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The application of the simulation software VeTESS to evaluate the environmental impact of traffic measures

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This paper demonstrates how the environmental consequences of traffic measures can be evaluated using the simulation software VeTESS. VeTESS (VEhicle Transient Emissions Simulation Software) was developed within the EU 5th framework project DECADE (2001-2003) as a vehicle level simulation tool for the simulation of fuel consumption and emissions. It is specifically designed to calculate dynamic emissions, reaching higher accuracy than traditional emission simulation models. Two different traffic measures were evaluated using the simulation software VeTESS. First the impact of a speed limiting measure, the conversion of 50 km/h zones into 30 km/h zones, on vehicle emissions was examined. The second application of VeTESS concerns the evaluation of a different gear changing behavior on vehicle exhausts.
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Paper 57 1
THE APPLICATION OF THE SIMULATION SOFTWARE VETESS TO EVALUATE
THE ENVIRONMENTAL IMPACT OF TRAFFIC MEASURES
Beckx Carolien
PhD Student
Integral Environmental Studies
Flemish Institute of Technological
Research
Boeretang 200
2400 Mol
Belgium
Tel: +32 14 33 59 58
Fax: +32 14 32 11 85
E-mail: carolien.beckx@vito.be
Int Panis Luc
Project manager
Integral Environmental Studies
Flemish Institute of Technological
Research
Boeretang 200
2400 Mol
Belgium
Tel: +32 14 33 55 87
Fax: +32 14 32 11 85
E-mail: luc.intpanis@vito.be
Torfs Rudi
Project and research manager
Integral Environmental Studies
Flemish Institute of Technological
Research
Boeretang 200
2400 Mol
Belgium
Tel: +32 14 33 58 56
Fax: +32 14 32 11 85
E-mail: rudi.torfs@vito.be
Janssens Davy
Researcher
Transportation Research Institute
Hasselt University
Wetenschapspark 5 bus 6
3590 Diepenbeek
Belgium
Tel: +32 11 26 91 28
Fax: +32 11 26 91 99
E-mail:davy.janssens@uhasselt.be
Broekx Steven
Researcher
Integral Environmental Studies
Flemish Institute of Technological
Research
Boeretang 200
2400 Mol
Belgium
Tel: +32 14 33 58 56
Fax: +32 14 32 11 85
E-mail: steven.broekx@vito.be
Abstract: This paper demonstrates how the environmental consequences of traffic
measures can be evaluated using the simulation software VeTESS. VeTESS
(VEhicle Transient Emissions Simulation Software) was developed within the EU 5th
framework project DECADE (2001-2003) as a vehicle level simulation tool for the
simulation of fuel consumption and emissions. It is specifically designed to calculate
dynamic emissions, reaching higher accuracy than traditional emission simulation
models. Two different traffic measures were evaluated using the simulation software
VeTESS. First the impact of a speed limiting measure, the conversion of 50 km/h
zones into 30 km/h zones, on vehicle emissions was examined. The second
application of VeTESS concerns the evaluation of a different gear changing behavior
on vehicle exhausts.
Keywords: VeTESS, vehicle emissions, traffic measures, gear change, driving
behavior
Paper 57 2
1. INTRODUCTION
The largest potential to improve fuel-use and reduce pollutant emissions in road
transport probably lies in enhancing vehicle technology. However, such an approach
involves a relatively large implementation time and considerable costs. Furthermore,
these measures are often regulated at a high policy level, limiting the contribution of
the local authorities to this regard. On the other hand, policy measures to improve
fuel economy can also be taken at a lower policy level, like actions focusing on a
change in driving behaviour (De Vlieger et al, 2000).
Speed limiting measures for example, mainly aimed at increasing traffic safety, are
usually seen or even promoted by local authorities as beneficial to the environment
because of reduced fuel consumption and emissions. However, the claims for these
environmental benefits need to be examined thoroughly before drawing any
conclusions. Next to speed limiting measures, actions to stimulate a more
fuel-efficient driving style are also put forward to contribute to a reduction in
environmental pollution. An environmentally friendly driving style includes different
behavioral aspects to obtain a more fuel-efficient driving, one of them being a
selective use of gears (Beckx et al, 2006). Unfortunately, a quantification of the
potential reduction one can achieve with a different gear changing behavior is very
difficult to make.
