Indicator Assessment

Load factors for freight transport

Indicator Assessment
Prod-ID: IND-118-en
  Also known as: TERM 030
Published 05 Jul 2010 Last modified 11 May 2021
7 min read
This is an old version, kept for reference only.

Go to latest version
This page was archived on 09 Feb 2021 with reason: Other (Discontinued indicator)

For countries where data is available, load factors have generally declined for road freight transport. Road freight empty running showed decrease (for the countries with data), while the general load factor also showed a decline. This indicates that an increasing share of light goods which fills the vehicle in therms of volume but not weight contributes to the declining load factor.

Load factor was gradually decreasing in inland shipping, while it has increased for air freight transport. The highest load factor for freight transport was in air freight.

This indicator is discontinued. No more assessments will be produced.

TERM30 Rail freight load factor (as % by tkm)

Note: N/A

Data source:

Data provenance info is missing.

TERM30 Road freight load factor utilisation during the laden trips

Note: N/A

Data source:

Data provenance info is missing.

Road freight

Load factors are generally far below the theoretical maximum. Whilst it is relatively easy to achieve full load on an outward trip, it is a complex puzzle to find return loads. Therefore, empty return trips are frequent, though decreasing. Transport of certain goods require specialised vehicles that make it impossible to find return loads - a gasoline tanker for example can neither bring milk nor pallets as a return load.

The average load factor utilisation rates from Denmark, Netherlands, Portugal, Sweden and the United Kingdom have decreased from 1998 to 2007 (see Figure 1). Portugal's average load factor utilisation has dropped by more than 20% between 1999 and 2006. Other countries experienced a smaller drop. This situation may change soon due to cabotage regulations being proposed on the EU level. Cabotage is seen as an instrument used to reduce 'empty runs', which account for 10% of long distance and 19 % of local and regional operations in Germany (BDI, 2007). Experience has shown that reducing barriers to the movement and activities of freight can lead to increased efficiency and reduced incidences of empty running. With the current barriers cabotage accounts for around 1 % of freight traffic (European Commission, 2005).

As illustrated by data from selected countries (where available), the percentage of vehicles carrying no load has decreased from 1998 to 2006 (see Figure 2). Portugal has had a significant decrease of more than 23% between 1999 and 2006, whereas the UK and Sweden have dropped by a share of 3-5 %.

For road transport, the slow decline in load factors hides more marked developments in opposite directions: on the one hand a decline of empty haulage as a result of better fleet management, and on the other hand a decline in load factors for laden trips. Companies are often more concerned with efficient time-management than efficient transport. This results in an increasing number (more vehicle-kilometres) and a decreasing size of shipments (TNO, 1999) thereby contributing to lower efficiencies. 'Just-in-time' deliveries may stimulate this development. On the other hand, increased use of IT has contributed to better fleet management and may have compensated. An alternative explanation for the decline in load factors could be that loads are being increasingly constrained by volume or deck space, or a shift in the goods market away from bulk or bundled cargo and towards palleted goods.

An easy answer cannot be given to the question of how much load factors can be improved. Large differences in load factors within market segments, and between countries (Figure 1) suggest that there is indeed room for improvements, but hauliers within the same market segments may still face different situations that may limit the potential improvement of load factors. Detailed surveys of utilisation can help identify where improvements can most easily be achieved. For example, in cases where deck space is the constraining factor, the use of double-deckers could significantly improve loading factors as well as cut total fuel consumption by up to 49 % (McKinnon, 2007).

Rail freight

Rail freight data was received from a few Eastern European countries and Turkey. They demonstrate that the rail freight loading factor is fluctuating around 50 % (Figure 3) and shows some, but very slowly rising trend. This mode of transportation as well as maritime freight (see below) has the highest potential in increasing load factor utilisation because they can carry containers as well as loaded or empty transport vehicles; however it has not see much improvement in Eastern Europe.


In the case of inland shipping, there is some practise of returning empty truck trailers by inland shipping, which may contribute to low load factors in certain market segments.

While there are limited policy options that directly address load factors, there may be more to be gained by focusing on objectives more directly related to environmental pressures. Striving to internalise external costs of transport will result in higher operating costs for transport companies, a powerful incentive to improve load factors and mitigate other inefficiencies.

