corridor Project (Scandria) was introduced to connect capitals and metropolitan regions from Scandinavia to the Adriatic Sea. Scandria is a cooperation of 19 partners from Germany, Denmark, Sweden, Finland and Norway willing to develop a green corridor. 6. In 2009, the TransBaltic project was introduced covering corridors across the Baltic Sea. The objective of this project was to promote the creation of multimodal sustainable logistic solutions. 7. In 2010, the SuperGreen project was kicked off. It was a 3-year project supported by the EC s 7th Framework Programme of Research and Technological Development. It focused on the definition, development and expansion of the green corridor concept. Its central activity was the development of a corridor benchmarking methodology using a set of indicators (KPIs) for studying and monitoring the sustainable goals of the Page 42

51 EU. The methodology developed was tested on nine corridors selected among an initial list of sixty potential ones (Table 1). Table 1: The nine SuperGreen Corridors. Source: Panagakos (2015) 8. In 2011, the STRING corridor was launched. The project s overall aim was to promote innovative and efficient transport solutions for corridor between the Öresund region and Hamburg. Page 43

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53 3. Legal Framework The purpose of this chapter is to briefly present the most important recent EU transport policies in the green corridor areas. Two qualifications are in order here: 1. The term green corridor was introduced in 2007 by the document.freight Transport Logistics Action Plan As such, green corridors, are considered a European concept and the legal framework analysis of this chapter will cover Europe only. 2. Given that the term green in this thesis is identical to sustainable, which in turn has economic, environmental and social dimension, it is of no surprise that almost every single policy document in the field of freight transport in Europe is relevant. It is, therefore, necessary to limit the coverage of the present chapter to only a handful of the most important documents. 3.1 Freight Transport Logistics Action Plan (2007) In 2007, the Freight Transport Logistics Action Plan (FTLAP) was launched by the EU to address current and future challenges in ensuring a competitive and sustainable freight transport system is Europe. A number of short/medium-term actions basically aimed at integrating transport modeswere introduced: Measuring performance of integrated systems. Exchange of information through interoperable ICT systems. Promoting regulatory requirements for the exchange of information between modes. Introducing green corridors. Improving the urban dimension of integrated transportation solutions. Two of these ballet points are related to cargo flows (green corridors and urban distribution), other two to information flows (exchange of information and Page 45

54 administrative procedures) and the last one,performance indicators, is related to both. In relation to this thesis, the most important among them is the introduction of the green corridor concept, as opening possibilities for the introduction of innovative solutions, despite the fact that intensity of transport activity associated with green corridors, applies additional pressure to the environment and the human habitat.as stated in the Impact Assessment document accompanying the FTLAP, sec (2007). Freight transport corridors are ideal environments for the development and introduction of solutions that help promote environmental sustainability and energy efficiency, so that they may become showcases of green freight transport. Among the other actions introduced by the FTLAP, the e-freight concept deserves special attention as information exchange and integration is considered as one of the most prominent future trends in supply chain management. It denotes the vision of paperless freight transport processes where an electronic flow of information is linked to the physical flow of goods and aims at developing interoperable information and booking tools that enable operators to enter information only own by the whole multimodal supply chains for planning, execution, monitoring and reporting purposes. Page 46

55 3.2 Rail Freight Corridors (2010) During the last decades, the European railways have seen their market share dropping dramatically. In order to strengthen their competitiveness against other transport nodes, the EC has been trying to restructure the rail transportation market, basically in the following three areas: Opening the rail transportation market to competition. Improving the interoperability and safety of national networks Developing rail transportation infrastructure. In this framework, the Communication on a freight-oriented rail network, which accompanied the FTLAP of the previous section in the so-called 2007 Freight Transport Agenda, eventually led to the adaption of Regulation No 913/2010, which lays down rules for the establishment organization and management of international rail corridors with a view to developing a European rail network for competitive freight. The basic intervention of this Regulation is the designation of the nine Rail Freight Corridors (RFCs) of Figure 6 and the introduction of a process of capacity allocation to freight trains along these corridors with better coordination of priority rules and prioritizing, among freight trains, those that cross at least one border. Figure 8: Rail Freight Corridor Network. Source: INFRABEL Page 47

56 RFC3, from Stockholm to Palermo, is the subject of this thesis. In addition to establish a detailed governance scheme for each RFC involving representatives of the Member States concerned (executive board), the infrastructure managers concerned (management board) and two advisory groups made up of terminal managers and railway undertakings, the Regulation describes the necessary implementation measures that include: Drafting a Transport Market Study (TMS) analyzing the current traffic along the corridor, as well as the expected developments in the future. The TMS to be updated periodically. Preparing an implementation plan that describes:the characteristics of the freight corridor including cross-borders and bottlenecks; the programme of measures necessary for establishing the RFC; and the objectives for the RFC, updating the quality of the service and the capacity of the corridor. Drafting and periodically updating an investment plan that provides; medium and long-term investments in infrastructure; financial requirements and sources of finance: an ERTMS development play and a management play of the freight train capacity along the corridor. Establishing of one-stop shop for displaying infrastructure capacity availability and handling applications for new services along the RFC. Monitoring the performance of the rail freight services follow developments in meeting the stated objectives, and publishing the results once a year. Page 48

57 Running an annual satisfaction survey of the corridor users and publishing its results. All these measures (with the exception of the one-stop shop) are depicted schematic allying Figure 9 below. Figure 9: Implementation Plan Rail Freight Corridor Network Source: Panagakos (2012) Due to the fact that the TMS plays a central role in this thesis, as it is the basic source of information, its functionality needs to be described in more detail in order to know what to expect. The TMS provides the basis for assessing the customers needs on the one hand and the bottlenecks to rail freight traffic on the other. This analysis is required for identifying existing gaps and setting the corridor objectives accordingly. In order to be effective the TMS has to reflect the views of all stakeholders involved like the infrastructure railway undertakings, other transport operators, freight forwarders and other transport services providers, the transport service buyers, the administration, etc. In addition, the TMS should provide information on the types of cargo using the corridor, their annual volumes, and other operational shipment size the typical vehicles used, speeds, load factors, etc. Page 49

58 3.3 The White Paper (2011) The White Paper on Transport are the most important documents in the EU transport policy, as they It describe the EC s vision of future transportation and the strategy for the next decade. The latest White Paper on Transport published in 2011 and contains the EC s vision of future transport about: a system that underpins European economic progress, enhances competitiveness and offers high quality mobility services while using resources more efficiently. Curbing mobility is not an option. New transport patterns must emerge, according to which larger volumes of freight are carried jointly to their destination by the most efficient (combination of) modes. Individual transport is preferably used for the final miles of the journey and performed with clean vehicles. Information technology provides for simpler and more reliable transfers. Transport users pay for the full costs of transport in exchange for less congestion, more information, better service and more safety. In order to meet the global target of limiting climate change to 2 C, the 2011 White Paper sets the objectives of reducing by 2050 transport GHG emissions by 60% in comparison to 1990, of drastically decreasing the oil dependency of EU transport over the same period, and of containing the growth of congestion. These objectives are pursued through a roadmap of forty initiatives, which are organized in the following three strands and their corresponding ten benchmarks: Improving the energy efficiency in all transport modes; developing clean fuels and developing sustainable propulsion systems. 1. Reduce by 50% the use of conventionally-fueled cars in cities by 2030 and phase them out by 2050; achieve CO 2 -free city logistics in the main urban centers by Increase the use of low-carbon sustainable fuels in aviation to 40% by 2050; reduce EU CO 2 emissions from maritime bunker fuels by Page 50

59 40% over the same period. Optimizing the performance of multi-modal logistic chains, by increasing the use of environmental friendlier modes among others. 3. Green freight corridors should contribute shifting 30% of road freight over 300 km to rail or waterborne transport by 2030, and more than 50% by Complete the European high-speed rail network by By 2030 the high-speed railway network should be tripled in length. By the majority of medium distance travels should be made by rail. 5. A completely functional EU multimodal TEN-T core network should be in place by Connect all core network airports to the rail network by 2050; connect all core seaports to the rail freight and inland waterway system. Using transport infrastructure more efficiently through smart proper pricing systems, information systems and advanced logistics, removal of remaining restrictions in cabotage, addressing administrative barriers to short sea shipping, etc. 7. Complete the European Sky by 2020 through deployment of a modern air traffic management system. Deploy smart ICT applications for both land and waterborne transports that exploit the European satellite System Galileo. 8. Complete the framework for a European multimodal information, management and payment system by Progressively bring road transport close to zero by Full application of the user pays and polluter pays principals. Page 51

60 In order to reach these goals, a four-tier strategy was adopted: Internal market: Eliminate all residual and national barriers between modes and national systems in order to create a genuine single European Transport Area. Innovation: EU research needs to address the full cycle of research, innovation and development in an integrated way. Infrastructure: Provide the common vision and sufficient resources needed by the EU transport infrastructure policy. Transport process should reflect costs in an undistorted way. International: Opening up third-country markets in transport services, products and investments. Thus, the 2011 White Paper on transport has incorporated the green corridors of the FTLAP into the strategy to be followed during the next decade in order to meet the ambitious EU targets. Page 52

61 3.4 The New TEN-T Policy (2013) In line with the 2011 White Paper presented in Section3.3 and in view of enduring obstacles like: Cross-border sections and other missing links. Considerable bottlenecks of existing infrastructure, especially in the eastwest connections. Fragmentation of infrastructure between modes. Significant investment requirements in order to reach the GHG emission reduction target. Interoperability problems due to diverse operational and administrative rules by the Member States. The EC decided in 2011 to redefine its long term transport infrastructure policy, which is described in a document called TEN-T guidelines. The revised TEN-T guidelines (EP&C, 2013), setting and priorities and providing implementation measures for the trans-european transport network (TEN-T) was adopted in Two fields of action were introduced by this document in pursuing its main objectives of establishing a genuine multi-modal transport network in Europe. The conceptual planning of the network is the subject of the first one. An approach consisting of the two layers, the comprehensive and the so-called core network has been adopted. The comprehensive network is the basic layer of the TEN-T, consisting of parts of the national networks. It should be completed by The core network consists of the strategically most important parts of the comprehensive network. Forming the backbone of the European multimodal transport infrastructure, it contains the TEN-T segments with the highest added value from a European perspective, such as important bottlenecks and multimodal nodes and cross border missing links. Electrification for the rail roads and availability of alternative fuels for the modes is required for the core network, a characteristic pertaining to green corridors.the core network should be completed by Page 53

62 The second field of action concerns the instruments i.e. how employed for implementing the new infrastructure policy. Following the corridor approach of the concept of core network corridors (Section 3.2) was taken from the Rail Freight Corridors Regulation No 913/2010 and was introduced for coordinating the implementation of the core network. A core network corridor can be described as follows: Covers the most important cross-border/long-distance flows in the network. Is multimodal, involving at least three modes of transportation. Is international, crossing at least three Member States Involves at least one maritime port and its accesses. Figure 10 presents the nine core network corridors that comprise the TEN-T core network. Special financial aid is foreseen for these corridors by the Connecting Europe Facility (CEF), which finances EU priority infrastructure in transport, energy and digital broad bound (EP&C, 2013b). Page 54

63 Figure 10: The nine TEN-T corridors. Source: EC (2013) The Scandinavian-Mediterranean corridor, which is the subject of this thesis, is one of the TENT-T core network corridors. Before changing subject, it would be worth investigating the relation of the TEN- T core network corridors presented above to the green corridors of the previous chapter. Panagakos (2015) has run this exercise and search for the green characteristics identifies in Section 2.2 to the new TEN-T guidelines of Regulation No. 1315/2013. His findings are summarized in next page: 1. Reliance on co-modality The term co-modality does not appear in the guidelines. However, when it comes to the comprehensive network, there is an entire section devoted to the infrastructure for multimodal transport, while in relation to the core network, Article 43 makes it clear:... In order to lead to resource-efficient multimodal transport, core network corridors shall be focused on modal integration, interoperability, and a coordinated development of infrastructure Furthermore, a number of Articles (12, 13, 22, 26, 30) deal with the provision of adequate transshipment facilities that are needed for exploiting co-modality. 2. Reliance on advanced technologies There are several references to advanced technology applications, and the use of clean fuels. The following example concerns the comprehensive network: In the development of the comprehensive network,... particular consideration shall be given to measures that are necessary for... ensuring fuel security through increased energy efficiency, and promoting the use of alternative and, in particular, low or zero carbon energy sources and propulsion systems (Article10) In relation to innovative logistics solutions, Article 32 is quite illustrative: Page 55

64 Member States shall pay particular attention to projects of common interest which. Aim to promote the development of innovative transport services.. As for the core network, Article 39 prescribes full electrification for the railroads and availability of alternative clean fuels for the road, inland waterways and maritime transport infrastructures. Airports are required to provide capacity to make alternative fuels. 3. Advanced telematics applications There are numerous references to advanced ICT applications. The following excerpt from Article 31 is an example: Telematics applications shall, for the respective transport modes, include in particular ERTMS (for railways), RIS (for inland waterways), ITS (for road transport), VTMIS and e-maritime services (for maritime transport) and the SESAR system (for air transport) 4. Collaborate business models Even though, there are not direct references to business models in the guidelines, the need for cooperation among stakeholders, particularly in the form of information sharing is mentioned explicitly. Two examples are shown below: Member States shall ensure... that freight terminals and logistic platforms, inland and maritime ports and airports handling cargo are equipped for the provision of information flows within this infrastructure and between the transport modes along the logistic chain (Article 28) Members Stated shall pay particular attention to projects of common interest which aim to facilitate multimodal transport services operations, including the necessary accompanying information flows, and improve cooperation between transport service providers (Article 31) It follows that all green characteristics are more or less shared by the TEN-T core network corridors, a fact that renders the TEN-T core network also a network of green corridors in Europe. Page 56

65 The implications of this conclusion is that the methodology developed by the SuperGreen project for monitoring the performance of green corridors can also be used for assessing the freight dimension of the TEN-T core network corridors. Page 57

66 Page 58

67 4. The TMS of the ScanMed Rail Freight Corridor The purpose of this chapter is to present the Transport Market Study (TMS) of the Scandinavian-Mediterranean Rail Freight Corridor. Given the fact that this corridor comprises the rail dimension of the multimodal corridor studied here, the present TMS constitutes one of the two main sources of information for this thesis; the other being the multimodal TMS of the Scandinavian-Mediterranean TEN-T core network corridor. The subject corridor of this study is one of the nine Rail Freight Corridors (RFCs) introduced by Regulation (EU) No 913/2010 in an effort to create a European network for competitive rail freight (refer to Section 3.2 for more details). The initial routing, designated as RFC 3, was Stockholm - Malmö - Copenhagen - Hamburg - Innsbruck - Verona - Palermo. In 2013, when the new TEN-T guidelines and the Connecting Europe Facility were adopted (refer to Section 3.4), RFC 3 was extended to include Oslo, Trelleborg, Livorno, La Spezia, Ancona, Bari, Taranto and Augusta, and was renamed into the Scandinavian- Mediterranean Rail Freight Corridor, also referred to as the ScanMed RFC. According to the policy documents mentioned above, the parts of the ScanMed RFC that correspond to the initial RFC 3 are expected to become operational by Nov. 2015, while the subsequent extensions need to be covered by Nov at the latest. The chapter follows the structure of the subject report. 4.1 Objectives of the TMS The TMS has been undertaken according to the stipulations of Regulation No 913/2010 (Article 9.3). Its main objective is to analyze current and future freight market developments and support setting the corridor targets in line with customer expectations. The following specific objectives are mentioned: Analysis of current market conditions of all transport modes along the corridor Page 59

