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Methodology for predicting vehicle emissions on motorways and their impact on air quality in the Netherlands
the Science of the Total E n v i r o n m e n t ELSEVIER
The Science of the Total Environment 146/147 (1994) 359-364
i
Methodology for predicting vehicle emissions on motorways and their impact on air quality in the Netherlands A.H. Versluis Road and Hydraulic Engineering Division, Ministry of Transport and Public Works, P.O. Box 5044, 2600 Delft, Netherlands
Abstract In 1989 the Road and Hydraulic Engineering Division of the Dutch Ministry of Transport and Public Works undertook to develop a system for predicting the concentration of air pollutants emitted by road vehicles travelling on motorways and for assessing the impact alternative routes have on air quality. The first stage of the development programme has recently been completed and has resulted in a methodology being devised that allows users to determine the average annual emission levels and concentrations of carbon monoxide, nitrogen oxides, total hydrocarbons, sulphur (tioxide, aerosols, benzene, benzo[a]pyrene and lead. This system is now available in the form of a handbook, and development work is continuing on a software version. The calculation method used in the handbook version of the model assumes that a given stretch of road can be divided into individual sections, along which key traffic parameters, environmental factors and the condition of the road do not change significantly. Use of this version of the model allows calculations to be made of vehicle emissions and pollutant concentrations as a function of distance from the road under various weather and environmental conditions, as well as exposure levels at peripheral structures. Analyses can be performed both for individual road sections and complete stretches of motorway. The model also enables assessments to be made of the relative merits of a range of alternative routes. Key words: Air pollution; Motorways; Environmental impact assessment; Handbook
1. Introduction In the Netherlands there is a statutory requirement for environmental impact assessments to be performed before road building schemes can be approved. When the merits of proposed schemes are being assessed, detailed consideration is given to air quality aspects. As the authority responsible for planning and constructing motorways, the Rijkswaterstaat (Department of Public Works) has
committed itself to developing a methodology for predicting the concentration of air pollutants emitted by road vehicles travelling on motorways and for assessing the impact this has on air quality. It is felt that such a methodology will enable environmental assessments to be made at an early stage in the planning cycle and facilitate the use of iterative techniques to optimise the various alternatives under consideration. It is also expected that this should simplify planning procedures in
0048-9697/94/$07.00 © 1994 Elsevier Science B.V. All rights reserved. SSDI 0048-9697(93)03494-M
360
that it will avoid the need for detailed design work to be performed on a range of alternative routes before meaningful environmental assessments can be made. The Road and Hydraulic Engineering Division of the Department of Public Works has recently developed a simplified model for predicting air quality parameters in closely defined situations. This version of the model, which has been published in the form of a handbook, is especially useful for assessing the impact of roads that do not pass through built-up areas. It is less well suited for performing detailed assessments in urban areas, as the model only takes limited account of the impact of obstacles such as houses on dispersion. The Road and Hydraulic Engineering Division is currently developing a software version of the model to extend the range of applications and to speed up assessment procedures. This paper describes the main technical features of the model as published in handbook form. Particular attention is focused on the following aspects: air pollution caused by road traffic; road traffic emissions; the concentration of pollutants in the vicinity of roads and related dispersion; and the impact on air quality of alternative routes.
2. Air pollution caused by road traffic In view of the steady growth in the number of kilometres travelled by car, road traffic has become an important source of air pollution in Europe. Much of this pollution derives from society's dependence on fossil fuels, with pollution levels being particularly acute in densely populated areas and along busy motorways. The concentration of pollutants released into the atmosphere is largely a function of engine size, fuel type, driving behaviour and speed of travel. An overview of the key pollutants emitted by typical cars on the road is given in Table 1 as a function of fuel type. It is, however, important to note that road traffic is not the only source of air pollution in developed countries. Table 2 compares the emission levels from road traffic with other sources of air pollution in the Netherlands.
A.H. Versluis /Sci. Total Environ. 146/147 (1994) 359-364 Table 1 Key pollutants emitted by motor vehicles Petrol engine
LPG engine
Diesel engine
CO NO x
CO a NO x
CO a NOx a
CxHy
CxHy
CxHy
PAH Benzene
PAH Formaldehyde Aldehydes Aerosols and soot
Aerosols Lead Offensive odours
aMuch less than other engines of the same size. Source: Central Bureau of Statistics, 1986 Ill.
