Relationships between transport emissions and travel patterns in Britain

PERGAMON

Transport Policy 6 (1999) 247–258 www.elsevier.com/locate/tranpol

Relationships between transport emissions and travel patterns in Britain D. Stead* The Bartlett School of Planning, University College London, 22 Gordon Street, London WC1H 0QB, UK Received 1 July 1999; received in revised form 1 October 1999; accepted 1 October 1999

Abstract This paper explores the relationship between transport emissions and various measures of passenger travel patterns in Britain. The paper uses original data from the 1989/91 National Travel Survey and identifies a method for incorporating a range of vehicle operating conditions into calculations of vehicle emissions and energy consumption for each journey recorded in the National Travel Survey data. The paper shows that travel distance is a reasonable proxy for vehicle energy consumption and emissions of most pollutants. Travel distance per person is therefore a simple and readily available environmental indicator for transport. This indicator has potential application in the assessment of current transport policies and programmes and in the development of future policies and programmes. q 2000 Elsevier Science Ltd. All rights reserved. Keywords: Transport emissions; Travel patterns; Transport energy consumption; National Travel Survey

1. Introduction Increasing numbers of environmental indicators are being monitored by a variety of agencies at the local, regional, national and international level. In transport policy, environmental indicators are becoming more important in the assessment of current local transport policies and programmes and in the development of future policies and programmes. Because of the limited data and resources available for monitoring, it is crucial that the environmental indicators, which are collected and monitored, are representative of environmental impacts, widely available, inexpensive and easy to collect. This paper explores the relationship between transport emissions and various measures of passenger travel patterns in Britain. It examines the usefulness of various measures of travel patterns as environmental indicators of vehicle emissions and energy use. If certain measures of travel patterns were reasonable proxies for vehicle emissions and energy use, and could be collected relatively easily without complex measurement or calculation, they would be useful for environmental monitoring and the assessment and development of transport policy. In order to examine the similarities of various measures of travel patterns with vehicle emissions and energy use, the paper uses original data from the 1989/91 National Travel * Tel.: 144-20-7380-7501; fax: 144-20-7380-7502. E-mail address: [email protected] (D. Stead).

Survey (one of the most recent sets of raw data available for analysis). The method developed in this paper identifies how a range of vehicle operating conditions can be incorporated into calculations of vehicle emissions and energy consumption using data from the National Travel Surveys. The paper is divided into four main sections. The first section of the paper identifies the main emissions from transport, their impacts and recent trends. The second section discusses the way in which various operating conditions affect transport emissions and energy consumption. The third section identifies how vehicle emissions and energy consumption can be calculated to take these operating conditions into account. In the fourth section of the paper, per capita energy consumption and vehicle emission figures are compared using correlation analysis to examine the extent to which travel patterns follow similar trends. The paper shows that certain measures of travel patterns such as travel distance are reasonable proxies for vehicle energy consumption and emissions of most pollutants. These measures are therefore potentially useful environmental indicators for transport. 2. Transport emissions—impacts and trends Transport produces a number of emissions and a range of environmental impacts. Emissions include global pollutants (such as carbon dioxide which contributes to global warming), national or regional pollutants (nitrogen oxides which produces acidification or ‘acid rain’ for example) and local

0967-070X/00/$ - see front matter q 2000 Elsevier Science Ltd. All rights reserved. PII: S0967-070 X( 99)00 025-6

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Table 1 Emission of pollutants from transport and their impacts (source: Department of the Environment, Transport and the Regions (1997a)) Pollutant

Proportion of pollutant from transport in 1995 (%)

Change in transport emissions between 1985 and 1995 (%)

Impacts

Carbon monoxide (CO)

76

215

Carbon dioxide (CO2) Nitrogen oxides (NOx) Particulate matter (PM10)

25 56 53

127 17 18

Volatile organic compounds (VOCs)

40

210

Exacerbates cardiovascular disease and respiratory conditions Climate change Acidification, photochemical smog Respiratory problems, increased susceptibility to asthma, soiling of buildings Various including cancer and plant damage

pollutants (such as particulates which contribute to respiratory problems including the increased susceptibility to asthma). Transport’s contribution to environmental pollution in urban areas is particularly large, where transport is by far the most significant contributor of most emissions. The temporal trends in air pollutants from transport over the last decade are mixed. Some emissions continue to increase whilst others are beginning to fall. However, some of the emissions that are decreasing may be a problem in the future if the growth in transport increases faster than improvements in technology (see for example Howard, 1990; Department of the Environment, 1997). Trends in some of the more important emissions are identified in Table 1 and are discussed below. 2.1. Carbon monoxide Carbon monoxide is responsible for health problems, particularly in urban areas, where it can exacerbate cardiovascular disease and contribute to respiratory conditions in combination with other pollutants (Barde and Button, 1990). More than three-quarters of all carbon monoxide emissions are produced by transport. Emissions of carbon monoxide follow very similar trends as emissions of nitrogen oxides. Emissions of carbon monoxide from the transport sector experienced a rapid increase up to 1989, followed by a steady decrease, due mainly to the introduction of catalytic converters. Emissions of carbon monoxide are expected to continue to decrease beyond 2000 but are likely to begin increasing again between 2000 and 2010 as increasing levels of traffic outweigh the emission reductions achieved by catalytic converters (Department of the Environment, 1997). 2.2. Carbon dioxide Carbon dioxide is mainly caused by the combustion of fuels. It is the most important greenhouse gas and is responsible for global warming and climate change. Transport now accounts for one quarter of United Kingdom carbon dioxide emissions, most of which comes from road transport. Emissions of carbon dioxide from transport increased rapidly (by 27%) between 1985 and 1995. On the basis of current

