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Energy consumption in transport in Great Britain: Macro level estimates
Transpn. Res.-A. Vol. 29A, No. I, pp. 21-32, 1995 Copyright 0 1994 Elsevier Science Ltd
Pergamon
Printed in Great Britain. All rights reserved 0965-8X4/95 19.50 + .OO
ENERGY CONSUMPTION BRITAIN: MACRO DAVID
IN TRANSPORT IN GREAT LEVEL ESTIMATES BANISTER
Planning and Development Research Centre, The Bartlett, University College London, London WClH OQB, U.K. CHRIS BANISTER Department of Planning and Landscape, University of Manchester, Manchester Ml3 9PL, U.K. (Received 30 May 1993)
Abstract-Transport has continued to increase its consumption of nonrenewable energy resources and to emit substantial levels of pollutants despite various attempts to limit that growth. This paper takes the two main sources of national travel data from Great Britain and subjects it to a comprehensive transport and energy-based analysis to establish the links between travel patterns, vehicle occupancy, modes used, and settlement type. The empirical evidence is presented together with interpretations on key factors in the linkages between transport and settlement patterns. Energy efficiency in transport could be increased substantially through higher vehicle occupancy levels, but as trips have become more frequent, dispersed, and longer, this option may be limited. This conclusion needs to be further researched together with the changes in demographic,work, and settlementpatternsall of whichare likely to compound the trends toward a continuation of the growth patterns in energy consumption in transport.
1. CONTEXT
Renewed interest has arisen in sustainable patterns of urban development and the relationship between energy consumption and land use. The focus on energy use is important because it is primarily a nonrenewable resource and because of its contribution to environmental pollution and global warming. Transport is a major contributor to that picture. As with other developed economies carbon emissions from fossil fuels in the United Kingdom is above the world average (1.08 tonnes per person) at 2.73 tonnes per person. Road transport makes a significant contribution to carbon monoxide, hydrocarbons, nitrogen oxides, and carbon dioxide emissions (Table 1) and in each case there has been a marked increase in the trends over the last decade. If one examines the trends in energy consumption in transport over the same period the same conclusions can be drawn (Table 2), namely that all the trends point toward increased energy depletion and more environmental pollution. Transport’s share of primary energy consumption is now 25.5% (in 1980 it was 20.3%) and the growth within the transport sector was over 35.8% with the most notable increases being in energy use for road and air transport (both nearly 40%). The picture is not one of an environmentally concerned transport system, but one in which all the trends are in the wrong direction. The notion of sustainability is a slippery one, particularly when one attempts to define it precisely. Catalogues of definitions have been presented (Prezzy, 1989; Breheny, 1990), but as yet there is no generally applicable or acceptable form. Breheny (1990) concluded that much greater care is required in assessing the role that cities play in consuming and degrading natural resources, and promoted the idea of a city as a resource and that it should be subjected to the rigorous “development-sustainable development-conditions-intergenerational-equity examination.” Cities, as with transport, are both consumers of resource and producers of pollution and environmental degradation. However, the city itself is a resource and produces wealth, culture, innovation, and education which in turn sustains much of modern eco21
D. BANISTERand C. BANISTER
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Table 1. Emission of pollutants from road vehicles 1978-1988
Pollutants
From Road Vehicles % Increase 1981-1990
Road Proportion of All Emission Sources
+42 f85 +13 +71 +44 -67
90% 46% 41% 51% 19%
Carbon Monoxide Black Smoke Volatile Organic Compounds Nitrogen Oxides Carbon Dioxide Lead
Effects Morbidity, Fertility Toxic Trace Substances Acid Rain Global Warming Mental Development
Source: Department of Transport (1992) Transport Statistics Great Britain 1992, HMSO: London, Tables 2.5 and 2.6.
nomic, social, and cultural life. It is a question of balance between the environmental arguments and those necessary to maintain and improve standards of living. The use of nonrenewable energy sources, particularly the use of fossil fuels, makes a major contribution to global warming and acid rain (Table 1). The European Community has set a target of reducing greenhouse emissions back to their 1990 levels for the year 2000. The overall level of carbon dioxide emissions in the United Kingdom have remained stable over the last decade and so this target is not an ambitious one. Within that total, transport has increased its share from 14.7% (1981) to 20.6% (1990) with road transport accounting for over 90% of the total. Carbon dioxide emissions in other sectors (power stations: 43070,domestic: 17% and industrial: 29%) have all declined over the decade. The year 2000 target is likely to be achieved despite the expected growth in car ownership in the European Community from 379 cars per 1000 population (1990) to 450 cars per 1000 population (2000), and a similar growth in traffic. Transport’s contribution to carbon dioxide emissions will have increased to about 30% with compensating reductions in other sectors. The background is one of increasing demand for travel, particularly by road and air, greater levels of car ownership and longer trip distances. Technological changes may make vehicles more efficient but the net effect is likely to be greater energy consumption as the function and form of cities changes, as people’s travel patterns become more oriented toward leisure activities, and as more and longer trips are made as national economies become more globalised. This paper presents a macro level analysis of travel and energy consumption and then relates each set of patterns to spatial factors. The data used is all from Great Britain. Calculations in Section 2 are based on data taken from the National Travel Survey (1985/86), the Primary Energy Consumption figures Hughes (1990), and figures from the Advisory Committee on Energy Conservation (1976). The distance travelled per person per week by type of area and the main mode of transport have been multiplied by energy
Table 2. Primary energy consumption in transport in Great Britain
All in TeraJoules (TJ) Rail Road Water Air All Transport All Energy
1980 78,554 1,246,547 56,544 234,927 1,616,572 7,972,871
crlo 4.9 77.1 3.5 14.5 20.3
1990 66,719 1,739,544 61,074 328,627 2,195,964 8,603,402
rrlo 3.0 79.2 2.8 15.0 25.5
Change 1980-1990 -15.1% + 39.5% -8.0% + 39.9% + 35.8% +7.9qo
For electricity, an attempt has been made to account for energy lost in generation and distribution. The overall thermal efficiency of power generation is about 3lqo (Department of Energy, 1990). There are further losses in transmission to electrically operated transport vehicles which it is thought to reduce the overall efficiency levels down to 23% (Hughes, 1990); these losses have not been included. For petroleum, about 7% of energy in crude oil is consumed in the refining process. Source: Department of Transport (1991) Transport Statistics Great Britain 1991, London: HMSO. Table 2.2.