Reference to Table 2 shows that road traffic is the most important source of carbon dioxide, lead and hydrocarbons pollutants discharged into the atmosphere in the Netherlands. It is also responsible for half the NOx emissions in the country. Nevertheless, it can be seen that only limited amounts of sulphur dioxide and aerosols are emitted by road vehicles.
3. Road traffic emissions To calculate the amount of air pollution that is likely to be emitted by road traffic on a given Table 2 Proportion of air pollutants emitted by road traffic in the Netherlands, 1985 Road traffic (t × 103)
Other sources (t × 103)
Contribution due to road traffic (%)
Relative pollution loading from passenger cars
(%) CO NO x
CxHy Benzene Aldehydes Aerosols Lead
905 279 169 6.4 5 25 1.3
388 237 261 1.8 2.6 70 0.3
70 54 39 78 66 26 81
Source: Central Bureau of Statistics, 1986 [1].
96 63 88 80 58 15 91
361
A.H. Versluis /Sci. Total Environ. 146/147 (1994) 359-364
stretch of motorway, it is necessary to divide the road into discrete sections. To determine the emission levels in a particular area, users are required to input a number of key traffic factors. The emission level E of a particular substance s can be calculated using Eq. 1: E s [g/24 h] = I x L x (A x E a + B
x Eb+C
X Ec)
(1)
where I = traffic intensity [vehicles/24 h] A = proportion of passenger cars [% x 0.01] B = proportion of light commercial vehicles [% x 0.01] C = proportion of heavy goods vehicles [% × 0.01] E a=emission factor for an average car [g/kg/vehicle] Eb = emission factor for an average light commercial vehicle [g/kg/vehicle] Ec = emission factor for an average heavy goods vehicle [g/kg/vehicle] L = length of the individual road section [km]
surrounding terrain (i.e. the density of the vegetation and the proportion of obstacles such as buildings that are present in the vicinity). Dilution factors have been determined as a function of the distance perpendicular to the road axis for various weather conditions (Schiphol and Eindhoven) and for specific roughness categories (terrain classes 2 and 4). These are shown in Fig. 2. It should be noted, however, that no account has been taken of the orientation of the road relative to the wind direction. By multiplying the dilution factors by the traffic intensity at a given location and the average emission factors, it is possible to calculate average annual pollutant concentrations at distances of up to 500 m from the centre of the road. To simplify the methodology used in the handbook version of the model, it was decided to differentiate between two characteristic weather patterns in the Netherlands, as shown in Fig. 2. In addition, only two roughness categories have been included. The dilution factors that have been
The total emission loading associated with a given stretch of road can be calculated as the sum of the emission loadings on the individual sections of road.
_Mr;
4. Dispersion patterns and concentrations To determine the degree to which pollutants disperse as a function of distance from motorways, use is made of dilution factors. The dilution factors at a given distance from a motorway represent the ratio of pollutant concentrations to emission rates (~ = C/E). The dilution factors used in the predictive system developed by the Road and Hydraulic Engineering Division have been derived from calculations performed with a detailed dispersion model, using long-term meteorological data such as the prevalence of certain wind directions, wind speeds and turbulence parameters. Turbulence parameters are important in that they allow account to be taken of the roughness of the
i
building
~ rF
tree
~' tow wooded oreo x A G receptor
/
~0 ~E •
dlv~ing-pomt 1 16 number of rood section xA O receptor
/~
/' ,~
O~
~U
Fig. 1. Case study area: Ca) plan view; (b) diagrammatic representation of individual road sections.
,4.H. l/ersluis /Sci. Total Environ. 146/147 (1994) 359-364
362
oo
rarefactionfacfor ~ (s/m 2)
0.28]~ t 0.20_1
0.12
roughness
meteostation • Schiphol • Schiph0l o Eindhoven
/'
classification
2 4
2
4j
SCHIPHOL
,;
~'~/
EINDHOVEN,.