Air freight

The air freight load factor ranges from low to fairly high load factors, as high as 86 % of Swiss WorldCargo to 67 % of Lufthansa Cargo (, 2005). As a comparison, statistics for the US domestic air capacity utilisation figures for freight and mail between 1992 and 2005 were below 40 % and falling as low as 30 % in 2005 (US DoT, 2005). Comparing load factors between modes should be done with great care and best for transport of similar goods in similar situations. For example, the types of goods transported have a decisive influence on load factors as well as whether it is national or international transport.

Supporting information

Indicator definition

Load Factor: The load factor is the ratio of the average load to total vehicle freight capacity (vans,
lorries, train wagons, ships), expressed in terms of vehicle kilometres. Empty running is excluded from the calculation.
Empty running is calculated as the percentage of total vehicle-kilometres which are run empty.


Load factors and empty running are both expressed as percentages.


Policy context and targets

Context description

Vehicle utilisation is a measure of how efficiently the freight sector is transporting goods with its vehicles. If vehicle utilisation can be improved, through reduced empty running and making better use of each vehicle's carrying capacity then the same goods can be carried with fewer vehicle movements. This helps to reduce total freight vehicle traffic, measured as vehicle-km, thereby leading to reduced congestion, emissions, accidents and other environmental impacts of freight transport.
The liberalisation of the internal EU market has led to complex freight transport movements, an impact of which has been the practice of cabotage whereby hauliers from one country pick up and deliver goods within another country. Cabotage, which constitutes approximately 1 % of national road transport demand within the EU (EC, 2006b) is only legal if hauliers conduct no more than three cabotage operations in the country of destination within seven days of completing a delivery. However, the European Parliament has called for the lifting of all limits on cabotage by 2014. This should reduce the levels of empty running, improving the efficiency of transporting goods.


No international targets have been specified (although individual countries may have national targets in place).

Related policy documents



Methodology for indicator calculation

The Indicator covers load factors, also known as lading factors. This is expressed as a percentage utilization of the available capacity in tonne-km. The indicator is based on qualitative information collected through the annual questionnaire (EEA) and other sources (studies and publications retrieved from the Internet).
As the maximum permissible load weight for a vehicle may vary between countries, the classifications from the country of vehicle registration are used. This should minimise inconsistencies when comparing data between countries.
Freight capacity for ships is equal to the deadweight (DWT), which is the difference between the displacement of a ship on summer load-line, and the total weight of the ship

Methodology for gap filling

Verification with EEA member countries via questionnaires.

Methodology references

No methodology references available.



Methodology uncertainty

The sources of data determining load factors as the number of tonne-km divided by the number of vehicle-km were disregarded. This was partly because this approach yields erratic results, and partly because the developments in tonnes per vehicle may equally well be explained by changes in vehicle size rather than degree of utilization of available capacity. Also, some countries report utilization as percentage of available tonne-km, others report as percentage of tonnes, not taking into account distances travelled. These two are not equivalent and show significant differences.
In road transport cases, the laden factor concerns transport of goods on national territory. Data has to be harmonised to include the contribution from empty running. In all cases the data included transport on own account and hired transport.
In addition, the base data could be inaccurate and may contain some errors due to low response rate of EU states. Errors could be reduced or eliminated with a higher response rate.

Data sets uncertainty

Strengths and weaknesses (at data level): load factors as expressed in percentage of maximum available tonne-km are not corrected for volume, as many loads are constrained by volume or deck space, rather than weight. A decline in weight-based load factors may hence be due to an increase in volume constrained loads rather than reduced utilization.
Questionnaire responses in 2008 were limited and scarce. However, TERM 2009 produced a higher number of responses than 2008. Therefore, it is likely that there will be considerable differences between the data collected in 2008 and data collected in 2009.

Rationale uncertainty

No uncertainty has been specified

Data sources

Other info

DPSIR: Driving force
Typology: Descriptive indicator (Type A - What is happening to the environment and to humans?)
Indicator codes
  • TERM 030
Frequency of updates
This indicator is discontinued. No more assessments will be produced.
EEA Contact Info






Filed under:
Filed under: transport
Document Actions