Energy consumption in Great Britain
23
consumption figures for the appropriate mode. This approach might be characterised as bottom up. Any conclusions reached should be treated with caution as they are all aggregated and do not take account of any local factors. The public transport figures would be increased if empty running was included, and the figures only cover the direct costs associated with each mode, not the indirect costs such as the construction of buildings and vehicles, track construction and maintenance, and other equipment costs. ACEC (1976) suggested that 30% should be added for car and the rail figure may be as high as 50%. The figures are based on current patterns of passenger travel demand at one point in time. No attempt has been made to assess energy consumption in the freight sector. Calculations in Section 3 are based on energy consumption figures for transport which are published on an annual basis by the Department of Transport (DOT, 1991). The 1991 edition gives consumption figures for each year between 1980 and 1990 by mode and fuel type. Data for travel by mode (measured in passenger kilometres (passkm) and tonne kilometres (tkm)) are also available in the same source. From these datasets it is possible to calculate figures for energy consumption by mode. This approach might best be characterised as being top down. Perhaps the biggest problem with the top down approach used in the analysis is that the data published by the Departments of Transport and Energy are not provided in sufficient detail. This inevitably means that assumptions need to be made to disaggregate the data sufficiently to obtain comparative figures. These assumptions are detailed later. To provide some analysis of the relationships between energy consumption and settlement patterns the various modal energy data have been applied to census travel to work data for the 403 local authority districts of England and Wales. This gives a very crude picture of the relationship between transport energy consumption and patterns of development. Again further assumptions have been needed in this analysis and are detailed in the paper. The relationships between land use and energy use have been explored elsewhere most notably by Rickaby and Steadman (1992). They use a land use, transport, and energy analysis model but in respect of theoretical configurations for towns as opposed to the existing towns which are studied here. 2. MACRO ANALYSIS
FROM THE NATIONAL
TRAVEL SURVEY
Table 3 gives a summary of the energy efficiency calculations for the National Travel Survey data (1985/86) by settlement size and for each of the main modes of transport used (Department of Transport, 1988). Some of the assumptions used and limitations of the analysis are noted at the bottom of Table 3. However, despite these limitations, certain clear messages come through: 1. The car is the dominant user of energy; 2. Occupancy rates are crucial to overall energy efficiency calculations for all modes; 3. Diesel is more efficient than petrol. Empirical studies for different types of vehicle suggest that 22% is the approximate difference (Redsell et al., 1988). Although it should be noted that some “lean burn” petrol engines, even with catalytic converters, now have fuel efficiencies approaching diesel engines; 4. Journey length distributions make the urban (>25,000) category the most efficient urban form; 5. To complement the transport assumptions, others need to be made on density, sufficiency, and containment to combine the land use factors with those on travel, but data problems preclude such an analysis at the aggregate level. Energy use as expected is dominated by the car with over 90% of all consumption attributed to this mode. Its dominance relates to its modal share of all trips (77%), its longer average journey length (8.66 miles for car drivers, 5.89 miles for noncar drivers and 7.5 miles overall), the assumption of 1.5 persons per car, and its higher basic energy consumption figure. Even if some compensation is made for improved efficiency of the
D. BANISTERand C. BANISTER
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Table 3. Simple energy efficiency and consumption calculations
MJ/Pass Mile
Transport Mode Car Petrol Adjusted* BR Electric LT Tube LT Bus Other Bus Minibus Bicycle Motorcycle Private Bus Other Private Walk > 1 mile
3.21 0.89 1.08 0.83 0.83 1.15 0.10 3.13 1.40 1.15 0.25
Total Car Proportion (To)
Urban >25,000
Intermediate 3,000-25,000
Rural <3,000
218.28 218.28 9.35 6.26 4.57 0.50 2.76 0.08 2.82 2.10 1.04 0.45
212.50 191.25 4.98 0.11
286.01 228.81 4.45
362.73 239.40 5.87 0.22
5.56 3.91 0.08 2.50 3.22 0.69 0.63
0.08 3.65 3.91 0.07 4.38 4.20 0.46 0.50
2.99 1.96 0.08 3.44 5.60 1.15 0.30
5.52 0.86 0.58 4.23 3.57 0.08 3.13 3.50 0.69 0.53
248.19 87.95
234.18 90.74
307.72 92.95
384.34 94.38
268.57 91.55
London
Overall 245.89
The calculations have been based on distance travelled per person per week and the primary energy
requirements (MJ per person per week: Hughes, 1990). *The figures in Row 2 give reduced values of energy consumption in non-London locations because of greater fuel efficiencies (ACEC, 1976): Rural = 66%. Intermediate = 80%, and Urban = 90% of the London level. ACEC (1976) quote two figures for car energy consumption: Rural = 3.20 MJ/ passenger mile and Urban = 4.96 MJ/passenger mile. The ratio of these two figures is about 66% and this the figure used here. The other two figures are interpolations between the rural and the London figure. The bus is assumed to be 33% full; LT Tube occupancy is assumed to be 33%; BR Electric suburban occupancy is 60% full: note that diesel suburban at the same occupancy level is 27Vo more costly and intercity is 43% more costly at the same occupancy levels; only walk and bicycle use renewable forms of energy and ail short walk trips (under 1 mile) are excluded from the aggregate analysis. This distorts travel patterns because those modes with naturally short journeys, e.g., walking and cycling, are under represented. In energy terms these shorter journeys are clearly likely to use less fossil fuel resource. Note, at this stage, the importance of walking as a main mode of transport. Walking is part of almost every trip it should be remembered and is thus not fully represented even in these data. Over a third of all trips are on foot (see Table 4).
Table 4. Main mode of travel for passenger trips Walk 34%
Pedal Cycle 2070
Car
Train
Bus
Other
51qo
2%
8%
3%
Note that no attempt has been made by the DOT to include an estimate for travel on foot thus for passenger transport the dominance of the car appears to be overwhelming.
car operating in less congested conditions (row 2 of Table 3), the overall picture is only marginally modified. Also note that outside of London, noncar energy consumption in transport is very similar at about 21.6 MJ per person per week; the figure for London is higher at 29.93 MJ per person per week and this may reflect a greater use of public transport and other forms of transport in the capital as well as the greater congestion experienced. Overall, the figures for the different area types do seem to be intuitively plausible in that there is a greater use of the car in rural areas and that urban energy consumption (settlements >25,000) is less than that for London. The reason for this is that the total travel distance per person per week is less, and the average trip length is also lower (Table 5). Journey length is closely correlated to mode with the more energy intensive modes being used for the longer journeys. The same assumptions have been used as in the previous calculations and it should again be noted that the figures are approximate. Short walk trips are also included (less than 1 mile). If these figures are now converted into Primary Energy Consumption (in MJ for each mode weighted by distance and importnnnn\ -‘- nverall view of the contribution that reductions in trip lengths and switches in
25
Energy consumption in Great Britain Table 5. Journey lengths by type of area
Total Journeys Total Distance Average Journey Length
London
Urban
13.6 98.5 1.24
13.1 88.9 6.19
Intermediate 12.9 109.4 8.48
Source: Department of Transport (1988)-distances
Rural
Overall
13.9 133.1 9.58
13.2 99.5 1.54
in miles.
modes can be obtained, and their relative importance in achieving energy saving objectives assessed (Table 6). Even though these figures are approximate, a series of ratios can be worked out for energy efficiency of modes for an average journey by the mode under consideration. The bicycle is the most efficient mode followed closely by walk. These two modes account for 39.5% of journeys but only 0.64% of the energy. The bus is the most efficient public transport mode being some three times as efficient as rail. The difference is mainly explained by the longer journey length of rail trips. Car and motorcycle are the least efficient modes using over 100 times the energy required for a walk or bicycle journey. Car accounts for 94% of the energy consumption to make 48.3% of the journeys. 3. MACRO ANALYSIS FROM THE CENSUS
These modal comparisons above show the energy consumption relationships between modes, but it is clear that they do not give a full picture particularly in terms of settlement Table 6. Travel distance by mode and energy consumption Travel Distance by Mode Distance
Walk
Bicycle
< 1 mile l-2 miles 2-3 miles 3-5 miles 5-10 miles 1O-25 miles > 25 miles
82% 42% 10% 2%
3% 4% 2% 2% 1%
M/C
2% 1%
Car
Bus
15% 40% 67% 13% 71% 86% 85%
14% 18% 18% 16% 7% 5%
Rail
Overall
3% 3% 5% 7% 10%
35% 17% 10% 14% 14% 7% 3%
Energy Use by Mode and Distance (MJ) < 1 mile 1-2 miles 2-3 miles 3-5 miles 5-10 miles 10-25 miles > 25 miles Total
359 268 63 28
5 10 5 11 11
351 329
718
42
680
843 3274 5377 13123 25953 33817 28649 111036
2% 374 837 610 712 436 3265
67 150 467 763 935 2382
1207 3848 5886 14500 27370 35292 30020 118123
Overall Energy Consumption per Journey Mode Walk Bicycle Motorcycle Car Bus Rail Total
Energy 718 42 680 111036 3265 2382 118123
Journeys
E/J in MJ
37.12% 2.35% 0.42% 48.32% 9.58% 2.21%
19.32 17.96 1617.16 2291.92 340.71 1077.51
100
1181.20
Note: The energy consumption figures are approximate as they relate to the midpoint of each distance range. This explains the difference in the car contribution of 91.5% in Table 3 and 94% in Table 6 despite short walk trips being included in the latter.