"~',
'-,
-.-
'
0.0/~ £3 J
II
I
I
I
I
I
0 10 30 60 5
20
I
160
260
80
360 d i s t a n c e from
'1
5O0 4o0 road- middte (m)
Fig. 2. Dilution factors as function of distance from centre of road.
determined for a class 2 surface roughness are representative of open terrain (e.g. meadows with a few trees), while those that have been determined for a class 4 roughness are representative of residential areas (e.g. high density of low-rise buildings, woodland or low-rise industrial buildings). Nomographs are supplied with the handbook, which allow the user to calculate the contribution road traffic makes to the average annual concentration of a particular pollutant in a given area. An example of such a nomograph is shown in Fig. 3. Each nomograph consists of three parts. The first graph enables the user to calculate the average emission factor on the basis of average vehicular speed and the proportion of heavy goods traffic expected to use the road. Projecting these data onto the second graph allows the traffic intensity to be determined, and in the third graph the user
can read off the concentration for a given distance from the centre of the road. To calculate the total average annual concentration of a particular pollutant, the background level must be added to the contribution from passing traffic, as shown in Eq.2: Cannual average = ACtraffic + Cbackground
(2)
For this purpose, use is made of data collected by a national network of monitoring stations, which measure the average background concentrations of all major pollutants in the Netherlands. Using this data, global background concentrations have been determined for specific areas, with a distinction being made between the north of the country, the south of the country, large cities and the centres of medium-sized towns. However, more accurate estimates can be obtained with the
A.H. Versluis /Sci, Total Environ. 146/147 (1994) 359-364 benzo(a) pyrene
o
10-
(b
@
> 10 2_ number of vehides m 2t, hours 3_
t_- 10
r
percentage lorries (%)
f
o
zo,,
~, 10 ~
£
363
The assessment procedure is as follows. For each alternative route, calculate the sum of the weighting factors of the individual pollutants which that can be applied to the assessment parameters for each of the target pollutants. The weighting factor for a particular substance that is associated with a given route is defined as
10
groute, substance
40 80 120 average vehlde velocity, km/h
101 [ONCENTRATION NOMOGRAM 10c
Wroute, substance -
® Schiphol roughness classification 2
=
(3) Ezero, substance
A
distonce from
~. 10 2
where: Eroute, substance"- the value of the assessment parameter for the alternative route under consideration Ezero, substance----" the value of the assessment parameter for the zero option.
o 10 ~
ld"
10 5
The sum of the weighting factors over the individual pollutants gives an indication of the degree of change in the assessment parameter under consideration. The order of priority to be attached to the given routes for an assessment parameter is determined by the relative sum,
Fig. 3. Emission nomograph for benzo[a]pyrene RSrout e =
model if actual background concentrations are substituted in Eq. 2. 5. Comparing alternatives on the basis of air pollution aspects
To compare the relative merits of alternative motorway routes, use is made of a system of weighting factors and quality ratings. These parameters quantify any changes relative to the existing situation or zero option. Each alternative route is assessed in relation to the individual pollutants that are defined in the handbook, with the analysis being performed for the entire stretch of motorway. Specific reference is made to the following assessment parameters: (i) total emission loadings; (ii) total pollutant concentrations at a number of selected locations; (iii) total exposure levels at peripheral structures.
Wroute, substance
(4)
Wzero, substance
where: RSrout e = the relative sum associated with a given route in respect of an individual assessment parameter. The lower the relative sum associated with a particular route, the better the ranking that is accorded to this route in relation to the specific assessment parameter under consideration. If the relative sum calculated for a given route is lower than 1, this means that the route can be considered an improvement on the existing situation, or the so-called zero option. To combine the individual assessment parameters, use is made of the following equation:
RSroute, overall= ~RSroute
(5)
where RSrout e - - t h e
relative sum for a given route in
364
relation to an individual assessment parameter; RSroute, overall_.w.the relative sum for a given route in relation to all assessment parameters combined; i = individual assessment parameter. 6. Conclusions and discussion
Although the methodology described in this paper is not sufficiently detailed or precise to replace existing calculation procedures included in environmental impact assessments for determining the effect road traffic has on air quality, it can be used for assessing the relative merits of alternative motorway routes. The Road and Hydraulic Engineering Division is currently engaged in developing a software version of the system, which will allow more complex situations to be studied to a higher degree of accuracy. A computer-based model will have the added
A.H. Versluis /Sci. Total Environ. 146/147 (1994) 359-364
advantage that calculations can be performed more rapidly and require less effort on the part of the user. This will allow planners to perform iterative calculations to optimise the various alternative road schemes under consideration by minimising the impact on air quality.