projections carbon dioxide emissions from the transport sector look set to continue increasing over the next 20 years (Department of Trade and Industry, 1995). At the European level a 40% increase in carbon dioxide emissions from transport might be expected between 1995 and 2010 if existing trends continue (Commission of the European Communities, 1998). 2.3. Nitrogen oxides Nitrogen oxides cause national and transnational pollution, contributing to acid deposition and, in combination with ozone, the formation of secondary pollutants, which give rise to photochemical smog and poor air quality. More than half of all emissions of nitrogen oxides originates from road transport. Emissions of nitrogen oxides from the transport sector experienced an increase up to 1989, followed by a steady decrease, due mainly to the introduction of catalytic converters. Emissions of nitrogen oxides are expected to continue to decrease beyond 2000 but are likely to begin increasing again between 2000 and 2010 as increasing levels of traffic outweigh the emission reductions achieved by catalytic converters (Department of the Environment, 1997). 2.4. Particulates Particulates consist of mainly carbon and unburned or partially burned organic compounds. Airborne particulate matter is the primary cause of the soiling of buildings and visibility loss on hazy days. The medical impacts associated with particulates include respiratory problems such as the increased susceptibility to asthma (Royal Commission on Environmental Pollution, 1994). Whereas the domestic sector was the largest source of emissions of particulates a decade ago, more than half of the United Kingdom’s emissions of particulates now originate from transport, particularly from diesel vehicles (Department of the Environment, Transport and the Regions, 1997a). Emissions of particulates (PM10) from transport increased up to 1991, from which time emissions have declined due to the introduction of less polluting diesel. Emissions of particulates are expected

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Table 2 Vehicle emissions relative to a medium-sized petrol car without a three-way catalyst (source: Department of Transport, 1996) Vehicle type

Car Car Car Van Van Goods Minibus Midibus Large bus Coach

Vehicle size/engine type

Petrol, without three way catalyst Petrol, with three way catalyst Diesel Petrol, without three way catalyst Diesel Diesel, 3.5–7.0 tonne up to 16 seats 17–35 seats over 36 seats over 36 seats

Relative emissions per vehicle kilometre (urban conditions) Carbon dioxide (CO2)

Carbon monoxide (CO)

Hydro-carbons (HC)

Nitrogen oxides (NOx)

1.0 1.1 0.9 0.9 1.0 2.6 1.6 2.6 5.9 5.1

1.0 0.4 0.0 0.6 0.0 0.1 0.1 0.1 0.6 0.2

1.0 0.2 0.0 0.5 0.1 0.2 0.1 0.2 1.3 0.2

1.0 0.2 0.3 0.8 0.6 3.0 1.1 3.0 7.1 6.5

to continue to decrease beyond 2000 but may begin to increase again in the longer term as increasing levels of traffic outweigh the emission reductions achieved by the use of less polluting fuel (Department of the Environment, 1997).

2.5. Volatile organic compounds Volatile organic compounds (VOCs) comprise a variety of chemical compounds. The major environmental impact of VOCs (other than methane) lies in their involvement in the formation of ground-level ozone, which can affect human health and damage plants (Department of the Environment, Transport and the Regions, 1997a). Some VOCs such as benzene are known to be carcinogenic and pose a threat to human health. Around 40% of VOCs are produced by transport. Emissions of VOCs from transport have decreased since the late 1980s and this trend is likely to continue in the next decade (Department of the Environment, 1997). Further on, however, it may be that emissions of VOCs begin to increase if increasing levels of traffic outweigh the emission reductions achieved by the use of less polluting fuel.

3. The effects of vehicle operating conditions on emissions and energy consumption Potter reports only a small improvement (5%) in the energy efficiency of new vehicles between 1970 and 1993. This corresponds with analysis of vehicle efficiency by Sorrell (1992), who reports that the average fuel consumption of new cars decreased through the 1970s until the late 1980s and then increased slightly until 1990. This is partly the consequence of trends towards more powerful and heavier cars which have mitigated against some of the fuel and emission reductions brought about by improvements in vehicle technology, and also the consequence of changes in vehicle operating conditions (see below). The introduction of new technology such as catalytic converters has resulted in faster improvements in emissions than in energy efficiency (although new technologies may create other environmental impacts—see for example Whitelegg, 1997). Vehicle emissions and energy consumption are dependent on journey distance and a number of different operating conditions such as mode, occupancy, vehicle age, fuel type, engine temperature, travel speed and engine size. This section discusses how each of these operating conditions can affect emissions and energy consumption. 3.1. Mode

2.6. Summary Transport is one of the largest sources of environmental pollution. The large number of environmental impacts associated with transport range from local through to global. Some of these impacts are increasing, such as those associated with carbon dioxide emissions. Other impacts are beginning to decrease (such as those associated with nitrogen oxides and particulates) but these may start to increase again in the longer term if increasing levels of traffic outweigh the emission reductions achieved through technology.

Table 2 shows how vehicle emissions vary by mode. 1 Emissions are related to the vehicle size and fuel type. Buses and coaches generally emit lower volumes of carbon monoxide and hydrocarbons but larger volumes of carbon dioxide and particulate matter relative to those of a mediumsized petrol car. The emissions and energy consumption characteristics of other modes, such as air and water transport, may be substantially different to the modes listed in Table 2, although this category makes up a small proportion 1 The comparison of emissions presented in this table does not account for the number of passengers typically carried by these different modes.