68 Expected future market developments on the basis of socio-economic trends SWOT analysis of rail freight traffic along the corridor Recommendations for operational and organizational improvements of rail freight Support defining the corridor capacity parameters. For general (not corridor-specific) information, TMS draws heavily on Eurostat, the ETISPlus database, as well as on national and regional statistic sources. Corridor-specific rail traffic is assessed based on data solicited from the infrastructure managers involved, while customer requirements, modal choice criteria and future market expectations are evaluated on the basis of 57 personal interviews and 79 web-based surveys among shippers, railway undertakings, terminal and port operators, road carriers, shipping companies, freight forwarders and other logistics service providers, and authorities in the corridor countries. 4.2 Catchment area The catchment area of the ScanMed RFC consists of the NUTS 2 or NUTS 3 regions surrounding the reference routing derived from the Corridor nodes, as listed in the Regulation No 1316/2013 (EP&C, 2013b). The catchment area (in green) together with the routing of the ScanMed RFC is presented in Figures below. Page 60

69 Figure 11: Catchment area and routing in Norway, Sweden, and Denmark. Source: ETC (2014) Page 61

70 Figure 12: Catchment area and routing in Germany and Austria. Source: ETC (2014) Page 62

71 Figure 13: Catchment area and routing in Italy. Source: ETC (2014) According to the glossary of the study, the preliminary route refers to the one used as reference for defining the catchment area of TMS, while the diversionary route refers to a line related to the preliminary routing, for which no obligation for Page 63

72 ERTMS implementation exists and which may temporarily considered in case of disturbances. 4.3 Analysis of current freight market The country-to-country freight volumes carried by rail, road and short-sea shipping in year 2012 appear in Tables 2-4 respectively (in thousand net tons). Table 2: Rail freight transport matrix for Source: ETC (2014) Table 3: Road freight transport matrix for Source: ETC (2014) Page 64

73 Table 4: Short-sea shipping matrix for Source: ETC (2014) Rail freight between the ScanMed RFC countries accounted for 58 million tons in Germany, Italy and Austria dominated this trade with almost 90% of the traffic in both directions. In the same year, road freight amounted to about 90 million tons. The share of Germany, Austria and Italy was once again predominant with about 78% in both directions. Ships carried almost 85 million tons in 2012, with Scandinavia now being the major player accounting for about 75% of the exports and 58% of the imports. It is worth noting that the shipping matrix is less balanced compared to those of the other modes. A possible explanation relates to shipments of Swedish iron ore to Germany via the port of Narvik, which enter the matrix as Norwegian loadings. A handy road freight traffic analysis at NUTS 3 level also appears in the TMS in the form of a table illustrating, among other information, the top 3 O/D (origin/destination) relations between NUTS 3 regions within the corridor catchment area (refer to Table 27). In relation to modal split, Table 5 provides estimates of both volumes and shares of bidirectional traffic between the ScanMed RFC countries for year The Germany-Italy trade stands out in terms of rail transport, while the Germany- Austria connection is the most important one when it comes to road hauling. The sea connections Norway-Germany and Sweden-Germany are quite vigorous in Page 65

74 terms of both volume and share. In order to know the criteria for modal choice consult Annex I. Regarding commodities, rail transport between ScanMed RFC countries is dominated by crude and manufactured minerals and building materials (24%), machinery and transport equipment (21%) and agricultural and forestry products (16%). The commodity structure for road transport appears broader in composition. The proportionately largest categories are agricultural and forestry products (21%), foods (15%), mining products and non-metallic minerals (12%), and chemicals and refined petroleum products (12%). As expected, the TMS contains a more detailed analysis of the rail freight traffic at corridor level. In 2012, the ScanMed RFC was used by approximately corridor trains, which by definition start and end in the corridor area and cross minimum one corridor border. The corridor train traffic composition is depicted schematically in Figure 14. Furthermore, about additional trains, i.e. trains that by definition end or start within the corridor area, cross at least one corridor border and enter/exit the corridor area, were operated on the corridor in With trains, the Germany-Italy bidirectional connection accounts for the vast majority of this trade. Table 5: Modal split for country-to-country transports (2012). Source: ETC (2014) Page 66

75 Figure 14: Corridor train traffic composition (both directions, 2012). Source: ETC (2014) The analysis of the current freight market finishes with a section on modal choice criteria grouped in the transport cost, time and quality categories. Although issues such as cargo type (time sensitive or not) and transport route (availability of alternative modes) can be critical, the interviewees considered price as the most prominent factor, followed by quality. Transit time received the lowest ratings, with stakeholders stating that often reliability of delivery is more important than total travel time. Among the quality criteria of punctuality, safety and security, tracking and tracing, flexibility, reliability and availability, the reliability and punctuality were selected by both shippers and operators as those of highest importance. 4.4 Expected future market developments Both the future freight traffic developments (up until 2017) and the long-term trends of this TMS chapter are based on a comprehensive PESTL (political, economic, social, technological and logistical) analysis of the current market situation, combined with the results of the stakeholder interviews. Page 67

76 In the near future, rail freight traffic is expected to increase faster than road transport for the majority of country-to-country connections. At this aggregate level, Norway and Sweden exports exhibit the highest growth rate in terms of both rail freight and short-sea shipping traffic. However, no significant changes are expected by 2017 in relation to the overall modal split of freight transport between the corridor countries. At the corridor level, the number of corridor trains is expected to increase by 5,7% (1.695 trains) up until For this kind of traffic, the highest growth rates should be expected between the Scandinavian countries. A similar increase (5,2% or 888 trains) is expected for the additional trains along the corridor by This forecast is confirmed by the stakeholders, more than 60% of which expect to upgrade their involvement in corridor-related services in both the near and the more distant future. In relation to technical parameters, the interviews revealed that stakeholders see longer and heavier trains as important contributors to the competitiveness of the rail freight transport through reducing transit costs per ton of transported cargo. They also emphasized the importance of harmonization along the entire corridor. On the contrary, the stakeholders consider the axle load of 22,5 t to be sufficient while, in relation to speed, they consider the average more important than the maximum speed, pinpointing to the significance of the last mile in the overall transit time. In identifying long-term trends, the widely used assumptions of an overall positive economic development, increased integration of European markets and a growing transport demand are accepted. In such an environment, long-distance hinterland transportation (>300km) is expected to increase. Rail freight might be able to take advantage of this growth if it manages to become more efficient through enhanced interoperability and higher investments in inter-modality. In general, intermodal transport is expected to contribute more to any additional rail volumes. In addition to a general growth of transport volumes along the corridor, rail traffic is expected to be affected positively by two major infrastructure projects: the Page 68

77 completion of the Brenner Base tunnel and the construction of the fixed Fehmarn Belt link. Although, in the best case scenario, the freight transport volumes can be doubled by 2030, no major change of modal split in favor of rail is likely on the basis of these investments alone. 4.5 Conclusions and Recommendations A SWOT analysis is deployed for reaching conclusions and producing recommendations. It appears that the most important factors in forming the future demand of rail freight transport are: GDP growth in the ScanMed RFC countries Elimination of barriers in international trade and transport Further development of combined transport in freight traffic Harmonization of costs, reliability and availability of rail freight services Further liberalization of rail freight services along the corridor In order to exploit these developments in the period up until 2017, major interventions by the infrastructure managers basically in terms of harmonization are required. They concern technical parameters of the network like train length and weight, the pricing regime, the path monitoring capabilities, and the provision of additional storage and siding capacity. The provision of flexible and reliable services facilitated by a corridor one-stop shop, in accordance with Regulation No 913/2010, is also considered important, together with improvements in accessibility of the network by existing and potential users. On the side of the railway undertakings, the decisive factors are the price, reliability and flexibility of the services, followed by tracking and tracing capabilities, and a general customer orientation of the services offered. For further information of the SWOT analysis consult Annex II. Page 69

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79 5. The TMS of the ScanMed TEN-T Core Network Corridor The purpose of this chapter is to present the Transport Market Study (TMS) of the Scandinavian-Mediterranean TEN-T Core Network Corridor. As mentioned in Section 3.4, the Core Network Corridors (CNCs) were introduced in late 2013 as an instrument for the coordinated implementation of the TEN-T core network, which needs to be in place by One of these nine corridors, the purple coloured line of Figure 10indicates the Scandinavian-Mediterranean CNC or simply ScanMed CNC. As with all CVCs, ScanMed is headed by a European Coordinator, Mr. Pat Cox, supported by the so-called Corridor Forum, a consultative body consisting of representatives of the Member States, the infrastructure managers, local andregional authorities, transport users and the civil society. As stipulated in the TEN-T guidelines (EP&C, 2013), one of the first tasks of corridor management is the preparation of a corridor work plan. A draft of this work plan, containing a detailed definition of the corridor and the Multimodal Transport Market Study (MTMS), was published in November 2014 (EC, 2014). This document will be the sole source of the information contained in this chapter 4. It is important to stress that the ScanMed CNC covers both passenger and freight transportation. However, as the scope of this thesis is limited to surface freight transportation, no reference to passenger or air freight traffic will be made here. Inland waterway transport is also excluded as its contribution to corridor flows is rather local (northern Germany) and insignificant in volume. 4 The final work plan of the ScanMed CNC was published in May 2015 (EC, 2015), too late to be considered in the thesis. However, no major modifications to the final draft of Nov have been identified. Page 71

80 5.1 Corridor Alignment The ScanMed CNC is an essential north-south axis for the European economy, as it crosses almost the entire continent and covers seven EU Member States and Norway. Linking the main urban centres of Germany and Italy to Scandinavia and Malta, it is the longest of all TEN-T CNCs. Its general alignment appears in Figure 15. Figure 15: General alignment of the ScanMed CNC. Source: EC, 2014 Page 72

81 Table 6 displays the main sections of all corridor branches, as well as the existing overlaps with the ScanMed RFC (RFC3) and the four former Priority Projects listed below, which address the major bottlenecks along the corridor: Table 6: Main sections of ScanMed CNC. Source: EC, 2014 Page 73

82 Priority Project 1: "Railway axis Berlin-Verona/Milano-Bologna-Napoli- Messina-Palermo", ongoing. Priority Project 11: "Öresund Fixed Link" to connect Malmö and København directly by rail and road, completed and opened in Priority Project 12: "Nordic Triangle railway/road axis", ongoing. Priority Project 20: "Fehmarn Belt railway axis", studies ongoing, construction will begin along The comparison of this alignment with that of ScanMed RFC reveals significant overlaps but also some differences. For example, Finland and Malta (which does not have a railway) are missing from the RFC, as well as some sections in Germany (Rostock Berlin Nürnberg and Bremen - Hannover) and Italy (some port accesses are not the same). It should be noted, however, that according to Regulation 1316/2013the missing sections which define the ScanMed CNC but not yet the ScanMed RFC "shall be included in the respective [freight] corridors at the latest 3 yearsafter their implementation" in November 2015, thus November Objectives and Methodology of the MTMS The general objective of the Multimodal Transport Market Study (MTMS) is to evaluate the capacity of the future infrastructure along the ScanMed corridor in relation to expected traffic volume in Its specific objectives include: the description of the present and expected conditions of the ScanMedcorridor, the comparison of available capacities to the expected traffic volume in year 2030 on the basis of information provided by "official" national/ regional/ local sources, and the qualitative indication of investments required. In terms of the methodology followed for the preparation of the MTMS, two options were considered: the model-based and the study-based approach. Despite Page 74

83 the inherent coherence problems and potential gaps of available material, especially outside the hot spots of the corridor, the study-based approach was finally selected basically in order to avoid contradictions to national or project specific forecasts and investment plans which, in general, have a binding character for the Member States. A large number of sources and studies were reviewed including 4 sources of general focus, 21 reports on market/corridor segments and another 21 studies on particular nodes. 5.3 Corridor Infrastructure and Traffic Volume An overview of the quantitative characteristics of the corridor infrastructure is displayed in Table 7 below. Table 7: Basic characteristics of the ScanMed CNC. Source: EC, In terms of traffic volume, the study has produced the following country-tocountry origin/destination tables for rail, road and sea freight transport (Tables 8 to 10 respectively). Although these tables refer to 2010 figures and are based on the same basic information of the ETISPlus database used in compiling Tables 2-4 of Section 4.3 (for the RFC TMS), there are significant differences between the two sets. Page 75

84 Table 8: International rail freight volume (1.000 tonnes). Source: EC, Table 9: International road freight volume (1.000 tonnes). Source: EC, Table 10: International sea freight volume (1.000 tonnes). Source: EC, Page 76

85 Firstly, the rail and road volumes are much lower than the corresponding RFC figures, despite the inclusion of one more country (Finland). The basic reason for this discrepancy, which however is not sufficient to explain all difference, stems from the fact that the Italian volumes have been modified to depict only flows via the Brenner axis. Secondly, the sea freight volumes are now much higher. The inclusion of the Finnish quantities explains only about 1/3 of the difference. A possible explanation of these inconsistencies can be the fact that information contained in AlpInfo 2012 and the ProgTrans 2012/2013 World Reports was used in addition to ETSPlus in calculating the CNC figures. The most important flows in Tables 8-10 are marked in pink. There are no discrepancies in this regard with the results of the RFC TMS. 5.4 KPIs and Compliance Analysis The regulation establishing the CNCs (EP&C, 2013) has set the overall objective of strengthening the social, economic and territorial cohesion of the EU. In terms of specific objectives, the Member States have agreed on the list of Table 11, which have to be met by 2030 at the latest. The objectives of Table 11 are also being used as Key Performance Indicators (KPIs) for monitoring compliance with the targets set for year The basic results of the compliance analysis are: Rail: The standard gauge is not a problem with the exception of Finland, which is exempted because of its isolated network. A few non-electrified sections still exist in Denmark and Germany. Substandard segments in terms of train length exist in Sweden, Germany and on many sections in Italy including the Brenner line. The Italian network south of Bologna includes substandard segments in relation to axle loads and loading profiles for the transport of semi-trailers. Serious interoperability constraints result from different electrification standards and low rate of ERTMS implementation. Page 77

86 Table 11: The objectives of the ScanMed CNC. Source: EC, Road:significant congestion problems exist around most largecities during peakperiods. The completion of the Fehmarn Belt fixed link will result in significant time savings. Most probably the public sector alone will be unable to finance the required infrastructure in relation to safe parking areas, refuelling stations, etc. but can affect transport choices through interventions of various forms. Ports: The requirements are basically fulfilled. The environmental infrastructure is still being developed in some of the 25 ScanMed core ports. VTMIS and SafeSeaNet are fully implemented. Harmonization of data exchange through e- Maritime needs further development. Page 78