Before implementing this kind of traffic measures, it is important to assess the
potential benefits of these actions. When public money is spent on schemes
designed to reduce air pollution, policy makers like to know in advance that the
objectives (complying with air quality standards) will be met. Therefore simulation
models are necessary to assess the impact of certain measures.
This paper presents how the simulation model VeTESS was used to assess the
impact of two different traffic measures on vehicle exhaust emissions. It will present
the results of calculations that were made with real driving cycles as with theoretical
driving cycles. Finally, the paper concludes and defines some interesting topics for
further research.
2. THE VETESS EMISSION MODEL
This section provides a brief description of the VeTESS model and the approach that
was used to develop this model. More detailed information can be found in Pelkmans
(2004) or in the VeTESS user manual (VeTESS V1.18B).
2.1 Description of the model
Within the EU 5th framework project DECADE (2001-2003) a vehicle level simulation
tool was developed for the simulation of fuel consumption and emissions of vehicles
in real traffic and transient operation conditions. The final simulation tool, which is
called VeTESS (Vehicle Transient Emissions simulation Software), calculates
emissions and fuel consumption made by a single vehicle during a defined
‘drive-cycle’. The drive cycle is a representation of the route to be driven by the
vehicle. It contains details of the speed of the vehicle and the road gradient over a
complete route. The drive-cycle could be from a recorded journey, calculated from
traffic flow models or produced from knowledge of typical journeys.
Paper 57 3
Starting with a given driving cycle, VeTESS uses simple mathematical calculations
involving gear ratios and their efficiencies to determine the engine’s operating
conditions from the force on the vehicle. The total force on the vehicle is calculated
through the equation of motion, namely: total force = acceleration resistance +
climbing resistance + rolling resistance + aerodynamic resistance. The engine
provides the force required to overcome the resistances to motion. This force is
produced by the engine as a torque. This torque is converted from rotational to linear
motion by the driven wheels.
2.2 DECADE approach for measuring dynamic emissions
Microscopic emission simulation generally starts from a map-based approach. Based
on the second-by-second duty cycle of a vehicle, the engine power and speed is
calculated. The simulation procedure assumes that the engine moves through a
series of “quasi steady-state” conditions, described by a combination of engine speed
and torque. The emissions and fuel consumption associated to each one of these
quasi steady-state conditions can be looked up on so-called emissions maps.
These maps are generated by operating the engine in a series of steady-state
conditions. In reality, the production of pollutants depends to a large extent on the
rate of change of load. Some of the emissions are generated by the change itself,
rather than as a function of a series of steady states. These dynamic, or “transient”
effects must be taken into account when doing the simulation. Therefore, the aim of
the DECADE project was to convert the quasi steady-state method into one that
takes into account the dynamic behavior of the engine system. The key implication
of this is that a new method of characterizing engine behavior had to be developed
that includes the description of transient effects.
Within the new measuring procedure, the effect on emissions and fuel consumption
of sudden torque changes (in a step of about 0.2 seconds) at constant speed are
recorded on an engine test bed. Based on three independent variables from the
experimental procedure, namely engine speed, engine torque and change in torque,
four parameters are defined for each pollutant: steady state emission rate, jump
fraction, time constant and transient emissions. The steady state emission rate is the
rate at which the pollutant is produced as the engine runs under steady state, i.e. at
constant speed and torque. The jump fraction characterizes the fraction by which the
emission rate increases or decreases after a change in torque not taking into account
the dynamic behaviour. The time constant is a measure for the time required to
approach the steady state emission value after a torque change. The transient
emission is a discreet amount of additional pollutant generated after the change of
torque. The overall emissions of the trip are obtained by adding up the emissions
produced under the different load conditions during the drive cycle. The emissions
considered are CO2, CO, HC, NOx and PM.
A lot of effort is put in the user-friendliness of VeTESS. The following
Figure 1 shows a typical user interface of VeTESS.
