eThekwini Municipality
Port Economic Decision Making Framework
Report: PEDMF 1.1_Present and Future Freight Flows and Risk
July 2008
Produced by a team coordinated by Conningarth Economists
PROJECT TEAM
Dr Dawie Mullins – Conningarth Economists – Team leader
Prof. Trevor Jones – University KwaZulu-Natal
Dr Jan Havenga – University of Stellenbosch
Dr Yolanda Fourie – Transport Research Associates
Mr Bernal Floor - Transport Research Associates
Mr Graham Muller – Graham Muller Associates
Mr Pieter Kruger – Techworld
Mr William Mullins – Conningarth Economists
Mr FX Jurgens – Development Bank of Southern Africa
PO Box 75 818, Lynnwood Ridge 0040, Pretoria, South
Africa
Tel: +27 (0)12 349 1915
Fax: +27 (0)12 349 1015
E-mail: [email protected]
ECONOMIC DEVELOPMENT UNIT OF THE ETHEKWINI MUNICIPALITY
REPORT DOCUMENTATION PAGE
This report contains confidential information and is for official use only.
1. RESPONSIBLE SECTION :
2. REPORT DATE:
ECONOMIC DEVELOPMENT UNIT July 2008
4: TITLE AND SUBTITLE:
PORT ECONOMIC DECISION MAKING FRAME WORK –
PRESENT AND FUTURE FREIGHT FLOWS AND RISKS
6: REPORT NO.:
PEDMF 1.1
8: REPORT STATUS:
FINAL DRAFT
3. REPORT TYPE:
TECHNICAL REPORT
5: AUTHOR(S):
Dr Jan Havenga
Graham Muller
Prof Trevor Jones
7: DISTRIBUTION:
PROJECT
IMPLEMENTATION UNIT
MEMBER
9: DATE OF SUBMISSION:
18 July 2008
STUDY TEAM: Approved for TEAM
____________________________
Dawie Mullins
Team Leader
_______________________
Dr Jan Havenga
Author
Approved for the Project Implementation Unit, eThekwini Municipality:
____________________________
Adrian Peters
Head of Engineering
_______________________
Trivi Arjunan
Economic Development Unit
PROJECT TEAM
Dr Dawie Mullins – Conningarth Economists – Team leader
Prof. Trevor Jones – University KwaZulu-Natal
Dr Jan Havenga – University of Stellenbosch
Dr Yolanda Fourie – Transport Research Associates
Mr Bernal Floor - Transport Research Associates
Mr Graham Muller – Graham Muller Associates
Mr Pieter Kruger – Techworld
Mr William Mullins – Conningarth Economists
Mr FX Jurgens – Development Bank of Southern Africa
i
TABLE OF CONTENTS
1
2
3
4
5
6
Introduction ................................................................................................................. 1
Methodology and National Perspective ...................................................................... 1
2.1
National Freight Flow Model.............................................................................. 2
2.2
Commodity Freight Demand Model ................................................................... 4
2.3
Imports and exports............................................................................................. 6
2.4
Container flows ................................................................................................... 8
The position of the eastern ports ................................................................................. 8
3.1
Hinterland volumes (The port of Durban in context) ......................................... 8
3.2
Understanding the Durban-Gauteng corridor (Natcor) in detail ....................... 11
Current Supply and demand, future demand and CHOICE Risks ............................ 15
4.1
Current volumes ................................................................................................ 15
4.2
Future Volumes ................................................................................................. 15
4.3
Options .............................................................................................................. 16
The risk to ethEkwini in terms of volumes ............................................................... 16
Conclusion ................................................................................................................ 22
ii
LIST OF TABLES
Table 1: The Effect on Road Volumes on the Durban-Gauteng Corridor given various
Port Switch Scenarios and Rail Market Share Targets
14
LIST OF FIGURES
Figure 1: The National Freight flow Model Methodology 2
Figure 2: Total Freight
3
Figure 3: Growth over the typologies 3
Figure 4: Freight Demand Model
4
Figure 5: Commodities as % of Total Weight now and forecasted 5
Figure 6: Higher Value Commodities as % of Total Weight now and forecasted 6
Figure 7: Expected Import/Export Growth for South Africa 7