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D. BANISTERand C. BANISTER Table 7. Trips by journey purpose 1975/z
Journey Purpose To and from work Education Shopping & personal business Eating & drinking Entertainment & watching sport
22% 10% 28% 3% 4%
Journey Purpose In course of work Escort and other Social Daytrips & sport participation Holidays
1985/86
Journey Purpose To and from work Education related Escorting-education Other personal business Holidays, daytrips & other
19.3qo 7.3% 3.3% 12.8olo 7.4%
1975176
Journey Purpose
4% 5% 15% 7% 1% 1985186
In course of work Escorting-work Shopping Social & entertainment
2.8% 1.5% 21.7% 23.9%
Source: Department of Transport (1979 & 1988).
and land use patterns. The Census of Population comprehensively covers the country. Unfortunately, in terms of the analysis conducted here it has three significant drawbacks. The work reported here uses the 1981 Census as the 1991 Journey to Work data are not yet available. Second, the Census only deals with people and not goods movements. The third major drawback is that the census data is collected for a specific purpose which means that there are only certain kinds of statistics are available. In terms of travel and transport the census only deals in the journey to work and thus only covers about 19% of all trips (Table 7). Table 7 shows how the relative importance of the trip to and from work has declined but it should be noted that some definitions have changed. Small area statistics (SAS) and workplace and transport statistics for the 403 districts (local authorities) of England and Wales have been used as the spatial units. These data are all taken from a 10% sample of the full dataset but at a district level it is safe to ignore the sampling error created. For each of these areas the mode of travel to work and the length of work trips are given. To appreciate these data more fully Table 8 gives details of the range and overall mean values for the data that have been used. These data show a very wide variation that clearly will have an impact on energy consumption with the impact of the two sustainable transport modes (walking and cycling) being crucial. The variation in car travel is also going to have a major impact because this is the mode that has the highest level of energy consumption and load factor variations will also impact on energy consumption. Travel is usually defined in terms of passenger kilometres. The Census gives journey mode and banded journey lengths but it does not present tables for the two combined. The National Travel Survey (NTS) gives journeys by mode and length for all trip purposes
Table 8. The distribution of work trips census variable (1981) Census Variable Travel by car Travel by bus Travel by train Travel by motor bike Travel by pedal cycle Travel by foot Travel by other means Work at home Car load factor Trip less than 5 km Trip between 5 & 9 km Trip between 10 & 19 km Trip between 20 & 29 km Trip more than 30 km
Overall
Maximum
Minimum
51% 15% 6% 3% 4% 15% 2% 4% 1.3 56% 22% 14% 4% 4%
71% 40% 31% 11% 27% 52% 8% 20% 1.7 99% 43% 39% 24% 26%
11% 0% 0% 1% 0% 6% 1% 1% 1.1 29% 1% 0% 0% 0%
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Energy consumption in Great Britain Table 9. Travel in passenger kilometres by mode
Travel Travel Travel Travel Travel Travel Travel
by car by bus by train by motor bike by pedal cycle on foot by other means
Overall
Maximum
Minimum
13% 10% 6% 2% 2% 5% 3%
81% 23% 17% 6% 12% 60% 6%
23%
1% 0% 1Vo 0% 1% 3%
(see Section 2). Combining the census and NTS data is possible but assumptions need to be made. For example, the NTS uses mile distance bands whereas the Census uses kilometres. The following methodology was used. All journeys over 30 km were distributed by mode. Then the next distance band was distributed by mode, followed by subsequent distance bands down to the 5 to 10 km band. All residual trips by mode were then assumed to be less than 5 km. This method was felt to be appropriate because the majority of journeys are less than 5 km. Using this approach for each of the 403 districts travel (in pass km) by mode could be calculated. Table 9 shows these details. This distribution of travel for the journey to work can be compared to Table 10 which details overall travel by mode for 1980 and 1990. The importance of these passenger kilometre data is that fuel efficiencies can be applied to each mode. The map (Fig. 1) shows this distribution of fuel used per (one way) work trip for England and Wales. The data have been classified using a nested means approach and the distribution of the data are seen in the histogram that is attached to the map (Fig. 1). The values range from 1.8 MJ/trip to 44.5 MJ/trip with an overall average of 17 MJ/trip. The patterns are very distinct. The area of highest overall energy use is in Outer London and the areas surrounding the London metropolitan area (Rest of South East England or Roseland). Lower energy consumption is found in Inner London and in self contained large towns. Table 11 gives these details and includes definitions for the various subdivisions used. Even when data are grouped there are clearly still very wide variations. The commuter hinterland surrounding London has fuel use levels which are 150% higher than inner areas of London. Away from London levels of fuel use in the larger metropolitan areas are 25% higher than in the smaller, but no less dense, settlements outside the largest metropolitan areas. 4. INTERPRETATIONS
OF THE DATA
The primary requirements for an analysis of travel and energy consumption are for details of travel by purpose, mode, distance, and frequency of trips. Certain assumptions Table 10. Travel by mode Passenger (billions pass km)
1980
1990
VoChange
Rail Car Motorcycle Pedal cycle Buses & coaches Air
35 395 8 5 45 3
41 561 7 5 41 5
17.1 42.0 - 12.5 0.0 -8.9 70.0
Overall
491
660
34.4
Goods (billions tkm)
1980
1990
% Change
18 92 54 10 174
16 136 53 11 216
- 10.2 47.4 -3.0 8.9 23.1
Rail Road Water Pipeline (oil only) Overall
D. BANISTERand C. BANISTER
c; Fig . 1. Fuel used per work trip for the districts of England and Wales. Source: 1981 Census.
Table 11. Fuel used in work travel in MJ for various subdivisions of the country Inner London Boroughs 28 nonmetro districts with population density greater than 21 p/ha Metropolitan counties (excludes London) Wales (excluding Cardiff which is with 28 denser districts) Outer London Boroughs Rest of nonmetro England (excludes Roseland and 22 larger districts) Rest of South East England (excludes 5 denser districts)
10.3 10.6 13.2 16.4 18.6 21.2 26.0
Twenty-eight nonmetro districts are: Bath, Bristol, Cambridge (Roseland), Middlesborough, Derby, Exeter, Plymouth, Bournemouth, Cheltenham, Gloucester, Gosport (Roseland), Portsmouth (Roseland), Southampton (Roseland), Hereford, Worcester, Grimsby, Hull, Blackpool, Leicester, Oadby & Wigston, Lincoln, Norwich, York, Nottingham, Oxford (Roseland), Stoke, Ipswich, and Cardiff (Wales). Metropolitan counties are: Greater Manchester, Merseyside, South Yorkshire, Tyne & Wear, West Midlands, and West Yorkshire. Rest of South East England (Roseland) is: Bedfordshire, Berkshire, Buckinghamshire, Cambridgeshire, Essex, Hampshire, Hertfordshire, Kent, Oxfordshire, Surrey, and Sussex.
Energy consumption in Great Britain
29
have then been made on average energy consumption figures for different types of vehicle, together with comment on the robustness of those assumptions (Table 3), in particular the crucial importance of occupancy rates in determining energy consumption. All the data have been collected at one point in time and so represent a static view of both travel and energy consumption. Some of the data form a repeated cross section taken at several points in time, but even here it is difficult to interpret the changes that have taken place in between the survey points. Two different approaches have been adopted. One based on fuel consumption by vehicle type calculated from empirical and monitoring surveys (bottom up) and the other based on breaking down total energy consumption figures (top down). The results are remarkably consistent as detailed in Table 3. However, despite these limitations, certain conclusions can be drawn with respect to the data for Great Britain: 1. In the domestic passenger transport sector the car is the dominant mode accounting for 48% of journeys but over 90% of energy consumption. Conversely, walk and bicycle account for nearly 40% of journeys but under 1% of energy use. 2. The vehicle occupancy assumptions are important in determining energy consumption. Relatively small changes in car occupancy levels or in public transport occupancy levels significantly affect energy consumption figures per passenger mile. Energy use per vehicle is almost independent of the number of people travelling. Perhaps a more stable measure would be to give estimates of energy consumption per vehicle mile (i.e., with an assumed occupancy of one) Car Bus Rail (Super Sprinter Diesel)
4.82 MJ per car mile 20.72 MJ per bus mile 78.32 MJ per train mile
In terms of policy options, the area of greatest benefit would be through increasing vehicle occupancy, particularly the car but also in other modes. The evidence over the last decade points in the opposite direction with vehicle occupancy levels declining rather than improving (see No. 5 below). The possibility of persuading large numbers of people to leave their cars at home and to use public transport is unrealistic. Any significant savings in energy require large scale investment in public transport to provide the necessary infrastructure. For example, a saving of 10% in energy would require more than a five-fold increase in total public transport use. 3. Significant increases in energy consumption have taken place since the 1960s when mass car ownership became a reality and this is reflected in an increase of 37% in road energy consumption in the 1982-1991 period (Table 2). It seems likely that this growth will continue in line with the expected growth in car ownership and traffic over the next two decades, whether predictions are taken from the Department of Transport, the Department of Energy or from the European Commission Directorate General on Energy (all 1989). 4. The importance of the journey to work is declining and it now accounts for around 20% of all trips. This reduction is partly explained by the decline in work journeys as more complex work patterns evolve but more importantly due to. the growth in other activities, particularly leisure, social, and shopping activities. Almost all of the growth is in car based activities (Table 7). 5. There has been some compensation through improvements in the energy efficiency of vehicles and through road construction that may reduce the amount of inefficient running of vehicles caused by congestion at least in the short term. In the 198Os, there have been improvements in the energy efficiency of both rail operations and cars, but reductions in the energy efficiency of motorcycles and buses have taken place giving a net reduction in the energy efficiency for all modes of 5.5% in MJ per passenger/km (Tables 12 and 13). The primary explanation is the fall in occupancy rates and load factors, particularly for buses. Using the 1990 energy patterns, cars with >2.4 people in them are more energy efficient than rail, and the break even point for bus is a car
