Paving the Way for Sustainable Freight Transport

Qatar National Convention Centre / Auditorium 3

Doha, 25 April 2012 - 15.00–18.00

“Sustainable Freight Transport:

Improving the environmental sustainability of transport and

logistics”

Professor Alan MCKINNON

Kühne Logistics University

Hamburg

Sustainable Freight Transport:

Improving the environmental sustainability of transport and logistics

Professor Alan McKinnon

Kühne Logistics University

Hamburg

UNCTAD 13

Paving the Way for Sustainable Freight Transport

Doha

25th April 2012

Economic

objectives

Environmental

objectives

Social

objectives

Sustainable

Logistics

Tightening Emission Standards

Part

icula

tes (

g / k

Wh)

NOx (g/kWh)

LOCAL

Health & air quality

REGIONAL

Acidification

photochemical

GLOBAL

Greenhouse -indirect

Greenhouse - direct

Effect PM HM NH3 SO2 NOx NMVOC CO CH4 CO2 N2O

EU India

(cities) India

(nationwide)

Euro 1 1993 2000 2000

Euro 2 1996 2003 2005

Euro 3 2000 2005 2010

Euro 4 2005 2010

Emission standard time-lag

Average Fuel Efficiency of New European Trucks (38 - 40t GVW) litres / 100 km

tightening Euro - emission standard

Source “Lastautomnibus” Test report 1966 - 2005, (all Brands) – quoted in Mercedes presentation (2011)

Test reports of new truck fuel efficiency 1966 - 2010

Steep reductions in fuel consumption and emissions per tonne-km

Growth of total tonne-kms counteracting this trend

Forecast Growth of Freight Transport Activity by Region 2000-2050

Source: World Business Council for Sustainable Development - Mobility 2030 report

Limited Evidence of Freight Traffic / GDP Decoupling

Ratio of Tonne-kms to GDP In

de

x (

20

00

= 1

00

)

0

20

40

60

80

100

120

140

EU27

UK

Spain

China

Sources: Eurostat and Chinese government

Objective is not to decouple freight volumes from GDP but rather

to decouple freight-related externalities from GDP

Minimising distances freight is moved will not necessarily

minimise environmental impacts on a full life cycle basis

Projected Growth of Inland Freight Movement (billion tonne-km)

Source: EU Transvisions project (2009)

(McKinsey, 2010)

India

EU

+160%

+166% 13 years

43 years

Improvements to transport

infrastructure – mainly road

Centralisation

Increased length of haul

Increased freight transport intensity

Change in commodity mix

Industrialisation

Lower density / higher value products

Consolidate loads in

larger / heavier vehicles

Stronger just-in-time

pressures

Poorer utilisation of

vehicle capacity

Decline in rail

freight

New industrial /

warehousing

development not

rail-connected

Enhance inter-modal

capabilities

Economic development

Wider sourcing

New patterns of

consumption

Growth in output

Much more freight being moved By less green mode

Higher externalities per unit of freight moved Greater environmental

degradation

Improve fuel

efficiency

Improvements to transport infrastructure

In less full vehicles

Weight of goods produced / consumed

Total tonnes- lifted

Tonne-kilometres

Road tonne-kms

Total vehicle-kms

energy-related externalities

Energy consumption

other noxious gases greenhouse gases other non-energy-related externalities

average handling factor

average length of haul

average load on laden trips

average % empty running

energy efficiency

noise, vibration, accidents, visual intrusion

emissions per unit of energy

other externalities per vehicle km

environmental impact of freight transport

modal split Similar analyses for other modes

outputs key ratios outputs key ratios

output key parameter

modal split

supply chain structure

emission intensity

energy efficiency

vehicle utilisation

Sustainable Freight Transport Framework

Relative importance of these

factors varies with the level of

economic development

Range of Public Policy Measures Affecting Key Freight Parameters

Variations in CO2 Intensity by Freight Transport Mode

0

200

400

600

800

1000

1200

1400

1600

1800

Airfre

ight

Vans

HGVs

Inla

nd w

aterw

ays

Coastal

ship

ping

Rail

Pipelin

e

CO

2 g

m p

er t

on

ne-

km

Source: McKinnon / Commission for Integrated Transport

• Over-reliance of average modal intensity values

• Need to allow for international variations

• Need to extend the calculation boundary to

include infrastructure and vehicle construction

and maintenance

g C

O2 /

tonne-k

m

Comparison of Indian and European Long-haul Trucks

84% are 2-3 axle rigids

30 – 40 cubic metres capacity

Max GVW: 9 t (2 axle) 25 t (3 axle)