87 Rail-road terminals: All RRTs are connected to the rail and road networks, so this criterion is met. The assessment of the other indicators like provision of information flows will be done later this year. 5.5 Capacity Constraints and List of Projects Through an extensive review of numerous studies, reports and forecasts, the MTMS concluded that the core network areas with highest transport volume in the year 2030 will be: Rail: Mjölby Malmö, Göteborg Malmö, Malmö København Taulov, Bremen/Hamburg Hannover Würzburg, München Innsbruck, Bologna Firenze Roma Napoli Road: Lübeck Hamburg/Bremen Hannover, Würzburg Nürnberg München, Firenze Roma. The comparison of the expected traffic volumes and network capacities in 2030 leads to the identification of possible bottlenecks. The analysis shows that, even after the construction of new infrastructure (Fehmarn Belt fixed link, Brenner Base Tunnel and their accesses), there will be bottlenecks impeding the transport of goods and passengers in the future. The most problematic areas will be: Finland, rail: Finland, road: Sweden, rail: Kouvola Hamina - Kotka, Luumäki Vainikkala, Helsinkinode, Helsinki Turku; Regions Turku and Helsinki, Koskenkylä Kotka Hamina Vaalimaa; Stockholm and Göteborg nodes, Hässleholm Lund, Trelleborg Malmö (- København); Page 79

88 Denmark, rail: Germany, rail: Germany, road: Austria: (Malmö-) København region; Bremen/Hamburg - Hannover, Würzburg - Nürnberg, München area; Regions Hamburg, Hannover, Würzburg Nürnberg, München; No capacity problems reported. The said analysis of documents, reports, studies and national development plans resulted in a long list of projects which will form the basis for the implementation of the corridor. This list is displayed in Table 12 below (the term Diverse refers to multi-country projects). Table 12: Number of projects by mode and country. Source: EC, Page 80

89 5.6 ScanMed CNC vs. ScanMed RFC Before changing subject it is worth mentioning a number of differences between the ScanMed CNC and RFC in addition to those concerning their geographical scope, which have been mentioned already in Section 5.1. As shown in Table 13, they mainly concern the scope (CNC, covering passengers and multimodal freight, is broader than RFC, which is restricted to rail freight), the objective (CNC deals with the coordinated infrastructure planning and implementation of the corridor, while RFC relates to annual timetabling and improvements of freight train path availability), the type of traffic(cnc examines the total traffic load of each corridor link, while RFC focuses on international trains having origin and/or destination on the corridor),the time horizon of the TMS (2030 for the CNC vs for the RFC) and the scheduling of the market studies (9/2014 for the CNC MTMS vs. 11/2014 for the RFC TMS). Table 13: Differences between ScanMed CNC and RFC. Source: EC, In view of these differences and in order to avoid overlaps in activities, it has been decided that CNC concentrates on infrastructural aspects, while the focus of RFC remains on interoperability improvements and other operational items leading to freight rail traffic increases in the short/medium term. Page 81

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91 6. Monitoring the Performance of the Corridor This chapter explains the approach that is going to be followed for monitoring the performance of the corridor. Chapters 2 and 3 have shown the similarities between the TEN-T core network corridors and the green corridors. It was, thus, concluded that the methodology developed by the SuperGreen project can be used to assess the ScanMed corridor. The different steps for an effective corridor benchmarking are going to be presented below. The text serves as a set of guidelines that takes into consideration the knowledge and experience of SuperGreen. 6.1 Benchmarking Goal Benchmarking a corridor can lead to important gains ranging from having a better understanding of the present state of affairs and locating problems that need attention to following developments over time and comparing with other cases. A clear benchmarking goal statement prior to the analysis usually assists decision making during all subsequent tasks. Such a statement is even more important for complex systems like a transport corridor that involve numerous stakeholders and sometimes conflicting priorities. In the ScanMed case, the setting of a clear list of specific objectives by the corridor management (refer to Table 11) adequately meets this requirement. For the present corridor benchmarking exercise, the objective is to assess the sustainability of the ScanMed corridor in the context of Figure 3 (Chapter 2). 6.2 Corridor Description Defining the corridor under investigation is another task that has to take place at a very early stage. The official policy documents establishing all types of corridors (RFCs, TEN-T CNCs, etc.) tend to define them by locations that represent rather broad geographical areas where the corridors start, end or pass through. This Page 83

92 needs to be worked out in a more detailed manner specifying the relevant modes, routes, links, terminals and supporting facilities. In fact, the MTMS of the ScanMed CNC devotes a lot of effort in providing an exact definition of the corridor. This is of high importance in the case of CNCs as, on one hand, the facilities included in the corridor description are subject to specific technical specifications to be met by 2030 and, on the other, are eligible for financial support from the available EU schemes. On the contrary, the description of the ScanMed RFC is much thinner. In relation to the present ScanMed assessment exercise: The scope of the analysis is limited to freight transport; passengers are excluded. The scope includes only rail, road and short-sea shipping transport; air transport, inland waterways and pipelines are excluded. As mentioned in Section 5.1 the alignment of the ScanMed RFC and CNC are not identical. When it comes to rail freight, CNC is broader than RFC. It is expected that in November 2015, when the RFC will become officially operational, its scope will be extended to cover the missing parts. However, for now the material that became available to us through the existing RFC TMS do not contain information on these missing parts. As such, we are forced to restrict coverage to the RFC alignment. For conformity reasons, and due to the fact that this thesis aims to demonstrate the application of the methodology rather than develop operational indices, we had to expand this restriction to the other modes, too. 6.3 KPI s Selection In general KPIs are selected by the corridor management on the basis of the objectives being pursued. In this sense, it is not surprising that the list of objectives that have been set for ScanMed (Table 11) is also used as the list of KPIs for monitoring compliance. Page 84

93 Along the same line of thinking, since the objective of this thesis is to assess the sustainability of the ScanMed corridor in the context of green corridors, the KPIs that need to be used are those suggested by the SuperGreen project: Out-of-pocket costs (excluding VAT), measured in /tonne-km, Average speed, measured in km/h, Reliability of service (in terms of timely deliveries), measured in percentage of consignments delivered within a pre-defined acceptable time window, Frequency of service, measured in number of services per year, CO 2 -eq emissions, measured in g/tonne-km, and SOx emissions, measured in g/tonne-km. For further information consult Annex III. 6.4 Methodological Principles The SuperGreen methodology involves the following four steps: Step 1: Step 2: Step 3: Step 4: Disaggregate the corridor into transport chains. Select a sample of representative transport chains. Estimate the KPI values for all chains in the sample. Aggregate these values into corridor-level indicators using appropriate weighs and methods. 6.5 Sample Construction The second step of the methodology presented above involves the selection of a sample. This sample should be viewed as a basket of typical transport chains describing the corridor. The approach resembles the functionalities of the Consumer Price Index (CPI) calculated by the statistical offices around the world. In the CPI context, the basket of goods and services that is used for calculating the CPI is selected based on information on the spending habits of the population examined, as provided by the so-called Household Expenditure Survey (HES). Page 85

94 The question is what source of information can play the HES role in the context of transport corridors. The use of transport model results is currently being examined in the framework of the GreCOR project in DTU Transport. The purpose of this thesis is to investigate the possibility of using the TMS of the RFCs or CNCs for creating meaningful samples and calculating the corresponding KPIs. The chains selection will be described in detail in the next chapter. Here only some broad guidelines are mentioned. The selected chains should cover: all segments of the corridor, all modes of transport performing in the corridor (rail, road, short-sea shipping), all types of transport chains appearing in the corridor, and all types of vehicles running along the corridor. 6.6 Data Collection The information for calculating the KPIs is essential. Preferably it should come from official statistics or other published sources. Missing information can be solicited directly from stakeholders, but in this case due care should be given to data verification. Models can prove very useful for quantifying variables that are commercially sensitive and rarely reported. In this case, consistency should be of primary concern. In general, the KPI values should fulfill the following criteria: Consistency: The methodology should permit meaningful comparisons over time. Change in data, default values, methods or other factors that affect the results must be adequately reported. Transparency: All assumptions, data sources or calculation methods must be clearly described. Accuracy: If the results are to have any practical value in decision making, KPI figures need to be sufficiently accurate. Uncertainties should be reduced as far as possible. Page 86

95 The present thesis draws on a number of different sources of information. Besides the RFC TMS and the CNC MTMS, which are basic documents reviewed, information has been sought from ETISPlus, Eurostat and some internal DTU Transport documents used in transport modeling. 6.7 Emissions Estimation Forfulfilling the above criteria (consistency, transparency and accuracy) in estimating emissions, it is necessary to set system boundaries. Swahn (2010) defines four system boundaries: System boundary A: includes traffic and transportation related activities concerning the operation and maintenance of the vehicles and the equipment used for climate control of goods. System Boundary B: includes on top of Boundary A the energy consumed for the extraction, production and distribution of the fuel used by the vehicles and their equipment. System Boundary C: includes on top of Boundary B the energy needed for the operation and maintenance of infrastructure. System Boundary D: includes on top of Boundary C the energy required for the production and scrapping of the vehicles/vessels and loading units themselves (life cycle approach). Page 87

96 Figure 16: Definition of system boundaries. Source: Swahn (2010) Another issue in estimating carbon emissions relates to their type. The most common measure is CO 2. However, if it is possible to calculate CO 2 -eq instead, which accounts for all other greenhouse gases, it is certainly preferable. For the purposes of this thesis, the emissions are calculated using the EcoTransIT web-based tool. The model is capable of calculating both CO2 and CO2-eq; so, the CO2-eq option is being used. In addition, the system provides also the option of calculating energy consumption and emissions at either the Tank-to-Wheel (Boundary A) or Well-to-Wheel (Boundary B) level. The Well-to-Wheel option is selected, as this is the minimum required boundary level permitting meaningful comparisons between modes and logistics solutions. 6.8 KPI Aggregation The weights used for aggregating chain-level KPIs to corridor-level ones should express the significance of each chain in the entire corridor and depend on the actual form of the KPI. For example, usuallycosts and emissions are expressed in relative form (per tonne*km). In such occasions, the tonne*km figure of each chain should be used as weight in the aggregation. Page 88

97 Time is usually expressed as average speed (unless all chains in the sample concern a single origin/destination pair). The best way to aggregate speed, reliability and frequency of service is probably through the use of cargo volume as weight. 6.9 Benchmarking Frequency The frequency of monitoring the performance of a corridor is decided by the corridor management, depending on the objectives pursued. The RFC regulation prescribes customer satisfaction surveys on an annual basis. Of course, developments concerning infrastructure do not need to be reported so frequently. Page 89

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99 7. Sample Construction and Estimation 7.1 Selection and Estimation of Rail Chains In order to create the sample, we need information at the corridor level. Only the RFC TMS provides such information. In fact, the study distinguishes between the so-called corridor trains, which start and end in the corridor area and cross at minimum one corridor border, and the additional trains, which start or end within the corridor area, cross at least one corridor border and enter/exit the corridor area. Given that neither the exact origin nor destination of the additional trains is known (we only have information about the countries of origin/destination), it was decided to exclude these trains from the analysis and restrict it to the corridor trains. The information provided on corridor trains concerns the 15 origin/destination pairs (O/D) of Table 14. They are the most important O/D pairs of corridor trains in 2012 (in both directions). The yearly trains were calculated by extrapolating the number of trains observed during two weeks of the year, as provided by the Infrastructure Managers along the corridor. These chains represent nearly 75% of the corridor trains running along the ScanMed RFC, which in turn account for 63% of the corridor-related trains (the sum of corridor and additional trains). So, the sample corresponds to about 47% of the corridor-related trains, which is more than enough by all means. Countries Chain O/D Relations Number of trains 1 Alnabru - Hallsberg 1820 Norway - Sweden 2 Kongsvinger - Karlstad Alnabru - Trelleborg Alnabru - Älmhult 624 Sweden - Denmark 5 Malmo - Taulov 624 Sweden - Germany 6 Malmo - Maschen Göteborg - Hannover 520 Denmark - Germany 8 Fredericia - Maschen Taulov - Hamburg 312 Germany - Austria 10 Munchen - Villach Munchen - Hall of Tirol Munchen - Verona 4992 Germany - Italy 13 Munchen - Brescia Lubeck/Hamburg - Verona 1248 Austria -Italy 15 Worgl - Trento 1664 Total Table 14: Corridor trains on ScanMed (both directions, 2012) Source: ETC (2014) Page 91

100 For validation purposes, this information was combined with cargo volume figures from the ETIS-Netter database. The results are presented in Table 15. The volume/train ratio ranges dramatically from 0,20 to 2.101,58 tons/train. Ratios below 20 tons/train (in pink) were considered outliers and were excluded from the analysis. The sample was, thus, reduced to the 10 chains of Table 16. The sample chains appear schematically in Figure 17. Countries Chain O/D Relations Number of trains 1000t Tons/Train 1 Alnabru - Hallsberg ,37 0,20 Norway - Sweden 2 Kongsvinger - Karlstad ,45 12,94 3 Alnabru - Trelleborg ,27 381,84 4 Alnabru - Älmhult ,02 126,64 Sweden - Denmark 5 Malmo - Taulov ,91 25,49 Sweden - Germany 6 Malmo - Maschen ,63 2,00 7 Göteborg - Hannover ,87 178,60 Denmark - Germany 8 Fredericia - Maschen ,89 179,13 9 Taulov - Hamburg 312 5,90 18,92 Germany - Austria 10 Munchen - Villach ,40 79,71 11 Munchen - Hall of Tirol ,63 17,03 12 Munchen - Verona ,91 146,42 Germany - Italy 13 Munchen - Brescia ,67 664,99 14 Lubeck/Hamburg - Verona ,73 91,93 Austria -Italy 15 Worgl - Trento , ,58 Table 15: Train utilization ratio Countries Chain O/D Relations Number of trains Norway - Sweden 1 Alnabru - Trelleborg Alnabru - Älmhult 624 Sweden - Denmark 3 Malmo - Taulov 624 Sweden - Germany 4 Göteborg - Hannover 520 Denmark - Germany 5 Fredericia - Machen 1222 Germany - Austria 6 Munchen - Villach Munchen - Verona 4992 Germany - Italy 8 Munchen - Brescia Lubeck/Hamburg - Verona 1248 Austria -Italy 10 Worgl - Trento 1664 Table 16: Rail freight sample chains Page 92