Paper 57 4
Figure 1: Example of the VeTESS user interface
2.3 Vehicle types
VeTESS calculates the emissions per second for CO2, CO, NOx, HC and PM based
on second-by-second speed profiles. The speed profiles can either be made
theoretically or recorded from real vehicle trips. For the moment, concerning
passenger cars, detailed engine maps are only available for three types of cars: a
Euro II LGV, a Euro III diesel car and a Euro IV petrol car (Table 1).
Table 1. The vehicle types considered in the VeTESS emissions model (Beevers and
Carslaw, 2005)
Skoda Octavia 1.9 Tdi Citroen Jumper 2.5D
VW Polo 1.4 16V
Engine size 1896 cm3 diesel engine 2446 cm3 diesel
engine
1390 cm3 petrol
engine
Fuel system Direct injection Indirect injection Multipoint fuel
injection
Euro class EURO III certified EURO II certified EURO IV certified
Max. power 66 kW at 4000 rpm 63 kW at 4350 rpm 74 kW at 6000 rpm
Max. torque 210 Nm at 1900 rpm 153 Nm at 2250 rpm 126 Nm at 4400
rp
m
Engine aspiration Turbo + intercooler
Exhaust gas
recirculation
Yes Yes Yes
Emissions control
device
Oxidation catalyst Oxidation catalyst Lambda control
three
way catalyst +
Paper 57 5
3. EVALUATION OF TRAFFIC MEASURES
In this section we demonstrate how the VeTESS emission model was used to assess
the environmental impact of two different traffic measures. First the impact of a speed
limiting measure was evaluated and next we examined the effect of a different gear
changing behavior on emissions.
3.1 Introduction of 30 km/h zones in urban areas
3.1.1 Description of the traffic measure
Since September 1st 2005 zone 30 stretches are mandatory near all Belgian schools
with some exceptions made for schools on the busiest regional roads. The
conversion of entire districts, streets or street sections into 30 km/h zones was
usually done in residential areas where the previous speed limit was 50 km/h (e.g.
city of Ghent; Int Panis et al, 2005).
These measures are usually seen as beneficial to the environment because of
reduced fuel consumption and emissions. The claims for these environmental
benefits stem from the believe that speed reduction measures in urban areas have
similar benefits as those on highways (Int Panis et al., 2006a). However, in contrast
to this popular believe, wide spread emission estimation methods using quadratic
functions such as the Copert/MEET approach would lead us to believe that
emissions may even rise dramatically. Unfortunately the speeds typical for urban
traffic (esp. congested traffic) are very close to or lower than what is usually
considered to be the minimum average trip speed for which relevant estimates can
still be made using the Copert/MEET approach (Int Panis et al., 2006b). Apparently
more sophisticated methods are needed to estimate the impact of this measure.
Therefore the VeTESS-tool was used to calculate the environmental effects of the
introduction of zone 30 stretches on vehicle exhaust emissions in urban areas.
VeTESS modeled the emissions for real-life urban driving cycles and for artificially
modified driving cycles limiting the top speed to 30 km/h. A comparison could then be
made between the emission results for both situations.
3.1.2 Description of the driving cycles
Modeled driving cycles were recorded during on-the-road emission measurements in
the cities of Mol (32 474 inhabitants, Belgium) and Barcelona (4.2 million inhabitants,
Spain), using three different vehicles: VW Polo (Euro 4, petrol), Skoda Octavia (Euro
3, diesel) and a Citroen Jumper (Euro 3, diesel) light commercial vehicle. We believe
these vehicles are representative for an important fraction of current car sales in
Belgium. We refer to Pelkmans et al. (2004) for a detailed technical description of the
vehicles and set-up of the test cycles.
From each of the 6 different driving cycles we derived a modified version in which the
top speed was limited to 30 km/h without changing the acceleration or deceleration.
The length of time driven at the new top speed was elongated to preserve the original
cycle distance. Figure 2 shows an example comparison between one of the original
driving cycles and the derived cycle.
