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3 QUALITIES OF AN EFFECTIVE TOOL In the previous chapter current methods for measuring emissions were reviewed and a definition of the carbon footprint of transportation in the supply chain was presented. In order to critique current methods a set of qualities that can be used to evaluate tools must be developed. This chapter explores how a number of different frameworks can be used to develop those criteria. GREENHOUSE GAS PROGRAMS, METHODS, AND TOOLS In discussing the transition from network models of transportation planning to tools designed to calculate greenhouse gas emissions, it is helpful to first begin with a discussion of how to classify different tools. Baldo et al.53 classified current carbon footprint measurement methodologies into three different main groups: â¢ General guidelines, such as ISO standards, that represent the normative standard references for CO2 calculation. â¢ Specific guidelines, such as PAS 2050, that contain ad hoc indication on GHG calculation and monitoring. â¢ Calculation tools that are aimed at calculating CO2 emissions of specific activities.The COFRET54 project, in performing a review of transportation carbon footprint methodologies, categorized items within four categories: â¢ Carbon footprint methodologies cover actual standards, standard-like guidelines, guidebooks and schemes that provide the framework for how to calculate and report carbon footprint of transport and logistics along the supply chain or some part of it. â¢ Carbon footprint calculation tools encompass all tools, instruments, software, algorithms and other applications, whether public, commercial or company specific, that are used to carry out and facilitate the calculations of carbon footprint of transport and logistics along the supply chain or some part of it. â¢ Emission factor databases are considered as collections of greenhouse gas emission data, either public or commercial, that are needed in order to calculate carbon footprint of transport and logistics along the supply chain or some part of it. Examples of emission factors in such databases are vehicle emissions, emissions from fuel production and emissions per transport unit. â¢ Other activities cover all items other than methodologies, calculation tools and databases that contribute to the topic of carbon footprint of transport and logistics along the supply chain. Examples of such activities include research projects, awareness raising initiatives and different types of communication forums and channels. 27
Both of these definitions include the idea of a difference between high-level standards that provide only guidance regarding calculating emissions and actual tools used for calculating emissions from specific activities. We consider existing greenhouse gas accounting tools to fit into a hierarchy of three different levels: Programs, Methodologies, and Tools. This hierarchy is shown in Figure 7. Figure 7: Classification of GHG Accounting Types Programs represent the highest level of the hierarchy, and consist of guidelines describing what activities should be accounted, which gases to track, as well as how they should be reported. A program need not specify the actual method used to perform the calculations, but may provide one or more approved methods. The methodology represents the next level in the hierarchy, and specifies the process by which emissions should be calculated. A single program might have a number of appropriate methodologies that could be used, and conversely a single methodology could be appropriate to use in a number of different programs. A tool represents the lowest level of the hierarchy, and at its core represents a specific implementation of a methodology. A tool provides the ability to produce an actual quantifiable value for greenhouse gas emissions by linking a methodology with data sources. Items categorized by COFRET as emission factor databases can be considered a version of a tool, since a tool requires a methodology and an emission factor to produce output. An emission factor implicitly requires a specific methodology, since a factor given in CO2 per mile requires activity data in miles to produce a carbon footprint value. This hierarchy can be demonstrated through an example drawn from the GHG Protocol. The GHG Protocol publishes âA Corporate Accounting and Reporting Standardâ55 that fits the definition of a program. These standards describe what emissions should be accounted for using three emissions scopes, specify which greenhouse gases are included, and describe how a company determines what activities fit within the program boundary. The standards do not describe how specifically the emissions should be calculated. The GHG Protocol does provide a number of tools that can be used to do this, including a cross-sector tool designed to calculate the emissions from mobile P r o g r a m M e t h o d o l o g y T o o l 28