Figure 8: Expected Import/Export and Local Supply and Demand for Durban and
Richards Bay 8
Figure 9: Metropolitan Freight volume Growth Rates for South Africa and the eThekwini
Metropolitan Area
9
Figure 10: Rural Freight Volume Growth Rates for South Africa and KZN 10
Figure 11: Corridor Freight Volume Growth Rates for South Africa and the Durban
Gauteng (Natcor) Corridor 10
Figure 12: The Freight Volume Relationship between the Durban-Gauteng Corridor and
the Port of Durban in 2006 11
Figure 13: The Forecasted Freight Volume Relationship between the Gauteng – Durban
Corridor and the Port of Durban in 2026
12
Figure 14: The Freight Volume Relationship between Richards Bay and the Port’s
Hinterland Corridor for 2006 14
Figure 15: The Freight Volume Relationship between Richards Bay and the Port’s
Hinterland Corridor for 2026 15
Figure 16: Import/Export Volumes for Eastern Ports in 2006
16
Figure 17: Import/Export Volumes for Eastern Ports in 2006 (Energy Related
Commodities Excluded)
17
Figure 18: The Character of Eastern Ports with Maximum Switch Scenario Considered in
2026 (Figure on the left without switch and to the right with switch)
17
Figure 19: Durban’s Specific Position in a Switch Scenario 18
Figure 20: Richards Bay’s Specific Position in a Switch Scenario 19
Figure 21: Import Commodities at risk in Durban 20
Figure 22: Export commodities at risk in Durban 21
iii
1
INTRODUCTION
The Port of Durban is a central point in South Africa’s freight network, providing the
primary economic connection between the country and its trading partners. It won the
race of the late nineteenth century between many southern African ports to become the
goldfields’ primary connection to the coast. Other than many other permanent
infrastructure decisions1 this precedence was not only driven by expedience, but by the
fact that the port is one of the few ports in sub-Saharan Africa that offers some natural
geographical protection.2
Over the last one and half century the Port of Durban has always grown in tandem with
South Africa’s economic growth and it attracted investment to achieve this naturally and
often without question. In recent times, however, questions about the sustainability of this
position have arisen. A few alternatives to expansion investment has been put forward,
each with its own advantages and disadvantages. Decisions of this kind should, however,
always be based on actual supply and demand information now and forecast into the
future.
Infrastructure problems are currently a common and often discussed issue in South
Africa, but few areas (such as telecommunications, energy and water) have such a poor
volume measurement history as the supply and demand for freight transport. This report
tables the findings of the latest research in this regard as well as including a brief
description of the methodology applied to generate current and future demand volumes. It
concludes by analysing traffic that could be at risk if a major alternative terminal were
built, especially in Richards Bay, and describes the position of Durban in such a case.
The ultimate goal is to analyse these options objectively in order to inform the eThekwini
Municipality of positioning options in this regard, especially around peripheral planning
and its effects.
2
METHODOLOGY AND NATIONAL PERSPECTIVE
The methodology used to establish current freight flows and future demand is based on
two distinct models that are used by the University of Stellenbosch. These are the
National Freight Flow Model and the Commodity Freight Demand Model.
1
Most freight network installations and the spatial organisation of South Africa are unrelated to natural
geographic factors such as rivers, mountains or arable land, but rather informed by the gold and diamond
rush, Anglo-Boer wars and politics. Even the port of Durban, that does provide some protection requires
significant ongoing engineering interventions
2
Most 1st world continents have broken coast lines and large river mouths, which are limited in subSaharan Africa, making ideal port sites a scarce and important resource
1
2.1
National Freight Flow Model
The national freight flow model utilises vehicle counting technology at various
permanent (398 stations) and secondary (430 stations) counting stations to model road
data. Actual rail data is used. The core methodology is depicted in Figure 1.