7. References
1 Central Bureau of Statistics, Luchtverontreiniging: Emissies door Wegverkeer, 1978-1984: Milieustatistieken. Staatsuitgeverij, Den Haag, 1986. 2 National Institute of Public Health and Environmental Protection, Luchtkwaliteit Jaarverslag 1986. RIVM, Laboratorium voor Luchtonderzoek, 1988. 3 J. den Boeft, Voorspellingssysteem Luchtkwaliteit voor Wegtrace-varianten (MI-OWo89-18). Rijkswaterstaat [Department of Public Works], Road and Hydraulic Engineering Division, 1989.
The Science of the Total Environment 146/147 (1994) 359-364
i
Methodology for predicting vehicle emissions on motorways and their impact on air quality in the Netherlands A.H. Versluis Road and Hydraulic Engineering Division, Ministry of Transport and Public Works, P.O. Box 5044, 2600 Delft, Netherlands
Abstract In 1989 the Road and Hydraulic Engineering Division of the Dutch Ministry of Transport and Public Works undertook to develop a system for predicting the concentration of air pollutants emitted by road vehicles travelling on motorways and for assessing the impact alternative routes have on air quality. The first stage of the development programme has recently been completed and has resulted in a methodology being devised that allows users to determine the average annual emission levels and concentrations of carbon monoxide, nitrogen oxides, total hydrocarbons, sulphur (tioxide, aerosols, benzene, benzo[a]pyrene and lead. This system is now available in the form of a handbook, and development work is continuing on a software version. The calculation method used in the handbook version of the model assumes that a given stretch of road can be divided into individual sections, along which key traffic parameters, environmental factors and the condition of the road do not change significantly. Use of this version of the model allows calculations to be made of vehicle emissions and pollutant concentrations as a function of distance from the road under various weather and environmental conditions, as well as exposure levels at peripheral structures. Analyses can be performed both for individual road sections and complete stretches of motorway. The model also enables assessments to be made of the relative merits of a range of alternative routes. Key words: Air pollution; Motorways; Environmental impact assessment; Handbook
1. Introduction In the Netherlands there is a statutory requirement for environmental impact assessments to be performed before road building schemes can be approved. When the merits of proposed schemes are being assessed, detailed consideration is given to air quality aspects. As the authority responsible for planning and constructing motorways, the Rijkswaterstaat (Department of Public Works) has
committed itself to developing a methodology for predicting the concentration of air pollutants emitted by road vehicles travelling on motorways and for assessing the impact this has on air quality. It is felt that such a methodology will enable environmental assessments to be made at an early stage in the planning cycle and facilitate the use of iterative techniques to optimise the various alternatives under consideration. It is also expected that this should simplify planning procedures in
0048-9697/94/$07.00 © 1994 Elsevier Science B.V. All rights reserved. SSDI 0048-9697(93)03494-M
360
that it will avoid the need for detailed design work to be performed on a range of alternative routes before meaningful environmental assessments can be made. The Road and Hydraulic Engineering Division of the Department of Public Works has recently developed a simplified model for predicting air quality parameters in closely defined situations. This version of the model, which has been published in the form of a handbook, is especially useful for assessing the impact of roads that do not pass through built-up areas. It is less well suited for performing detailed assessments in urban areas, as the model only takes limited account of the impact of obstacles such as houses on dispersion. The Road and Hydraulic Engineering Division is currently developing a software version of the model to extend the range of applications and to speed up assessment procedures. This paper describes the main technical features of the model as published in handbook form. Particular attention is focused on the following aspects: air pollution caused by road traffic; road traffic emissions; the concentration of pollutants in the vicinity of roads and related dispersion; and the impact on air quality of alternative routes.
2. Air pollution caused by road traffic In view of the steady growth in the number of kilometres travelled by car, road traffic has become an important source of air pollution in Europe. Much of this pollution derives from society's dependence on fossil fuels, with pollution levels being particularly acute in densely populated areas and along busy motorways. The concentration of pollutants released into the atmosphere is largely a function of engine size, fuel type, driving behaviour and speed of travel. An overview of the key pollutants emitted by typical cars on the road is given in Table 1 as a function of fuel type. It is, however, important to note that road traffic is not the only source of air pollution in developed countries. Table 2 compares the emission levels from road traffic with other sources of air pollution in the Netherlands.