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of passenger travel within Britain (see Calculation of Vehicle Emissions and Energy Consumption below). 3.2. Vehicle occupancy Vehicle occupancy is clearly an important determinant of emissions and energy consumption per passenger-kilometre. Simple calculations using data from Table 2 show that the emissions of carbon dioxide per passenger-kilometre from a medium sized car carrying two passengers are similar to those of a minibus carrying three passengers or a coach carrying 10 passengers. In terms of fuel consumption, a similar amount of fuel is required to carry four people in a medium-sized car as six people in a minibus, 12 people in a large bus or one person on a motorcycle. Analysis of data from the 1989/91 National Travel Survey reveals that car occupancy shows some significant variations by journey purpose but that the time of travel has less effect on car occupancy. Potter (1997) reports that there has been a 7% decline in car occupancy between the National Surveys of 1972/73 and 1992/94. The decline has been much greater for some types of journeys such as for commuting and escort trips.

vehicle kilometre. 2 The energy consumption and emissions from vehicles propelled by alternative fuels (such as electricity, liquid petroleum gas, compressed natural gas, methanol, ethanol or liquid hydrogen) are quite different to petrol and diesel vehicles (see for example OECD, 1993). 3 3.5. Engine temperature Emissions of carbon dioxide, carbon monoxide, hydrocarbons and particulate matter are higher when the engine temperature is cold (Gover et al., 1994). This is true for both petrol and diesel engines. Fuel efficiency is likely to be of the order of 25% lower under cold conditions. Emissions of carbon monoxide and hydrocarbons from petrol vehicles when operating cold are approximately double the emissions from a hot engine since the catalytic converter does not operate efficiently when cold. High emissions under cold conditions can be expected for around the first 3 km of the journey (Eggleston, 1992). A large proportion of pollutants are emitted under cold conditions for the reasons that a large share of journeys are made by car, most car journeys begin from cold-starts and approximately a quarter of all journeys in Great Britain are under 3 km (Department of Environment, Transport and the Regions, 1997c).

3.3. Vehicle age 3.6. Vehicle speed Vehicle age, according to Anable et al. (1997), can influence emissions in two ways. Firstly, age is often a surrogate for the general state of maintenance—the older the car, the less well maintained it is likely to be. Secondly, age is related to vehicle technology—newer cars are likely to have more fuel efficient and less polluting features. Thus, as vehicle age increases, emissions and energy consumption are also likely to increase. 3.4. Fuel type Fuel type significantly affects energy consumption and emissions. Under urban conditions (where vehicle speeds are low) a car with a petrol engine and a threeway catalytic converter typically produces more emissions of carbon dioxide, carbon monoxide, hydrocarbons and nitrogen oxides than a similarly sized vehicle with a diesel engine (Gover et al., 1994). The diesel car is likely to consume less energy but produce more particulate matter. At higher speeds (such as motorway driving), emissions of carbon dioxide and hydrocarbons are likely to be similar for both petrol and diesel cars. The petrol car is likely to produce more carbon monoxide, whilst the diesel car is likely to produce more nitrogen oxides and particulate matter. Empirical studies suggest that diesel cars may be 20–30% more energy efficient in terms of kilometres per litre of fuel than petrol cars of a similar size and specification (Redsell et al., 1988; Eggleston, 1992), which is between 9 and 18% greater energy efficiency in terms of energy consumption per

There is a non-linear relationship between vehicle speed, pollution emissions and energy consumption. At low speeds, high emission levels and poor energy efficiency are the consequence of inefficient engine conditions. At high speeds, fuel consumption begins to increase as a result of greater wind resistance. Increased energy consumption results in higher emissions. According to Anable et al. (1997), cars are usually designed to operate most efficiently at road speeds between around 80 and 95 km/h for petrol cars and between around 65 and 80 km/h for diesel cars. A number of studies have examined the effects of average vehicle speed on fuel economy (see for example Redsell et al., 1988 or Eggleston, 1992). Redsell et al. (1988) report that the energy consumption of petrol cars is lowest when the average vehicle speed is around 65 km/h. 3.7. Engine size Vehicle engine size (capacity) is directly related to emissions and energy consumption. Vehicles with larger engines consume more fuel and emit more pollution, particularly carbon dioxide and nitrogen oxides. Calculations by Gover et al. (1994) suggest that vehicles with large engines 2 The calculations assume that 1 l of petrol is equivalent to 35.1 MJ and 1 l of diesel is equivalent to 38.6 MJ (Department of Trade and Industry, 1995). 3 Because the proportion of the vehicle stock propelled by alternative fuels is currently very small in Britain, their impact on total energy consumption and emissions is not examined in this paper.

D. Stead / Transport Policy 6 (1999) 247–258

produce at least 50% more emissions of carbon dioxide and nitrogen oxides than vehicles with small engines operated under similar driving conditions. Sorrell (1992) reports a linear relationship between engine size and fuel consumption. There is often however a large difference between the most and the least efficient vehicle within each engine size range. For example, the fuel consumption of various petrol cars with a 1.3 l engine can range from 11.8 to 18.5 km/l: a difference of 57% (Sorrell, 1992). Factors such as turbocharging, fuel injection, vehicle weight and two/four wheel drive are cited as reasons for this large variation. The average engine size of new vehicles increased from 1.40 to 1.54 l between 1973 and 1992 and the average power output increased by 35% (Royal Commission on Environmental Pollution, 1994) which has mitigated against some of the fuel and emission reductions brought about by improvements in vehicle technology.