sources. The tool allows for the use of two primary methodologies: one based on total fuel use and the other based on activity data. Within these methodologies there are several choices of emissions factor data that can be used. In order to calculate greenhouse gas emissions the user is thus required to first choose the methodology and next choose which emissions factors to use. A view of this hierarchy is shown in Figure 8. The accounting standards represent the program, and define what emissions are to be accounted for. Two possible methodologies are available, representing the choice of either fuel or activity data to calculate emissions. Finally, in order to use the tool the specific emissions factors appropriate for that methodology must be chosen in order to produce the actual output. Figure 8: View of GHG Protocol Hierarchy METHODOLOGIES While a number of programs exist, there are two primary methods for quantifying greenhouse gas emissions from transportation: fuel-based methodologies and activity-based methods. Fuel-based methodologies use fuel consumption data to estimate emissions based on the content of the fuel and assumptions regarding its combustion. The fuel-based methodology is listed as the methodology of first choice for the GHG Protocol, as well as serving as the primary methodology for use in the IPCC national emissions inventories. While fuel based methodologies are the preferred approach to calculating emissions inventories, they are by nature backwards looking, and not appropriate for use in the planning and decision making process. They rely on accounting for actual fuel consumed, but this information is not known for future transportation operations. Fuel-based methods also require knowledge about actual fuel consumption, data that may not be available to many shippers. Activity-based approaches provide a methodology that, while not as accurate for historical emissions of CO2 as fuel based approaches, is also suitable for planning situations. In activity-based methods some measure of activity, such as vehicle miles traveled or ton-miles moved, are multiplied by an emission factor to estimate total emissions. The emission factors can be calculated in a number of ways, including 29
simulations, surveys, LCA, and econometric analysis. Shippers may prefer activity-based approaches, as they can be used to estimate emissions from more widely available data, such as shipment distances and weight, rather than fuel consumption. PERFORMANCE FRAMEWORKS In order to define the criteria that should be used to evaluate methodologies, three different performance frameworks are considered. First, an accounting framework is used to assess how well it provides information, both internally and externally. Second, a supply chain framework is used to understand how well suited it is to measuring the performance of a supply chain. Third, an environmental framework is used to understand how effective it is as a method of measuring and reporting environmental impacts. ACCOUNTING The use of activity-based methods allows for use as both a planning tool and a tool for accounting of historical emissions. The question of whether such a method is better than the fuel-based methodology is dependent on the intended use of the tool. Zimmerman56 identifies three main areas where the information generated by accounting systems is used. First, the information is collected and processed into external reports that provide information to outside organizations such as regulators. These systems are primarily concerned with producing information in a manner that meets the requirements of the external consumers of the information. The second and third areas of information use are both internal, where information is used for two primary purposesâdecision-making and control. For decision-making, the goal of the system is to provide managers with information that is relevant to the decision at hand, allowing them to make the current decision. The control function is related to performance measurementâby providing information related to specific targets or measures the accounting system is used to incentivize managers in the correct manner. As an example, a manager may have a target to reduce total emissions from transportation by 10%. By calculating total emissions from transportation and providing feedback the accounting system is used to incentivize the manager to reduce emissions. This may be separate from the information needed for decision-making, which might include data such as the estimated emissions to send a specific shipment by several different choices of mode or carrier. 30
When evaluating the performance of any tool it must be done with the intended use in mind. Some tools may fulfill multiple roles, or fill different roles for different users. Consider the EPA SmartWay 2.0 tool. This tool provides a method for carriers to calculate emissions using a fuel-based methodology57. In addition, the tool captures certain activity data. Together this data is used to provide each carrier with a score, give in both CO2 per mile and CO2 per ton-mile58. Carriers are separated based on different services they provide, such as truckload, less-than-truckload, drayage, intermodal, and rail. The EPA then groups the carriers into different performance bins and makes the average scores of the carriers in those bins publicly available. In this use the tool provides a methodology for external reporting, as the tool provides guidelines that each carrier must follow, and the information is then used to provide reports to shippers. The tool also provides the capability for shippers to calculate their emissions based on an activity-based methodology that tracks the amount of shipping done by each carrier. The tool calculates the total emissions for the shipper, as well as an overall performance score, based on how the shipper makes use of higher or lower ranked carriers. This serves to influence the decision making of the shippers, as the availability of the carrier scores allows them to prioritize carriers with low emission during the procurement process. Finally, the shippers are awarded a score based on the scores of the carriers they use, and this is also made publicly available. Figure 9 shows how the tool fills various roles for the shippers and carriers. 31 Figure 9: SmartWay Tool Uses E P A S m a r t W a y 2 . 0 E x t e r n a l R e p o r t s C a r r i e r D e c i s i o n M a k i n gC o n t r o l S h i p p e r D e c i s i o n M a k i n gC o n t r o l I n t e r n a l R e p o r t s Ca rri e r Be nc hm a rki ng S hi ppe r Be nc hm a rki ng Ca rri e r S c ore s