101 Figure 17: Map of rail freight sample chains. Source: Own compilation Page 93

102 The next task is to estimate the KPI values for each and every chain of the sample. Several databases were consulted to find the data needed. The KPIs and the source of information used in calculating the corresponding values are listed below: Costs: The estimation is based on internal unpublished information of DTU Transport, taking into consideration the train traction (diesel or electric). The estimation is described in detail in Section Time: Average speed figures come from ETIS-Netter database. It appears, however, that the information does not fluctuate per chain (80 Km/h for all chains), basically nullifying the effect of this parameter in assessing the corridor. Reliability: No data was found for this indicator. Frequency: The number of trains per year figure of the RFC TMS can be used as the KPI value for this indicator. CO 2 -eq emissions: The EcoTransIT World tool was used for estimating these values (refer to Section 7.1.2). SO X emissions: The EcoTransIT World tool was used for estimating these values (refer to Section 7.1.2). The information extracted directly from various databases is summarized in Table 17 below. Distance figures are extracted from the ETIS-Netter database. Countries Chain O/D Relations Number of trains 1000t Distance (Km) Speed (Km/h) Norway - Sweden 1 Alnabru - Trelleborg , Alnabru - Älmhult , Sweden - Denmark 3 Malmo - Taulov , Sweden - Germany 5 Göteborg - Hannover , Denmark - Germany 6 Fredericia - Machen , Germany - Austria 7 Munchen - Villach , Munchen - Verona , Germany - Italy 9 Munchen - Brescia , Lubeck/Hamburg - Verona , Austria -Italy 11 Worgl - Trento , Table 17: KPI values extracted from databases Page 94

103 7.1.1 Cost Calculations Obtaining cost estimates is quite difficult, as this kind of information is usually lacking due to its sensitive nature. So, cost estimation is the only available option, usually performed under a set of assumptions. The data needed for this calculation are distance, cargo volume, frequency of service and the type of traction. Even though, the 96% of the total rail distance is electrified, it is necessary to know if the non-electrified segments play a significant role in any of the selected chains. In Norway, Sweden, Austria and Italy all corridor rail lines are fully equipped with electrification. On the other hand, Denmark has a small region (119,3 Km) between Ringsted and Rødby (northern access to Fehmarn Belt Fixed Link) which is not electrified. In Germany, there are two stretches not electrified, the connection between Puttgarden and Bad Schwartau (83,6 Km, southern access to Fehmarn Belt Fixed Link) and the connection between Hof and Regensburg (179,3 Km, Leipzig München connection). The connection between Hof and Regensburg is not important for cost calculations, since it is not part of the ScanMed RFC alignment. Checking of all non-electrified segments of the corridor has confirmed that none of our sample chains is affected. Therefore, the train traction is of no concern. The fixed and variable costs of running a train are presented in Table 18. Costs Fixed Costs ( /year) Variable Costs Electric Locomotive Maintenance - 1 /Km Consumption - 21,8 KWh/Km Wagon - 79,47 /day Driver Infrastructure - 0,289 /Km Table 18: Fixed and variable costs for train operations ( ) Source: DTU Transport Eurostat data was used for obtaining the cost of electricity in the corridor countries. Table 19 shows the prices of electricity per kwh in each of the corridor countries and calculates the average value (for year 2012). The value obtained Page 95

104 from this calculation was 0,114 /kwh, which is very close to the EU-28 area average (0,116 /kwh). Countries Prices ( /kwh) Norway 0,09 Sweden 0,08 Denmark 0,10 Germany 0,13 Austria 0,11 Italy 0,18 Average 0,114 Table 19: Price of kwh ( ) Source: Eurostat The fixed costs consist of the rental expense for the electric locomotive and the driver s salary. The data used for fixed costs (Table 18) are given on a yearly basis. Therefore, it is necessary to calculate the time (in days), say d, required for a train to run from origin to destination. Then, the total fixed costs of the chain (Fixed_Costs) are calculated by the formula: The variable costs concern the maintenance of the locomotive, the electric consumption, the rental cost per wagon and the infrastructure costs (Table 18). Both maintenance costs and infrastructure costs are given in /Km, so the maintenance and infrastructure cost per trip (MI) is: In order to calculate the wagon rental cost, we need to know the average number of wagons a train has. It is mentioned in the RFC TMS that a number of 30 wagons per train is a reasonable assumption. Then, the wagon cost per trip (W) is: Page 96

105 The energy cost per trip (C) is straightforward: It follows that the total variable costs of the chain (Variable_Costs) are: and the total chain costs (Total_Costs) are: The costs of the rail chains are displayed in Table 20, while the mode-level cost KPI is calculated in Table 21. Countries Chain Fixed Costs ( ) Variable Costs ( ) Norway - Sweden Sweden - Denmark Sweden - Germany Denmark - Germany Germany - Austria Germany - Italy Austria -Italy Corridor - Level Table 20: Fixed and Variable Costs Values ( ) Countries Chain Total Costs ( ) 1000t Distance (Km) Weigh (T*Km) Costs ( /T-Km) Norway - Sweden , , , ,053 Sweden - Denmark , ,262 Sweden - Germany , ,037 Denmark - Germany , ,037 Germany - Austria , , , ,046 Germany - Italy , , , ,073 Austria -Italy , ,003 Mode - Level , ,022 Table 21: Chain and Mode level Costs ( /T-Km) Page 97

106 7.1.2 Emissions Both CO 2 -eq emissions and SO X emissions are estimated using the EcoTransIT World tool. The methodology is supported by scientific institutes that enjoy high reputation internationally. The minimum requirements of the model in terms of user inputs (in the so-called standard input mode ) are the cargo volume and unit (tons or TEUs), the origin and destination, and the mode of transport. In the extended input mode, which is much more flexible, the user needs to specify the type of vehicle. As we do not have information on the type of trains using the corridor, we were obliged to use the standard input mode. The default train of this standard mode is the following: Characteristics Train Train Weight 1000 T Emission Standard 5 Electrified Load Factor 6 60% ETF 7 50% Table 22: EcoTransIT default train characteristics Using this type of train both CO 2 -eq emissions and SO X emissions were estimated. The input for ETcoTransIT is cargo volume. As mentioned in Section 6.7, EcoTransIT can produce Well-to-Wheel emission figures. The absolute values of total emissions per chain are presented in Table 23 and are converted in specific values (in g/t-km) in Table 24. What is impressive in these results, is the very low emissions produced in the chains involving Sweden. Apparently, this has to do with the fact that trains in this country are run on renewable energy. 5 Emission Standard: Defines the traction of the train (diesel or electrified). 6 Load Factor: Defines the cargo weight as a percentage of the payload capacity of the train. 7 Empty Trip Factor: Defines the additional distance that the vehicle runs empty related to the distance loaded. Page 98

107 Countries Chain CO2-eq emissions (T) SO X emissions(kg) Norway - Sweden 1 21,00 29,00 2 6,53 8,92 Sweden - Denmark 3 49,00 88,00 Sweden - Germany , ,00 Denmark - Germany , ,00 Germany - Austria 6 333,00 240, , ,00 Germany - Italy , , , ,00 Austria -Italy , ,00 Total , ,92 Table 23: Total emissions per chain. Source: EcoTransIT Countries Chain CO2-eq emissions (g/t-km) SO X emissions(g/t-km) 1 0,133 0,000 Norway - Sweden 2 0,136 0,000 Sweden - Denmark 3 12,273 0,022 Sweden - Germany 4 10,683 0,012 Denmark - Germany 5 16,431 0,017 Germany - Austria 6 10,923 0, ,391 0,032 Germany - Italy 8 15,250 0, ,998 0,020 Austria -Italy 10 11,367 0,032 Mode-Level 12,108 0,027 Table 24: Chain-level emissions and Mode-level related emissions (g/t-km) Page 99

108 7.1.3 Rail Freight KPI s values To conclude with the rail chains, Table 25 summarizes all chain-level KPI values and assesses the performance of this mode along the ScanMed corridor. Countries Chain O/D Relations Costs ( /T-Km) Speed (Km/h) Frequency CO2-eq emissions (g/t-km) SO X emissions(g/t-km) Norway - Sweden 1 Alnabru - Trelleborg 0, ,133 0,000 2 Alnabru - Älmhult 0, ,136 0,000 Sweden - Denmark 3 Malmo - Taulov 0, ,273 0,022 Sweden - Germany 4 Göteborg - Hannover 0, ,683 0,012 Denmark - Germany 5 Fredericia - Machen 0, ,431 0,017 Germany - Austria 6 Munchen - Villach 0, ,923 0,008 7 Munchen - Verona 0, ,391 0,032 Germany - Italy 8 Munchen - Brescia 0, ,250 0,036 9 Lubeck/Hamburg - Verona 0, ,998 0,020 Austria -Italy 10 Worgl - Trento 0, ,367 0,032 Mode-Level 0, ,108 0,027 Table 25: Rail Freight KPI values Page 100

109 7.2 Selection and Estimation of Road Chains The basic information for constructing the sample of road chains also comes from the RFC TMS. The difference is that now we have cargo volume figures for the chains. The criteria used are the following: 1. Select the three country-to-country connections with the highest cargo volume on each direction. 2. Unify locations that are located within a radius of 20 kilometres. 3. Select the route with the lowest total costs, calculated on the basis of an average variable cost of 0.75 /Km inflated by toll and ferry costs, if applicable. 8 The O/D data extracted from the RFC TMS was on a NUTS 3 9 basis. In order to comprehend the chains, the most important city of each NUTS 3 area was selected as its centre. Some areas have the same name as the major city; thus, only those in which this doesn t happen are mentioned below: Table 26: NUTS 3 Areas. Source: Own Compilation The application of all the above mentioned criteria to the data provided by the RFC TMS results in a total of 76 one-directional chains, covering all corridor area. These chains can be seen in Table 27 together with the corresponding cargo volumes and the ferry route involved, if any. The routes are schematically depicted in Figure Source: ETIS-Plus and DTU Transport. 9 Nomenclature of Units for Territorial Statistics. Page 101

110 Countries Chain O/D Relations Ferry Route 1000t 1 Ostfold - Goteborg None 281,7 Norway - Sweden 2 Oslo - Goteborg None 237,0 3 Oslo - Malmo None 223,2 4 Goteborg - Oslo None 469,3 Sweden - Norway 5 Malmo - Oslo None 322,9 6 Goteborg - Ostfold None 245,9 7 Oslo - Kolding Goteborg - Frederiksavn 41,6 Norway - Denmark 8 Ostfold - Kolding Goteborg - Frederiksavn 41,4 9 Ostfold - Aarhus Goteborg - Frederiksavn 20,1 Denmark - Norway Norway - Germany Germany - Norway Austria - Norway Italy - Norway Sweden - Denmark Denmark - Sweden Sweden - Germany Germany - Sweden Sweden - Austria Austria - Sweden Kolding - Oslo Aarhus - Oslo Goteborg - Frederiksavn Goteborg - Frederiksavn 130,0 34,5 12 Ostfold - Hamburg Rødby - Puttgarden 6,0 13 Oslo - Hamburg Rødby - Puttgarden 3,8 14 Ostfold - Lubeck Rødby - Puttgarden 2, Hamburg - Oslo Hamburg - Ostfold Rødby - Puttgarden Rødby - Puttgarden 15,2 5,5 17 Innsbruck - Ostfold Gedser - Rostock 0, Innsbruck - Oslo Verona - Oslo Gedser - Rostock Gedser - Rostock 0,9 1,1 20 Bolzazo - Oslo Gedser - Rostock 1,0 21 Bolzano - Ostfold Gedser - Rostock 0,7 22 Malmo - Kolding None 188,8 23 Goteborg - Kolding Goteborg - Frederiksavn 158,1 24 Malmo - Aarhus None 80,6 25 Kolding - Malmo None 244,3 26 Kolding - Goteborg Goteborg - Frederiksavn 216,1 27 Malmo - Aarhus None 84,1 28 Malmo - Hamburg Rødby - Puttgarden 36,2 29 Goteborg - Hamburg Rødby - Puttgarden 33,2 30 Malmo - Lubeck Rødby - Puttgarden 12,2 31 Hamburg - Malmo Rødby - Puttgarden 41,0 32 Hamburg - Goteborg Rødby - Puttgarden 31,9 33 Lubeck - Malmo Rødby - Puttgarden 13,0 34 Goteborg - Innsbruck Rødby - Puttgarden 1,9 35 Malmo - Innsbruck Rødby - Puttgarden 1,1 36 Innsbruck - Malmo Rødby - Puttgarden 1,4 37 Innsbruck - Goteborg Rødby - Puttgarden 2,0 Page 102

111 Countries Chain O/D Relations Ferry Route 1000t 38 Malmo - Brescia Rødby - Puttgarden 2,3 Sweden - Italy 39 Goteborg - Brescia Rødby - Puttgarden 2,0 40 Malmo - Verona Rødby - Puttgarden 1,7 41 Verona - Malmo Rødby - Puttgarden 3,2 Italy - Sweden 42 Bolzano - Malmo Rødby - Puttgarden 2,5 43 Verona - Goteborg Rødby - Puttgarden 1,9 44 Kolding - Hamburg None 194,2 Denmark - Germany 45 Kolding - Lubeck None 58,4 46 Aarhus - Hamburg None 57,7 47 Hamburg - Kolding 182,3 None Germany - Denmark 48 Lubeck - Kolding 67,6 49 Hamburg - Aarhus None 62,8 None 51 Kolding - Innsbruck Denmark - Austria None 4,5 52 Aarhus - Innsbruck None 0,9 Austria - Denmark 53 Innsbruck - Kolding None 2,8 None 54 Kolding - Verona None 8,8 Denmark - Italy 55 Kolding - Bolzano 7,3 None 56 Kolding - Brescia 6,5 57 Verona - Kolding None 9,1 Italy - Denmark 58 Bolzano - Kolding None 6,1 59 Brescia - Kolding None 5,2 60 Munchen - Innsbruck None 35,5 Germany - Austria 61 Hamburg -Innsbruck None 34,2 62 Rosenheim - Innsbruck None 33,0 63 Innsbruck - Munchen None 27,1 Austria - Germany 64 Innsbruck - Rosenheim None 23,8 65 Innsbruck - Hamburg None 19,0 66 Hamburg - Bolzano None 21,6 Germany - Italy 67 Hamburg - Verona None 20,9 68 Hamburg - Brescia None 19,6 69 Verona - Hamburg None 29,1 Italy - Germany 70 Verona - Hannover None 28,9 71 Bolzano - Hamburg None 21,3 72 Innsbruck - Bolzano None 50,2 Austria -Italy 73 Innsbruck - Verona None 35,4 74 Innsbruck - Trento None 24,8 Italy - Austria 75 Bolzano - Innsbruck None 60,8 76 Verona - Innsbruck None 21,6 Table 27: Representative transport chains (2012) Source: ETC (2014) Page 103