A.H. Versluis /Sci. Total Environ. 146/147 (1994) 359-364 Table 1 Key pollutants emitted by motor vehicles Petrol engine
LPG engine
Diesel engine
CO NO x
CO a NO x
CO a NOx a
CxHy
CxHy
CxHy
PAH Benzene
PAH Formaldehyde Aldehydes Aerosols and soot
Aerosols Lead Offensive odours
aMuch less than other engines of the same size. Source: Central Bureau of Statistics, 1986 Ill.
Reference to Table 2 shows that road traffic is the most important source of carbon dioxide, lead and hydrocarbons pollutants discharged into the atmosphere in the Netherlands. It is also responsible for half the NOx emissions in the country. Nevertheless, it can be seen that only limited amounts of sulphur dioxide and aerosols are emitted by road vehicles.
3. Road traffic emissions To calculate the amount of air pollution that is likely to be emitted by road traffic on a given Table 2 Proportion of air pollutants emitted by road traffic in the Netherlands, 1985 Road traffic (t × 103)
Other sources (t × 103)
Contribution due to road traffic (%)
Relative pollution loading from passenger cars
(%) CO NO x
CxHy Benzene Aldehydes Aerosols Lead
905 279 169 6.4 5 25 1.3
388 237 261 1.8 2.6 70 0.3
70 54 39 78 66 26 81
Source: Central Bureau of Statistics, 1986 [1].
96 63 88 80 58 15 91
361
A.H. Versluis /Sci. Total Environ. 146/147 (1994) 359-364
stretch of motorway, it is necessary to divide the road into discrete sections. To determine the emission levels in a particular area, users are required to input a number of key traffic factors. The emission level E of a particular substance s can be calculated using Eq. 1: E s [g/24 h] = I x L x (A x E a + B
x Eb+C
X Ec)
(1)
where I = traffic intensity [vehicles/24 h] A = proportion of passenger cars [% x 0.01] B = proportion of light commercial vehicles [% x 0.01] C = proportion of heavy goods vehicles [% × 0.01] E a=emission factor for an average car [g/kg/vehicle] Eb = emission factor for an average light commercial vehicle [g/kg/vehicle] Ec = emission factor for an average heavy goods vehicle [g/kg/vehicle] L = length of the individual road section [km]
surrounding terrain (i.e. the density of the vegetation and the proportion of obstacles such as buildings that are present in the vicinity). Dilution factors have been determined as a function of the distance perpendicular to the road axis for various weather conditions (Schiphol and Eindhoven) and for specific roughness categories (terrain classes 2 and 4). These are shown in Fig. 2. It should be noted, however, that no account has been taken of the orientation of the road relative to the wind direction. By multiplying the dilution factors by the traffic intensity at a given location and the average emission factors, it is possible to calculate average annual pollutant concentrations at distances of up to 500 m from the centre of the road. To simplify the methodology used in the handbook version of the model, it was decided to differentiate between two characteristic weather patterns in the Netherlands, as shown in Fig. 2. In addition, only two roughness categories have been included. The dilution factors that have been
The total emission loading associated with a given stretch of road can be calculated as the sum of the emission loadings on the individual sections of road.
_Mr;
4. Dispersion patterns and concentrations To determine the degree to which pollutants disperse as a function of distance from motorways, use is made of dilution factors. The dilution factors at a given distance from a motorway represent the ratio of pollutant concentrations to emission rates (~ = C/E). The dilution factors used in the predictive system developed by the Road and Hydraulic Engineering Division have been derived from calculations performed with a detailed dispersion model, using long-term meteorological data such as the prevalence of certain wind directions, wind speeds and turbulence parameters. Turbulence parameters are important in that they allow account to be taken of the roughness of the
i
building
~ rF
tree
~' tow wooded oreo x A G receptor
/
~0 ~E •
dlv~ing-pomt 1 16 number of rood section xA O receptor
/~
/' ,~
O~
~U
Fig. 1. Case study area: Ca) plan view; (b) diagrammatic representation of individual road sections.
,4.H. l/ersluis /Sci. Total Environ. 146/147 (1994) 359-364
362
oo
rarefactionfacfor ~ (s/m 2)
0.28]~ t 0.20_1
0.12
roughness
meteostation • Schiphol • Schiph0l o Eindhoven
/'
classification
2 4
2
4j
SCHIPHOL
,;
~'~/
EINDHOVEN,.