Working in this manner the tool is used for all three roles, though not necessarily for all users. For carriers the tool acts as both an external reporting tool and an internal control tool. The external reporting function sets reporting guidelines and scores that are shared externally to the shipper, as well as other carriers. The tool can also fulfill the internal control function, by allowing carriers to measure their performance. However, the tool does not provide the capability to help carriers make better decisionsâthe actual strategies that can be used to reduce emissions and improve their score are not included in the tool. This can be contrasted with the way the tool works for shippers. In this case the tool is designed to improve decision-making by helping shippers choose better-ranked carriers, allowing the shipper to improve their performance. This is provided in addition to the internal control and external reporting uses that work in a similar manner as it does for the carriers. SUPPLY CHAIN Traditional supply chain models have predominantly utilized two different performance measures: cost and a combination of cost and customer responsiveness (which includes many customer oriented aspects such as time, reliability, and quality). Such measurements are generally inadequate, as they are not inclusive, ignore interactions among important supply chain characteristics, and 32 ignore critical aspects of organizational strategic goals59. Further, such measure-ments fail to capture any aspects of environmental performance60. Most organizations focus on metrics within their organization61, but supply chain level capabilities are even more essential when supply chains incorporate social and environmental goals, as sustainability goals require even closer interactions between all firms involved 62 . In making decisions for the supply chain, environmental performance must be included with non-environmental performance requirements such as cost, quality, time, and flexibility so that alternatives that best support the environmental performance also make business sense63. Bringing together both environmental and non-environmental performance requires a performance measurement system that provides information necessary for decision-making64. A performance measure can be defined as a metric used to quantify the efficiency and/or effectiveness of an action 65 . A performance management system brings together individual performance metrics to measure system level performance66. A number of individual metrics can be developed that are appropriate to measuring the environmental performance of a supply chain67. The carbon footprint is an environmental common denominator that runs across all processes and operations. These common denominators identify specific information that can be gathered across the supply chain to provide a measure of environmental performance for the supply chain as a whole, and within distinct functional areas68.
Whether the carbon footprint is a metric that measures performance across the supply chain or within a functional area is dependent on how it is defined. Metrics can be evaluated in a number of categories, but designing metrics that excel in each category is not practically possible. Instead firms must choose metrics that tradeoff between certain criteria. Two of the primary trade-offs are between integrative and useful metrics, and between robust and valid metrics69. Figure 10: Tradeoffs Between Criteria69 Integrative metrics promote coordination across functions, while useful metrics are easily understood and provide managers with direct guidance. Providing managers with actionable guidance requires a level of specificity that makes promoting coordination across functions difficult. In this sense measuring the carbon footprint Promotes coordination Captures specific aspects Allows for comparability Provides actionable guidance Integrative Useful Valid Robust 33 Source: Caplice, C. and Y. Sheffi (1994). "A review and evaluation of logistics metrics." The International Journal of Logistics Management 5(2): Page 17. Copyright, Emerald Group Publishing. Permission has been granted for this image to appear here (http://www.trb.org/Main/Blurbs/169329.aspx). Emerald does not grant permission for this image to be further copied/distributed or hosted elsewhere without the express permission from Emeral Group Publishing Limited. of transportation is a useful metric, since it provides guidance on one specific aspect, but not across functions. As such it must be incorporated as one metric in an entire performance measurement system that covers both environmental and non-environmental aspects across the functions of the supply chain. The other primary trade-off is between a robust metric that allows for comparability and a valid metric that captures specific aspects. This represents a similar situation as the internal and external uses of accounting information. A valid metric provides help with making a specific decision, but is less suitable to external uses where it might be compared with similar metrics for other organizations.