112 Figure 18: Map of Road Freight Transport Chains. Source: Own compilation Page 104

113 The data sources used for calculating the KPI values for the road chains are shown below: Costs: Cost estimates were only obtained for Denmark, but were used for the entire corridor area due to the lack of a better approximation (refer to Section 7.2.1). Source: DTU Transport and ETIS-Netter Tool. Time: Average speed (in Km/h). Source: ETIS-Netter Tool. Reliability: No data was found for this indicator. Frequency: It should be noted that, when it comes to road transport, the meaning of this indicator is rather limited due to the fact that a voyage can be arranged basically at any time the need arises. Nevertheless, a theoretical frequency value can be calculated on the basis of the total tonnage moved and the average payload (refer to Section 7.2.2). CO 2 -eq emissions: The EcoTransIT World tool was used for estimating these values (refer to Section 7.2.3). SO X emissions: The EcoTransIT World tool was used for estimating these values (refer to Section 7.2.3) Cost Calculation Due to data unavailability, the road freight costs will be calculated on the basis of the Danish figures provided by DTU Transport. The data obtained concern the average cost per Km that includes maintenance costs, the daily cost for renting a trailer, and the toll costs where applicable. The average cost per Km is 0.75 /Km and the rental cost of a trailer is /day. In addition, as shown in Table 27, some routes involve a ferry, as this is the lowest cost alternative. In these cases the ferry costs will be included in the final cost of the chain. Table 28 shows the cost calculations per chain. The toll costs, ferry costs and the distances were taken from the ETIS-Plus Database. It is mentioned that for chains involving a ferry connection, the distance at sea has been excluded from the millage cost, as this is included in the ferry cost. Page 105

114 Countries Chain O/D Relations 1000t Estimated Costs ( ) Toll Costs ( ) Ferry Cost ( ) Trailer Cost ( ) Total Cost ( ) Cost (cent/t-km) 1 Ostfold - Goteborg 281,7 158, , ,66 Norway - Sweden 2 Oslo - Goteborg 237,0 219, , ,54 3 Oslo - Malmo 223,2 421, , ,38 4 Goteborg - Oslo 469,3 219, , ,54 Sweden - Norway 5 Malmo - Oslo 322,9 421, , ,38 6 Goteborg - Ostfold 245,9 158, , ,66 7 Oslo - Kolding 41,6 417, , ,84 Norway - Denmark 8 Ostfold - Kolding 41,4 279, , ,08 9 Ostfold - Aarhus 20,1 286, , ,07 Denmark - Norway 10 Kolding - Oslo 130,0 417, , ,84 11 Aarhus - Oslo 34,5 348, , ,94 12 Ostfold - Hamburg 6,0 607, , ,40 Norway - Germany 13 Oslo - Hamburg 3,8 668, , ,30 14 Ostfold - Lubeck 2,5 564, , ,49 Germany - Norway Austria - Norway Italy - Norway Sweden - Denmark Denmark - Sweden Sweden - Germany Germany - Sweden Sweden - Austria Austria - Sweden Hamburg - Ostfold 5,5 668, , ,30 17 Innsbruck - Ostfold 0, , , ,90 19 Verona - Oslo 1, , , ,78 20 Bolzazo - Oslo 1, , , ,82 21 Bolzano - Ostfold 0, , , ,85 22 Malmo - Kolding 188,8 195, , ,69 23 Goteborg - Kolding 158,1 202, , ,44 24 Malmo - Aarhus 80,6 254, , ,43 25 Kolding - Malmo 244,3 195, , ,69 26 Kolding - Goteborg 216,1 202, , ,44 27 Malmo - Aarhus 84,1 254, , ,43 28 Malmo - Hamburg 36,2 246, , ,72 29 Goteborg - Hamburg 33,2 450, , ,65 30 Malmo - Lubeck 12,2 204, , ,18 31 Hamburg - Malmo 41,0 246, , ,72 32 Hamburg - Goteborg 31,9 450, , ,65 33 Lubeck - Malmo 13,0 204, , ,18 34 Hamburg - Oslo 18 Innsbruck - Oslo Goteborg - Innsbruck 15,2 0,9 1,9 35 Malmo - Innsbruck 1, , , ,07 36 Innsbruck - Malmo 1,4 942, , ,99 37 Innsbruck - Goteborg 2,0 668, , , , , ,73 41,61 41, ,30 5,86 6,05 5,92 Page 106

115 Countries Chain O/D Relations 1000t Estimated Costs ( ) Toll Costs ( ) Ferry Cost ( ) Trailer Cost ( ) Total Cost ( ) Cost (cent/t-km) 38 Malmo - Brescia 2, , , ,93 Sweden - Italy 39 Goteborg - Brescia 2, , , ,97 40 Malmo - Verona 1, , , ,02 41 Verona - Malmo 3, , , ,02 Italy - Sweden 42 Bolzano - Malmo 2,5 981, , ,04 43 Verona - Goteborg 1, , , ,90 44 Kolding - Hamburg 194,2 184, , ,60 Denmark - Germany 45 Kolding - Lubeck 58,4 191, , ,59 46 Aarhus - Hamburg 57,7 255, , ,49 47 Hamburg - Kolding 182,3 184, , ,60 Germany - Denmark 48 Lubeck - Kolding 67,6 191, , ,59 49 Hamburg - Aarhus 62,8 255, , ,49-27,73 5,37 51 Kolding - Innsbruck 4,5 892, Denmark - Austria - 52 Aarhus - Innsbruck 0,9 966, , ,36-27,73 Austria - Denmark 53 Innsbruck - Kolding 2,8 892, ,37-54 Kolding - Verona 8, , , ,41 Denmark - Italy 55 Kolding - Bolzano 7,3 984,00-27, ,36-56 Kolding - Brescia 6, ,25-27, ,34 57 Verona - Kolding 9, , , ,41 Italy - Denmark 58 Bolzano - Kolding 6,1 984, , ,36 59 Brescia - Kolding 5, , , ,34 60 Munchen - Innsbruck 35,5 117, , ,82 Germany - Austria 61 Hamburg -Innsbruck 34,2 700, , ,41 62 Rosenheim - Innsbruck 33,0 78, , ,13 63 Innsbruck - Munchen 27,1 117, , ,82 Austria - Germany 64 Innsbruck - Rosenheim 23,8 78, , ,13 65 Innsbruck - Hamburg 19,0 700, , ,41 66 Hamburg - Bolzano 21,6 767, , ,40 Germany - Italy 67 Hamburg - Verona 20,9 880, , ,37 68 Hamburg - Brescia 19,6 895, , ,37 69 Verona - Hamburg 29,1 880, , ,37 Italy - Germany 70 Verona - Hannover 28,9 798, , ,39 71 Bolzano - Hamburg 21,3 767, , ,40 72 Innsbruck - Bolzano 50,2 93, , ,98 Austria -Italy 73 Innsbruck - Verona 35,4 207, , ,56 74 Innsbruck - Trento 24,8 135, , ,74 Italy - Austria 75 Bolzano - Innsbruck 60,8 196, , ,66 76 Verona - Innsbruck 21,6 207, , ,56 Table 28: Costs of Road Freight Traffic. Sources: TMS RFC3, ETIS-Plus Page 107

116 7.2.2 Frequency As mentioned before, the theoretical frequency KPI is calculated on the basis of total quantities moved and the average shipment size. This latter figure is estimated on the basis of a standard truck, which has been chosen to be the one used for the emissions calculation by EcoTransIT (Table 29). Characteristics Truck Vehicle Type T Emission Standard Euro 5 Load Factor 60% ETF 20% Table 29: EcoTransIT Truck Model This truck has a gross weight of 40 t, which corresponds to a payload of 24 t. Because of the load factor (60 %) the truck carries on average 14,4 t of cargo. The number of trucks is obtained for each chain by dividing the annual cargo volume of the chain by 14,4 t. The resulting frequency figures are shown in Table Emissions Both CO2-eq emissions and SOx emissions are estimated using the EcoTransIT World tool. The standard input mode of the tool was used as mentioned previously. Both chain-level and mode-level emissions are presented in Table Vehicle Type: Gross weight class of the truck. Page 108

117 Countries Chain O/D Relations CO 2 -eq emissions (T) SOX emissions (Kg) CO2-eq emissions (g/t-km) SOX emissions (g/t-km) 1 Ostfold - Goteborg ,2 0,074 Norway - Sweden 2 Oslo - Goteborg ,2 0,082 3 Oslo - Malmo ,5 0,081 4 Goteborg - Oslo ,2 0,082 Sweden - Norway 5 Malmo - Oslo ,5 0,081 6 Goteborg - Ostfold ,2 0,074 7 Oslo - Kolding ,4 0,135 Norway - Denmark 8 Ostfold - Kolding ,9 0,170 9 Ostfold - Aarhus ,1 0,145 Denmark - Norway 10 Kolding - Oslo ,4 0, Aarhus - Oslo ,3 0, Ostfold - Hamburg ,1 0,115 Norway - Germany 13 Oslo - Hamburg ,9 0, Ostfold - Lubeck ,3 0,118 Germany - Norway Austria - Norway Italy - Norway Sweden - Denmark Denmark - Sweden Sweden - Germany Germany - Sweden Sweden - Austria Austria - Sweden 15 Hamburg - Oslo ,9 0, Hamburg - Ostfold ,0 0, Innsbruck - Ostfold ,0 0, Innsbruck - Oslo ,1 0, Verona - Oslo ,4 0, Bolzazo - Oslo ,5 0, Bolzano - Ostfold ,2 0, Malmo - Kolding ,1 0, Goteborg - Kolding ,3 0, Malmo - Aarhus ,0 0, Kolding - Malmo ,0 0, Kolding - Goteborg ,3 0, Malmo - Aarhus ,0 0, Malmo - Hamburg ,1 0, Goteborg - Hamburg ,0 0, Malmo - Lubeck ,9 0, Hamburg - Malmo ,1 0, Hamburg - Goteborg ,0 0, Lubeck - Malmo ,9 0, Goteborg - Innsbruck ,1 0, Malmo - Innsbruck ,8 0, Innsbruck - Malmo ,9 0, Innsbruck - Goteborg ,0 0,092 Page 109

118 Countries Chain O/D Relations CO 2 -eq emissions (T) SOX emissions (Kg) CO2-eq emissions (g/t-km) SOX emissions (g/t-km) 38 Malmo - Brescia ,0 0,088 Sweden - Italy 39 Goteborg - Brescia ,5 0, Malmo - Verona ,6 0, Verona - Malmo ,8 0,097 Italy - Sweden 42 Bolzano - Malmo ,7 0, Verona - Goteborg ,3 0, Kolding - Hamburg ,0 0,079 Denmark - Germany 45 Kolding - Lubeck ,0 0, Aarhus - Hamburg ,1 0, Hamburg - Kolding ,0 0,079 Germany - Denmark 48 Lubeck - Kolding ,0 0, Hamburg - Aarhus ,1 0,081 Denmark - Austria 51 Kolding - Innsbruck ,8 0, Aarhus - Innsbruck ,7 0,079 Austria - Denmark 53 Innsbruck - Kolding ,5 0, Kolding - Verona ,9 0,079 Denmark - Italy 55 Kolding - Bolzano ,6 0, Kolding - Brescia ,2 0, Verona - Kolding ,9 0,079 Italy - Denmark 58 Bolzano - Kolding ,6 0, Brescia - Kolding ,3 0, Munchen - Innsbruck ,9 0,080 Germany - Austria 61 Hamburg -Innsbruck ,4 0, Rosenheim - Innsbruck ,9 0, Innsbruck - Munchen ,0 0,087 Austria - Germany 64 Innsbruck - Rosenheim ,6 0, Innsbruck - Hamburg ,4 0, Hamburg - Bolzano ,4 0,082 Germany - Italy 67 Hamburg - Verona ,5 0, Hamburg - Brescia ,0 0, Verona - Hamburg ,5 0,080 Italy - Germany 70 Verona - Hannover ,1 0, Bolzano - Hamburg ,4 0, Innsbruck - Bolzano ,6 0,081 Austria -Italy 73 Innsbruck - Verona ,1 0, Innsbruck - Trento ,5 0,079 Italy - Austria 75 Bolzano - Innsbruck ,4 0, Verona - Innsbruck ,9 0,092 Table 30: Emissions of Road Freight Traffic Page 110

119 7.2.4 Road Freight KPI s values To conclude with the road chains, Table 31 summarizes all chain-level KPI values and assesses the performance of this mode along the ScanMed corridor. Countries Chain O/D Relations Costs ( /T-Km) Speed (Km/h) Frequency CO2-eq emissions (g/t-km) SOX emissions (g/t-km) 1 Ostfold - Goteborg 5, ,20 0,074 Norway - Sweden 2 Oslo - Goteborg 5, ,22 0,082 3 Oslo - Malmo 5, ,47 0,081 4 Goteborg - Oslo 5, ,21 0,082 Sweden - Norway 5 Malmo - Oslo 5, ,46 0,081 6 Goteborg - Ostfold 5, ,20 0,074 7 Oslo - Kolding 5, ,41 0,135 Norway - Denmark 8 Ostfold - Kolding 6, ,91 0,170 9 Ostfold - Aarhus 6, ,09 0,145 Denmark - Norway 10 Kolding - Oslo 5, ,41 0, Aarhus - Oslo 5, ,33 0, Ostfold - Hamburg 6, ,09 0,115 Norway - Germany 13 Oslo - Hamburg 6, ,87 0, Ostfold - Lubeck 6, ,31 0,118 Germany - Norway 15 Hamburg - Oslo 6, ,94 0, Hamburg - Ostfold 6, ,97 0, Innsbruck - Ostfold 5, ,01 0,129 Austria - Norway 18 Innsbruck - Oslo 5, ,13 0, Verona - Oslo 5, ,38 0,123 Italy - Norway 20 Bolzazo - Oslo 5, ,50 0, Bolzano - Ostfold 5, ,22 0, Malmo - Kolding 10, ,08 0,082 Sweden - Denmark 23 Goteborg - Kolding 6, ,33 0, Malmo - Aarhus 9, ,99 0, Kolding - Malmo 10, ,02 0,082 Denmark - Sweden 26 Kolding - Goteborg 6, ,34 0, Malmo - Aarhus 9, ,97 0, Malmo - Hamburg 7, ,12 0,152 Sweden - Germany 29 Goteborg - Hamburg 6, ,96 0, Malmo - Lubeck 8, ,90 0, Hamburg - Malmo 7, ,09 0,151 Germany - Sweden 32 Hamburg - Goteborg 6, ,96 0, Lubeck - Malmo 8, ,89 0,180 Sweden - Austria 34 Goteborg - Innsbruck 6, ,10 0, Malmo - Innsbruck 7, ,77 0, Innsbruck - Malmo 5, ,87 0,093 Austria - Sweden 37 Innsbruck - Goteborg 5, ,00 0,092 Page 111