3.8. Other factors Other factors such as catalytic converters, driving style, vehicle type and upstream processes also affect emissions and energy consumption (but are not considered in the calculations of vehicle emissions and energy consumption in this paper). Driving style, particularly the effects of acceleration, deceleration and overall speed, can have a considerable influence on emissions and energy consumption. It is estimated that between 10 and 15% of fuel could be saved by avoiding rapid acceleration and the inappropriate use of gears (Royal Commission on Environmental Pollution, 1994). Redsell et al. (1988) report that ‘expert’ driving can result in a 9% reduction in fuel under urban driving conditions, a 10% reduction under suburban driving conditions and a 24% reduction in fuel consumption for motorway driving, compared to the ‘typical’ driving style. Emissions and energy consumption may vary even when vehicle specifications such as age, fuel type and engine size are similar. There may be differences in emissions and energy consumption between different models of vehicle and between automatic and manual models for example. As well as emissions and energy consumption from vehicle operation, there are also those from upstream processes. These upstream processes include the manufacture of vehicles (including component manufacture and assembly), the construction of transport infrastructure and the processing of fuel from raw materials. According to Hughes (1993), the total of these upstream impacts may account for up to one-sixth of all energy used in the transport sector and presumably a similar proportion of emissions such as carbon dioxide. The OECD (1993) suggest that upstream processes make a smaller contribution to CO2 emissions—around one-tenth of all CO2 emissions from petrol and diesel cars, although this figure does not account for the energy used in providing the road infrastructure.

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4. Calculation of vehicle emissions and energy consumption This section describes how vehicle emissions and transport energy consumption was calculated from the 1989/91 National Travel Survey (Department of Transport, 1995) to take into account the effect of the various operating conditions identified above. The method is similar to the one used by Anable et al. (1997) in calculating travel emission profiles for rural areas. 4.1. Vehicle emissions The method of calculating emissions uses a set of emission factors for each type of pollutant, derived from the results of on-road vehicle tests in the United Kingdom under different traffic conditions. Emissions of carbon dioxide, carbon monoxide, hydrocarbons, nitrogen oxides and particulate matter per passenger were calculated by multiplying the journey distance by the emission factor for each pollutant. For example, carbon dioxide emissions for each journey were calculated as follows: CO2 emissions per passenger …g† ˆ CO2 emission factor …g=passenger-kilometre† × journey distance …km† The CO2 emission factor (like all other emissions factors) is dependent on the mode, fuel, vehicle speed, engine size and temperature of the journey. Emission factors for carbon dioxide (CO2), carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx) and particulate matter (PM) are presented according to each of these operating conditions in Table 3. The table shows that emissions and energy use is substantially higher under cold-start conditions for most types of vehicle. Emissions are generally lower as the average journey speed increases, with the exception of emissions of nitrogen oxides. In order to account for the effects of vehicle occupancy and age on emissions and energy consumption, the figure was then adjusted using correction factors (see below). 4.2. Vehicle energy consumption Two figures for transport energy consumption are calculated for each journey, termed ‘complex’ and ‘simple’ energy consumption. Both measures refer to primary energy consumption, which takes into account the energy used to obtain, process and deliver the fuel. The first calculation of energy consumption, termed ‘complex’ energy consumption, is calculated in a similar way to the calculation of emissions, where energy consumption per passenger for each journey is calculated by multiplying the journey distance by the energy consumption factor, derived from the results of on-road vehicle testing in the United Kingdom under different traffic conditions (shown in Table 3). As with the calculation of emissions, the energy consumption figure was then adjusted to account for two other factors that

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Table 3 Emission and energy consumption factors by mode, fuel type, engine size, temperature and average speed (based on Gover et al. (1994)) Mode

Fuel type

Engine size a

Car c

Petrol

Small

Car

Petrol

Medium

Car

Petrol

large

Car

Diesel

Small

Car

Diesel

Medium

Car

Diesel

Large

Van d

All

All

Motorcycle e

All

All

Taxi f

All

All

Bus g

All

All

Coach h

All

All

Rail i Underground i

All All

All All

Average speed

Cold 0–30 mph 30–40 mph 40 mph 1 Cold 0–30 mph 30–40 mph 40 mph 1 Cold 0–30 mph 30–40 mph 40 mph 1 Cold 0–30 mph 30–40 mph 40 mph 1 Cold 0–30 mph 30–40 mph 40 mph 1 Cold 0–30 mph 30–40 mph 40 mph 1 Cold 0–30 mph 30–40 mph 40 mph 1 Cold 0–30 mph 30–40 mph 40 mph 1 0–30 mph 30–40 mph 40 mph 1 0–20 mph 20 mph 1 0–20 mph 20–30 mph 30 mph 1 All All

Energy consumption per passenger-km (MJ/pass-km) b

2.16 1.49 1.21 1.16 2.47 1.76 1.39 1.22 3.50 2.57 1.80 1.45 1.24 1.03 0.88 0.84 1.51 1.26 1.06 1.02 2.04 1.70 1.43 1.37 2.73 2.10 1.75 1.73 3.71 2.57 2.08 2.00 4.03 3.36 2.24 1.21 1.03 0.62 0.53 0.43 1.60 1.60

Emissions per passenger kilometre (g/pass-km)

CO2

CO

HC

NOx

PM

96 75 66 67 120 94 78 72 187 146 110 90 83 69 59 56 101 84 71 68 136 113 96 92 154 123 105 105 165 129 113 116 269 224 149 78 67 40 34 27 30 30

22.15 10.91 5.97 2.99 20.08 9.89 4.63 2.59 20.34 10.02 2.28 1.02 0.42 0.30 0.20 0.15 0.45 0.31 0.21 0.16 0.49 0.35 0.23 0.17 9.76 4.98 3.03 2.55 38.10 18.77 10.27 5.14 1.20 0.83 0.40 0.76 0.37 0.24 0.15 0.07 0.36 0.36

3.23 1.31 0.71 0.41 3.09 1.25 0.71 0.41 3.06 1.24 0.34 0.27 0.05 0.04 0.03 0.02 0.08 0.06 0.04 0.03 0.10 0.08 0.05 0.03 1.38 0.79 0.49 0.34 5.56 2.25 1.22 0.70 0.21 0.16 0.05 0.24 0.11 0.03 0.01 0.01 0.27 0.27