Figure 1: The National Freight flow Model Methodology
Step 1
Plot Traffic per
Route
Allocate Route
Sections to Metro,
Rural, Corridor
Verify with:
• Known flows
• Rail data
• Freight Demand Model
SANRAL Average
Daily Truck Traffic
Data
Determine Annual
Weight per Station
Consolidation of
data into corridor
and rural flows
Strategic interpretation
Short Medium Long
Truck Assumptions
(Weight, tons)
Step 2
Route Assumptions
(Distance, km)
Step 3
For road data the average daily truck traffic per short, medium and long truck route is
available. This is possible, because counting sensors can determine truck configuration
based on space between axles and profile height. Standard classification schemes that
provide information on carrying capacity made it possible to determine freight load per
truck. Corridor traffic is determined by the stabilisation of traffic counts in the middle of
a corridor on national routes away from normal production and consumption points. The
balance of stations is allocated to metropolitan and rural areas based on count size and
location. The freight load per truck multiplied by trucks counted is annualised, and the
results averaged for stations per corridor, metro and rural area to determine freight
volumes.
Actual rail data is used to determine rail freight flows. The railroad’s origin to
destination data is allocated to the same corridor, rural and metropolitan typologies as
used for road data. The model is then run for 1993, 1997, and then from 2003 annually,
with the last measurement in 2006. The overarching model results are depicted in figure
2.
2
Figure 2: Total Freight
2
6%
1.5
7%
Rail GFB
1
Export lines
0.5
Road
87%
0
1993
1997
2003
2004
2005
2006
The research therefore confirms that in the absence of intermodal traffic South Africa’s
rail system (which is bigger than the next four in Africa combined) is in serious decline
for the general freight mode. Total freight expanded by 71% with road expanding 87%.
The growth over the various typologies is illustrated in Figure 3:
Figure 3: Growth over the typologies
Bulk Mining
250
120
200
100
150
Road
Rail
100
50
Million Tons
Million Tons
Corridor Traffic
80
60
Rail
40
20
0
1993
1997
2003
2004
2005
0
2006
1993
1997
Year
2004
2005
2006
Year
Rural Traffic
Metropolitan Traffic
450
400
350
300
250
200
150
100
50
0
800
700
Road
Rail
Million Tons
Million Tons
2003
600
500
Road
Rail
400
300
200
100
1993
1997
2003
2004
Year
2005
2006
0
1993
1997
2003
2004
2005
2006
Year
3
The only rail growth was on ring-fenced export volumes that grew by about a third;
whilst rail based general freight business is in decline. Even worse, corridor freight, often
typified by break bulk domestically and container freight internationally is almost
exclusively carried by road. The important point in this regard is that current Transnet
management developed extensive plans to turn the situation around and is rolling out
comprehensive investment, strategic and business plans to this end. This is aimed at
turning the international intermodal situation around, establishing rail based domestic
intermodal flows and the linking of international port movements to organic growth in its
rail based intermodal market. This approach will therefore have an effect on decision
making, also as far as container port investments are concerned and will impact on all
logistics infrastructure planning such as ports, the ancillary and peripheral infrastructure
around ports, railway lines, roads and other terminals. Institutions such as metropolitan
governments and SANRAL will be affected.
2.2
Commodity Freight Demand Model
The Commodity Freight Demand model was developed for Transnet in 2006 and updated
in 2007. The model’s objective was to translate total flows into commodity flows and
develop a 20-year forecast. It was believed that forecasting on a commodity level will
provide better insight into transport infrastructure demand planning. The model approach
is depicted in Figure 4.
