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3.6.3 Guidelines for Corridor Benchmarking

In place of the usual concluding remarks, this section provides a set of guidelines for effective corridor benchmarking that takes into consideration the experiences of SuperGreen and other projects in this field.

Bench marking goal: Monitoring the performance of a transportation corridor can serve several purposes. Obtaining a better understanding of the present conditions, identifying problems to be addressed, observing developments over time and comparing with benchmarks are some of them. Also important is the perspective of the analysis. A multiplicity of actors is involved in a corridor and their priorities do not always coincide. A corridor consists of various types of services offered by competing operators through organized supply chains over a multimodal infrastructural network within an international regulatory and administrative framework. In a complex system like this, setting the exact purpose of the analysis and its intended use is essential. A clear goal statement will assist decision making throughout the analysis and will affect all subsequent tasks. In general, it should be kept in mind that due to resource limitations, there is a trade-off between the width and the depth of analyses of this sort.

Corrido r descr iption: The next task cannot be different than defining the corridor under investigation. As can be inferred from Sect. 3.4, corridors tend to be described by locations that represent rather broad geographical areas/places where the corridors start, end or pass through. This has to be translated into a more detailed definition that includes the modes to be examined and the routes comprising the corridor. Each route should be described as a set of designated links, terminals and supporting facilities. Only existing major links should be designated to a route. Parallel secondary links or by-passes should be mentioned only as enhancing the resilience of a corridor. As for terminals, all uniand/or multi-modal terminals should be designated to a route, except if irrelevant to the corridor traffic or unwilling to take part in it.

KPI select ion: After extended consultation with stakeholders, the SuperGreen project proposes the following set of KPIs for corridor benchmarking applications:

• Out-of-pocket costs (excluding VAT), measured in €/tonne-km,

• Transport time, measured in hours (or average speed, measured in km/h, depending on the application),

• 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,

• CO2-eq emissions, measured in g/tonne-km, and

• SOx emissions, measured in g/tonne-km.

Among them, the cost indicator is the most difficult one to calculate due to scarcity of relevant data. In such cases, the volume of cargo moved along the corridor can serve as a proxy for describing its efficiency.

Other projects suggest different indicators. It needs to be emphasized that KPIs should be selected by the corridor management on the basis of the objectives being pursued.

Meth odolog ical pr inciples: The methodology is built around the principle described by the following four steps:

Step 1. Disintegrate the corridor into transport chains.

Step 2. Select a representative set of typical transport chains.

Step 3. Estimate KPI values for each and every chain selected in Step 2.

Step 4. Aggregate these values into corridor level KPIs by using appropriate weights and methods.

Sample construction: In view of the problems encountered with the 'critical segment' notion applied in SuperGreen, it is suggested to construct a 'basket' of typical transport chains on the basis of traffic model results. Alternatively, the information of the 'Transport Market Study' foreseen by Reg. No 913/2010 for the Rail Freight Corridors and, through them, for the TEN-T core network corridors can be used for the sample construction (Panagakos, 2012). The proposed methodology resembles the functionalities of the Consumer Price Index (CPI) calculated by the statistical bureaus around the world. In the CPI context, the basket of goods and services used for CPI calculations is selected on the basis of the so-called Household Expenditure Survey (HES) that provides information on the spending habits of the population. In the context of green corridors, a traffic model can play the HES role.

The international character of a green corridor calls for a model covering effectively all of its routes. The European TRANS-TOOLS model (Iba´nez-Rivas, 2010) is an ideal source of information, provided that its updating is successfully completed. Until then, national transport models can be used, but care should be taken to ensure compatibility.[1]

In selecting typical chains coverage of:

• all segments of the corridor,

• all modes of transport participating in the analysis,

• all possible types of transport chains examined by the model, and

• all types of vehicles examined by the model should be ensured.