1.05 1.03 1.09 1.23 1.32 1.31 1.36 1.42 1.83 1.81 1.68 1.51 0.26 0.22 0.19 0.20 0.42 0.37 0.31 0.32 0.57 0.49 0.42 0.44 1.04 1.04 0.91 0.96 1.80 1.78 1.87 2.12 1.12 0.99 0.53 0.93 0.82 0.59 0.56 0.41 1.10 1.10

0.07 0.03 0.03 0.03 0.07 0.03 0.03 0.03 0.07 0.03 0.03 0.03 0.14 0.07 0.06 0.05 0.20 0.10 0.08 0.06 0.21 0.10 0.09 0.08 0.27 0.13 0.11 0.11 0.12 0.06 0.06 0.06 0.53 0.27 0.13 0.16 0.12 0.06 0.04 0.03 0.15 0.15

Small car ˆ 1.4 l or smaller; medium car ˆ 1.4–2.0 l; large car ˆ larger than 2.0 l. Figures expressed as Megajoules per passenger kilometre have been converted from the original figures expressed in terms of litres per 1000 km, assuming: (i) one litre of petrol is equivalent to 35.1 MJ and 1 l of diesel is equivalent to 38.6 MJ (Department of Trade and Industry 1995); and (ii) an average occupancy of 1.6 persons per car (Potter, 1997). c Emissions and energy per passenger kilometre of cars have been calculated assuming 1.6 persons per vehicle. d Emissions and energy per passenger kilometre of vans have been calculated assuming 1.5 persons per van. e Emissions and energy per passenger kilometre of motorcycles have been calculated assuming 1 person per motorcycle. f Emissions and energy per passenger kilometre of taxis have been calculated assuming 0.6 persons per taxi (excluding the driver) and a medium-sized diesel engine. g Emissions and energy per passenger kilometre of buses have been calculated by taking the average of three types of bus (minibus, midibus and doubledecker) and assuming 20% occupancy. h Emissions and energy per passenger kilometre of coaches have been calculated assuming 50% occupancy. i Emissions and energy per passenger kilometre for rail and underground calculated from 1990 emissions and energy consumption estimates and rail passenger kilometre figures (Department of the Environment, Transport and the Regions, 1997a,b; Department of Trade and Industry, 1997). a

b

D. Stead / Transport Policy 6 (1999) 247–258

influence energy consumption (vehicle occupancy and age) using correction factors presented below. Thus, the calculation of ‘complex’ energy consumption takes account of mode, fuel type, engine size, engine temperature, average speed, occupancy and vehicle age. The second method for calculating energy consumption, which provides a second value of energy consumption (‘simple’ energy consumption), only takes into account the journey distance and mode of transport used and uses just one typical energy consumption factor for each mode. The energy consumption factors used to calculate the ‘simple’ value of energy consumption are presented in the final column of Table 4. These figures are derived from a review of literature sources and comparison with national energy statistics (see Stead, 1999). The ‘simple method’ does not account for factors such as vehicle speed, fuel, engine size, engine temperature, occupancy and vehicle age. The ‘simple’ and ‘complex’ energy consumption figures are used to check the consistency of the two calculations and to examine whether the results of the ‘simple method’ can be used as an indicator of energy consumption without resorting to the ‘complex method’ which requires information about vehicle speed, engine size, engine temperature, occupancy and vehicle age for each journey. 4.3. Correction factors The variations in vehicle occupancies by journey purpose are used to adjust the calculations of emissions and energy consumption. Examination of data from the 1989/91 National Travel Survey data indicates that there is little variation in car occupancy during the day but that there are significant differences in car occupancy by journey purpose. 4 Average car occupancies by journey purpose are presented in Table 5. Correction factors are applied to all car journeys to account for these differences in vehicle occupancy. The correction factor is calculated from the ratio of the overall car occupancy rate and the car occupancy rate for the journey purpose. For example, the occupancy correction factor for commuting journeys is 1.45 (equal to 1.72/1.19). In other words, lower than average car occupancy for commuting journeys results in 1.45 times more emissions per passenger-kilometre and 1.45 more energy consumed per passenger-kilometre than the average journey. The occupancy correction factor for holiday journeys, on the other hand, is 0.65 (equal to 1.72/2.66). Typical holiday journeys produce approximately two-thirds of emissions per passenger-kilometre than the average journey and consume around two-thirds of the energy per passengerkilometre compared to the average journey since car occupancy is higher than average. The emissions and energy consumption factors presented 4 Car occupancy is calculated from the ratio of the number of journeys made by both car passengers and car drivers to the number of journeys made by car drivers: car occupancy (persons per car) ˆ (journeys by car passengers 1 journeys by car drivers)/(journeys made by car drivers).