Figure 4: Freight Demand Model
Step 1
Step 2
Actual data – based
on publications and
personal interviews
Macro-economic
data
National I-O model
Macro-economic
forecast
Apportionment Supply and demand
per commodity on a
geographical basis
Commodity
forecasts
Verify with:
• Known flows
• Rail data
• National freight flow model
Allocation - Flows
per commodity
Consolidation of
data into corridor
and rural flows
Step 3
Strategic interpretation and
presentation of results
The model utilises the input-output model of the economy, disaggregated to 354
magisterial districts and translated from value to tons. Gravity modelling principles were
applied to determine flows for 28 commodity groups. Forecasting is done at a commodity
4
level, referenced independently and the top 28 commodities’ distribution, flow and
forecasts are independently researched and verified.
The model clearly illustrated that the dense corridors will grow by more than 100% over
the next 20 years that growth will occur faster in automotive, wood and chemical
products and very fast in most commodities that can be containerised. It highlighted the
specific nature of intermodal solutions and the size of container terminals that could be
developed and provides a platform from which container terminal placement could be
developed.
Figure 5 illustrates the relative growth in commodities over the next 20 years.
Figure 5: Commodities as % of Total Weight now and forecasted
TRANSPORT EQUIPMENT
METAL PRODUCTS EXCLUDING MACHINERY
MOTOR VEHICLE PARTS AND ACCESSORIES
MACHINERY AND EQUIPMENT
FERTILIZERS AND PESTICIDES
CHEMICAL & FERTILIZER MINERALS
MANGANESE
MAIZE
PAPER
NON-FERROUS METAL BASIC INDUSTRIES
INDUSTRIAL CHEMICALS
NON-METALLIC MINERAL PRODUCTS
BRICKS
BEVERAGES
PERISHABLES
OTHER BREAK BULK
WOOD
AUTOMOTIVE
CHROME
OTHER CHEMICALS
CEMENT
STEEL
SUGAR
CRUDE
LIMESTONE
PROCESSED FOODS
FUEL
OTHER DRY BULK
IRON ORE
STONE
COAL
0%
5%
10%
15%
20%
25%
30%
35%
40%
% of Total Freight
2026
2006
The three most volumous commodities are overpowering in such an illustration, but two
of these are largely low value export commodities with dedicated harbour terminals and
the third (stone) refers to extremely low value aggregate with a very high transport decay
factor.3 The harbours that support these commodities are primary economy harbours that
3
A transport decay factor refers to the extent that it is worthwhile to transport a commodity. High value
branded products, such as motor cars have a relatively low decay factor and extremely high valued
5
have to be designed with mass throughput of single commodities in mind (in order to
ensure global competitiveness).
With the next few commodities (Figure 6) transport decay factors are lower and higher
value exchanges in the economy appears (such as for steel, cement, chemicals and
automotive). Expected growth is high and multi-purpose and container terminals are
needed with significant industrial centres around them. This is how Durban harbour
developed. Growth in this sector of the economy in terms of imports/exports and
domestic volumes will be faster than in the primary economy.
Figure 6: Higher Value Commodities as % of Total Weight now and forecasted
TRANSPORT EQUIPMENT
METAL PRODUCTS EXCLUDING MACHINERY
MOTOR VEHICLE PARTS AND ACCESSORIES
MACHINERY AND EQUIPMENT
FERTILIZERS AND PESTICIDES
CHEMICAL & FERTILIZER MINERALS
MANGANESE
MAIZE
PAPER
NON-FERROUS METAL BASIC INDUSTRIES
INDUSTRIAL CHEMICALS
NON-METALLIC MINERAL PRODUCTS
BRICKS
BEVERAGES
PERISHABLES
OTHER BREAK BULK
WOOD
AUTOMOTIVE
CHROME
OTHER CHEMICALS
CEMENT
STEEL
SUGAR
CRUDE
LIMESTONE
PROCESSED FOODS
FUEL
OTHER DRY BULK
0%
1%
2%
3%
4%
5%
6%
% of Total Freight
2026
2.3
2006
Imports and exports
Import and export data, specifically, were obtained from official sources and translated
(in cases where this data is not available in weight format; value or units in some
instances) to weight data. This forms part of the supply and demand data discussed in
paragraph 2.2. Imports are seen as supply in the port of import and exports as demand at
commodities, such as gold and diamonds attract more or less no additional value from transportation. This
is not the case for sand, rubble, aggregate or other more or less limited use commodities
6
the port of export. The combined data set is therefore both separately and in integrated
format available for modelling purposes.