MEASURING ENVIRONMENTAL IMPACT Life Cycle Assessment provides a general framework for measuring the environmental burden of a product or function. Its general structure allows for application to a wide variety of systems, but also allows considerable freedom in implementation. Differences in implementation can be separated between issues of methods, whether process-based or EIO-LCA, and purpose, whether attributional or consequential. This freedom makes for difficulty in comparison between any two separate LCAs. The high cost and time of performing process-based LCAs poses difficulties for products with complex supply chains spanning many organizations. A survey of LCA practitioners identified data collection as the most time consuming and costly aspect of performing an LCA70. Collecting data across organizational boundaries presents issues with proprietary and confidential information, data accuracy, and a lack of representative data.71,72 EIO-LCA provides an approach that requires less detailed process data. By including all upstream activity within the economy the data is more complete, and there is no need to draw system boundaries. The data is generally compiled from publicly available sources, allowing for greater transparency than process-based LCAs that use proprietary data. Finally, the EIO approach allows a much cheaper and faster method of providing results. In cases where only an approximate result is needed an EIO LCA can provide a very rapid and inexpensive answer73. The assumptions and methods of EIO analysis do have drawbacks for determining the environmental burdens of a specific product. Though EIO tables may contain hundreds of sectors, this still requires significant aggregation of different products and processes. Some sectors may be too heterogeneous to produce correct results74. The information in the Input-Output tables only captures the effects of production and therefore the use and disposal phases are not included75. Many countries lack the sectoral environmental data needed for analysis, meaning that imports must be assumed to be homogeneous with domestic products76. Finally, the nature of Input-Output analysis assumes proportionality between monetary and production flows77. That is, if a product doubles in cost then the environmental burden doubles as well. Though necessary for the computational results this may not reflect the reality of the production process. 34
LCAs generally fall into two categories based on their purpose. An attributional LCA is focused on looking back on a product and determining what emissions can be attributed to it. A consequential LCA is focused on the environmental effects of what will happen due to a decrease or increase demands for goods and services78. The two types of LCAs are suitable for different purposes and require different types of data. An attributional LCA is appropriate for making specific environmental claims regarding a product, and typically makes use of average data for the product. The consequential category is more suited to performing scenario analysis. It uses marginal data for the product, as it requires making assumptions about economic factors related to changes in product consumption or production79. The distinction between the attributional and consequential approach reflects similar issues to those of the accounting and supply chain performance measurement frameworks. The differing approaches between attributional and consequential methods represent the core difference in perspective between decision-making and control. The attributional approach is designed to be a backward looking accounting of environmental impact, suitable for measuring performance. The consequential approach is designed for decision-making, taking a forward-looking view. IDENTIFYING CRITERIA These ideas can be used to develop a framework for evaluating tools designed to measure the carbon footprint of transportation in the supply chain. Tools can be classified based on their ability to fulfill each of the three functions of an accounting system: external reporting, internal control, and decision-making. Evaluation of a tool must consider its intended use, and tools may perform better for some uses than others. Measuring the carbon footprint of transportation is just one metric that captures a specific aspect of performance, and can be integrated into a larger system to measure overall performance. A metric must trade-off between being suitable for general use or to making a specific decision. This trade-off must be considered in how the metric will be used, and the method for measuring it. The concepts of breadth, depth, and precision can be used to classify how different GHG programs measure the carbon footprint of transportation. Breadth and depth together provide a description of the scope of the program, defining what is included in the program, from the different activities to the range of the fuel cycle. This is illustrated in Figure 11. 35