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in Table 3 (above) refer to vehicles produced around 1990. According to government statistics, the energy consumption of cars produced before 1980 is of the order of 5% higher than those produced around 1990 (Department of the Environment, Transport and the Regions, 1997b). Emissions from older vehicles are also likely to be higher by a similar order of magnitude. In this paper a correction factor is used to account for the difference in emissions and energy consumption due to the age of the car used for each journey. To determine the age of the vehicle used for each journey it is assumed that the household’s own vehicle is used for each car journey (the same assumption used earlier to identify the engine size and fuel type). Where the household owns more than one car the average age of all cars in the household is used determine which correction factor for vehicle age to use. In the case of car journeys made by residents of households without a car, the car used is assumed to be newer than a 1985 model. These vehicle age correction factors apply a 2.5% higher rate of emissions and energy consumption to cars made between 1980 and 1985 and a 5% higher rate of emissions and energy consumption to cars made prior to 1980 (Table 6). The 1989/91 National Travel Survey data used in the analysis did not allow differentiation between vehicles with or without catalytic converters. It was not therefore possible to adjust emissions and energy consumption for journeys made in vehicles fitted with a catalytic converter. Because there were relatively few vehicles fitted with catalytic converters by 1991, it is unlikely that this adjustment would have made much difference to the overall emissions and energy consumption totals. 5 4.4. Other assumptions In order to determine the vehicle engine size for each journey it is assumed that the household’s own vehicle is used for each car journey. In cases where households had more than one car, the average engine size of all cars in the household is used determine which emission and energy consumption factors to use. In cases where the residents of households without a car made car journeys, the car used for the journey is assumed to be a medium-sized car (1.4–2.0 l). In order to determine the vehicle fuel type for each journey it was assumed that the household’s own vehicle is used for each car journey. In cases where households had more than one car, the fuel type is assumed to be petrol unless more than half the vehicles in the household were diesel. In cases where the residents of households without a car made car journeys, the car used for the journey is assumed to be a petrol car. All car and van journeys are assumed to start from cold. Emissions and energy consumption for the first 3 km of all journeys by car or van are calculated using ‘cold-start’ 5 Catalytic converters for new cars became mandatory in 1992 in the United Kingdom.

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Table 4 Typical primary energy consumption factors by mode (specific energy consumption in MJ/passenger-kilometre)

Car Stage bus Express bus Rail Underground Van/lorry Walk Motorcycle Bicycle Taxi a b

Source Banister et al., 1997 Low–high

CEC, 1992 a Low–high

Hillman and Whalley, 1983 b Low–high

Hughes, 1992 Low–high

Martin and Shock, 1989 Low–high

Tomkins and Wade, 1989 b Low–high

Summary Low–high

Stead, 1999

1.30–3.00 0.75–1.20 0.98–0.98 1.10–2.30 1.70–1.70 – – 1.60–1.60 – –

1.13–4.65 0.35–1.17 0.50–0.95 0.57–2.86 – – 0.16–0.16 – 0.06–0.06 –

1.47–3.22 0.49–0.98 0.32–0.32 0.56–1.89 – – – 0.74–1.75 – –

1.50–3.08 0.52–0.87 0.38–0.38 0.44–0.65 – – 0.16–0.16 1.52–1.52 0.06–0.06 –

1.30–2.80 0.30–1.60 0.50–1.00 1.20–1.40 1.40–1.40 – – – – –

1.07–3.09 0.56–0.94 0.16–0.16 0.79–2.86 – – – 1.16–1.65 – –

1.07–4.65 0.30–1.60 0.16–1.00 0.44–2.86 1.40–1.70 – 0.16–0.16 0.74–1.75 0.06–0.06 –

1.96 1.28 0.79 1.65 1.55 2.94 0.16 0.99 0.06 2.94

The range assumes an occupancy of 25–50% for each mode. Calculated from figures expressed in terms of litres per passenger-kilometre, assuming that 1 l petroleum is equivalent to 35.1 MJ (Department of Trade and Industry 1995).

D. Stead / Transport Policy 6 (1999) 247–258

Mode

D. Stead / Transport Policy 6 (1999) 247–258 Table 5 Car occupancy rates and correction factors by journey purpose (based on Potter (1997)) Journey purpose

Commuting Business/work/education Escort to education Other escort Shopping Holiday/day trip Other leisure All purposes

Average car occupancy (persons per vehicle)

Correction factor

1.19 1.22 2.20 2.10 1.87 2.66 2.05 1.72

1.45 1.43 0.78 0.82 0.92 0.65 0.84 –

factors. The emissions and energy consumption for the remaining part of the journey are calculated according to the average journey speed. ‘Hot’ operating conditions are assumed for all journeys by public transport (bus and rail) and by taxi. Journeys by modes other than those indicated in Tables 3 and 4, such as water and air transport, accounted for less than half of 1% of all passenger journeys and just over 1% of total passenger travel distance within Britain in 1989/91 (Department of Transport, 1996). 6 The energy consumption and vehicle emissions and for these journeys were calculated using the same energy consumption and emission factors as for a medium-sized petrol car. 5. Comparing vehicle emissions, energy consumption and travel patterns Having calculated energy consumption and vehicle emission figures for each journey, aggregated figures of energy consumption and emissions per person were calculated. These aggregate figures were then compared using correlation analysis in order to examine the extent to which they follow similar trends. The energy consumption and vehicle emission were then aggregated again to give average figures per person in each survey area. The figures were compared with various measures of travel patterns for each area to examine the extent to which trends in travel patterns follow trends in vehicle emissions. 5.1. Comparison of vehicle emissions and energy consumption After calculating energy consumption and vehicle emission figures for each journey, aggregated figures for each 6 International travel is not included in the National Travel Survey. If it were, the proportion of journeys by modes such as air and water would be substantially higher than the small proportion reported in National Travel Survey. The environmental impacts of international journeys are often more significant than those of national journeys (see for example Banister, 1999).