Paper 57 6
Figure 2. Example showing the conversion of cycle 6 to a cycle with limited top speed
Table 2 shows a summary of statistics describing the cycles and the modifications
that were made. It is clear from the average speeds and the number of stops that
these cycles represent urban trips in heavy traffic.
Table 2. Summarized descriptive statistics for the urban driving cycles used in this
study (Cycles 1-3: Barcelona, Cycles 4-6: Mol). Data for modified cycles in last two
columns.
Cycle
Length Stops Max a Max -a Avg v Additional
length
New
avg v
(s) (km) m/s.s -m/s.s km/h (s) km/h
1 1615 6.6 22 7.8 10.2 14.8 107 13.9
2 1765 7.1 27 7.8 10.5 14.5 72 13.9
3 1475 7.3 22 9.4 15.4 17.8 173 15.9
4 1497 10.5 16 8.3 11.3 25.2 163 22.7
5 2003 10.5 22 6.7 8.8 18.9 68 18.3
6 1735 10.5 22 9 11.3 21.8 125 20.3
3.1.3 Results
The emissions of each of the three vehicles were modeled with each of the 6
available urban driving cycles, resulting in 18 emission estimates for a reduction of
the top speed from 50 km/h to 30 km/h. Overall results are summarized in Figure 3.
Positive values indicate that emissions go up when the new speed limit is
implemented. Negative values indicate that pollutant emissions decrease.
Driving Cycle
Barcelona Urban
0
10
20
30
40
50
60
1 121 241 361 481 601 721 841 961 1081 1201 1321 1441 1561 1681
Time (seconds)
Speed (km/h)
Derived cycle
Original cycle
Paper 57 7
Results for CO and HC differ widely between vehicles and cycles. Because
emissions of these pollutants are very low in modern cars, we believe that they are
not modeled with sufficient accuracy to lend credibility to the relative changes shown
in the graph (even a 100% increase represents only a tiny amount of pollutants
emitted, close to the smallest amount that can be measured). For the emissions of
CO2 and hence fuel consumption it was found that the change to the driving cycle
only had a limited impact, either positive or negative, on the emission. Concerning
the emissions of NOx the model results differ between cycles and vehicle types. Both
diesel vehicles (Octavia and Jumper) showed a moderate to large decrease in the
modeled emissions of PM in each of the cycles (no PM emissions could be modeled
with VeTESS for petrol fueled vehicles).
Figure 3: Estimated relative change in emission for 5 pollutants. Average and range
for 18 estimates.
In Figure 4 we present the detailed VeTESS results for the Skoda Octavia for one
representative cycle in each city. Results for most other vehicle/cycle combinations
yield similar results. It is clear that emissions of CO2, NOx and PM decrease in each
situation for this specific vehicle. This is the combined result of lower top speeds,
longer driving periods at 30 km/h and extended driving to reach the end of the cycle
(i.e additional length in Table 2). Emissions of CO2 are marginally smaller and NOx
emission factors are also lower. The largest reduction however is found for emissions
of PM which decrease in most cases by approximately one third.
-100%
-50%
0%
50%
100%
150%
200%
CO2 (g/km) CO (g/km) NOx (g/km) HC (g/km) PM (g/km)
Paper 57 8
Figure 4. Relative change between two normal urban drive cycles (up to 50km/h) and
drive cycles limited at 30 km/h (Skoda Octavia; Cycle 4: 25.2->22.7 km/h in Mol,
Cycle 1: 14.8->13.9 km/h in Barcelona
In Figure 5 we present some detailed results for the light delivery van. In this case
the result of detailed emission modeling predicts a slight increase for both fuel
consumption and CO2 emissions. Results for NOx emissions are mixed, but for the
PM emissions, this vehicle would show an important decrease (although smaller than
for the passenger cars) under the speed-limited driving cycle.