30
D. BANISTERand C. BANISTER Table 12. Relative fuel efficiency changes 1980 to 1990 Relative to Car
Passenger Transport in MJ/pass km 1980
1990
% Change
1980
1990
Rail Cars Motorcycles Buses & Coaches
1.90 2.24 1.19 0.65
1.44 2.03 1.73 1.29
-24.4 -9.1 44.8 99.4
- 15.3% 0.0% -46.8% -71.1%
Overall
2.05
1.94
-5.5
-8.5%
-29.1% 0.0% - 14.7% -36.2% -4.3%
Relative to Road
Goods Transport Rail Road Water
0.69 3.49 1.05
0.50 3.95 1.16
-21.6 13.3 11.3
-80.3% 0.0% - 70.0%
- 87.4% 0.0% - 70.6%
Overall
2.38
2.97
24.6%
-31.7%
- 24.9%
occupancy level of >2.7 persons. Policies to increase car occupancy rates would include (a) providing road space for high occupancy vehicles through the provision of special lanes or through the provision of preferential parking that is both cheap and convenient; (b) linking the charges made for road pricing to the car occupancy with cheaper rates for vehicles with passengers. 6. Overall however, it seems that lifestyles and trip patterns are becoming more complex and car oriented. There has been unprecedented growth in travel over the last decade and it could be argued that the transport system has been taking the strain. Family relations are becoming more varied with the diminished importance of the nuclear family and the growth in single parent families and young adults with no children. The workforce has expanded with part-time labour, job sharing, and increased female participation. More recently, these changes have been compounded by a stagnant housing market, high interest rates, and growing unemployment. The uncertainty in the economic situation may result in people not moving so frequently but adopting temporary patterns of travel to work and other activities, which in turn results in more and longer trips being made, principally by car (Banister & Bayliss, 1991). 7. However, as Gordon and Richardson (1989) emphasized, the pursuit of a single objective such as “minimising gasoline consumption makes no sense.” They quote Lowry who points out that “efficiency does not imply rearranging our lives to minimise transport costs. Rather it implies a search for a suitable balance between transport costs of compatibly configured land uses.” The complexity of the urban policy process requires the use of several policy levers (e.g., pricing, regulation, and taxation) to achieve a spatial structure that reflects the land, labour, and housing markets as well as the transport market. From the empirical data for Great Britain and the evidence cited from other sources, some tentative conclusions can be drawn on the relationships between transport and Table 13. Unit load factors
Passenger in Persons/Unit Rail Car Motorcycle Buses & Coaches Goods in t/unit Rail Goods Road Goods
1980
1990
% Change
89.2 1.8 1.0 12.8
96.6 1.7 1.1 a.7
8.3 -7.7 4.9 -31.8
336.5 2.0
329.2 2.1
-2.2 2.5
Note: load factors for water transport cannot be calculated. A transport unit refers to a single vehicle or complete train.
Energy consumption in Great Britain
31
energy and the importance of settlement patterns. At the general level it seems that travel distances and mix of activities should be reduced so that residential development can be related to local jobs and services not as a dormitory settlement (Owens, 1987). However, concentration of new development into smaller centres outside the urban area may save less fuel than concentrating that same level of development into the urban area itself. But fuel savings in developments outside the urban area are less costly because of reduced levels of traffic congestion and the greater availability of space (Rickaby, 1987). Notions of self containment are perhaps less valid in a highly mobile car oriented society as it would be impossible for any one town or city to have a complete range of activities. Even though many people may commute to another centre for employment, that settlement may still be relatively efficient if a range of other facilities and services are provided within walking or cycling distance. The large and isolated settlement would probably be more self contained than the small and isolated settlement, but a series of small free standing towns in close proximity to each other (and perhaps a major city) would probably be the most energy efficient form in a society that is dependent on the car for most travel. The free standing town (about 25,000) would have the shortest trip lengths, lowest door to door trip times, and a high proportion of facilities and services within walking and cycling distance (Banister, 1992). In related work carried out at the microlevel in a rural area of England (Banister, 1992), the largest and most energy efficient settlement is the most urban-it has the highest trip generation rate but the lowest energy consumption figures per trip and per person. This is because of the availability of good local services and facilities, local employment, good public transport, and a high proportion of walk trips, The National Travel Survey information has supported this conclusion (Table 3). This conclusion contradicts that reached by Newman and Kenworthy (1989) on density of development being the most important single determinant of energy consumption. The Census analysis suggests that relatively densely populated areas (District level densities above 21 persons per hectare) which are not part of a large conurbation use considerably less energy than most other locations. It seems that the physical characteristics of the urban settlement are important (size, availability of facilities and services, public transport), but that this basic relationship is modified both by the socioeconomic characteristics of the population (as different people have different propensities to travel with different frequencies, trip lengths, and modes) and by the location of the settlement in relation to other large urban areas. The EC’s notion of a compact city with greater diversity and people living close to their workplaces simplifies the complexity of lifestyles (Commission of the European Communities, 1990). A holistic view must encompass the full range of activities that people participate in. Many would argue that the car has improved their quality of life, the opportunities available to them, and the flexibility and independence which is offered by personal transport. The concept of the sustainable city goes beyond one which is energy efficient or transport efficient and explores the city as a place in which people want to live.
REFERENCES Advisory Committee on Energy Consumption (1976). Passenger transport: Short and medium term considerations. EnergyPaper 10, ACEC, Department of Energy, London: HMSO. Banister, D. and Bayliss, D. (1991, June). Structural changes in population and impacts on passenger transport demand. Paper presented at the European Conference of Ministers of Transport Round Table 88, Paris. Banister, D. (1992). Energy use, transport and settlement patterns, Breheny, M. J. (ed) Sustainable development and urban form. London: Pion, pp 160-181. Breheny, M. J. (1990, November). Strategic planning and urban sustainability. Paper presented to the Town and Country Planning Association Conference on Planning for Sustainable Development, London. Commission of the European Communities (1990). Green Paper on the urban environment. Brussels EUR 12902. Department of Energy (1989). Energy use and energy efficiency in UK transport to the year 2010. London: HMSO. Department of the Environment (1990). This common inheritance: Britain’s environmental strategy. London: HMSO. TR(A) 29:1-C
32
D. BANISTERand C. BANISTER
Department of Transport (1979). National travelsurvey 1975/76 report. London: HMSO. Department of Transport (1988).National travel survey 1985/86 report. London: HMSO. Department of Transport (1989).National road trrlfficforecasts (Great Britain) 1989. London: HMSO. Department of Transport (l!Wl).Transport statistics Great Britain 1991. London: HMSO. Department of Transport (1992). Transport statistics Great Britain 1992. London: HMSO. European Commission DG for Energy (1989, September). Mqior themes in energy: Energy in Europe. Brussels. Gordon, P. and Richardson, H. W. (1989). Gasoline consumption and cities: A reply. J. American Prclnning Assoc. S(3), pp. 342-346. Hughes, P. (1990, January). Transport emissions and the greenhouse effect. Paper presented to the Universities Transport Studies Group Conference. Newman, P. W. G. and Kenworthy, J. R. (1989). Gasoline consumption and cities: A comparison of U.S. cities with a global survey. J. American Planning Assoc. 55(l), 24-37. Owens, S. (1987). The urban futures: Does energy really matter? In Hawkes, D., Owens, J.. Rickaby, P.. and Steadman, P. (eds), Energy and urban builtform. London: Butterworths; pp. 169-189. Prezxy, J. (1989, August). Definitions of sustainability. UKCEED, Discussion Paper 9. Redsell, M., Lucas, G., and Ashford. N. (1988). Comparison of on roadfuelconsumption for diesetandpetrol cars. Transport and Road Research Laboratory, Crowthorne. Rickaby, P. (1987). Six settlement patterns compared. Environment and Planning B M(3), 193423. Rickaby, P. and Steadman, P. (1992). Patterns of land use in English towns: Implications for energy use and carbon dioxide emissions. Breheny, M. J. (ed) Sustainable development and urban form. London: Pion, 182-l%.