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Table 6 Vehicle age correction factors Vehicle age

Correction factor

Post-1985 1980–1985 Pre-1980

1.000 1.025 1.050

person were calculated. Table 7 presents a comparison of the correlation coefficients between emissions and energy consumption for over 30,000 persons, aggregated from more than 500,000 journeys. Most emissions are highly correlated with others. The two values of energy consumption (‘complex’ and ‘simple’) are very strongly correlated. Transport energy consumption is well correlated with most types of pollutant, particularly carbon dioxide and nitrogen oxides. Particulate emissions are the least well correlated with other types of pollutant, particularly with carbon monoxide and hydrocarbons. Thus, energy consumption calculated using the ‘simple’ method (taking account of travel distance and mode only) appears to be a good proxy for energy consumption calculated using the ‘complex’ method (taking account of mode, fuel type, engine size, engine temperature, average speed, occupancy and vehicle age) and also a good proxy for most vehicle emissions, particularly carbon dioxide and nitrogen oxides. 5.2. Comparison of vehicle emissions, energy consumption and travel patterns After aggregating the energy consumption and vehicle emission figures to give an average per person in each survey area, the figures were then compared with various measures of travel patterns for each area to examine the extent to which travel patterns represent trends in vehicle emissions. The travel patterns examined include measures of journey distance, journey frequency, travel time, modal share and transport energy consumption (Table 8). Table 9 presents the results of the correlation analysis of these measures of travel patterns with per capita emissions of carbon dioxide, carbon monoxide, hydrocarbons, nitrogen oxides and particulate matter. The results of the correlation analysis show that some of the measures of travel patterns are quite representative of atmospheric pollutants whilst others are not. Transport energy consumption is the most representative measure of travel patterns to indicate the atmospheric emissions from transport. The complex calculation of energy consumption (which takes into account the vehicle age, fuel type, engine size, engine temperature, travel speed and vehicle occupancy) is slightly more representative of emissions than the simple calculation of energy consumption as would be expected. As indicators of transport emissions, however, there is very little difference between the simple calculation of energy consumption and travel distance. Measures of travel patterns such as the travel distance by

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Table 7 Pearson’s correlation coefficients between transport emissions and energy consumption Pearson’s correlation coefficients a Energy consumption Energy Energy use per use per person: person: ‘complex ‘simple method’ b method’ c Energy use per person: ‘complex method’ b Energy use per person: ‘simple method’ c CO2 emissions per person CO emissions per person HC emissions per person NOx emissions per person PM emissions per person

Transport emissions Carbon Carbon monoxide dioxide (CO) emissions per (CO2) person emissions per person

Hydrocarbon (HC) emissions per person

Nitrogen oxides (NOx) emissions per person

Particulate matter (PM) emissions per person

1.00

0.94

0.97

0.78

0.81

0.96

0.82

0.94

1.00

0.93

0.71

0.74

0.91

0.80

0.97 0.78 0.81 0.96 0.82

0.93 0.71 0.74 0.91 0.80

1.00 0.76 0.78 0.94 0.75

0.76 1.00 1.00 0.77 0.39

0.78 1.00 1.00 0.81 0.46

0.94 0.77 0.81 1.00 0.72

0.75 0.39 0.46 0.72 1.00

a Pearson’s correlation coefficient is used for variables measured on an interval or ratio scale. The correlation coefficient varies between 21.0 and 11.0. These extremes represent respectively the perfect negative and positive relationship between two variables, whilst a value of zero indicates the complete absence of any statistical relationship. The table summarises the correlation analysis of more than 500,000 journeys aggregated per person (approximately 30,000 persons) using the 1989/91 National travel Survey data. All values are significant at the 99% confidence level. b The complex energy use calculation takes into account the vehicle age, fuel type, engine size, engine temperature (hot or cold operation) travel speed and vehicle occupancy. c The simple energy use calculation is the product of journey distance and the typical energy consumption of the mode of transport used.

car, the travel time by car, the total non-work distance by all modes and the travel time by all modes are all reasonable indicators of transport emissions but are less representative than transport energy use or travel distance. These four

measures do not correlate so well with emissions of particulate matter. Other measures of travel patterns are not such good indicators of transport emissions.

Table 8 Measures of travel patterns examined

6. Conclusions

Type of travel pattern

Travel pattern examined

1. Journey distance:

Travel distance by all modes Total work distance by all modes Total non-work distance by all modes Travel distance by car Average journey distance Number of journeys by all modes Number of journeys by car Number of journeys by public transport Number of journeys by foot Number of journeys by cycle Travel time by all modes Travel time by car Average journey time Proportion of journeys made by car Proportion of journeys made by public transport Proportion of journeys made by foot Proportion of journeys made by cycle Energy use—‘complex method’

2. Journey frequency:

3. Travel time:

4. Modal share:

5. Transport energy consumption:

Energy use—‘simple method’

This paper has explored the relationship between transport emissions and the relationship between various measures of travel patterns. It has examined whether the travel patterns within an area can be used to represent trends in vehicle emissions using data from the 1989/91 National Travel Survey. The paper has identified the main emissions from transport, their impacts and recent trends. It has identified the way in which vehicle operating conditions affect emissions and energy consumption and has described how vehicle emissions and energy consumption can be calculated to take account of various operating conditions. Using data from the 1989/91 National Travel Survey, energy consumption and vehicle emission figures were compared with each other using correlation analysis in order to examine the extent to which travel patterns follow similar trends. The energy consumption and vehicle emission figures were then compared with various measures of travel patterns for each area using correlation analysis to examine the extent to which travel patterns can be used to represent trends in vehicle emissions. The analysis suggests that the ‘simple’ calculation of energy consumption (which takes account of mode and distance only) is very similar to the ‘complex’ calculation of energy consumption (which also takes account of a range operating conditions including occupancy, vehicle age, fuel

D. Stead / Transport Policy 6 (1999) 247–258

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Table 9 Pearson’s correlation coefficients between transport emissions and various measures of travel patterns Travel patterns

Energy use per person—‘complex method’ b Energy use per person—‘simple method’ c Travel distance per person by all modes Travel distance per person by car Travel time per person by car Total non-work distance per person by all modes Travel time per person by all modes Total work distance per person by all modes Number of journeys per person by car Average journey distance per person by all modes Average journey time per person by all modes Proportion of journeys made per person by car Number of journeys per person by all modes Number of journeys per person by cycle Proportion of journeys made per person by cycle Number of journeys per person by public transport Proportion of journeys per person made by public transport Number of journeys per person by foot Proportion of journeys per person made by foot