120 Countries Chain O/D Relations Costs ( /T-Km) Speed (Km/h) Frequency CO2-eq emissions (g/t-km) SOX emissions (g/t-km) 38 Malmo - Brescia 5, ,98 0,088 Sweden - Italy 39 Goteborg - Brescia 5, ,47 0, Malmo - Verona 6, ,59 0, Verona - Malmo 6, ,76 0,097 Italy - Sweden 42 Bolzano - Malmo 6, ,73 0, Verona - Goteborg 5, ,26 0, Kolding - Hamburg 5, ,98 0,079 Denmark - Germany 45 Kolding - Lubeck 5, ,02 0, Aarhus - Hamburg 5, ,13 0, Hamburg - Kolding 5, ,98 0,079 Germany - Denmark 48 Lubeck - Kolding 5, ,05 0, Hamburg - Aarhus 5, ,12 0,081 Denmark - Austria 51 Kolding - Innsbruck 5, ,77 0, Aarhus - Innsbruck 5, ,68 0,079 Austria - Denmark 53 Innsbruck - Kolding 5, ,52 0, Kolding - Verona 5, ,87 0,079 Denmark - Italy 55 Kolding - Bolzano 5, ,58 0, Kolding - Brescia 5, ,24 0, Verona - Kolding 5, ,93 0,079 Italy - Denmark 58 Bolzano - Kolding 5, ,60 0, Brescia - Kolding 5, ,29 0, Munchen - Innsbruck 5, ,92 0,080 Germany - Austria 61 Hamburg -Innsbruck 5, ,41 0, Rosenheim - Innsbruck 6, ,92 0, Innsbruck - Munchen 5, ,98 0,087 Austria - Germany 64 Innsbruck - Rosenheim 6, ,63 0, Innsbruck - Hamburg 5, ,40 0, Hamburg - Bolzano 5, ,45 0,082 Germany - Italy 67 Hamburg - Verona 5, ,48 0, Hamburg - Brescia 5, ,95 0, Verona - Hamburg 5, ,47 0,080 Italy - Germany 70 Verona - Hannover 5, ,12 0, Bolzano - Hamburg 5, ,43 0, Innsbruck - Bolzano 5, ,60 0,081 Austria -Italy 73 Innsbruck - Verona 5, ,10 0, Innsbruck - Trento 5, ,51 0,079 Italy - Austria 75 Bolzano - Innsbruck 11, ,39 0, Verona - Innsbruck 5, ,92 0,092 Table 31: Road Freight KPI values Page 112

121 Total values and mode-level values for Road Freight Transport are presented below: Cargo Volume (1000T) Distance Costs ( ) CO2 (T) SOX (Kg) Total Table 32: Road Freight KPI S total values Cost ( /T-Km) CO2-eq (g/t-km) SOX (g/t-km) Total 0, , ,09754 Table 33: Road Freight KPI S corridor-level values The number of the mode-level values come from dividing the total KPI s value by the total sum of tons times total kilometers. Page 113

122 7.3 Selection and Estimation of Short-sea Shipping Chains The information used for constructing the sample for this mode comes from sources other than the RFC TMS and the CNC MTMS, as none of these two documents provides port-to-port flows. The results of the TRANS-TOOLS model was used instead. The criteria for the chain selection are now: Choose the ports with the highest volume per country. Ports must be within the catchment area of the RFC. The ScanMed corridor ports are shown in Chapter 5. However, not all of these ports are selected in our corridor sample. It is reminded that the alignment of the corridor is the one of the RFC; therefore, it excludes Finland (Helsinki, Kotka, Hamina, Naantali, Turku), Malta (Marsaxlokk, Valletta) and some German ports (Bremen, Rostock). Furthermore, Italy is excluded as the international seaborne freight traffic of the Italian ports within the corridor is negligible in comparison to rail and road traffic. The following ports were selected: Country Sweden Norway Denmark Germany Ports Stockholm Malmö Göteborg Oslo Grenland København Hamburg Lübeck Table 34: Ports of the corridor sample. Source: TMS RFC3 Page 114

123 The geographical coverage of TRANS-TOOLS varies from country to country. NUTS 3 is used for Germany, NUTS 2 for Sweden and Norway, and NUTS 1 for Denmark. For the Danish case, it was assumed that all freight traffic goes from/to København because this is the only major Danish port within the catchment area. The following table presents the assumptions made to extract data from TRANS- TOOLS in terms of geographical regions. Countries NUTS 1 NUTS 2 NUTS 3 City Västsverige Göteborg Sweden Sydsverige Malmö Denmark Denmark Sjælland København Oslo og Akershus Oslo Norway Sør-Østlandet Grenland Germany Schleswig-Holstein Lübeck Table 35: NUTS assumptions The sample short-sea shipping chains are presented in Table 34 together with the corresponding distances and cargo volumes. The chains are shown graphically in Figure 19. The sources of data used for calculating the KPI values are specified below: Costs: No data was found for this indicator. Time: An average speed of 15 knots/h was used. Source: Rodrigue (2013) Reliability: No data was found for this indicator. Frequency: Taking into consideration the average ship used at EcoTransIT estimations, the ship frequency was calculated (refer to Section 7.3.1). It is mentioned that such an estimate is meaningful only on liner trades. As was the case for road transport, tramp shipping does not serve specific schedules, and figures of this nature have only a theoretical character. CO 2 -eq emissions: The EcoTransIT World tool was used for estimating these values (refer to Section 7.3.2). Page 115

124 SO X emissions: The EcoTransIT World Tool was used for estimating these values (refer to Section 7.3.2). Country-Country Relation Germany - Sweden Sweden - Germany Germany - Denmark Denmark - Germany Germany - Norway Norway - Germany Denmark - Sweden Sweden - Denmark Denmark - Norway Norway - Denmark Sweden - Norway Norway - Sweden O/D Relations Volume (1000T) Distance (Km) Hamburg -Malmö 45, Hamburg -Götebrog 113, Hamburg -Stockholm 215, Lübeck - Malmö 538, Lübeck -Götebrog 298, Lübeck -Stockholm 210, Malmö - Hamburg 54, Götebrog - Hamburg 124, Stockholm - Hamburg 247, Malmö - Lübeck 843, Götebrog - Lübeck 430, Stockholm - Lübeck 372, Hamburg - Køvenhavn 329, Lübeck - Køvenhavn 237, Køvenhavn - Hamburg 417, Køvenhavn - Lübeck 366, Hamburg - Oslo 184, Hamburg - Grenland 124, Lübeck - Oslo 46, Lübeck - Grenland 30, Oslo - Hamburg 972, Grenland - Hamburg 599, Oslo - Lübeck 1.131, Grenland - Lübeck 390, Køvenhavn - Malmö 677,83 41 Køvenhavn - Götebrog 416, Køvenhavn - Stockholm 1.549, Malmö - Køvenhavn 705,08 41 Götebrog - Køvenhavn 487, Stockholm - Køvenhavn 1.654, Køvenhavn - Oslo 566, Køvenhavn - Grenland 555, Oslo - Køvenhavn 1.973, Grenland - Køvenhavn 1.903, Malmö - Oslo 61, Malmö - Grenland 136, Göteborg - Oslo 181, Göteborg - Grenland 330, Stockholm - Oslo 127, Stockholm - Grenland 385, Oslo - Malmö 78, Grenland - Malmö 193, Göteborg - Oslo 133, Grenland - Göteborg 138, Stockholm - Oslo 258, Grenland - Stockholm 321, Table 36: Representative short-sea shipping chains (2010.) Source: TRANS-TOOLS Page 116

125 Figure 19: Map of Short-sea Shipping Transport Chains (Table 36 Page 117

126 7.3.1 Frequency As done with the road transport, a theoretical frequency can be approximated by divided the yearly cargo tonnage moved between two ports with the average shipment size. The standard ship used by EcoTransIT to calculate emissions is also used here. Its characteristics are shown below: Characteristics Ship Ship Type BC Intra-continental (<35 dwt) Speed reduction 25% Load Factor 57% Table 37: EcoTransIT Ship Characteristics BC Intra-continental (<35 dwt) means that the total deadweight of the ship is tons. We assume that the payload is about the same. The average load factor according to EcoTransIT is 57%, which means that the total useful capacity would be tons. On the basis of these assumptions, frequency values can be estimated. They are shown in Table Emissions Both CO 2 -eq emissions and SO X emissions are estimated using the EcoTransIT World tool. The chain- and mode-level emissions are presented in Table 38. Page 118

127 Country-Country Relation Germany - Sweden Sweden - Germany Germany - Denmark Denmark - Germany Germany - Norway Norway - Germany Denmark - Sweden Sweden - Denmark Denmark - Norway Norway - Denmark Sweden - Norway Norway - Sweden O/D Relations CO2 -eq emissions (T) SOX emissions (Kg) CO2 -eq emissions (g/t-km) SOX emissions (g/t-km) Frequency Hamburg -Malmö ,246 0,090 3 Hamburg -Götebrog ,214 0,090 6 Hamburg -Stockholm ,223 0, Lübeck - Malmö ,311 0, Lübeck -Götebrog ,230 0, Lübeck -Stockholm ,222 0, Malmö - Hamburg ,228 0,090 3 Götebrog - Hamburg ,227 0,090 7 Stockholm - Hamburg ,222 0, Malmö - Lübeck ,228 0, Götebrog - Lübeck ,231 0, Stockholm - Lübeck ,224 0, Hamburg - Køvenhavn ,227 0, Lübeck - Køvenhavn ,206 0, Køvenhavn - Hamburg ,224 0, Køvenhavn - Lübeck ,961 0, Hamburg - Oslo ,229 0, Hamburg - Grenland ,222 0,090 7 Lübeck - Oslo ,226 0,090 3 Lübeck - Grenland ,220 0,090 2 Oslo - Hamburg ,226 0, Grenland - Hamburg ,224 0, Oslo - Lübeck ,216 0, Grenland - Lübeck ,212 0, Køvenhavn - Malmö ,153 0, Køvenhavn - Götebrog ,215 0, Køvenhavn - Stockholm ,221 0, Malmö - Køvenhavn ,157 0, Götebrog - Køvenhavn ,220 0, Stockholm - Køvenhavn ,221 0, Køvenhavn - Oslo ,222 0, Køvenhavn - Grenland ,228 0, Oslo - Køvenhavn ,223 0, Grenland - Køvenhavn ,457 0, Malmö - Oslo ,235 0,090 4 Malmö - Grenland ,217 0,090 7 Göteborg - Oslo ,224 0, Göteborg - Grenland ,233 0, Stockholm - Oslo ,145 0,031 7 Stockholm - Grenland ,223 0, Oslo - Malmö ,238 0,090 4 Grenland - Malmö ,221 0, Göteborg - Oslo ,220 0,090 7 Grenland - Göteborg ,191 0,090 7 Stockholm - Oslo ,273 0, Grenland - Stockholm ,223 0, Table 38: Emissions and frequency of shipping sample chains Page 119

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129 8. Performance Assessment This final chapter presents the performance assessment of the corridor sample and compares the mode specific indices between them and in relation to the entire corridor. The chapter also summarizes the conclusions of the thesis, as well as the comments regarding the obtained and missing data. Each section of the chapter describes in detail a KPI, comparing them between modes. Finally, a corridor-wide value is calculated. These final KPI values show how the corridor performs, in general terms. In Table 39 below the KPI values per mode are presented, as they have been calculated in the previous chapter. Transport Mode Costs ( /T-Km) Time (Km/h) Frequency Reliability CO2-eq emissions (g/t-km) SO X emissions(g/t-km) Rail 0, No data 12,11 0,03 Road 0, No data 75,43 0,10 Short-sea Shipping No data No data No data 6,02 0,09 Table 39: Mode-level values (all transport modes) 8.1 Costs Calculations Firstly, it is important to mention the difficulties for calculating this KPI. The main difficulty lies on data gathering. It is hard to know exactly how many voyages take place per year along the corridor. In addition, the prices for fuel, maintenance, personnel and so on vary significantly with the nationality of the physical and legal entities involved, not to mention that soliciting sensitive information of this nature is almost impossible. Given the absence of real cost figures, one has to rely on cost estimations, which depend on transport mode. These estimations are usually based on a number of explicit or implicit assumptions that influence the quality of the results achieved. The assumptions made here for each mode are discussed below: Page 121

130 Rail Freight Traffic The data gathered for rail is the most complete of all modes. However, some assumptions were made here as well. The cost figures used are derived from internal, still unpublished, DTU Transport information (Table 18), which basically concerns Denmark. The very high driver s salary is indicative of this fact. Nevertheless, the analysis shows that the variable costs are more than four times the fixed ones (Table 20), reducing the importance of the nationality bias. As expected, the fixed costs are reduced with the distance of the chain. Another assumption relates to the average number of wagons a train running on the corridor has. The figure of 30 wagons/train comes from the RFC TMS As for the energy cost, an average price of KWh was used for the entire corridor (Table 19). The average price per KWh was close to the EU average, so the approximation cannot be far from reality. However, there are variations from country to country that can affect the cost of a chain depending on each country s share in the length of the chain. Road Freight Traffic The basic assumption of these cost estimates is the 0,75 /Km figure used in calculating fuel and maintenance costs. Although this value comes from DTU Transport, it refers to international trucking and it is the value used for the whole corridor area. DTU Transport also provided the daily rental cost for a trailer. In relation to routing, the lowest cost criterion was used. In this calculation, ferry and toll costs as provided by the ETIS Plus database were used. Probably the most decisive assumption in terms of road KPIs has been the choice of the average vehicle, which affects costs, frequency and both emission indicators. Among the vehicle types suggested by EcoTransIT, the Page 122

131 26-40t truck was selected due to the length of the corridor (it is reminded here that ScanMed is the longest of all TEN-T core network corridors). Short-sea Shipping Finding the costs values for maritime transportation is much harder than for either rail or road transportation. The main issue here is the huge variety of ships and the even bigger variety of goods transported. The commodity affects not only the type of ships used but also the loading units, the type and frequency of services, the type of terminals used etc. Due to these difficulties, we did not succeed in obtaining cost figures. The corridor-level KPI can now be calculated using the formula: The total corridor value is 0,0397 /T-Km (Table 40). Transport Mode Rail Road Short-Sea Costs ( ) No data (T*Km) Cost Transport Mode ( /T-Km) 0,02 0,06 - Corridor Value ( /T-Km) 0,0397 Table 40: Corridor-level costs From the table above, one can conclude that rail is three times cheaper than truck. Although rail was expected to be relative cheaper than road over long distances, Page 123

132 the extent of the difference is surprising. An explanation might be that the cost figure derived from our analysis does not include the first and last mile costs usually associated with rail transport, which can inflate significantly these numbers. 8.2 Time The time related KPI in this thesis appears as average speed, measured in Km/h. Once again, no direct speed data were identified in the two basic TMS documents reviewed. In fact, the CNC MTMS contains a chapter on speed but the primary concern there is the maximum allowable speed, something that makes sense, as the purpose of this document relates basically to the design and provision of infrastructure rather than on operational issues. Both rail and road average speeds were extracted from ETIS-Netter. The figure for both of them is 80 Km/h. There are two points here that need to be made: Firstly, this number is much higher than what SuperGreen calculated along their corridors (closer to 40 km/h for both rail and road). Probably the difference lies to the fact that ETIS-Netter provides the average speed along the network links and not the average speed of a whole transport chain. The former calculation concerns only the periods that the vehicles are running, excluding delays in terminals for loading/unloading, idling etc. Secondly, the uniform use of a single figure (80 Km/h) on all corridor segments seems to be an overall average figure, which is inappropriate for our particular application. But unfortunately this is all we ve got. Similarly, an overall average figure of 15 Knots (equivalent to ~28Km/h) was applied on all shipping chains. The method for calculating the corridor-level speed value is weighted average using cargo volumes as weights. The formula and the results achieved are presented below: Page 124