Figure 7 illustrates the growth in imports and exports that is expected for South Africa.
Figure 7: Expected Import/Export Growth for South Africa
300
250
200
Tons
('000 000)
Import
150
Export
100
50
0
2006
2011
2016
2021
2026
Figure 8 depicts export/import growth demand for the ports of Durban and Richards Bay.
These figures assume no shift in traffic and that the Port of Durban will fulfil its natural
historic role. In the graphs the difference between supply and imports is equal to local
production. This figure is high for Durban relative to Richards Bay. The difference
between demand and exports is equal to local consumption. This figure show that not
only is Richards Bay’s local consumption much lower, it is also unrelated to its exports.
It is therefore much more of a “tap” at the end of a long line, rather than a large industrial
centre. Durban is a genuine “terminal” port for general (now effectively containerised)
cargo, based on substantial cargo sources and sinks in the local economy. Richards Bay,
by contrast, is really not a genuine “terminal” port for general cargo at all, with the
exception of a few capitals intensive “enclaves” like Alusaf.
7
Figure 8: Expected Import/Export and Local Supply and Demand for Durban and
Richards Bay
Richards Bay
Durban
25
160
140
120
100
80
60
40
20
0
20
Import
15
Import
Supply
10
Supply
5
0
2006
2011
2016
2021
2006
2026
2011
2021
2026
Richards Bay
Durban
140
90
80
70
60
50
40
30
20
10
0
120
100
Export
80
Export
Demand
60
Demand
40
20
0
2006
2.4
2016
2011
2016
2021
2026
2006
2011
2016
2021
2026
Container flows
Container flows, specifically, are difficult to forecast and globally mistakes are made.
These are notoriously incorrect such as in the case of the port of Los Angeles where
container growth was forecast for 2007 whilst the port eventually experienced the first
decline in volumes in the last two decades.
Two methods are available to forecast containerised freight i.e. a forecast of the
underlying commodities (which will then need assumptions to approximate the weight
and contents of containers in order to translate the commodity data into container
volumes) or an econometric modelling method that forecasts container volumes only
(without regard of its contents). Neither method is perfect, but both are applied in the
forecasts and aligned, which is by far better than any other methodology available in the
world.
3
THE POSITION OF THE EASTERN PORTS
3.1 Hinterland volumes (The port of Durban in context)
In order to understand the Port of Durban’s positioning it is important to note that the port
as a systym that is not connected to its surrounding area has little value. The only
potential value in this regard would be as a relay or hub port in which case it would still
8
require services, but which it arguably could install for itself. Neither of the east coast
ports has a significant hub or relay role, although the enhancement of this position is most
certainly possible. In stead the east coast ports, and especially the Port of Durban, is
integrated into a complex freight system that serves a metropolitan area, rural hinterland
and corridor, especially to the industrial heartland of South Africa.
Metropolitan freight volume growth since 1993 compared to the total of all other
metropolitan areas in the country is shown in figure 9.
Figure 9: Metropolitan Freight volume Growth Rates for South Africa and the
eThekwini Metropolitan Area
2
16%
1.8
1.6
Total
eThekwini
1.4
eThekwini
Other metropolitan
1.2
1
84%
0.8
1993
1997
2003
2004
2005
2006
The eThekwini metropolitan area has grown slightly faster in terms of freight volumes
since 2003. This confirms that congestion, which is already a problem in all of South
Africa’s major centres, could be worse for eThekwini.