Pergamon
Printed in Great Britain. All rights reserved 0965-8X4/95 19.50 + .OO
ENERGY CONSUMPTION BRITAIN: MACRO DAVID
IN TRANSPORT IN GREAT LEVEL ESTIMATES BANISTER
Planning and Development Research Centre, The Bartlett, University College London, London WClH OQB, U.K. CHRIS BANISTER Department of Planning and Landscape, University of Manchester, Manchester Ml3 9PL, U.K. (Received 30 May 1993)
Abstract-Transport has continued to increase its consumption of nonrenewable energy resources and to emit substantial levels of pollutants despite various attempts to limit that growth. This paper takes the two main sources of national travel data from Great Britain and subjects it to a comprehensive transport and energy-based analysis to establish the links between travel patterns, vehicle occupancy, modes used, and settlement type. The empirical evidence is presented together with interpretations on key factors in the linkages between transport and settlement patterns. Energy efficiency in transport could be increased substantially through higher vehicle occupancy levels, but as trips have become more frequent, dispersed, and longer, this option may be limited. This conclusion needs to be further researched together with the changes in demographic,work, and settlementpatternsall of whichare likely to compound the trends toward a continuation of the growth patterns in energy consumption in transport.
1. CONTEXT
Renewed interest has arisen in sustainable patterns of urban development and the relationship between energy consumption and land use. The focus on energy use is important because it is primarily a nonrenewable resource and because of its contribution to environmental pollution and global warming. Transport is a major contributor to that picture. As with other developed economies carbon emissions from fossil fuels in the United Kingdom is above the world average (1.08 tonnes per person) at 2.73 tonnes per person. Road transport makes a significant contribution to carbon monoxide, hydrocarbons, nitrogen oxides, and carbon dioxide emissions (Table 1) and in each case there has been a marked increase in the trends over the last decade. If one examines the trends in energy consumption in transport over the same period the same conclusions can be drawn (Table 2), namely that all the trends point toward increased energy depletion and more environmental pollution. Transport’s share of primary energy consumption is now 25.5% (in 1980 it was 20.3%) and the growth within the transport sector was over 35.8% with the most notable increases being in energy use for road and air transport (both nearly 40%). The picture is not one of an environmentally concerned transport system, but one in which all the trends are in the wrong direction. The notion of sustainability is a slippery one, particularly when one attempts to define it precisely. Catalogues of definitions have been presented (Prezzy, 1989; Breheny, 1990), but as yet there is no generally applicable or acceptable form. Breheny (1990) concluded that much greater care is required in assessing the role that cities play in consuming and degrading natural resources, and promoted the idea of a city as a resource and that it should be subjected to the rigorous “development-sustainable development-conditions-intergenerational-equity examination.” Cities, as with transport, are both consumers of resource and producers of pollution and environmental degradation. However, the city itself is a resource and produces wealth, culture, innovation, and education which in turn sustains much of modern eco21
D. BANISTERand C. BANISTER
22
Table 1. Emission of pollutants from road vehicles 1978-1988
Pollutants
From Road Vehicles % Increase 1981-1990
Road Proportion of All Emission Sources
+42 f85 +13 +71 +44 -67
90% 46% 41% 51% 19%
Carbon Monoxide Black Smoke Volatile Organic Compounds Nitrogen Oxides Carbon Dioxide Lead
Effects Morbidity, Fertility Toxic Trace Substances Acid Rain Global Warming Mental Development
Source: Department of Transport (1992) Transport Statistics Great Britain 1992, HMSO: London, Tables 2.5 and 2.6.
nomic, social, and cultural life. It is a question of balance between the environmental arguments and those necessary to maintain and improve standards of living. The use of nonrenewable energy sources, particularly the use of fossil fuels, makes a major contribution to global warming and acid rain (Table 1). The European Community has set a target of reducing greenhouse emissions back to their 1990 levels for the year 2000. The overall level of carbon dioxide emissions in the United Kingdom have remained stable over the last decade and so this target is not an ambitious one. Within that total, transport has increased its share from 14.7% (1981) to 20.6% (1990) with road transport accounting for over 90% of the total. Carbon dioxide emissions in other sectors (power stations: 43070,domestic: 17% and industrial: 29%) have all declined over the decade. The year 2000 target is likely to be achieved despite the expected growth in car ownership in the European Community from 379 cars per 1000 population (1990) to 450 cars per 1000 population (2000), and a similar growth in traffic. Transport’s contribution to carbon dioxide emissions will have increased to about 30% with compensating reductions in other sectors. The background is one of increasing demand for travel, particularly by road and air, greater levels of car ownership and longer trip distances. Technological changes may make vehicles more efficient but the net effect is likely to be greater energy consumption as the function and form of cities changes, as people’s travel patterns become more oriented toward leisure activities, and as more and longer trips are made as national economies become more globalised. This paper presents a macro level analysis of travel and energy consumption and then relates each set of patterns to spatial factors. The data used is all from Great Britain. Calculations in Section 2 are based on data taken from the National Travel Survey (1985/86), the Primary Energy Consumption figures Hughes (1990), and figures from the Advisory Committee on Energy Conservation (1976). The distance travelled per person per week by type of area and the main mode of transport have been multiplied by energy
Table 2. Primary energy consumption in transport in Great Britain
All in TeraJoules (TJ) Rail Road Water Air All Transport All Energy
1980 78,554 1,246,547 56,544 234,927 1,616,572 7,972,871
crlo 4.9 77.1 3.5 14.5 20.3
1990 66,719 1,739,544 61,074 328,627 2,195,964 8,603,402
rrlo 3.0 79.2 2.8 15.0 25.5
Change 1980-1990 -15.1% + 39.5% -8.0% + 39.9% + 35.8% +7.9qo
For electricity, an attempt has been made to account for energy lost in generation and distribution. The overall thermal efficiency of power generation is about 3lqo (Department of Energy, 1990). There are further losses in transmission to electrically operated transport vehicles which it is thought to reduce the overall efficiency levels down to 23% (Hughes, 1990); these losses have not been included. For petroleum, about 7% of energy in crude oil is consumed in the refining process. Source: Department of Transport (1991) Transport Statistics Great Britain 1991, London: HMSO. Table 2.2.