Figure 11: Breadth and Depth Rather than identify what is included in the program, the precision determines the level of detail the program provides. Depending on the level of aggregation in data sources or the approach for generating emissions, programs may provide more or less precision in their estimates of GHG emissions. Some programs may provide only rough estimates by mode, while others allow calculations based on specific shipment level details. As the scope of the decision narrows, from mode to equipment type to carrier to individual shipment, more precision is required in the calculation to differentiate between options. This is shown in Figure 12. Figure 12: Precision Based on the concept of traceability, the carbon footprint of any shipment can be defined in terms of the breadth, depth, and precision of the measurement. The breadth and depth together consider the scope of emissions included in the measurement. They define what modes and logistics activities should be considered in the network, which greenhouse gases to measure, and which portions of the full life cycle of the transportation process should be included. The precision of the measurement defines at what level of precision a distinction can be drawn between calculating the carbon footprint of two separate shipments. Together the breadth, depth, and precision cover how relevant a measurement is for making a specific decision. The scope of the supply chain must include enough breadth and depth to R o a d D i r e c t E m i s s i o n s I n f r a s t r u c t u r e R a i l D i r e c t E m i s s i o n s I n f r a s t r u c t u r e A i r D i r e c t E m i s s i o n s Upstream fuel production I n f r a s t r u c t u r e W a t e r D i r e c t E m i s s i o n s I n f r a s t r u c t u r e L o g i sti c s D i r e c t E m i s s i o n s I n f r a s t r u c t u r e B r e a d t h D e p t h Upstream fuel production Upstream fuel production Upstream fuel production Upstream fuel production 36
capture the relevant emissions, while the measurement must be precise enough to allow differentiation between the options. BREADTH, DEPTH, AND PRECISION IN PRACTICE The approaches of two popular GHG calculators provide an illustration of how the breadth, depth, and precision can vary between different programs, and how this impacts the ability to calculate emissions. The GHG Protocol is the most widely used tool for corporate level GHG accounting, and offers a tool for the calculation of emissions from mobile sources. NTM is a calculator more narrowly focused on transportation in Europe. Both sources provide calculators for greenhouse gas emissions from transportation, but use different methods for the calculation. NTM The NTM methodology uses a bottom-up methodology to calculate emission factors for road80. Figure 13 depicts the decision flow used by NTM to calculate emissions. By standardizing the road types, fuel, energy content and emission factors, and abatement equipment, NTM is able to provide emissions factors on a vehicle-distance traveled basis for 10 vehicle types at any load utilization between 0 and 100%. Thus, NTM operates at a vehicle and load level of precision. The calculator is also able to provide an emissions factor on a per tonne-km basis, which is done by making use of an assumed load factor, which represents less precision than the vehicle distance traveled factor. 37
Figure 13: NTM Methodology80 NTM considers only emissions from transportation, and not additional logistics activities. The calculator does include CH4 and N2O in addition to CO2. These decisions define the breadth of the system chosen by NTM. Finally, NTM does not include the emissions from the upstream production of fuel, nor from any life cycle impacts of the vehicle and infrastructure. Thus the depth of the system is limited to only the direct emissions from the combustion of fuel. THE GHG PROTOCOL The GHG Protocol provides a calculator for the emissions from transportation called âGHG emissions from transport or mobile sources"81. The tool allows for calculation of emissions using both a fuel-based and activity-based methodology. The activity-based methodology gets emissions factors from two sources, the EPA Climate Leaders82 program for the US and Defra83 for the UK. The EPA Climate Leaders program uses a top down methodology to estimate freight emissions per ton-mile. The process uses total emissions from the transportation sector, separated between road, rail, air, and water modes, taken from the EPA divided by activity data, in ton-miles by mode, from the Federal Highway Administration84 (FHWA) to calculate an emissions factor in kg CO2/ton-mile for each of the four modes. In addition, the US factors include a vehicle distance factor based on estimated miles per gallon. However, factors are provided for only a limited selection of vehicle classes (light duty, heavy duty rigid, and heavy duty articulated). 38
