Introduction and framework for comparison
Someone starting out in emissions estimation goes a long way by reading guidelines and setting up a simple model in Excel. That gives a nice sense of what it means, how the chain fits together and what order sizes are. If you then want to take the next step, you automatically end up with the carbon footprinting tools that are available on the market.
Models and (chain) accounting tools
Most tools help the user create a complex model of the chain, and estimate or predict the amount of fuel consumed.
But at the moment a new generation of tools is emerging. These are more focused on “accounting” for the primary data from the operation and calculating emissions from it in a standardized way so that they can be assigned to the right activity. The “accounting” means that an administrator or an auditor can check whether the results are reliable and thus give a true picture of reality. This is important if unqualified opinions are required, for example, for reports or calculations of emissions costs.
Different tools with different objectives
Roughly speaking, there are two groups of tools:
- Tool that facilitate allocation of emissions
- Tools that help estimate consumption
Tools from the first group focus on the effective processing of detailed data on fuel and transport activity and their allocation to activities. With this approach, total emissions and emission intensity can be determined without assumptions based on measured values. This provides an accurate picture of the true effectiveness of the underlying operation.
Tools from the second group are often focused on transport networks. They help in making choices of partners for shippers. These tools often make more use of estimates. By using standard emission intensities, total consumption can be estimated based on activity, without having to allocate accurate fuel values. This makes it possible to estimate emissions for operations that have not yet been performed. In this way you can easily see the consequences of different ways of working. The downside is that this is less accurate.
This means that these tools require the user to understand what prescriptive choices have been made for determining emission and performance. And what assumptions were made in estimating consumption or missing activities. Because only then can you use the results for decisions.
Below we have included a list of tools based on public information. It is regularly improved and refreshed, based on both our own work and input from readers. New tools or improved information about the tools can be submitted through email@example.com. This information will be reviewed and processed by the editors.
ABCO2 (CE Delft)
ABCO2 is a model developed by CE Delft and Cape Group for calculating emissions at mission level. The tool aims at real-time estimation of emissions for decision support. The possibility is offered to use specific emission intensities based on past shipments.
For the input values for activity the tool uses order lines specifying origin and destination, volume and weight and means of transport. Through a simulation environment these properties can be varied, giving the user insight into (the emissions of) alternative routes and modes. Consumption can be estimated based on key figures or based on emission factors determined from historical orders with corresponding energy consumption.
The tool uses emission intensities in the STREAM methodology, which are tightened based on measured consumption of the carrier. The standards, allocation and estimates used are also in line with the STREAM method. Distance is allocated based on distance travelled or planned, load based on weight or volume.
BigMile is a chain accounting tool developed by the Top Sector Logistics and Connekt, and subsequently privatized.
The tool focuses on accurate justification of consumption through allocation of primary fuel data, but is also capable of modeling missing consumption data. In doing so, BigMile provides a comprehensive analysis environment to further disaggregate emission (intensity) by underlying operational characteristics.
Input values for activity and fuel are determined case-dependently based on a profile of operational characteristics and information availability. This profile can be determined by the user using an automatic query by the tool. Here, BigMile distinguishes three levels for data quality (gold, silver and bronze) based on the availability and aggregation level of primary fuel data.
The user has the choice to use fuel emission factors from CO2emissiefactoren.nl (Dutch standard) or the GLEC framework, for estimating fuel data where this is not available from primary sources. For determining the transport performance both weight and volume limits can be used, the distance is determined based on direct ‘bird’s eye view’ distance. Total emission and emission intensity is determined using guidelines from EN16258, COFRET and GLEC. The methodological choices are further explained in the explained in interoperability guidelines and publications by Lean and Green Europe.
Carbon Care is a model for estimating emissions, developed with support from the Swiss Federal Office of Civil Aviation.
Transportation activity is entered based on origin, destination, weight and mode. Consumption is estimated based on general route and load factor assumptions explained on the website.
EN 16258 is followed for allocation to determine emission intensity. Emission factors are also based on EN 16258. To determine transport performance, direct distance is used for air and road transport, shortest feasible distance for water and rail transport.