133 Transport Mode Rail Road Short-Sea Average Speed (Km/h) Cargo Volume (T) Weight (%) 0,19 0,14 0,67 Corridor Value (Km/h) 45 Table 41: Corridor-level average speed It is of no surprise that shipping carrying 67% of the corridor cargoes is much more influential in forming the corridor average index than any of the other two modes. 8.3 Frequency Frequency has different importance among the transport modes. For rail, it was the main factor, helping choosing the transport chains. For both road and short-sea shipping, frequency is of a rather theoretical nature, as voyages in these two transport segments are basically arranged on demand. The basic assumption in deriving frequency values for road and shipping relates to the selection of the standard vehicle/vessel used for converting yearly cargho volumes to number of shipments. As explained in the relevant sections, the selection was made among the EcoTransIT types of vehicles/vessels; the type deemed as most appropriate for the needs of the present thesis was selected. As in the case of speed, the corridor-level frequency value was calculated from the corresponding mode-level ones as a weighted average, using the cargo volumes as weights. The formula used and the results attained are presented below: Page 125

134 Transport Mode Rail Road Short-Sea Frequency (Number of vehicles) Cargo Volume (T) , , ,00 Weight (%) 0,19 0,14 0,67 Corridor Value (Vehicles) Table 42: Corridor-level average frequency 8.4 Reliability No data on reliability was found for any transport mode. Some numbers were only located in relation to the Brenner rail pass (BRAVO project), but they were the exception rather than the rule. It was, thus, decided to drop reliability from the analysis. 8.5 Emissions As explained in Chapter 7, the EcoTransIT World web-based tool was used for emission calculations. The standard input mode of this tool was used. The Wellto-Wheel approach was used because it permits comparisons across modes. In addition, CO 2 -eq emissions was selected instead of merely CO 2 in order to cope for all GHG emissions. As both emission related KPIs are defined on a per tonne*km basis, the corridorlevel averages were calculated using tonne*km as weights. The formula used for both CO2-eq and SOx emissions is: Page 126

135 The relevant estimations are presented in Tables 43 and 44 below: Transport Mode Rail Road Short-Sea CO2-eq emissions (T) (T*Km) CO2-eq emissions (g/t-km) 12,11 75,43 6,02 Corridor Value (g/t-km) 13,79 Table 43: Corridor-level CO 2 -eq emissions Transport Mode Rail Road Short-Sea SOX emissions (Kg) (T*Km) SOX emissions (g/t-km) 0,03 0,10 0,09 Corridor Value (g/t-km) 0,08 Table 44: Corridor-level SO X emissions In terms of CO 2 -eq, the results are in line with what was more or less expected. Road transportation is by far the most environmentally unfriendly way of moving cargo. The SOx results, however, came to a surprise, as the shipping emissions were expected to be much higher. The fact that they are comparable with road transport can only be attributed to the enforcement as of 1 January 2015 of the new stricter regulations regarding the sulpfur content of marine fuels in all Sulphur Emission Control Areas (SECAs), which include the North Sea and the Baltic Sea where all our chains take place. According to these regulations, the maximum sulphur content of marine fuels used in SECAs was brought down on 1 January 2015 from 1% (in mass) to 0.1%. Given that the cargo flows of the analysis relate to 2010, the sulphur emissions of Table 42 need to be adjusted upwards. Due to the fact that the amount of SOx emissions produced by a kg of fuel is directly proportional to the sulphur content of this fuel (for reasons that have to do with the chemical reaction of sulphur oxidation), the SOx emissions calculated for a 0.1% S fuel need to be multiplied Page 127

136 by 10 to refer to a 1% S fuel 11. As such, the SOx emission indicator for shipping should be corrected to 0,086 g/t-km and the corridor-level KPI should become 0,068 g/t-km, reflecting the significant share of shipping in the transport work (tonnes*km) of the corridor. The results of Tables 43 and 44 are schematically depicted in Figures 20 and 21 respectively. 80,00 70,00 60,00 50,00 40,00 30,00 20,00 10,00 - CO2 emissions (g/t-km) 75,43 12,11 13,79 6,02 Rail Road Short-Sea Corridor Figure 20: Corridor-level CO 2 -eq emissions (Chart) SOX emissions (g/t-km) 0,12 0,10 0,08 0,10 0,09 0,08 0,06 0,04 0,02-0,03 Rail Road Short-Sea Corridor Figure 21: Corridor-level SO X emissions (Chart) 11 This correction factor would have been exact if all the fuel consumed by ships in 2010 was of the 1% S type. However, this is not the case, as even then the ships had to burn 0.1% S fuel while at berth. But since the time in port is usually a small percentage of the total voyage time of a ship, the correction factor of 10 can still be used for the purposes of this study. Page 128

137 The supremacy of shipping and rail in the case of greenhouse gases is evident, even if a Euro 5 truck was taken as standard in calculating the road emissions. The trend towards bigger ships and longer trains certainly help in this respect. The energy mix used to power trains makes a lot of difference as has been shown by the Swedish chains of Section As explained above, Figure 21 shows the 2015 reality (with 2010 cargo mix conditions), where the performance of shipping has improved to the road-level standards. The rail, however, remains the front runner here, and as the Swedish example has shown, the renewable energy sources can eliminate SOx emissions altogether. 8.6 Conclusions The results of the corridor performance in relation to the individual KPIs have been discussed above and are summarized below for easy reference: Costs: Speed: Frequency of service: CO2-eq emissions: SOx emissions: 0,04 /T-Km 45 Km/h services per year (one every 11 min) 13,8 g/t-km 0,68 g/ T-Km Here some concluding comments on the applied methodology will be made. The first one relates to the appropriateness of the sample. Table 45 and Figure 22 compare the sample with the ScanMed CNC corridor in terms of modal composition.. Page 129

138 Transport mode Sample ScanMed CNC Volume (1000T) Share (%) Volume (1000T) Share (%) Rail , ,74 Road , ,38 Short-sea shipping , ,89 Total , ,00 Table 45: Sample suitability 80,00 70,00 60,00 50,00 40,00 30,00 20,00 10,00 0,00 Rail Road Short-sea shipping Figure 22: Sample composition It appears that in general the sample is sufficiently good. It covers the transport of 32 out of the 215 million tonnes of the corridor, accounting for 14,7%, which is not bad at all. The modal composition of the sample is not bad either, as the magnitude of the shares of each mode in the volume of transported cargo is right. The mode with the highest difference is road, which comprises 14% of the sample when the actual share in the corridor is 23%. This 9% differential is gained by the other modes; 2% goes to rail (19 against 17%) and 7% to shipping (67 against 60%). The basic reason for this difference stems from the fact that road transport activities are much more evenly distributed over the catchment area of the corridor than rail and shipping, which materialize through a certain small number of terminals/ports. The sample already includes 76 road chains in comparison to 10 for rail and 46 for seaborne transport. Certainly the sample could be modified Page 130

139 to include more road chains, but given that the most important ones are already present, the number of additional chains required to bring the road share in line with its actual figure would be quite large. On the other hand, a reduction of the shipping sample would lead to a higher share of the rail sector, which is already above its actual contribution. It is concluded that with some more effort the sample could be brought closer to the actual corridor composition but, given the demonstrative nature of this thesis, the selected sample is a pretty good first approximation. The second comment relates to the usefulness of the corridor transport market studies as a tool for assessing its performance. The answer to this question is mixed. As mentioned in Sections 7.1 and 7.2, the selection of the rail and road chains was based on information contained in the RFC TMS. On the contrary and despite its very detailed description of the corridor, the CNC MTMS was on less importance in constructing the sample, as its information is more tuned towards the infrastructural than the operational perspective. None of these studies was useful in selecting the shipping chains, which was based on model results (TRANS-TOOLS). As for information in relation to calculating the KPIs, none of the studies proved helpful. The CNC MTMS provides a list of KPIs (Table 11) and the data needed for their assessment. However, there is no connection to the SuperGreen KPIs used in this thesis and as such, no use was possible. In fact, as mentioned in Section 8.2, the CNC MTMS contains a chapter on train speed but its primary concern is the maximum allowable speed, which is a design parameter for the infrastructure having no relation to the average speed of a railroad line that characterizes the operations that take place on this piece of infrastructure. And this brings to our third comment that relates to the difficulty in obtaining the necessary information for assessing the corridor. Various sources, external and internal (to DTU), official and unofficial, were consulted for obtaining these data. The information solicited has been presented in Section 7. The reliability KPI had to be removed, as the information found was so little and localised that its Page 131

140 inclusion had no meaning. The information on speed was included but it concerns basically broad average figures that do not permit discrimination by chain, which is what we need. Albeit with validity constrained in Denmark only, the information on cost that we obtained from DTU Transport made a difference in calculating the relevant KPI. The frequency and emissions calculations were based on aggregate cargo volumes and the standard types of vehicles/vessels provided by the EcoTransIT World tool. It can, thus, be concluded that a lot more need to be done before we reach operable KPI values. Other than that, the SuperGreen methodology applied here seems to work quite well. However, it needs to be repeated that the method does not consider differences in specific corridor characteristics and as such, cannot be applied for comparing different corridors to each other. Instead, if applied periodically on a single corridor, it can be a useful tool for the corridor management to assess performance and identify areas that require their attention. Page 132

141 References ArcGIS. (2015). DTU Transport Department. Arnold J. (2006). Best Practices in Management of International Trade Corridors. Trade Logistics Group, The World Bank Group, Washington D.C, Council of the European Union. (2012). General approach on the Proposal for a Regulation of the European Parliament and of the Council on Union guidelines for the development of the trans-european transport network, 8047/12, Brussels, Ec.europa.eu. (2015a). Database - Eurostat. Retrieved 24 June 2015, from Ec.europa.eu. (2015b). Energy price statistics. Retrieved 24 June 2015, from Ec.europa.eu. (2015c). Eurostat - NUTS. Retrieved 24 June 2015, from Ec.europa.eu. (2015d). New TEN-T guidelines and CEF - Transport. Retrieved 24 June 2015, from Ec.europa.eu. (2015e). Scandinavian-Mediterranean Core Network Corridor - Transport. Retrieved 24 June 2015, fromhttp://ec.europa.eu/transport/themes/infrastructure/ten-tguidelines/corridors/scan-med_en.htm Ec.europa.eu. (2015f). Trans-European Transport Network TENTEC - European Commission. Retrieved 24 June 2015, from EcoTransIT World Tool. (2015) Engström, R. (2011a). Green Corridors in Sweden - A Governmental Commission Steers the Second Phase. Retrieved 24 June 2015 from een_corridors_in_sweden_a_governmental_commission_steers_the_second_phas e.pdf Engström, R. (2011b). Swedish Green Corridors Initiative. Retrieved from _swedish_green_corridor_initiative_history_current_situation_and_thoughts_abo ut_the_future.pdf Page 133

142 ETC Transport Consultants. (2014). Transport Market Study for the Scandinavian Mediterranean RFC. ScanMed RFC. ETIS-Netter. (2015). ETIS-Plus. (2014). ETIS-Plus Final Report. Etisplus.eu. (2015). Home - ETIS plus. Retrieved 24 June 2015, fromhttp:// ETIS-View. (2012). European Commission (2014), Council Conclusions on Transport infrastructure and the Trans European Network. (EC, 2014) (1st ed.). Brussels. European Commission. (2007). Freight Transport Logistics Action Plan. Brussels. Retrieved 24 June 2015 from ort_en.pdf European Commission. (2011) Handbook on the Regulation concerning a European rail network for competitive freight (Regulation EC 913/2010). European Commission. (2011). WHITE PAPER on Transport. Roadmap to a Single European Transport Area Towards a competitive and resource efficient transport system. Brussels. Retrieved 24 June 2015 from European Commission. (2014). TEN-T Core Network Corridors: Scandinavian- Mediterranean Corridor. Draft final report, 7 November European Commission (2015). Scandinavian-Mediterranean: Work Plan of the European Coordinator Pat Cox. May European Parliament & Council (2013). Regulation (EU) No 1315/2013 of the European Parliament and of the Council of 11 December 2013 on Union guidelines for the development of the trans-european transport network and repealing Decision No 661/2010/EU. Strasbourg. Ewtcassociation.net. (2015) EWTC Association. Retrieved 24 June 2015, from Georgopoulou, C. (2015). Benchmarking the SuperGreen Corridors with green technologies. In H. Psaraftis, Green Transport Logistics in Search of Win-Win Solutions (1st ed.). Ibañez - Rivas. (2010). Peer review of the TRANS-TOOLS reference transport model.energy.jrc.ec.europa.eu. Retrieved 24 June 2015, from Page 134

143 IEA Statistics. (2014). CO2 Emissions from fuel Consumption. Retrieved from FuelCombustionHighlights2014.pdf Infrabel. (2015). Rail Freight Corridors. Retrieved 24 June 2015 from Moyano, H. (2012). Green Corridors Handbook - Vol I. Öberg M. (2013). Measurement of green corridor environmental impact performance A2A logistic corridor concept. A Bothnian Green Logistic Corridor report, June Pålsson (2010). Definition of benchmark indicators and methodology. SuperGreen project Deliverable D2.2. Panagakos, G. (2012). Green Corridors Handbook - Vol II. Panagakos, G. (2015a). Green Corridor and Network Design. In H. Psaraftis, Green Transport Logistics in Search of Win-Win Solutions (1st ed.). Panagakos, G. (2015b). Green Corridor Basics. In H. Psaraftis, Green Transport Logistics in Search of Win-Win Solutions (1st ed.). Psaraftis, H. (2015). Green Transport Logistics in Search of Win-Win Solutions. Rodrigue, J. (2013). Maritime Transportation. In J. Rodrigue, The Geography of Transport Systems (3rd ed.). New York: Routledge. Retrieved 24 June 2015 from Rousseaux Patrick (2012). Rail freight corridors. Presentation at the RNE Business Conference, Frankfurt, Germany. Supergreenproject.eu. (2015). SuperGreen Project - Project Information. Retrieved 24 July 2015, from Swahn Magnus (2010). How to evaluate transport s environmental performance. Article at GreenPort Journal, June Swedish Logistics Forum s. (2011). Green Corridor Manual (Draft) - Purpose, definition and vision for Green Transport Corridors. Danish Transport Authority. Retrieved 24 June 2015 from The Sustainable Leader. (2015). The Sustainable Leader. Retrieved 24 June 2015, from Yearbook, E. R. (2012). Eurostat. European Commission. Page 135