9
Rural freight volume growth is depicted in Figure 10.
Figure 10: Rural Freight Volume Growth Rates for South Africa and KZN
2.4
2.2
2
1.8
1.6
1.4
1.2
1
0.8
18%
T
K
KZN
Other rural
1993
1997
2003
2004
2005
2006
82%
The freight volume growth for rural KZN illustrates the industrialization of the province.
A significant portion of freight volumes is growing in the north east and could also play a
role in decision making around port growth positioning.
Figure 11: Corridor Freight Volume Growth Rates for South Africa and the
Durban Gauteng (Natcor) Corridor
1.6
1.5
16%
1.4
1.3
Total
Gauteng - Durban
1.2
1.1
Gauteng - Durban
1
Other corridor
0.9
0.8
1993
1997
2003
2004
2005
2006
84%
10
Corridor volumes according to the National Freight Flow Model4 (figure 11) eased in
2006 and have been growing slower than the rest of the country’s corridors. This growth
is, however, from an extremely high base. Industrialisation in South Africa is spreading5
to a degree, but the support infrastructure space is more readily available in the North and
West. In the East, even little growth from this high base contributes to congestion that has
probably already crossed the tipping point.6
3.2
Understanding the Durban-Gauteng corridor (Natcor) in detail
Critical congestion on the Durban-Gauteng corridor requires a more in depth
understanding. Figure 12 illustrates the relationship between the Port of Durban and the
Durban-Gauteng corridor.
Figure 12: The Freight Volume Relationship between the Durban-Gauteng
Corridor and the Port of Durban in 2006
The National Freight Flow Model’s methodology utilizes a “longer” view of the corridor (i.e. freight
needs to travel over a longer part of the corridor before it is classified as such). The Commodity Freight
Demand Model, with a “shorter” view does show some growth
5
Spreading in this context means moving to other centres, rather than fixating on Durban and Gauteng
6
The tipping point in this context refers to a point of rapid deterioration. Most systems grow or decline at
an even tempo, but at a point just before full capacity is reached or deterioration becomes critical, change is
rapid
4
11
Corridor
60
Port
50
Million tons
40
30
20
10
Switchable
(imports / exports
on corridor)
Imports / Exports
not on NATCOR
Imports & exports
Domestic corridor
traffic
Total corridor
0
Of the 43 million tons total freight on the corridor just less than 10 million tons of
imports and exports are transported on the corridor? This means that only 10 million tons
of imports and exports relates to the corridor and contributes only about 25% to the
congestion on it. It should be remembered, however, that a critical point of congestion on
this corridor has already been reached. More importantly a view of the future should be
considered as depicted in Figure 13:
Figure 13: The Forecasted Freight Volume Relationship between the Gauteng –
Durban Corridor and the Port of Durban in 2026
12
Corridor
140
Port
120
Million tons
100
80
60
40
20
Switchable
(imports / exports
on corridor)
Imports / Exports
not on NATCOR
Imports & exports
Domestic corridor
traffic
Total corridor
0
The less than 10 million import/export tons currently on the corridor could grow
significantly by the year 2026. A critical decision is therefore necessary that could be
considered in two parts and could indicate that a new approach to corridor infrastructure
would be required. Only 8 million tons of the current 43 million tons are on rail. Will the
corridor prepare for growth to where all possible traffic is switched out of the port or not
and what will rail market share be? These questions are analysed in Table 1:
13
Table 1: The Effect on Road Volumes on the Durban-Gauteng Corridor given
various Port Switch Scenarios and Rail Market Share Targets
Durban-Gauteng
road corridor traffic
[Million Tons]
2006
road corridor
traffic
Volumes
Rail maintains current
tonnage levels
Rail maintains current
market share (19.1%)
Rail grows market share
to 50%
Scenario 1 for 2026:
All possible traffic
switched out of the
port
Scenario 2 for 2026:
No traffic switched out
of the port
87
101
77
88
48
55
35
The figures in Table 1 leads to an inescapable conclusion, i.e. that Transnet decisions
around the port and railway infrastructure will have a profound impact on other
infrastructure, such as the road corridor. In fact, actions of Transnet can lead to a
differential of between 48 and 101 million tons road freight requirements.