Figure 5: Relative change in emissions between two urban driving cycles and a
derived cycle limited at 30 km/h (Citroen Jumper Van; Cycle 5: 18.9 -> 18.3 km/h in
Mol, Cycle 2: 14.5 ->13.9 km/h in Barcelona)
-20%
-15%
-10%
-5%
0%
5%
10%
Mol Barcelona
CO2 (g/km)
NOx (g/km)
PM (g/km)
-40%
-30%
-20%
-10%
0%
10%
Mol Barcelona
CO2 (g/km)
NOx (g/km)
PM (g/km)
Paper 57 9
3.2 Introduction of an environmentally friendly gear changing behavior
3.2.1 Description of the traffic measure
Environmentally friendly driving includes different behavioral aspects to obtain a
more fuel-efficient driving, one of them implying a selective use of gears. By shifting
up gear early one can avoid high engine speeds and therefore should achieve a
reduction of emissions and fuel consumption (Beckx et al, 2006). Campaigns and
education should be organized to inform people, especially drivers with an
aggressive driving style, about this potential fuel-saving technique.
Before investing in campaigns that stimulate people to display an environmentally
friendly driving behavior authorities are interested in knowing the potential impact of
this kind of measure. What will it yield to avoid people from driving aggressively?
Since the VeTESS model is able to simulate different kinds of gear changing
behavior, this simulation tool is suited for this kind of impact assessment.
3.1.2 Description of the driving cycles
Real-life driving cycles were obtained in a small scale travel survey collecting trip
information from 32 respondents driving a diesel car for a period varying from two
days to one week. The use of a GPS receiver allowed to acquire accurate
second-by-second trip information (speed, location,…) for every vehicle trip during
the survey. In total 235 vehicle trips were recorded by the GPS receiver and these
were used for the calculation of emission estimates and fuel consumption with the
VeTESS emission model.
When calculating the emissions for certain driving cycles with VeTESS one can
indicate which gear changing behavior, gentle, normal or aggressive, is most
appropriate for each driving cycle. VeTESS uses specific gear change rules to
determine the gear change points for the vehicle for each of these driving styles. A
custom option is also available allowing the user to alter the values to suit a particular
driving style.
When selecting the ‘normal’ gear changing assumptions VeTESS will simulate
average engine speeds and an average number of gear changes over a given route.
‘Normal’ gear changing settings will assume a gear shift to a higher gear when the
engine speed exceeds 55% of the maximum engine speed. For this case study, only
the passenger diesel car was used for modeling in VeTESS (see Table 1). The
maximum engine speed for this EURO III diesel car in the model amounts 4800 rpm.
The ‘aggressive’ gear changing assumptions on the other hand will allow higher
engine speeds and less engine torque than values used during normal driving. This
will result in a larger number of gear changes. When using this ‘aggressive’ setting,
gear shifting will occur at 80% of the maximum engine speed.
3.1.3 Results
This section presents the results of the calculations where 235 real driving cycles
where converted into emission estimates using the VeTESS emission tool. The
results from the emission estimates are presented for the trips made by two different
gear changing assumptions: normal and aggressive.
Paper 57 10
Table 3 and Table 4 present the calculated values for respectively the total emissions
and the emission factors. These results indicate that an aggressive gear changing
behaviour will result in significantly higher emissions of CO2, NOX, PM and HC and in
an increased fuel consumption. This conclusion accounts for the average total values
as well as for the emission factors of those pollutants. The emissions of CO seem to
be influenced differently since an aggressive gear shifting apparently implies a
decrease of the average CO emissions per trip. A paired two-sided t test was
performed on the results to check the differences between the values of different
gear changing settings. The statistical test demonstrated that the differences were all
significant (p<0.05).
Table 3. Average total emissions and fuel consumptions per trip using 2 different
gear changing assumptions.
Fuel CO
2
CO NO
x
PM HC
Normal 0.76 1996.98 0.43 9.31 0.09 0.99
Aggressive
0.95 2475.43 0.28 11.91 0.14 1.24
Ttest
(p
value)
<0.05 <0.05 <0.05 <0.05 <0.05 <0.05
Table 4. Average emissions factors and fuel consumptions per trip using 2 different
gear changing assumptions.