The Defra emissions factors are calculated using a survey methodology, which captures average vehicle fuel consumption and load factors for a number of different vehicle types. Emissions factors are provided per tonne-km for a number of different types of road vehicles and watercraft, as well as for rail and air. Emission factors are also provided by vehicle distance and load factor, allowing for calculation at any load factor for a number of different vehicle types. Thus, even within a single program a number of different levels of precision are available depending on the source of the data. In contrast to the NTM program, the GHG Protocol also provides tools capable of measuring the emissions from other logistics activities. Tools are provided that can measure the emission from electricity and other fuel combustion used in buildings and for operating equipment. Thus, from a breadth standpoint the GHG Protocol is capable of measuring transportation related logistics activities in addition to the direct emissions from transportation, but requires multiple tools to accomplish this. The mobile calculator provides a similar breadth to NTM in terms of greenhouse gases included, as factors for CH4 and N2O are provided in addition to CO2. The GHG Protocol uses the same level of depth as NTM, as emissions are based only on direct emissions from fuel combustion, and other portions of the fuel cycle are not included. A comparison of these two programs shows how the concepts of breadth, depth, and precision relate to the capabilities of the programs. The GHG Protocol offers the ability for greater breadth of activity due to the inclusion of calculators capable of measuring non-transport logistics activities, while the NTM program provides more precision in the ability to measure emissions due to the high level of aggregation provide by the GHG Protocol, particularly for the US emission factors. OTHER CHARACTERISTICS While breadth, depth, and precision cover the relevant aspects needed to decide if a tool is capable of making a specific decision they do not cover all the aspects of a good tool. In addition to decision-making a tool must also be capable of providing information externally for reporting purposes, and internally for measuring performance. This is especially true in the context of a supply chain, where effectively communicating performance between firms and functional units is necessary to effectively manage the supply chain as a whole. In order to identify characteristics of a tool that go beyond making individual decisions, it is helpful to identify the principles around which many tools designed for external reports have been organized. The CDP85, GRI86, and Greenhouse Gas Protocol 87 were all created with the idea of measuring the environmental performance of many different firms in a standardized way. The principles each of them has been designed around are shown in Table 2. 39
Carbon Disclosure Project Global Reporting Initiative Greenhouse Gas Protocol Relevance Relevance Relevance Faithful Representation Reliability Completeness Comparability Clarity Consistency Timeliness Comparability Transparency Understandability Timeliness Accuracy Verifiability Verifiability Table 2: Comparison of Principles The high degree of similarity around their principles is immediately obvious. All three programs have been designed around the core principles of financial accounting. The Federal Accounting Standards Board (FASB) set forward a set of principles to be used as a conceptual framework for financial accounting88. This principle-based view of financial accounting came about in response to criticism of the traditional rules-based approach due to several recent accounting scandals89. The FASB standards were developed and harmonized with the International Accounting Standards Board (IASB)90 to converge the standards. These standards identified two fundamental qualitative characteristics: relevance and faithful representation. In addition, they identified four enhancing characteristics: comparability, verifiability, timeliness and understandability. These characteristics were explicitly adopted for use by the CDP. According to the IASB: âcomparability is the quality of information that enables users to identify similarities in and differences between two sets of information. Consistency refers to the use of the same policies and procedures, either from period to period within an entity or in a single period across entities. Comparability greatly enhances the value of information to investors and is therefore the objective of this requirement; consistency is the means.