The same analysis is possible for Richards Bay and the corridor hinterland relationship is
shown in figures 14 and 15.
Figure 14: The Freight Volume Relationship between Richards Bay and the Port’s
Hinterland Corridor for 2006
Corridor
120
Port
100
60
40
20
Switchable
(imports / exports
on corridor)
Imports / Exports
not on Corridor
Imports & exports
Domestic corridor
traffic
0
Total corridor
Million tons
80
14
Figure 15: The Freight Volume Relationship between Richards Bay and the Port’s
Hinterland Corridor for 2026
Corridor
180
Port
160
140
Million tons
120
100
80
60
40
20
Switchable
(imports / exports
on corridor)
Imports / Exports
not on Corridor
Imports & exports
Domestic corridor
traffic
Total corridor
0
Currently, and if the role of the Port of Richards Bay doesn’t change in future as well, the
Port of Richards Bay has little or no effect on the corridor infrastructure behind it.
4
4.1
CURRENT SUPPLY AND DEMAND, FUTURE DEMAND AND CHOICE
RISKS
Current volumes
Current volumes through the harbour and its supporting network of metropolitan, corridor
and rural infrastructure has been researched and is available by mode. This is the typical
supply and demand situation of the day. Modality choices inform current problems and
facilitate the generation of solutions.
4.2
Future Volumes
Volumes that could be expected in the future cannot be forecasted as supply and demand
as certain choices has not yet been made. SANRAL’s position is unknown, the
governments national freight master plan is not completed, Transnet decisions around
port infrastructure is not finalised and rail plans do not address the problem from a
national carrier perspective (as it is in competition with other modes). Demand can be
forecast, but to determine which modalities in terms of port infrastructure, supporting
infrastructure, rail and road are to be used in the future is not possible. Against this
background only scenarios can be proposed and in this report the specific scenario of an
import and export freight switch from Durban to Richards Bay is considered.
15
4.3
Options
Various options could be available. It would seem, however, as if an integrated decision
or decisions might not be what will happen. The delicate interplay between the
infrastructures that is directly involved in freight, in this case, the quays, terminals, roads
and railways are not necessarily considered. As these infrastructure becomes critically
congested this view might change. For the purpose of this report only one risk is
considered, i.e. the possible switch to Richards Bay of some traffic.
5
THE RISK TO ETHEKWINI IN TERMS OF VOLUMES
Understanding the possible switch of traffic requires an understanding of the underlying
commodities as the commodities in question and the hinterland (or local) origin or
destination of these commodities will determine to what extent a switch to Richards Bay
might be possible. Figure 16 depicts the commodities in question for each harbour for
2006.
100
90
80
70
60
50
40
30
20
10
-
RB
COAL MINING
CRUDE PETROLEUM &…
PETROLEUM REFINERIES …
WOOD AND WOOD …
OTHER DRY BULK
OTHER IRON AND STEEL …
OTHER MINING
OTHER BREAK BULK
CHEMICALS
MOTOR VEHICLES
FOOD AND FOOD …
CEMENT AND BRICKS
NON-FERROUS METAL …
EQUIPMENT
MANUFACTURED…
FERTILIZERS AND…
BEVERAGES
PERISHABLES
MOTOR VEHICLE PARTS …
GRAIN AND BEANS
Millions
Figure 16: Import/Export Volumes for Eastern Ports in 2006
DBN
Two dedicated commodities determine a core characteristic of each port, i.e. coal for
Richards Bay and fuel for Durban. No plans that will change this position are known. To
understand the picture the illustration is repeated, but without the three energy-related
commodities as shown in Figure 17.