Data collec tion: The task relates to the information needed for calculating KPI values for each and every transport chain of the basket. Readily available information from official statistics and other sources should be exploited to the extent possible. More detailed information should be solicited directly from stakeholders willing to take part in such an effort. To this end:

• a sample of transportation providers and major shippers should be formed for soliciting information,

• a questionnaire should be prepared for gathering the necessary information,

• follow-up actions should be foreseen for data collection including interviews if necessary, and

• a procedure addressing missing observations and quality adjustments should be designed.

As a general rule, the reported values should be:

• Consistent: The methodology employed should be consistent to allow for meaningful comparisons over time. Any changes to data, system boundaries, methods or any other relevant factor in the time series has to be clearly documented.

• Transparent: All relevant issues need to be addressed in a factual and coherent manner. The underline assumptions, calculation methodologies and data sources used have to be disclosed.

• Accurate: Ensure that uncertainties are reduced as far as practicable. Values reported should be of sufficient accuracy to enable users to make decisions with reasonable assurance as to the integrity of the reported information.

Emissi on estimati on: When it comes to emissions, the definition of system boundaries is crucial in fulfilling all three criteria mentioned above (consistency, transparency and accuracy). Swahn (2010) defines four system boundaries (refer to Fig. 3.16):

• System boundary A includes traffic and transportation related activities regarding engine operation for the propulsion and equipment for climate control of goods, as well as losses in fuel tanks and batteries. This includes the trafficrelated terminal handling, i.e. when goods do not leave their vehicle/vessel.

Fig. 3.16 Definition of system boundaries. Source: Swahn (2010)

• System boundary B includes in addition the supply of energy from energy source to the tank, battery and electric motor (trains). This is the minimum required system boundary for performance of comparisons between different modes of transportation.

• System boundary C includes in addition traffic infrastructure operation and maintenance.

• System boundary D includes in addition vehicle, vessel, load units production and scrapping (life cycle approach).

Although the introduction of the Life Cycle Assessment (LCA) methodology in decision making happens to be one of the policy recommendations that resulted from the SuperGreen project, it is essential to keep things as simple as possible in the early stages of a green corridor development. It is for this reason that the system boundary B is recommended to begin with. Later on, the boundary can be expanded to reach level D. Chapter 11 of this book deals with LCA considerations, with a focus on maritime transportation.

Another comment relates to the type of carbon emissions measured. In discussions of emissions, lots of terms are used—carbon emissions, carbon dioxide, greenhouse gases (GHGs). In fact, climate change is caused by a range of gases, known collectively as 'greenhouse gases'. Of these, the most common is carbon dioxide (CO2). However, other GHGs are emitted from vehicle exhausts (i.e. nitrous oxide and methane), and their reporting is also valuable. This is done through CO2-equivalent (CO2-eq) units expressing GHGs as if they had the same climate change effects as CO2. The choice between CO2 and CO2-eq depends on the availability of data and/or the capabilities of the emissions calculator used. CO2-eq, if available, is preferable to CO2.

In general, a specialized emission calculator is needed for estimating the emission KPIs. In SuperGreen, the web-based tool EcoTransIT World has been used but, as long as certified footprint calculators are not available, any other model could be used in its position, provided that a relevant qualification escorts the results. In the framework of the BGLC project, O¨ berg (2013) compared EcoTransIT World with NTM, a Swedish emission calculator, with inconclusive results. The announced cooperation between the two models towards creating synergies in their methodological expertise on carbon accounting is welcomed (EcoTransIt, 2014).

In relation to emission calculators, it should be mentioned that user specified inputs are preferred to any model's default values, only when they are adequately verified and there is consistency across all chains examined. Otherwise, it is safer to use the default values of the selected model.