â while verifiability: âis the characteristic of information that helps to assure users that it has been faithfully represented. Verifiable information is characterized by supporting evidence that provides a clear and sufficient trail from monitored data to the information presented in disclosures. â Together comparability and verifiability provide the final two criteria for evaluating tools. Comparability ensures that the results of a tool are comparable to those of other users, an especially important consideration in the context of a supply chain. Verifiability provides increased trust in the results of the tool, providing 40
reassurance that the results can be used as part of an overall performance measurement system. SUMMARY In all three performance frameworks a common distinction between internal and external uses are present. The accounting framework makes this distinction between managerial accounting and financial reporting; the supply chain literature in the tradeoff between useful and robust metrics; and in the LCA literature on the distinction between consequential and attributional studies. Thus, any evaluation of current tools must recognize this distinction. Based on our review of performance frameworks we propose the following five criteria for evaluating carbon footprint tools: 1. Breadthâthe scope of activities included in the measurement2. Depthâthe range of direct and indirect emissions included in themeasurement3. Precisionâthe level of detail provided by the measurement4. Comparabilityâthe degree with which measurements can be comparedacross time and organizations5. Verifiabilityâthe degree of assurance in the results and methodologyThe first three criteria together capture how relevant a measure is for decision-making. This is generally captured by the idea of relevance from the accounting standards. The other two criteria provide a measure of how well suited the tool is for external useâcan the results of the tool be compared with other organizations and trusted to accurately and faithfully represent the actual performance. A tool is useful internally if it can provide relevant information to help make decisions. The exact information needed may vary depending on the decision being made, and a toolâs relevance is determined by whether it is sufficient for that decision. As the breadth, depth, and precision of a tool increases the range of decisions for which it is relevant increases. The results of the tool should show a high level of comparability. This is useful for internal benchmarking, where a firm compares its year-on-year performance to itself, and externally, where a firm compares its performance to competitors. Further, in a supply chain context where information is shared between firms, the results of the tool must represent a common language between the firms. This is reflected in the degree of comparability between the results of different firms. Finally, due to the credence nature of carbon footprints, the output of a tool cannot be directly verified. Instead, verification can come only indirectly through examining this inputs and methods of the tool. Tools that provide more transparent methods or external verification increase the verifiability of the results, making the results more trustworthy to external viewers. Together these five criteria cover the major characteristics of a tool needed for both internal and external use. Higher degrees of performance across these categories 41
increase the relevance of the results to making decisions; the ability to incorporate the results into benchmarking and information sharing; and the trustworthiness of claims based on the results. 53 Baldo, G. L., M. Marino, et al. (2009). "The carbon footprint measurement toolkit for the EU Ecolabel." The International Journal of Life Cycle Assessment 14(7): 591--596. 54 VTT Technical Research Centre of Finland (2012). Methodologies for emission calculations - Best practices, implications and future needs, COFRET. 55 WRI and WBCSD (2004). The Greenhouse Gas Protocol: A Corporate Accounting and Reporting Standard. Washington, D.C., World Resources Institute and World Business Council for Sustainable Development. 56 Zimmerman, J. (2005). Accounting for Decision Making and Control, McGraw-Hill. 57 EPA (2012). Truck Carrier FLEET Tool: Getting Started Guide Part 1, U.S. Environmental Protection Agency. 58 EPA (2012). SmartWay Carrier Ranking System, U.S. Environmental Protection Agency. 