16
GRAIN AND BEANS
MOTOR VEHICLE…
PERISHABLES
BEVERAGES
FERTILIZERS AND…
MANUFACTURED…
EQUIPMENT
NON-FERROUS METAL…
CEMENT AND BRICKS
FOOD AND FOOD …
MOTOR VEHICLES
CHEMICALS
OTHER BREAK BULK
OTHER MINING
OTHER IRON AND …
RB
OTHER DRY BULK
8
7
6
5
4
3
2
1
-
WOOD AND WOOD…
Millions
Figure 17: Import/Export Volumes for Eastern Ports in 2006 (Energy Related
Commodities Excluded)
DBN
Richards Bay is, by its nature and the commodities that are currently handled, more of a
port that serves the primary economy, compared to Durban which is more secondary
economy orientated. In a scenario where all traffic that possibly can switch, does, the
character of Richards Bay will change to handle a combination of freight from the
primary and secondary economies (Figure 18).
120
Millions
Millions
Figure 18: The Character of Eastern Ports with Maximum Switch Scenario
Considered in 2026 (Figure on the left without switch and to the right with switch)
100
80
100
80
60
40
120
60
RB
40
DBN
RB
DBN
20
20
-
-
Durban’s character will not really change (Figure 19) as far as the container terminal is
concerned, in fact it would be of the same size as now), but fuel might become an
overriding characteristic.
17
Millions
Figure 19: Durban’s Specific Position in a Switch Scenario
70
60
50
40
30
2006
20
2026
10
2026 Switched
-
18
The position for Richards Bay is somewhat different from Durban. It seems that the growth in activity around Richards Bay will mean
that the port will require a container terminal anyway. (Figure 20).
Millions
Figure 20: Richards Bay’s Specific Position in a Switch Scenario
120
100
80
60
2006
40
2026
20
2026 Switched
-
19
It is merely the size of the terminal that is in play which means that a cost benefit analysis should consider a wide variety of factors in
this case. This includes the industries that could be affected or should over time relocate. Affected commodities are depicted in figure
21.
Millions
Figure 21: Import Commodities at risk in Durban
10
9
8
7
6
5
4
2006
3
2026
2026 Switched
2
1
-
20
Millions
Figure 22: Export commodities at risk in Durban
8
7
6
5
4
3
2006
2026
2
2026 Switched
1
-
21
The risk analysis considered the position of industries in terms of freight origins and
destinations. Assuming that freight that originates and terminates far away or equidistant
from Durban and Richards Bay means that certain industries will be induced by lower
costs and shipping line movements (which in turn will also have to be induced to use an
alternative port) to switch. Many of these industries are also present in Durban and over
the medium term this will not change, but the risk is there that some of these industries
could relocate operations from Durban which will have an impact on Durban’s economy
and positioning in especially regarding the motor vehicle, steel, chemical and food
processing industries. Not all industries can, however, move. The important conundrum
here is that shipping lines will resist stopping in both ports, which means that significant
water or overland feeder traffic will arise between Durban and Richards Bay.
6
CONCLUSION
It was illustrated that the effect of Transnet decisions will be profound by showing that
road freight corridor volumes in two decades time on the Gauteng – Durban corridor
differs significantly depending on what Transnet might do. (In fact the maximum
difference is between 48 and 101 million tons). This is obviously also true for all other
ancillary infrastructure and it would seem as if integrated planning is not only a good idea
but a critical requirement in this regard.
The suggestion is, however, not only to induce Transnet to support institutions such as
the eThekwini Municipality and SANRAL through integrated planning in order to enable
these institutions to position better for the future. It is also for the municipality to support
Transnet better in aspects such as improving rail movements through Durban, intermodal
terminal positioning and effective support infrastructure.
22