Finally, it is important to note that in a multi-load multi-drop vehicle trip the allocation of emissions to specific loads becomes quickly almost unworkably complex, requiring far more data than is likely to be available. A simplification is suggested by DEFRA (UK) according to which, emissions are allocated on the basis of the number of EDUs (Equivalent Delivery Units) transported for each customer. Generally speaking, the choice of EDU should reflect the limiting factor on the loading of the vehicle. If the load is typically limited by volume, then a volumebased EDU such as pallets or cube should be used. If the load is more often limited by weight, then a weight-based EDU such as tonnes will be more appropriate and provide more accurate results.

KPI aggrega tion: The weights needed for aggregating chain-level KPIs into corridor-level ones depend on the relative significance of each chain in the route it belongs and in the entire corridor. As such, they have to be determined by using the model results that were considered in constructing the chain basket. These weights should be relatively fixed to permit historical comparisons.

It is noted that normally the weights for aggregating unit costs, CO2 and SOx emissions should be in tonne-km units. Transport time can only be aggregated if

expressed as average speed, unless all chains examined concern a single origindestination pair. The volume of cargo is probably the most suitable weight for aggregating transport time (or speed) and reliability. As for frequencies, one needs to be careful to avoid adding pears with apples. As a general rule of thumb, in serial services it is the least frequent one that determines the frequency of the chain.

Data verificat ion: Before closing, it is necessary to alert the reader on the data verification issue. Verification is an independent assessment of the accuracy and completeness of data. Confidence in the quality and integrity of the data supports internal operations and decision making, by revealing existing problems or points for potential improvement. It can, thus, lead to improved performance, reliability and quality of operations. Another common reason for verifying data is to increase external stakeholder confidence. For example it may reassure a transport operator that they can include the green corridor data in what they report about their services, by demonstrating:

• credibility and reliability of the corridor data,

• consistency and accuracy of performance monitoring approach, and

• completeness of assessment.

Furthermore, verification can provide confidence that the data reported is fit for the purpose for which it is intended, for example, target setting or service benchmarking.

In general, it is not always necessary to get an external party to verify the

reported data if reasonable and transparent processes are established. However, in the case of monitoring a complex system such as a transportation corridor, the engagement of an external verifier seems unavoidable. In such cases it is particularly important to be sure that the reported information is genuine and based on a consistent and accurate approach to measurement over time.

It is, thus, suggested the verification to be undertaken by a third party accredited by an internationally recognized body. Especially for GHG emission reporting, there are a number of internationally recognized standards and protocols that can be applied, like:

• ISO14064—Greenhouse gas accounting

• ISO14065—Requirements for greenhouse gas validation and verification bodies for use in accreditation or other forms of recognition.

• IEN 16258—The methodology and requirements for calculating and reporting energy consumption and greenhouse gas emissions in transport services.

Bench marking freque ncy: The frequency of monitoring the performance of a corridor depends on the objectives set by the corridor management. As far as transportation services are concerned, an annual benchmarking is both feasible and practical, especially if customer satisfaction needs to be reported which happens to be the case with Rail Freight Corridors (Reg. 913/2010). Infrastructural developments can be reported on a less frequent basis.

A relevant issue relates to the periodical adjustments needed to account for changes in the composition of cargoes and transport chains using the corridor. As such changes would affect the model results (and the corresponding chain basket and weights), they can only be accounted for whenever the model is updated. In the CPI context, the HES is usually updated every 5–7 years.

General qua lification: The method outlined above permits monitoring of the performance of a single corridor over time. It is not suitable for comparisons between corridors, as it does not consider differences in corridor characteristics that can be decisive in the overall performance of a corridor. This statement excludes the parameters determined by the Handbook on Reg. 913/2010 concerning railway transportation (EC, 2011b), as they have been aligned with the reports on train performance management of RNE in order to ensure a consistent quality of performance monitoring reports.

Acknowledgement Work reported herein was supported in part by EU project SuperGreen and an internal grant at the Technical University of Denmark.

  • [1] The author of this chapter has used the Danish National Transport Model (LTM-Lands Trafik Modellen) for applying this methodology to the GreCOR corridor
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