Energy consumption in Great Britain
23
consumption figures for the appropriate mode. This approach might be characterised as bottom up. Any conclusions reached should be treated with caution as they are all aggregated and do not take account of any local factors. The public transport figures would be increased if empty running was included, and the figures only cover the direct costs associated with each mode, not the indirect costs such as the construction of buildings and vehicles, track construction and maintenance, and other equipment costs. ACEC (1976) suggested that 30% should be added for car and the rail figure may be as high as 50%. The figures are based on current patterns of passenger travel demand at one point in time. No attempt has been made to assess energy consumption in the freight sector. Calculations in Section 3 are based on energy consumption figures for transport which are published on an annual basis by the Department of Transport (DOT, 1991). The 1991 edition gives consumption figures for each year between 1980 and 1990 by mode and fuel type. Data for travel by mode (measured in passenger kilometres (passkm) and tonne kilometres (tkm)) are also available in the same source. From these datasets it is possible to calculate figures for energy consumption by mode. This approach might best be characterised as being top down. Perhaps the biggest problem with the top down approach used in the analysis is that the data published by the Departments of Transport and Energy are not provided in sufficient detail. This inevitably means that assumptions need to be made to disaggregate the data sufficiently to obtain comparative figures. These assumptions are detailed later. To provide some analysis of the relationships between energy consumption and settlement patterns the various modal energy data have been applied to census travel to work data for the 403 local authority districts of England and Wales. This gives a very crude picture of the relationship between transport energy consumption and patterns of development. Again further assumptions have been needed in this analysis and are detailed in the paper. The relationships between land use and energy use have been explored elsewhere most notably by Rickaby and Steadman (1992). They use a land use, transport, and energy analysis model but in respect of theoretical configurations for towns as opposed to the existing towns which are studied here. 2. MACRO ANALYSIS
FROM THE NATIONAL
TRAVEL SURVEY
Table 3 gives a summary of the energy efficiency calculations for the National Travel Survey data (1985/86) by settlement size and for each of the main modes of transport used (Department of Transport, 1988). Some of the assumptions used and limitations of the analysis are noted at the bottom of Table 3. However, despite these limitations, certain clear messages come through: 1. The car is the dominant user of energy; 2. Occupancy rates are crucial to overall energy efficiency calculations for all modes; 3. Diesel is more efficient than petrol. Empirical studies for different types of vehicle suggest that 22% is the approximate difference (Redsell et al., 1988). Although it should be noted that some “lean burn” petrol engines, even with catalytic converters, now have fuel efficiencies approaching diesel engines; 4. Journey length distributions make the urban (>25,000) category the most efficient urban form; 5. To complement the transport assumptions, others need to be made on density, sufficiency, and containment to combine the land use factors with those on travel, but data problems preclude such an analysis at the aggregate level. Energy use as expected is dominated by the car with over 90% of all consumption attributed to this mode. Its dominance relates to its modal share of all trips (77%), its longer average journey length (8.66 miles for car drivers, 5.89 miles for noncar drivers and 7.5 miles overall), the assumption of 1.5 persons per car, and its higher basic energy consumption figure. Even if some compensation is made for improved efficiency of the
D. BANISTERand C. BANISTER
24
Table 3. Simple energy efficiency and consumption calculations
MJ/Pass Mile
Transport Mode Car Petrol Adjusted* BR Electric LT Tube LT Bus Other Bus Minibus Bicycle Motorcycle Private Bus Other Private Walk > 1 mile
3.21 0.89 1.08 0.83 0.83 1.15 0.10 3.13 1.40 1.15 0.25
Total Car Proportion (To)
Urban >25,000
Intermediate 3,000-25,000
Rural <3,000
218.28 218.28 9.35 6.26 4.57 0.50 2.76 0.08 2.82 2.10 1.04 0.45
212.50 191.25 4.98 0.11
286.01 228.81 4.45
362.73 239.40 5.87 0.22
5.56 3.91 0.08 2.50 3.22 0.69 0.63
0.08 3.65 3.91 0.07 4.38 4.20 0.46 0.50
2.99 1.96 0.08 3.44 5.60 1.15 0.30
5.52 0.86 0.58 4.23 3.57 0.08 3.13 3.50 0.69 0.53
248.19 87.95
234.18 90.74
307.72 92.95
384.34 94.38
268.57 91.55
London
Overall 245.89
The calculations have been based on distance travelled per person per week and the primary energy
requirements (MJ per person per week: Hughes, 1990). *The figures in Row 2 give reduced values of energy consumption in non-London locations because of greater fuel efficiencies (ACEC, 1976): Rural = 66%. Intermediate = 80%, and Urban = 90% of the London level. ACEC (1976) quote two figures for car energy consumption: Rural = 3.20 MJ/ passenger mile and Urban = 4.96 MJ/passenger mile. The ratio of these two figures is about 66% and this the figure used here. The other two figures are interpolations between the rural and the London figure. The bus is assumed to be 33% full; LT Tube occupancy is assumed to be 33%; BR Electric suburban occupancy is 60% full: note that diesel suburban at the same occupancy level is 27Vo more costly and intercity is 43% more costly at the same occupancy levels; only walk and bicycle use renewable forms of energy and ail short walk trips (under 1 mile) are excluded from the aggregate analysis. This distorts travel patterns because those modes with naturally short journeys, e.g., walking and cycling, are under represented. In energy terms these shorter journeys are clearly likely to use less fossil fuel resource. Note, at this stage, the importance of walking as a main mode of transport. Walking is part of almost every trip it should be remembered and is thus not fully represented even in these data. Over a third of all trips are on foot (see Table 4).
Table 4. Main mode of travel for passenger trips Walk 34%
Pedal Cycle 2070
Car
Train
Bus
Other
51qo
2%
8%
3%
Note that no attempt has been made by the DOT to include an estimate for travel on foot thus for passenger transport the dominance of the car appears to be overwhelming.
car operating in less congested conditions (row 2 of Table 3), the overall picture is only marginally modified. Also note that outside of London, noncar energy consumption in transport is very similar at about 21.6 MJ per person per week; the figure for London is higher at 29.93 MJ per person per week and this may reflect a greater use of public transport and other forms of transport in the capital as well as the greater congestion experienced. Overall, the figures for the different area types do seem to be intuitively plausible in that there is a greater use of the car in rural areas and that urban energy consumption (settlements >25,000) is less than that for London. The reason for this is that the total travel distance per person per week is less, and the average trip length is also lower (Table 5). Journey length is closely correlated to mode with the more energy intensive modes being used for the longer journeys. The same assumptions have been used as in the previous calculations and it should again be noted that the figures are approximate. Short walk trips are also included (less than 1 mile). If these figures are now converted into Primary Energy Consumption (in MJ for each mode weighted by distance and importnnnn\ -‘- nverall view of the contribution that reductions in trip lengths and switches in
25
Energy consumption in Great Britain Table 5. Journey lengths by type of area
Total Journeys Total Distance Average Journey Length
London
Urban
13.6 98.5 1.24
13.1 88.9 6.19
Intermediate 12.9 109.4 8.48
Source: Department of Transport (1988)-distances
Rural
Overall
13.9 133.1 9.58
13.2 99.5 1.54
in miles.
modes can be obtained, and their relative importance in achieving energy saving objectives assessed (Table 6). Even though these figures are approximate, a series of ratios can be worked out for energy efficiency of modes for an average journey by the mode under consideration. The bicycle is the most efficient mode followed closely by walk. These two modes account for 39.5% of journeys but only 0.64% of the energy. The bus is the most efficient public transport mode being some three times as efficient as rail. The difference is mainly explained by the longer journey length of rail trips. Car and motorcycle are the least efficient modes using over 100 times the energy required for a walk or bicycle journey. Car accounts for 94% of the energy consumption to make 48.3% of the journeys. 3. MACRO ANALYSIS FROM THE CENSUS
These modal comparisons above show the energy consumption relationships between modes, but it is clear that they do not give a full picture particularly in terms of settlement Table 6. Travel distance by mode and energy consumption Travel Distance by Mode Distance
Walk
Bicycle
< 1 mile l-2 miles 2-3 miles 3-5 miles 5-10 miles 1O-25 miles > 25 miles
82% 42% 10% 2%
3% 4% 2% 2% 1%
M/C
2% 1%
Car
Bus
15% 40% 67% 13% 71% 86% 85%
14% 18% 18% 16% 7% 5%
Rail
Overall
3% 3% 5% 7% 10%
35% 17% 10% 14% 14% 7% 3%
Energy Use by Mode and Distance (MJ) < 1 mile 1-2 miles 2-3 miles 3-5 miles 5-10 miles 10-25 miles > 25 miles Total
359 268 63 28
5 10 5 11 11
351 329
718
42
680
843 3274 5377 13123 25953 33817 28649 111036
2% 374 837 610 712 436 3265
67 150 467 763 935 2382
1207 3848 5886 14500 27370 35292 30020 118123
Overall Energy Consumption per Journey Mode Walk Bicycle Motorcycle Car Bus Rail Total
Energy 718 42 680 111036 3265 2382 118123
Journeys
E/J in MJ
37.12% 2.35% 0.42% 48.32% 9.58% 2.21%
19.32 17.96 1617.16 2291.92 340.71 1077.51
100
1181.20
Note: The energy consumption figures are approximate as they relate to the midpoint of each distance range. This explains the difference in the car contribution of 91.5% in Table 3 and 94% in Table 6 despite short walk trips being included in the latter.