59 Beamon, B. M. (1999). "Measuring supply chain performance." International Journal of Operations and Production Management 19(3): 275-292. 60 Beamon, B. M. (1999). "Designing the green supply chain." Logistics Information Management 12(4): 332-342. 61 Lambert, D. M. and T. L. Pohlen (2001). "Supply Chain Metrics." The International Journal of Logistics Management 12(1): 1-19. 62 Gold, S., S. Seuring, et al. (2010). "Sustainable supply chain management and inter-organizational resources: a literature review." Corporate social responsibility and environmental management 17(4): 230--245. 63 Sarkis, J. (2003). "A strategic decision framework for green supply chain management." Journal of Cleaner Production 11(4): 397--409. 64 Gunasekaran, A. and B. Kobu (2007). "Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995--2004) for research and applications." International Journal of Production Research 45(12): 2819--2840. 65 Neely, A., M. Gregory, et al. (1995). "Performance measurement system design." International Journal Of Operations & Production Management 15(4): 80. 66 Caplice, C. and Y. Sheffi (1995). "A review and evaluation of logistics performance measurement systems." The International Journal of Logistics Management 6(1): 61-74. 67 Hervani, A. A., M. M. Helms, et al. (2005). "Performance measurement for green supply chain management." Benchmarking: An International Journal 12(4): 330--353. 68 McIntyre, K., H. Smith, et al. (1998). "Environmental performance indicators for integrated supply chains: the case of Xerox Ltd." Supply Chain Management: An International Journal 3(3): 149--156. 69 Caplice, C. and Y. Sheffi (1994). "A review and evaluation of logistics metrics." The International Journal of Logistics Management 5(2): 11-28. 70 Cooper, J. S. and J. A. Fava (2006). "Life-Cycle Assessment Practitioner Survey: Summary of Results." Journal of Industrial Ecology 10(4): 12-14. 71 Huijbregts, M. A. J., G. Norris, et al. (2001). "Framework for modelling data uncertainty in life cycle inventories." The International Journal of Life Cycle Assessment 6(3): 127-132. 72 Chevalier, J.-L. and J.-F. Teno (1996). "Life cycle analysis with ill-defined data and its application to building products." The International Journal of Life Cycle Assessment 1(2): 90-96. 73 Hendrickson, C., A. Horvarth, et al. (1998). "Economic input-output models for environmental life-cycle assessment." Environmental Science & Technology 32(7): 184. 74 Hendrickson, C., A. Horvarth, et al. (1998). "Economic input-output models for environmental life-cycle assessment." Environmental Science & Technology 32(7): 184. 75 Joshi, S. (2000). "Product environmental life-cycle assessment using input-output techniques." Journal of Industrial Ecology 3(2-3): 95-120. 42
76 Suh, S. and G. Huppes (2005). "Methods for Life Cycle Inventory of a product." Journal of Cleaner Production 13(7): 687-697. 77 Lenzen, M. (2001). "Errors in conventional and input-output-based life-cycle inventories." Journal of Industrial Ecology 4(4): 127-148. 78 Ekvall, T. and B. P. Weidema (2004). "System Boundaries and Input Data in Consequential Life Cycle Inventory Analysis." International Journal of Life Cycle Assessment 9(3): 161-171. 79 Tillman, A.-M. (2000). "Significance of decision-making for LCA methodology." Environmental Impact Assessment Review 20(1): 113-123. 80 NTM (2010). Road Transport Europe, Network for Transport and Environment. 81 WRI (2011). GHG Protocol tool for mobile combustion. Version 2.3, The Greenhouse Gas Protocol. 82 EPA (2008). Direct Emissions from Mobile Combustion Sources. Washington, D.C., U.S. Environmental Protection Agency. 83 Defra (2010). 2010 Guidelines to Defra/DECC's GHG Conversion Factors for Company Reporting, Defra. 84 FHWA (2005). Highway Statistics 2005, U.S. Federal Highway Administration. 85 Carbon Disclosure Standards Board (2012). Climate Change Reporting Framework, London, UK, Carbon Disclosure Standards Board. 86 Global Reporting Initiative (2000). Sustainability Reporting Guidelines on Economic, Environmental, and Social Performance. Boston, MA, GRI. 87 WRI and WBCSD (2004). The Greenhouse Gas Protocol: A Corporate Accounting and Reporting Standard. Washington, D.C., World Resources Institute and World Business Council for Sustainable Development. 88 Financial Accounting Standards Board (2010). Conceptual Framework for Financial Reporting, Financial Accounting Foundation. 89 Benston, G. J., M. Bromwich, et al. (2006). "Principles- versus rules-based accounting standards: the FASB's standard setting strategy." Abacus 42(2): 165-188. 90 International Accounting Standards Board (2010). The Conceptual Framework for Financial Reporting, IFRS Foundation. 43