Fuel CO
2
CO NO
x
PM HC
Normal 7.15 186.59 0.05 0.97 0.01 0.09
Aggressive
9.19 240.21 0.03 1.1 0.01 0.12
Ttest
(p
value)
<0.05 <0.05 <0.05 <0.05 <0.05 <0.05
Table 5 and Table 6 present the relative difference of the ‘aggressive’ estimates in
comparison with the ‘normal’ estimates to demonstrate the extra emissions one can
cause by using an aggressive gear changing behaviour (or the reductions of
emissions one can achieve by avoiding an aggressive driving style). In these tables
the results indicate that one will increase the emissions of CO2 and the average fuel
consumption per trip by 30% when applying the aggressive gear changing settings in
the VeTESS model in stead of the normal settings. This means that one can save an
average of 30% of the fuel consumption per trip by avoiding an aggressive gear
change.
The results for the NOx emissions also indicate an increase of the emissions when
the aggressive gear settings were applied. NOx emissions will increase by 15% when
changing gear at higher engine speeds. Concerning the emissions of PM and HC the
results show an average increase of the pollutant emissions of respectively 41 and
38 %. The impact on CO emissions on the other hand shows an average decrease of
the emissions by 30%. Apparently the emissions of this pollutant are influenced
differently than the pollutants mentioned before.
Paper 57 11
Table 5. Average total emissions and fuel consumptions using 2 different gear
changing assumptions. Relative difference of aggressive to normal settings (%).
Fuel CO
2
CO NO
x
PM HC
Aver
age % 29.45 29.47 -29.67 15.79 41.59 38.80
Stdev 8.41 7.88 37.90 17.02 29.44 14.11
Table 6. Average emission factors and fuel consumptions using 2 different gear
changing assumptions. Relative difference of aggressive to normal settings (%).
Fuel CO
2
CO NO
x
PM HC
Average %
29.27 29.35 -29.38 15.74 22.84 38.58
Stdev 7.79 7.86 43.97 17.08 40.54 14.81
4. CONCLUSION
This paper demonstrates how the simulation software VeTESS can contribute to the
assessment of the environmental impact of traffic measures. Two case studies were
examined in this paper. First of all the VeTESS model was used to evaluate the
impact of lowering a speed limit from 50 km/h to 30 km/h. Next, the simulation tool
was applied to assess the impact of an environmentally friendly driving behavior.
Future research should further explore the use of this model for other purposes and
should examine the possibility of using more vehicle types in the model.
ACKNOWLEDGEMENTS
The authors wish to thank Luc Pelkmans for making the VeTESS model and driving
cycles available for this study.
Paper 57 12
REFERENCES
a) Journal papers
Beevers, S.D. and Carslaw D.C. (2005). The impact of congestion charging on
vehicle speed and its implications for assessing vehicle emissions. Atmospheric
Environment, Vol. 39, 6875-6884.
De Vlieger, I., De Keukeleere, D. and Kretzschmar J. G. (2000). Environmental
effects of driving behaviour and congestion related to passenger cars. Atmosferic
Environment, Vol. 34, 4649-4655.
b) Papers presented to conferences
Beckx, C., Int Panis, L., De Vlieger, I. and Wets, G. (2006). Influence of gear
changing behaviour on fuel-use and vehicular exhaust emissions. Proceedings of
the 8th International Symposium on Highways and the Urban Environment.
Rauch S. & Morrisson G. (eds.), Chalmers University (in press).
Int Panis L., Cosemans G., Torfs R., Liekens I., De Nocker L., Broekx S. and Beckx
C. (2005). Mobilee: effect of a local traffic plan on exposure to local air pollution.
Proceedings of the Conference on Transport and Air pollution. VKM-THD
Mitteilungen, Heft/Volume 85/II, pp.13-21.
Int Panis, L., De Vlieger, I., Pelkmans, L., Schrooten, L. (2006a). Effect of speed
reduction on fuel consumption and emissions of heavy duty lorries in Belgium.
Proceedings of the 8th International Symposium on Highways and the Urban
Environment. Rauch S. & Morrisson G. (eds.), Chalmers University. (in press)
Int Panis, L., Beckx, C. and Broekx, S. (2006b). Impact of zone 30 introduction on
vehicle exhaust emissions in urban areas. Proceedings of the European Transport
Conference, Straatsburg, France.