26
D. BANISTERand C. BANISTER Table 7. Trips by journey purpose 1975/z
Journey Purpose To and from work Education Shopping & personal business Eating & drinking Entertainment & watching sport
22% 10% 28% 3% 4%
Journey Purpose In course of work Escort and other Social Daytrips & sport participation Holidays
1985/86
Journey Purpose To and from work Education related Escorting-education Other personal business Holidays, daytrips & other
19.3qo 7.3% 3.3% 12.8olo 7.4%
1975176
Journey Purpose
4% 5% 15% 7% 1% 1985186
In course of work Escorting-work Shopping Social & entertainment
2.8% 1.5% 21.7% 23.9%
Source: Department of Transport (1979 & 1988).
and land use patterns. The Census of Population comprehensively covers the country. Unfortunately, in terms of the analysis conducted here it has three significant drawbacks. The work reported here uses the 1981 Census as the 1991 Journey to Work data are not yet available. Second, the Census only deals with people and not goods movements. The third major drawback is that the census data is collected for a specific purpose which means that there are only certain kinds of statistics are available. In terms of travel and transport the census only deals in the journey to work and thus only covers about 19% of all trips (Table 7). Table 7 shows how the relative importance of the trip to and from work has declined but it should be noted that some definitions have changed. Small area statistics (SAS) and workplace and transport statistics for the 403 districts (local authorities) of England and Wales have been used as the spatial units. These data are all taken from a 10% sample of the full dataset but at a district level it is safe to ignore the sampling error created. For each of these areas the mode of travel to work and the length of work trips are given. To appreciate these data more fully Table 8 gives details of the range and overall mean values for the data that have been used. These data show a very wide variation that clearly will have an impact on energy consumption with the impact of the two sustainable transport modes (walking and cycling) being crucial. The variation in car travel is also going to have a major impact because this is the mode that has the highest level of energy consumption and load factor variations will also impact on energy consumption. Travel is usually defined in terms of passenger kilometres. The Census gives journey mode and banded journey lengths but it does not present tables for the two combined. The National Travel Survey (NTS) gives journeys by mode and length for all trip purposes
Table 8. The distribution of work trips census variable (1981) Census Variable Travel by car Travel by bus Travel by train Travel by motor bike Travel by pedal cycle Travel by foot Travel by other means Work at home Car load factor Trip less than 5 km Trip between 5 & 9 km Trip between 10 & 19 km Trip between 20 & 29 km Trip more than 30 km
Overall
Maximum
Minimum
51% 15% 6% 3% 4% 15% 2% 4% 1.3 56% 22% 14% 4% 4%
71% 40% 31% 11% 27% 52% 8% 20% 1.7 99% 43% 39% 24% 26%
11% 0% 0% 1% 0% 6% 1% 1% 1.1 29% 1% 0% 0% 0%
27
Energy consumption in Great Britain Table 9. Travel in passenger kilometres by mode
Travel Travel Travel Travel Travel Travel Travel
by car by bus by train by motor bike by pedal cycle on foot by other means
Overall
Maximum
Minimum
13% 10% 6% 2% 2% 5% 3%
81% 23% 17% 6% 12% 60% 6%
23%
1% 0% 1Vo 0% 1% 3%
(see Section 2). Combining the census and NTS data is possible but assumptions need to be made. For example, the NTS uses mile distance bands whereas the Census uses kilometres. The following methodology was used. All journeys over 30 km were distributed by mode. Then the next distance band was distributed by mode, followed by subsequent distance bands down to the 5 to 10 km band. All residual trips by mode were then assumed to be less than 5 km. This method was felt to be appropriate because the majority of journeys are less than 5 km. Using this approach for each of the 403 districts travel (in pass km) by mode could be calculated. Table 9 shows these details. This distribution of travel for the journey to work can be compared to Table 10 which details overall travel by mode for 1980 and 1990. The importance of these passenger kilometre data is that fuel efficiencies can be applied to each mode. The map (Fig. 1) shows this distribution of fuel used per (one way) work trip for England and Wales. The data have been classified using a nested means approach and the distribution of the data are seen in the histogram that is attached to the map (Fig. 1). The values range from 1.8 MJ/trip to 44.5 MJ/trip with an overall average of 17 MJ/trip. The patterns are very distinct. The area of highest overall energy use is in Outer London and the areas surrounding the London metropolitan area (Rest of South East England or Roseland). Lower energy consumption is found in Inner London and in self contained large towns. Table 11 gives these details and includes definitions for the various subdivisions used. Even when data are grouped there are clearly still very wide variations. The commuter hinterland surrounding London has fuel use levels which are 150% higher than inner areas of London. Away from London levels of fuel use in the larger metropolitan areas are 25% higher than in the smaller, but no less dense, settlements outside the largest metropolitan areas. 4. INTERPRETATIONS
OF THE DATA
The primary requirements for an analysis of travel and energy consumption are for details of travel by purpose, mode, distance, and frequency of trips. Certain assumptions Table 10. Travel by mode Passenger (billions pass km)
1980
1990
VoChange
Rail Car Motorcycle Pedal cycle Buses & coaches Air
35 395 8 5 45 3
41 561 7 5 41 5
17.1 42.0 - 12.5 0.0 -8.9 70.0
Overall
491
660
34.4
Goods (billions tkm)
1980
1990
% Change
18 92 54 10 174
16 136 53 11 216
- 10.2 47.4 -3.0 8.9 23.1
Rail Road Water Pipeline (oil only) Overall
D. BANISTERand C. BANISTER
c; Fig . 1. Fuel used per work trip for the districts of England and Wales. Source: 1981 Census.
Table 11. Fuel used in work travel in MJ for various subdivisions of the country Inner London Boroughs 28 nonmetro districts with population density greater than 21 p/ha Metropolitan counties (excludes London) Wales (excluding Cardiff which is with 28 denser districts) Outer London Boroughs Rest of nonmetro England (excludes Roseland and 22 larger districts) Rest of South East England (excludes 5 denser districts)
10.3 10.6 13.2 16.4 18.6 21.2 26.0
Twenty-eight nonmetro districts are: Bath, Bristol, Cambridge (Roseland), Middlesborough, Derby, Exeter, Plymouth, Bournemouth, Cheltenham, Gloucester, Gosport (Roseland), Portsmouth (Roseland), Southampton (Roseland), Hereford, Worcester, Grimsby, Hull, Blackpool, Leicester, Oadby & Wigston, Lincoln, Norwich, York, Nottingham, Oxford (Roseland), Stoke, Ipswich, and Cardiff (Wales). Metropolitan counties are: Greater Manchester, Merseyside, South Yorkshire, Tyne & Wear, West Midlands, and West Yorkshire. Rest of South East England (Roseland) is: Bedfordshire, Berkshire, Buckinghamshire, Cambridgeshire, Essex, Hampshire, Hertfordshire, Kent, Oxfordshire, Surrey, and Sussex.
Energy consumption in Great Britain
29
have then been made on average energy consumption figures for different types of vehicle, together with comment on the robustness of those assumptions (Table 3), in particular the crucial importance of occupancy rates in determining energy consumption. All the data have been collected at one point in time and so represent a static view of both travel and energy consumption. Some of the data form a repeated cross section taken at several points in time, but even here it is difficult to interpret the changes that have taken place in between the survey points. Two different approaches have been adopted. One based on fuel consumption by vehicle type calculated from empirical and monitoring surveys (bottom up) and the other based on breaking down total energy consumption figures (top down). The results are remarkably consistent as detailed in Table 3. However, despite these limitations, certain conclusions can be drawn with respect to the data for Great Britain: 1. In the domestic passenger transport sector the car is the dominant mode accounting for 48% of journeys but over 90% of energy consumption. Conversely, walk and bicycle account for nearly 40% of journeys but under 1% of energy use. 2. The vehicle occupancy assumptions are important in determining energy consumption. Relatively small changes in car occupancy levels or in public transport occupancy levels significantly affect energy consumption figures per passenger mile. Energy use per vehicle is almost independent of the number of people travelling. Perhaps a more stable measure would be to give estimates of energy consumption per vehicle mile (i.e., with an assumed occupancy of one) Car Bus Rail (Super Sprinter Diesel)
4.82 MJ per car mile 20.72 MJ per bus mile 78.32 MJ per train mile
In terms of policy options, the area of greatest benefit would be through increasing vehicle occupancy, particularly the car but also in other modes. The evidence over the last decade points in the opposite direction with vehicle occupancy levels declining rather than improving (see No. 5 below). The possibility of persuading large numbers of people to leave their cars at home and to use public transport is unrealistic. Any significant savings in energy require large scale investment in public transport to provide the necessary infrastructure. For example, a saving of 10% in energy would require more than a five-fold increase in total public transport use. 3. Significant increases in energy consumption have taken place since the 1960s when mass car ownership became a reality and this is reflected in an increase of 37% in road energy consumption in the 1982-1991 period (Table 2). It seems likely that this growth will continue in line with the expected growth in car ownership and traffic over the next two decades, whether predictions are taken from the Department of Transport, the Department of Energy or from the European Commission Directorate General on Energy (all 1989). 4. The importance of the journey to work is declining and it now accounts for around 20% of all trips. This reduction is partly explained by the decline in work journeys as more complex work patterns evolve but more importantly due to. the growth in other activities, particularly leisure, social, and shopping activities. Almost all of the growth is in car based activities (Table 7). 5. There has been some compensation through improvements in the energy efficiency of vehicles and through road construction that may reduce the amount of inefficient running of vehicles caused by congestion at least in the short term. In the 198Os, there have been improvements in the energy efficiency of both rail operations and cars, but reductions in the energy efficiency of motorcycles and buses have taken place giving a net reduction in the energy efficiency for all modes of 5.5% in MJ per passenger/km (Tables 12 and 13). The primary explanation is the fall in occupancy rates and load factors, particularly for buses. Using the 1990 energy patterns, cars with >2.4 people in them are more energy efficient than rail, and the break even point for bus is a car
