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2.2.2 The Activity Based or Bottom Up Approach

Sometimes, fuel consumption data is either not available or is unreliable in order to estimate emissions using the “top-down” approach. In this case we use a different approach to estimating emissions, the so-called “activity based”, or “bottom-up” method. In activity-based approaches, one tries to estimate emissions based on modeling of the transportation activity or by using conversion factors that convert the available data into emissions.

There are various ways to estimate emissions based on the approach that uses the conversion factors and the approach used depends on the available data and inventory purpose. In order to report the emissions associated with a transportation activity, the 'activity data' such as distance travelled must be converted into emissions by using an appropriate conversion factor. For instance in the case that distance travelled is available, conversion factors in terms of kg of CO2 per vehiclekm can be used. In this case, an average payload is assumed since the cargo transported is unknown. If the amount of cargo transported (e.g. in tonnes) is available, conversion factors in terms of kg of emissions per tonne-km can be used to estimate emissions.

As an example, for CO2 emissions of a certain transportation mode one can use the following equation:


V is the transportation volume (in tonnes)

D is the average transportation distance (in kilometers) and

F is the average CO2-emission factor per tonne-km

The aforementioned conversion factors allow organizations, companies and individuals to calculate emissions from a range of activities, including transportation activities, in a simple and acceptable way. More information on conversion factors for transportation activities can be found in the 2014 Government GHG Conversion Factors for Company Reporting: Methodology Paper for Emission Factors of the UK Department for Environment, Food and Rural Affairs (Defra), see Defra (2013).

Estimating emissions using the activity-based approach contains many uncertainties and is therefore not a trivial task. For instance, emissions from road freight or passenger transportation depend on the vehicle (e.g. engine type and age, tires, fuel used, the condition of the vehicle) but also on the way the vehicle is used (e.g. the payload, which may vary along the route, the traffic conditions like congestion and weather, the driver's behavior, etc). Chapter 7 of this book on green vehicle routing provides, among other things, some modeling details on possible fuel consumption functions in a road setting. Emissions from ships depend on the characteristics of the vessel and its engine, but also on the operating profile, mainly speed and payload. Weather is also an important factor. For aviation,

Fig. 2.2 Emissions calculation flowchart. Source: Psaraftis and Kontovas (2009)

payload, weather conditions, cruising speed and altitude are important parameters in estimating emissions.

As an example, Fig. 2.2 is a flowchart representation of the logic of an activitybased model to estimate emissions from international shipping, and how each of the emissions statistics is computed (see Psaraftis and Kontovas (2009) for more details). Total fuel consumption is the sum of the consumptions at sea and in port. Bunker consumption at sea is estimated based on an average consumption per day and the total time spend at sea. Total tonne-km's are computed by multiplying the average payload carried by the ship when at sea by the total sea kilometers traveled by the ship in a year.

Detailed modeling methodologies of emissions are available for all transportation modes. The interested reader is referred to the US Environmental Protection Agency (EPA) methods for calculating on-road (e.g. cars, trucks and motorcycles), non-road (e.g. cargo handling equipment) and off-road (e.g. commercial marine, locomotives, and aircraft). The EPA provides both software solutions and detailed methodologies on how to model emissions and the relevant emission factors. MOVES (MOtor Vehicle Emission Simulator) is EPA's current official model for estimating air pollution emissions from cars, trucks and motorcycles (EPA, 2014a). The so-called NONROAD emission inventory model (EPA, 2014b) can be used to predict emissions of hydrocarbons, carbon monoxide, oxides of nitrogen, particulate matter, and sulphur dioxides from small and large nonroad vehicles, equipment, and engines. The NONROAD model does not include aircraft and aircraft engines, locomotives, or commercial marine vessels but detailed information on how to model emissions from these activities can be found at EPA's website at

The European Environment Agency (EEA) publishes a very detailed air pollutant emission inventory guidebook (formerly called the EMEP/CORINAIR emission inventory guidebook) that provides guidance on estimating emissions from both anthropogenic sources, including transportation activities. Although this guidebook is mainly used to provide technical guidance to prepare national emission inventories, it provides information on how to model emissions and presents emission factors also for individual transportation activities and is one of the most recognized sets of emission estimation methods used in air pollution studies in Europe. Part B of the '2013 EMEP EEA air pollutant emission inventory guidebook', see EMEP/EEA (2013) deals with emissions from combustion of energy for aviation (Sect. 1.A.3.a), road transportation (Sect. 1.A.3.b), railways (Sect. 1.A.3.c), navigation (shipping) (Sect. 1.A.3.d), pipeline transportation (Sect. 1.A.3.e) and non-road mobile sources and machinery (Sect. 1.A.4).

An interesting question is, are there differences between emissions estimates based on top-down versus bottom up? The answer is yes, and Fig. 2.3 is illustrative for international shipping. It can be seen that bottom up estimates are higher than equivalent top-down figures, and that differences can be important. These differences add to the overall uncertainty of estimating emissions. They can be attributed to a number of reasons, including inaccurate or unreliable fuel sales statistics for the top-down approach and the great number of modeling assumptions and uncertain data for the bottom-up approach.

Fig. 2.3 Differences between top-down and bottom-up emissions estimates for international shipping. IEA statistics are much lower than bottom-up estimates. Source: IEA, adapted from Buhaug et al. (2009)

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