Pelkmans, L., Debal, P., Hood, T., Hauser, G. and Delgado, M.R. (2004).
Development of a simulation tool to calculate fuel consumption and emissions of
vehicles operating in dynamic conditions. SAE 2004 Spring Fuels & Lucbricants ,
2004-01(1873), SAE International (Society of Automotive Engineers), Warrendale,
PA, (USA). 2004.
c) Other documents
VeTESS User Manual. Software version V1.18B
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This study explores the influence of gear-changing behaviour on vehicular exhaust emissions and fuel consumption using real drive cycles as an input. As many as 235 different drive cycles, recorded from people participating in a survey, were imported in an emission simulation tool called Vehicle Transient Emissions Simulation Software (VeTESS). Emissions and fuel consumption were calculated with VeTESS using two different gear change assumptions (normal and aggressive). This paper reports on the differences in vehicle exhaust emissions between trips made with those two different settings.
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Previous analysis of London's congestion charging scheme (CCS) has shown that changes in vehicle speed are an important factor in reducing vehicle emissions. Therefore, a detailed investigation of network average vehicle speed in both central and inner London has been undertaken using a combination of the non-parametric Wilcoxon sign ranks test and a method for calculating the cumulative difference between mean speeds pre- and post-CCS, or cumulative sum (CUSUM) analysis. Within the charging zone (CZ), the Wilcoxon test has shown that the difference in speed between pre- and post-CCS periods has increased on average by 2.1 km h−1 and that these changes are significant at the p=0.05 level. The CUSUM analysis has provided evidence of the timing of this change in mean speed in the CZ and this agrees well with the introduction of the CCS on the 17 February 2003. In combination, these results provide compelling evidence that the introduction of congestion charging has significantly increased vehicle speed in the CZ and by comparison with the results in inner London, that these changes are not part of a wider trend. To examine one impact of this change we used an instantaneous emissions model, the Vehicle Transient Emissions Simulation Software, to undertake a comparison between the change in vehicle emissions associated with changing driving characteristics, between pre- and post-charging periods, and those associated with a change in average speed. The analysis was limited to three vehicle types: a Euro II LGV, a Euro III diesel car and a Euro IV petrol car, but showed that driving characteristics in central London have a relatively small effect on emissions of NOX and CO2 compared with the average vehicle speed. However, for PM10 emissions from the Euro II LGV the opposite was found and for this vehicle the driving characteristics were more important than the average speed in estimating exhaust emissions. For this vehicle, emissions increased between pre- and post-CCS periods by 4%. For the Euro IV petrol car NOX emissions also increased by 6% between pre- and post-CCS periods. These findings will help to further understand the extent to which congestion charging reduces vehicle emissions in London.
Article
Using Vito's on-board measuring system the influence of track, driving behaviour and traffic conditions on fuel consumption and emissions were studied for a small test fleet of passenger cars. City traffic resulted in the highest fuel consumption and emissions. Fuel consumption was about two times higher than for ring roads, which generally gave the lowest values. This was even more pronounced for emissions. Depending on road type and technology, fuel consumption increased with up to 40% for aggressive driving compared to normal driving. Again, this was more pronounced for emissions, with increases up to a factor 8. Driving behaviour had a greater influence on petrol-fuelled than on diesel-fuelled cars.Traffic condition also has a major effect on fuel consumption and emissions. For city driving intense traffic increased fuel consumption by 20–45%. The increase in fuel consumption and emissions during rush hours were the highest on ring roads, with increases between 10 and 200%. In absolute terms, a surplus of up to 5 l fuel per 100 km was measured. More environment-friendly route option requires the use of ring roads and motorways during rush hours instead of short cuts.
Impact of zone 30 introduction on vehicle exhaust emissions in urban areas
  • L Int Panis
  • C Beckx
  • S Broekx
Int Panis, L., Beckx, C. and Broekx, S. (2006b). Impact of zone 30 introduction on vehicle exhaust emissions in urban areas. Proceedings of the European Transport Conference, Straatsburg, France.