30
D. BANISTERand C. BANISTER Table 12. Relative fuel efficiency changes 1980 to 1990 Relative to Car
Passenger Transport in MJ/pass km 1980
1990
% Change
1980
1990
Rail Cars Motorcycles Buses & Coaches
1.90 2.24 1.19 0.65
1.44 2.03 1.73 1.29
-24.4 -9.1 44.8 99.4
- 15.3% 0.0% -46.8% -71.1%
Overall
2.05
1.94
-5.5
-8.5%
-29.1% 0.0% - 14.7% -36.2% -4.3%
Relative to Road
Goods Transport Rail Road Water
0.69 3.49 1.05
0.50 3.95 1.16
-21.6 13.3 11.3
-80.3% 0.0% - 70.0%
- 87.4% 0.0% - 70.6%
Overall
2.38
2.97
24.6%
-31.7%
- 24.9%
occupancy level of >2.7 persons. Policies to increase car occupancy rates would include (a) providing road space for high occupancy vehicles through the provision of special lanes or through the provision of preferential parking that is both cheap and convenient; (b) linking the charges made for road pricing to the car occupancy with cheaper rates for vehicles with passengers. 6. Overall however, it seems that lifestyles and trip patterns are becoming more complex and car oriented. There has been unprecedented growth in travel over the last decade and it could be argued that the transport system has been taking the strain. Family relations are becoming more varied with the diminished importance of the nuclear family and the growth in single parent families and young adults with no children. The workforce has expanded with part-time labour, job sharing, and increased female participation. More recently, these changes have been compounded by a stagnant housing market, high interest rates, and growing unemployment. The uncertainty in the economic situation may result in people not moving so frequently but adopting temporary patterns of travel to work and other activities, which in turn results in more and longer trips being made, principally by car (Banister & Bayliss, 1991). 7. However, as Gordon and Richardson (1989) emphasized, the pursuit of a single objective such as “minimising gasoline consumption makes no sense.” They quote Lowry who points out that “efficiency does not imply rearranging our lives to minimise transport costs. Rather it implies a search for a suitable balance between transport costs of compatibly configured land uses.” The complexity of the urban policy process requires the use of several policy levers (e.g., pricing, regulation, and taxation) to achieve a spatial structure that reflects the land, labour, and housing markets as well as the transport market. From the empirical data for Great Britain and the evidence cited from other sources, some tentative conclusions can be drawn on the relationships between transport and Table 13. Unit load factors
Passenger in Persons/Unit Rail Car Motorcycle Buses & Coaches Goods in t/unit Rail Goods Road Goods
1980
1990
% Change
89.2 1.8 1.0 12.8
96.6 1.7 1.1 a.7
8.3 -7.7 4.9 -31.8
336.5 2.0
329.2 2.1
-2.2 2.5
Note: load factors for water transport cannot be calculated. A transport unit refers to a single vehicle or complete train.
Energy consumption in Great Britain
31
energy and the importance of settlement patterns. At the general level it seems that travel distances and mix of activities should be reduced so that residential development can be related to local jobs and services not as a dormitory settlement (Owens, 1987). However, concentration of new development into smaller centres outside the urban area may save less fuel than concentrating that same level of development into the urban area itself. But fuel savings in developments outside the urban area are less costly because of reduced levels of traffic congestion and the greater availability of space (Rickaby, 1987). Notions of self containment are perhaps less valid in a highly mobile car oriented society as it would be impossible for any one town or city to have a complete range of activities. Even though many people may commute to another centre for employment, that settlement may still be relatively efficient if a range of other facilities and services are provided within walking or cycling distance. The large and isolated settlement would probably be more self contained than the small and isolated settlement, but a series of small free standing towns in close proximity to each other (and perhaps a major city) would probably be the most energy efficient form in a society that is dependent on the car for most travel. The free standing town (about 25,000) would have the shortest trip lengths, lowest door to door trip times, and a high proportion of facilities and services within walking and cycling distance (Banister, 1992). In related work carried out at the microlevel in a rural area of England (Banister, 1992), the largest and most energy efficient settlement is the most urban-it has the highest trip generation rate but the lowest energy consumption figures per trip and per person. This is because of the availability of good local services and facilities, local employment, good public transport, and a high proportion of walk trips, The National Travel Survey information has supported this conclusion (Table 3). This conclusion contradicts that reached by Newman and Kenworthy (1989) on density of development being the most important single determinant of energy consumption. The Census analysis suggests that relatively densely populated areas (District level densities above 21 persons per hectare) which are not part of a large conurbation use considerably less energy than most other locations. It seems that the physical characteristics of the urban settlement are important (size, availability of facilities and services, public transport), but that this basic relationship is modified both by the socioeconomic characteristics of the population (as different people have different propensities to travel with different frequencies, trip lengths, and modes) and by the location of the settlement in relation to other large urban areas. The EC’s notion of a compact city with greater diversity and people living close to their workplaces simplifies the complexity of lifestyles (Commission of the European Communities, 1990). A holistic view must encompass the full range of activities that people participate in. Many would argue that the car has improved their quality of life, the opportunities available to them, and the flexibility and independence which is offered by personal transport. The concept of the sustainable city goes beyond one which is energy efficient or transport efficient and explores the city as a place in which people want to live.
REFERENCES Advisory Committee on Energy Consumption (1976). Passenger transport: Short and medium term considerations. EnergyPaper 10, ACEC, Department of Energy, London: HMSO. Banister, D. and Bayliss, D. (1991, June). Structural changes in population and impacts on passenger transport demand. Paper presented at the European Conference of Ministers of Transport Round Table 88, Paris. Banister, D. (1992). Energy use, transport and settlement patterns, Breheny, M. J. (ed) Sustainable development and urban form. London: Pion, pp 160-181. Breheny, M. J. (1990, November). Strategic planning and urban sustainability. Paper presented to the Town and Country Planning Association Conference on Planning for Sustainable Development, London. Commission of the European Communities (1990). Green Paper on the urban environment. Brussels EUR 12902. Department of Energy (1989). Energy use and energy efficiency in UK transport to the year 2010. London: HMSO. Department of the Environment (1990). This common inheritance: Britain’s environmental strategy. London: HMSO. TR(A) 29:1-C
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D. BANISTERand C. BANISTER
Department of Transport (1979). National travelsurvey 1975/76 report. London: HMSO. Department of Transport (1988).National travel survey 1985/86 report. London: HMSO. Department of Transport (1989).National road trrlfficforecasts (Great Britain) 1989. London: HMSO. Department of Transport (l!Wl).Transport statistics Great Britain 1991. London: HMSO. Department of Transport (1992). Transport statistics Great Britain 1992. London: HMSO. European Commission DG for Energy (1989, September). Mqior themes in energy: Energy in Europe. Brussels. Gordon, P. and Richardson, H. W. (1989). Gasoline consumption and cities: A reply. J. American Prclnning Assoc. S(3), pp. 342-346. Hughes, P. (1990, January). Transport emissions and the greenhouse effect. Paper presented to the Universities Transport Studies Group Conference. Newman, P. W. G. and Kenworthy, J. R. (1989). Gasoline consumption and cities: A comparison of U.S. cities with a global survey. J. American Planning Assoc. 55(l), 24-37. Owens, S. (1987). The urban futures: Does energy really matter? In Hawkes, D., Owens, J.. Rickaby, P.. and Steadman, P. (eds), Energy and urban builtform. London: Butterworths; pp. 169-189. Prezxy, J. (1989, August). Definitions of sustainability. UKCEED, Discussion Paper 9. Redsell, M., Lucas, G., and Ashford. N. (1988). Comparison of on roadfuelconsumption for diesetandpetrol cars. Transport and Road Research Laboratory, Crowthorne. Rickaby, P. (1987). Six settlement patterns compared. Environment and Planning B M(3), 193423. Rickaby, P. and Steadman, P. (1992). Patterns of land use in English towns: Implications for energy use and carbon dioxide emissions. Breheny, M. J. (ed) Sustainable development and urban form. London: Pion, 182-l%.