EcoTransIT is a model developed by an independent industry driven foundation Eco Trans World Innitive. The tool focuses on estimating energy consumption based on activities and a large database of emission intensities.
Activity is specified in origin, destination, weight (or container) and transport mode, possibly supplemented by type of goods and specific vehicle. The tool estimates routes based on large database of road, shipping, rail and aviation networks. Input of primary fuel data is not possible, but the tool offers the possibility to input customer specific emission intensity factors and routes. Emission factors and assumptions used for calculating load factors and vehicle selection are explained in detail in the technical documentation.
The tool determines well-to-wheel emissions according to guidelines and default values of EN 16258 and GLEC Framework guidelines and with HBEFA key figures, supplemented with NOx, SOx, NMHC and PM from other data sources. For ocean freight the methodology of Clean Cargo Working Group is used. The transport performance standard used is weight and distance travelled. The tool is accredited by the Smart Freight Center.
LogEC is a tool developed by Bearingpoint, aimed at accurate justification of emissions based on consumption data or estimated consumption if consumption data is not available.
Technical documentation on the tool is not available. Therefore it is not clear what aggregation levels for fuel data and assumptions for estimating consumption are applied. The EN16258 standard and French decree 2011:1336 are followed, but exact interpretation is unknown. The tool reports CO2, CO, N2O, CH4, HC and NOX, used emission factors are not mentioned. The determination of the transport performance (distance and unit) are also unknown.
Microsoft Cloud for Sustainability
is a cloud platform that provides insight into an organization’s emissions based on automatic data connections with other (cloud) data systems. The platform is focused on the real-time display of emissions within Scope 1, 2 and 3 of the Greenhouse Gas Protocol. These emissions are displayed in customizable dashboards, analyses and reports, with the ability to zoom in on the development of emissions per business unit and location. The structure of the platform is similar to Microsoft Power BI (some functions even require this license) and other Microsoft cloud platforms such as Dynamics 365.
The platform provides for calculating emissions in CO2e by linking fuel data with emission factors. By default, the U.S. Environmental Protection Agency (EPA) are included in the tool, users can add their own factors. In the data, emissions can be specified per period and it is possible to add a data quality field. The platform initially focuses purely on emissions, the performance that stands against the emissions is not included in the standard views of the platform. Allocation of fuel to transport performance is therefore not included by default, but automatic workflows to facilitate this can (to some extent) be added to the platform by users.
NOTE: Microsoft Cloud for Sustainability focuses on primary fuel data, so is best categorized under accounting, but does not provide for the allocation of fuel, which the other tools do specialize in.
MIXMOVE (CO2 calculator module)
CO2 calculator is a tool for determining CO2e emissions that is used in combination with MIXMOVE. The tool determines well-to-wheel emissions according to guidelines and standard values of EN 16258 and the GLEC Framework. Emissions are allocated to transport performance based on weight and distance travelled (birds-eye distance for lunch cargo). For estimation of emissions the tool uses the GLEC framework in combination with its own database to estimate distances. In addition, for each type of vehicle a specific consumption can be entered so that also based on measured values emissions can be determined.
The results are displayed in various overviews showing emissions per category, data type and mode. These results also appear in Corporate Social Responsibility reports in line with the GLEC framework.
The SmartWay program of The United States Environmental Protection Agency (US EPA) has developed models to assist member shippers, carriers and LSPs in determining their emissions. The tools for carriers focus on measuring consumption and emissions, and are broken down by mode. The tools for shippers use the data collected in the carrier tool to estimate emissions.
Depending on the type of organization and transportation mode, the tools use fixed levels of aggregation to enter transportation activity and, in the case of carriers, consumption data. Categories and assumptions for estimates are described in detail in the technical documentation.
SmartWay shares detailed emission intensities for the categories with users through its tools, and uses self-established fuel emission factors to determine CO2, PM, NOx, PM2.5, PM10 and black carbon emissions. For transport performance uses weight and volume for trucks, for other modes only weight. Allocation is based on distance travelled.