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146 ANNEX I Criteria for choice of transport mode Factors influencing choice of mode There are generally numerous variables influencing the decision-making process for the choice of transport mode. From a careful appraisal of the literature review it appears that three main factors influence the decisions taken: the characteristics of the goods to be transported the needs and necessities of the company the characteristics of the transport network of each transport mode The characteristics of goods will directly influence the choice of mode in relation to mass, unitary value, time-sensitivity and the frequency of transports. Transportation for bulk goods has different requirements to transport modes than high-value chemical or pharmaceutical goods, for instance, or individually packaged goods. Consolidated research on TEN-T Corridors stated that rail competes with road in markets for manufactured goods, chemicals, crude materials and fuels and even foodstuffs and beverages. This implies a considerable up-market shift from bulk haulage where rail used to compete with low-value high-volume sea-going cargo. The characteristics of the decision maker, i.e. number of workers, turnover, possession of or access to a railway interchange or truck fleet, will influence heavily the convenience of one mode versus another. Recent researches showed that the most important users of rail services are medium-sized shipper companies with yearly turnover of 10 and 50 million Euros. This important and counter-intuitive finding emphasizes that market potentials for rail may increase considerably with improved service qualities, due to the fact that medium-size business are much more numerous in Europe than very large establishments. Page 138

147 The network characteristics include access to the network, availability of terminals and shunting yards, travel costs, travel time, reliability, security as well as possible technical and infrastructural bottlenecks. They are understood to be the main drivers of the decision-making process for the choice of transport mode (in a mono- or multimodal chain). In this sense, the travel cost has to consider both travel and eventual inventory cost, while reliability and security include delays in the shipment processes, theft protection and damages. Choice of transport mode is driven by a company s desire to remain competitive by serving their customers both effectively and efficiently. As findings from research into choice of mode suggest, major criteria, which strongly influence the choice of transport mode, could be grouped into the three categories: transport cost transport time (i.e. speed) transport quality, where several figures can be identified and include a.o. reliability, punctuality, safety & security and travel information As each freight transport mode differs in its unique selling points, so will their ratings of these criteria. The following table rates these major criteria for the four main transport modes for freight. (+ ad- vantage, - disadvantage, 0 medium). Transport quality encompasses several components, therefore it has been split into two sub-criteria, namely predictability (Will goods arrive at the scheduled time?) and adaptation (Are alternative routes available? Can varying transhipment volumes be accommodated? Are several departure times available?). Inland waterway s high score in terms of flexibility can be explained by this mode s advantage to offer varying shipment sizes, variable available capacities and frequent departures. For short-sea shipping it depends largely on the ship type. Furthermore, where IWW can rely on a modern terminal infrastructure (high degree of automation and long opening hours), flexibility of this mode is further enhanced. Page 139

148 Choice Criteria Road Rail Short sea shipping Inland Waterways Transport time Transport costs Quality: Predictability (punctuality) Quality: Adaptation (flexibility) Table I-1: Profile for choice of transport mode Rail scores medium on time and costs, but has an advantage in terms of predictability/punctuality and a disadvantage in terms of adaptation/flexibility. This was mirrored in reports by the stakeholders in the personal interviews who stated that ad-hoc train services (as opposed to timetable traffic) offer the necessary flexibility for customers, although today the proportion of ad-hoc traffic is reportedly low. Also, both in personal and online interviews, most stakeholders either assumed that the proportion of ad-hoc traffic will remain at its current level or at best experience a moderate increase. This could there- fore be a response of rail to enhance its attractiveness to customers in terms of one central aspect to transport quality, i.e. flexible adaptation to customer needs in form of ad-hoc traffic. This could also include the option to book smaller loading units onto combined transport services at short notice via a logistics service provider also offering rail-based transport. Some of the stakeholders interviewed commented on the observed trend towards shorter contractual agreements, suggesting that customers do not wish to bind themselves over long periods but retain a certain degree of flexibility to adapt their need for rail freight services in accordance to changes in the market segment(s) they serve. Regarding the interview results on choice of transport mode, personally interviewed stakeholders and online respondents were asked to rate transport criteria to indicate mode choice factors. Price emerged as the most prominent mode-determining factor. However, further issues such as type of cargo (time sensitive or not) and transport route (and hence available alternative modes) must be taken into the equation as well, when considering a mode s competitiveness. Both online respondents and personally interviewed stakeholders were asked to rate the relevance of market-related criteria (price, time, quality according to the definition Page 140

149 given above) for the choice of transport mode they, respectively their company take into consideration when deciding how to transport goods. Transport price received the most high and very high ratings from both. This finding is in line with the common credo that, to both the customer and the operator price is all that matters. Thus, price emerges as the determining factor in mode choice (before further factors are considered). This is also underlined, when the transport criteria are presented by commodity group. As Figure 3-43 merely offers a very general overview regarding stakeholder ratings for transport price, time and quality, a breakdown by the self-reported commodity groups can highlight potential divergences in dependence on the type of good(s) a stakeholder s company transports or handles. Page 141

150 Figure I-2: Relevance of price in dependence of commodity group From the personal interviews, price emerges as a paramount criterion across all commodity groups, the vast proportion of ratings attributed to either high or very high relevance. Figure I-3: Relevance of transit time in dependence of commodity group Transit time, thus was attributed medium relevance in >20% across all commodity groups. The distribution pattern of the ratings across the commodity groups was similar with a spread from medium to very high for most commodities. As expected, time-insensitive commodities such as building materials received some low relevance ratings, too. Page 142

151 Figure I-4: Relevance of transport quality in dependence of commodity group Asked to rate the importance of transport quality, stakeholders indicate again a very similar picture across all commodity groups. The very high proportion of high and very high ratings given to this criteria mirrors its relevance. Representing these findings by commodity group has, however, not highlighted any stark differences between the type of cargo handled and the relevance ratings given to transport price, time and quality by the stakeholders interviewed. This is possibly due to the fact that stakeholders usually reported handling a number of commodities (some even all) and thereby gave an overall rating rather than an individual rating per commodity group. Consequently, only very general findings can be derived from this information, as the questionnaire was not designed to ask stakeholders to rate the relevance for each handled commodity individually. Transport quality was rated equally as important by respondents of the online survey as well as by the personal interviews, with the majority of responses deeming these criteria high or very high. Transit time received the most medium ratings, with stakeholders clarifying that very often not the total travel time but the reliability for goods to arrive at the pre-arranged time is crucial. With regard to terminology, punctuality refers to the arrival of freight (trains) at exactly the scheduled time and reliability refers to the ability of freight services to consistently perform the functions required and under the conditions agreed upon, i.e. the repeated successful fulfilment Page 143

152 of contractual agreements. From this distinction it becomes clear that punctuality is one of the functions freight services are required to meet, should they wish to be perceived as reliable by customers. Consequently the quality parameters listed in the figure below are all intertwined to some degree, with reliability forming an umbrella term. As the above graph shows, all quality criteria received around three quarters or more high and very high ratings, especially reliability and punctuality were deemed paramount by both operators and customers. These findings were closely mirrored by the ratings given by online respondents. The consistently high relevance attributed to these criteria also illustrates that it is the mix of all of these factors that determines the successful operation of rail freight. Consequently, no single attribute can be regarded in isolation, when considering improvements to the system as a whole. Infrastructural issues The analysis on mode choice criteria revealed that infrastructural bottlenecks along the network play a key role in the attractiveness of railway services and therefore need to be addressed to change modal split from road to rail. The following table shows the specification of transport modes in relation to the volumes transported and the distance covered. Page 144

153 Mode choice High Volumes Low Medium High Rail Sea Sea Distance Medium Low Road Rail Road Rail Rail Road Rail Short-sea Rail Short-sea Road Road Road Rail Table I-2: Specification of transport mode in relation with good size and distance In general, intervention on infrastructure and services in a currently well-connected railway network, aims at reducing travel costs and increasing service quality in terms of pre-trip and on-trip information, security & safety, reduction of delays and time-to-market reliability. These measures will induce small and medium companies to choose more often railway services instead of other alternatives. In a well-connected network time and cost reduction can be achieved in a higher efficiency of intermodal nodes, the reduction of bureaucracy as well as in an increased use of harmonised core tools for inter- national path allocation and for information regarding train delays (as offered as a service by RNE). Northern Italy and continental sections of the corridor are very interested in these kinds of improvement in order to have a wider choice set for inland transportation. On the other hand infrastructure improvements along important railway sections with existing bottle- necks will allow for more numerous, longer and heavier train passages. These measures, due to high investments and long realisation periods, will be a key issue for those companies that at the moment have a prevalent mode/path for goods transportation different from rail or choose rail but they necessarily use longer alternative paths. All the customers along areas subjected to hard orography where Page 145

154 slope problems induce directly strong limitations on train length, weight and loading gauge need new opportunities for freight transport, in order to increase competitiveness in the market. Appennini Mountains become a high barrier dividing Italy in two branches where north-south freight transport often use road or need to change path by rail passing along the Adriatic side. Also in this sense, expectations are very high both in terms of train length/train weight as for the loading gauge size. Finally, infrastructure improvements in a low performance network, with particular reference to south- ern Italy, would induce a radical change on freight transport, where most of the industrial settlements have no alternatives of transportation than road. Expectations in this sense are very high and are strictly related also to the line speed. Southern Italy is first of all an important food and beverage market, which refers to perishable goods that need to be on time at final destination. Moreover, that area is not characterized by high level of goods production nor consuming demand; nevertheless, it is one of the most important sea-port platform at the Mediterranean Sea. It is deemed important to strengthen the connections of ports with railway terminals to simplify rail customs procedures at terminals (e.g. introduction of an electronic seal) and to optimize the inland intermodal centres. This would have an important impact on the very-high-distance shipment paths, as some stakeholders asserted. These changes would allow for general changes in the role of several sea-railway nodes: with a more competitive inland network at hand, ports would grab demand of goods coming from Far East and with destination the central and northern Europe, avoiding extra days of navigation and fuel consumption for the passage through Gibraltar and circumnavigation of Europe. Especially transhipment ports in the southern part of Italy with a higher rail network performance and better connectivity with the inland will strengthen the position among national and international Mediterranean ports in terms of goods managed and will also induce changes in its role with the possibility to finally express new potentiality. Page 146

155 Comparison between transport modes In the last decade combined and intermodal services for freight have been developed very rapidly due to the articulation and complexity of customer needs. In this sense, the comparison between modes has changed meaning toward the sense of the choice for the prevalent mode along the intermodal chain of freight transport. Regarding road transport, it can be assumed that the cost of transport is proportional to the distance travelled without interruption. In railway transportation it is necessary to consider high costs for access/egress from the railway node on the network to get to the main terminal of origin/destination. On the other hand, apart from the problem of access/egress, under optimal conditions (block train and long-distance) railway generally has lower costs per tons/km than road. The figure below shows the cost trends for the two modes of transportation, highlighting the high cost of access/egress of the train for the distance to be covered between the terminals (o/d of the goods) and the departure station/arrival of the train block. It seems that after a specific distance rail is cheaper that road also considering initial costs. Road Rail df dlim/r Figure I-5: cost trends for the two modes of transport Rail and Road Page 147

156 It is evident from the figure below the target of combined rail and road (green line) for the abatement of costs through the exploitation of the benefits from both transport modes. Thus, after a specific distance d lim/c, lower than d lim/r, combined transport is the best choice. Road Rail Combined d f d lim/c d lim/r Figure I-6: cost trends for the two modes of transport Rail and Road Furthermore, in this context and for this particular corridor it is necessary to consider the key role played by the sea shipping, because of the presence of several ports in Italy, Scandinavia and Germany. In relation to this issue, stakeholders interviewed gave some key points to take into consideration: In general, it is necessary to distinguish between two major categories of transport: The "merchant", where the movement of containers is directly under the control of the recipient using the nominated haulage contractor. In this case road is the predominant choice of mode for inland movements; The "carrier", where the movement of the container is under the control of the shipping line, using a haulage contractor nominated by the shipping line. In this Page 148

157 case the large shipping companies control the whole chain and, due to the high volumes transported, railway has a predominant role in the inland movements. In addition to this, large shipping companies choose the transport mode in relation to the distance covered and the origin/destination served. Whenever the inland section becomes pre- dominant, shipping companies try to find another port as much close to the origin/destination as possible. This decision is taken almost independently from railway/road network performances as well as even more with the rising of the number of cross-border to pass through. The following table offers a general overview of advantages and disadvantages of each transport mode. As Inland Waterways do not play a crucial role in this corridor it is not included in the analysis below. Page 149

158 Table I-3: Comparison of transport modes Personally interviewed stakeholders were asked to rate (from their company s point of view) which transport mode is most competitive with regards to transport price, time and quality. It emerged that rail and short-sea shipping received about a third of ratings for being most competitive in terms of price, whilst road clearly dominated in terms of price and quality. Interestingly, stakeholders were unable to rate inland waterways in most instances, suggesting that this mode does not play a significant role as a viable alternative transport option in the corridor. Figure I-6: Comparison of most competitive transportation mode Competitive position of rail freight services It emerged in stakeholder interviews that railway transport mode is of common use depending on goods transported and distances covered, but faces challenges for the next future. "Railway mode is less flexible than road but when it works in the right way is really efficient" is one of the assertions collected during personal interviews trying to summarise the role of railway service in freight transport. Transportation costs still remain the main issue in the global market and, as a result of the survey, rail- way together with short-sea shipping is the cheapest way to move Page 150

159 goods on long distances. Both transport modes are strong in the transportation of mass goods and are in some cases in competition with each other, often due to the lack of access to the railway network. Their integration would surely lead to a more efficient trip chain and would strengthen the role of each mode in their respective area of influence. Travel time does not appear to be a peculiar quality of railway mode. Nonetheless, time is not generally considered to be a key issue in the current global market, especially for those good categories that mainly interest railway mode. On the other hand, railway could really grab position in the "time competition" due to the improvements in the node management and in the communication and cooperation among infrastructure companies, terminals, ports, shippers and other stakeholders. The flexibility and ability to adapt to customer requirements remains highly important. Its implementation is highly complex in the railway sector as it requires a strong relationship between Infrastructure Manager and Railway Operators whose "time to market" are different and of different nature. Page 151

160 ANNEX II Conclusions and recommendations SWOT analysis Concerning the short-term forecast period from a SWOT analysis has been carried out covering the institutional, economic, organisational and technical parameters with relevance for the development ScanMed RFC. The SWOT analysis is an analytical tool where strengths and weaknesses of certain elements identified with potential relevance for the development of a project in this case the development of rail freight traffic in ScanMed RFC are gathered and elaborated. The possible opportunities and threats are de- rived from these strengths and weaknesses and assessed according to their influence on rail freight developments. For the means of this study, four categories have been identified and assessed by SWOT analysis technique: Institutional elements are understood to be external factors, such as EU regulations, safety standards, and organizational frameworks in the ScanMed RFC countries. Economic elements refer to overall economic developments in the EU as well as per ScanMed RFC country, per transport mode and per type of good. Organisational elements represent the internal dimension that can be influenced by the IMs themselves (while the institutional elements influence the overall market development and its functions). These include cross-country cooperation, information policies and other general factors. Technical and infrastructural elements include issues such as ERTMS deployment status along ScanMed RFC as well as bottlenecks. Page 152

161 Institutional Table II-1: SWOT analysis of institutional factors Page 153

162 Economic Table II 2: SWOT analysis of economic factors Page 154