Pearson’s correlation coefficients a Transport emissions: Carbon Carbon dioxide monoxide (CO2) (CO) emissions emissions per person per person

Hydrocarbons (HC) emissions per person

Nitrogen oxides (NOx) emissions per person

Particulate matter (PM) emissions per person

0.97 0.93 0.91 0.81 0.71 0.76 0.70 0.59 0.42 0.50 0.39 0.30 0.23 20.06 20.08 20.11 20.16 20.17 20.28

0.81 0.74 0.73 0.78 0.81 0.59 0.64 0.50 0.65 0.32 0.24 0.50 0.33 20.07 20.09 20.24 20.29 20.20 20.34

0.96 0.91 0.92 0.83 0.69 0.77 0.68 0.59 0.39 0.53 0.40 0.29 0.20 20.05 20.07 20.06 20.12 20.15 20.25

0.82 0.80 0.81 0.43 0.35 0.66 0.64 0.56 0.16 0.50 0.43 0.03 0.16 20.04 20.05 0.19 0.09 20.12 20.20

0.78 0.71 0.70 0.78 0.82 0.57 0.62 0.48 0.65 0.30 0.23 0.50 0.32 2 0.07 20.09 20.27 20.31 20.20 20.33

a Pearson’s correlation coefficient is used for variables measured on an interval or ratio scale. The correlation coefficient varies between 21.0 and 11.0. These extremes represent respectively the perfect negative and positive relationship between two variables, whilst a value of zero indicates the complete absence of any statistical relationship. The table summarises the correlation analysis of more than 500,000 journeys aggregated per person (approximately 30,000 persons) using the 1989/91 National travel Survey data. All values are significant at the 99% confidence level. b The complex energy use calculation takes into account the vehicle age, fuel type, engine size, engine temperature (hot or cold operation) travel speed and vehicle occupancy. c The simple energy use calculation is the product of journey distance and the typical energy consumption of the mode of transport used.

type, engine temperature, travel speed and engine size). Energy consumption appears to be a reasonable indicator of most atmospheric pollutants and is therefore a useful environmental indicator. The most representative measures of travel patterns to indicate the atmospheric emissions from transport are transport energy consumption and travel distance. Measures of travel patterns such as the travel distance by car, the travel time by car, the total non-work distance by all modes and the travel time by all modes are all reasonable indicators of transport emissions but are less representative than transport energy use or travel distance. Travel distance per person is a simple and readily available indicator of the atmospheric environmental impacts of transport. It could be used both locally and nationally (and internationally) to indicate environmental trends over time in the assessment of current transport policies and programmes and in the development of future policies and programmes. Travel distance per person is one of the national indicators of sustainable development for the United Kingdom (Department of the Environment, 1996). At the local level, local authorities might use travel distance per person as a way of comparing the environmental

impacts of transport use in different areas to identify more sustainable locations (see for example Stead, 1999). Local authorities might also use travel distance per person to identify the environmental impacts of transport across different groups in society as part of the Local Agenda 21 process or as a way of identifying target groups for travel or emission reduction strategies or travel awareness campaigns. In summary, the atmospheric environmental impacts of transport are closely related to travel distance. The mode of travel and vehicle operating conditions affects total emissions but these do not substantially alter the general observation that people who travel most cause most pollution. 7 This is because much of the distance travelled per person is likely to be by motorised modes, and pollution emissions per passenger-kilometre from most motorised modes (whether car, bus, train or taxi) are currently a similar order of magnitude. There is of course a certain amount of variation in pollution emissions per passenger-kilometre between modes but often not a huge difference. At current levels of occupancy, emissions of pollutants per 7 There will of course be some be exceptions, such as keen walkers or cyclists, who might travel long distances but cause few emissions.

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passenger-kilometre from public transport are sometimes equal to or higher than cars operating at average occupancy (Table 3). For example, average emissions of NOx and particulates per passenger-kilometre from buses and trains are sometimes higher than cars operating at average occupancy. However, this is not to say that mode is not important when considering how to reduce emissions from transport. Public transport could potentially reduce emissions of most pollutants substantially if occupancy was increased (thus lowering emissions per passenger-kilometre). Increasing car occupancy could also lead to significant reductions in vehicle emissions. Extra travel could of course be generated by increases in vehicle occupancy unless capacity is also managed. Maximum reductions in vehicle emissions therefore require measures to increase occupancy and measures to manage transport capacity. Acknowledgements The author wishes to thank David Banister (University College London) and Stephen Potter (Open University) for their constructive and encouraging comments on this paper. The author also wishes to acknowledge the research studentship from the Engineering and Physical Sciences Research Council, which made this study possible. References Anable, J., Boardman, B., Root, A., 1997. Travel Emission Profiles: A Tool for Strategy Development and Driver Advice. Environmental Change Unit Research Report 17, University of Oxford, Oxford. Banister, D., 1999. Some thoughts on a walk in the woods. Built Environment 25 (2), 162–167. Banister, D., Watson, S., Wood, C., 1997. Sustainable cities, transport, energy, and urban form. Environment and Planning B: Planning and Design 24 (1), 125–143. Barde, J.-P., Button, K., 1990. Introduction. In: Barde, J.-P., Button, K. (Eds.). Transport Policy and the Environment. Six Case Studies, Earthscan, London, pp. 1–18. Commission of the European Communities, 1992. The Impact of Transport on the Environment. Office for Official Publications of the European Communities, Luxembourg. Commission of the European Communities, 1998. Communication from the Commission on Transport and CO2 —Developing a Community Approach. Office for Official Publications of the European Communities, Luxembourg.

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