5-6 axle articulated vehicle

82 cubic metres capacity

Max GVW: 40 - 44 t

Indian trucks are: slower - average speed: 35 km per hour vs 70 km per hour

more densely loaded ( + more frequently overloaded)

often under-powered (European typically over-powered)

less fuel-efficient per tonne-km and per cubic metre -km

Need to Adapt Green Logistics Strategies to Local Circumstances

Pressure to Increase the Maximum Size and Weight of Trucks

Teardrop Cheetah

DolphinBoat-tails Trailer under-tray

Over cab spoiler

Improving the Aerodynamic Profiling of Trucks

Limited benefit in developing countries where average truck speed is low

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 4 7

10

13

16

19

22

25

28

31

34

37

40

43

46

49

52

55

58

61

64

67

70

73

76

79

82

85

88

91

94

97

10

0

Speed (km/h)

Ve

hic

le r

es

isti

ve

fo

rce

s (

%)

Internal vehicle friction (gear box, drive shaft, bearings, ...)

Tire rolling resistance

Aerodynamic forces

Source: Michelin

Aerodynamics have limited influence on fuel consumption at lower speeds

speed

Vehic

le r

esis

tive forc

e (

%)

EU average

speed

India average

truck speed

Future Advances in Truck Technology

• Accelerate the diffusion of new truck technology into developing countries

within infrastructural, financial and market constraints.

• Displacement of 2nd hand truck purchases from developed countries with

indigenous production of freight vehicles

• Long vehicle life and lack of finance favours retrofitting of vehicles with

energy-saving and emission-reducing equipment

Telematics

real time fleet management

increased confidence in schedule for backloading

easing the impact of traffic congestion

monitoring of driver behaviour to promote and

embed eco-driving practices

Public Cost per tonne of CO2 saved: £8

Advice and Encouragement on Sustainable Logistics

Green Freight Europe (launched March (2012)

US Environmental

Protection Agency

UK Government: Freight Best Practice Programme

China Green Freight Initiative (April 2012)

Widening Responsibility for the Greening of Freight Transport

Logistics System Design

Vehicle Maintenance

Driving

Vehicle Loading

Vehicle Routing and Scheduling

Vehicle Design

Supply Chain Structure

Vehicle + equipment

manufacturers

Logistic service providers

Individual shippers

Supply chain partners

Government

Levels of Logistical Decision-making

STRATEGIC: numbers, locations and capacity of factories and warehouses

Restructuring of logistical systems

COMMERCIAL: trading links to suppliers, customers and sub-contractors

Reconfiguring supply chains

OPERATIONAL: scheduling of production and distribution operations

Rescheduling of freight flows

FUNCTIONAL: day-to-day management of the logistics function

Changes in the management of freight transport

Interaction between decisions at different level determines

volume of freight traffic and related externalities

Green measures implemented at lower levels offset by

effects of higher level strategic decisions

Euro / tonne of CO2 emitted0 50 100 150 200 250

Driver training in fuel efficient driving

Aerodynamic profiling of trucks

Application of computerised vehicle

routing

Hybridisation of delivery vans

Rail infrastructure investment

Major switch to localised sourcing

Decentralisation / relocation of

warehousing

Economic Appraisal of Green Freight / Logistics Measures

$ / tonne of pollutant emissions saved

Need more research on cost-effectiveness of Green Logistics measures

in both developed countries and emerging markets.

Availability of Freight Data to Monitor Impact of Freight Transport Policy

road rail waterway intermodal

Tonnes-lifted

Tonne-kms

Unit loads

Distance travelled

Average payload weight

Vehicle utilisation by weight

Vehicle utilisation by volume

% of empty running

Fuel efficiency

Carbon intensity of fuel

in some EU countries for most / all EU countries

• Much less freight data available in developing

countries

• Prevents macro-level analysis of the potential for

improving the environmental performance of freight

transport and the monitoring of trends

Conclusions

• Freight sector has already achieved large reduction in externalities per tonne-km

• Rate of tonne-km growth is exceeding rate of externality reduction per tonne-km

• Little prospect of significant tonne-km : GDP decoupling in emerging markets

• Broad array of mutually re-inforcing technological and behavioural options

• Need to adapt green logistics policies to the circumstances of developing countries

• Most eco-efficiency measures are self-financing often with short payback times

• Still significant ‘low hanging fruit’ to be harvested

• Need more data for the analysis of potential benefits and monitoring trends

Contact details

Kühne Logistics University – The KLU Wissenschaftliche Hochschule für Logistik und

Unternehmensführung Brooktorkai 20

20457 Hamburg

Tel.: +49 40 328707-271 Fax: +49 40 328707-109

E-Mail: alan.mckinnon@the-klu.org

Website: www.the-klu.org