"~',
'-,
-.-
'
0.0/~ £3 J
II
I
I
I
I
I
0 10 30 60 5
20
I
160
260
80
360 d i s t a n c e from
'1
5O0 4o0 road- middte (m)
Fig. 2. Dilution factors as function of distance from centre of road.
determined for a class 2 surface roughness are representative of open terrain (e.g. meadows with a few trees), while those that have been determined for a class 4 roughness are representative of residential areas (e.g. high density of low-rise buildings, woodland or low-rise industrial buildings). Nomographs are supplied with the handbook, which allow the user to calculate the contribution road traffic makes to the average annual concentration of a particular pollutant in a given area. An example of such a nomograph is shown in Fig. 3. Each nomograph consists of three parts. The first graph enables the user to calculate the average emission factor on the basis of average vehicular speed and the proportion of heavy goods traffic expected to use the road. Projecting these data onto the second graph allows the traffic intensity to be determined, and in the third graph the user
can read off the concentration for a given distance from the centre of the road. To calculate the total average annual concentration of a particular pollutant, the background level must be added to the contribution from passing traffic, as shown in Eq.2: Cannual average = ACtraffic + Cbackground
(2)
For this purpose, use is made of data collected by a national network of monitoring stations, which measure the average background concentrations of all major pollutants in the Netherlands. Using this data, global background concentrations have been determined for specific areas, with a distinction being made between the north of the country, the south of the country, large cities and the centres of medium-sized towns. However, more accurate estimates can be obtained with the
A.H. Versluis /Sci, Total Environ. 146/147 (1994) 359-364 benzo(a) pyrene
o
10-
(b
@
> 10 2_ number of vehides m 2t, hours 3_
t_- 10
r
percentage lorries (%)
f
o
zo,,
~, 10 ~
£
363
The assessment procedure is as follows. For each alternative route, calculate the sum of the weighting factors of the individual pollutants which that can be applied to the assessment parameters for each of the target pollutants. The weighting factor for a particular substance that is associated with a given route is defined as
10
groute, substance
40 80 120 average vehlde velocity, km/h
101 [ONCENTRATION NOMOGRAM 10c
Wroute, substance -
® Schiphol roughness classification 2
=
(3) Ezero, substance
A
distonce from
~. 10 2
where: Eroute, substance"- the value of the assessment parameter for the alternative route under consideration Ezero, substance----" the value of the assessment parameter for the zero option.
o 10 ~
ld"
10 5
The sum of the weighting factors over the individual pollutants gives an indication of the degree of change in the assessment parameter under consideration. The order of priority to be attached to the given routes for an assessment parameter is determined by the relative sum,
Fig. 3. Emission nomograph for benzo[a]pyrene RSrout e =
model if actual background concentrations are substituted in Eq. 2. 5. Comparing alternatives on the basis of air pollution aspects
To compare the relative merits of alternative motorway routes, use is made of a system of weighting factors and quality ratings. These parameters quantify any changes relative to the existing situation or zero option. Each alternative route is assessed in relation to the individual pollutants that are defined in the handbook, with the analysis being performed for the entire stretch of motorway. Specific reference is made to the following assessment parameters: (i) total emission loadings; (ii) total pollutant concentrations at a number of selected locations; (iii) total exposure levels at peripheral structures.
Wroute, substance
(4)
Wzero, substance
where: RSrout e = the relative sum associated with a given route in respect of an individual assessment parameter. The lower the relative sum associated with a particular route, the better the ranking that is accorded to this route in relation to the specific assessment parameter under consideration. If the relative sum calculated for a given route is lower than 1, this means that the route can be considered an improvement on the existing situation, or the so-called zero option. To combine the individual assessment parameters, use is made of the following equation:
RSroute, overall= ~RSroute
(5)
where RSrout e - - t h e
relative sum for a given route in
364
relation to an individual assessment parameter; RSroute, overall_.w.the relative sum for a given route in relation to all assessment parameters combined; i = individual assessment parameter. 6. Conclusions and discussion
Although the methodology described in this paper is not sufficiently detailed or precise to replace existing calculation procedures included in environmental impact assessments for determining the effect road traffic has on air quality, it can be used for assessing the relative merits of alternative motorway routes. The Road and Hydraulic Engineering Division is currently engaged in developing a software version of the system, which will allow more complex situations to be studied to a higher degree of accuracy. A computer-based model will have the added
A.H. Versluis /Sci. Total Environ. 146/147 (1994) 359-364
advantage that calculations can be performed more rapidly and require less effort on the part of the user. This will allow planners to perform iterative calculations to optimise the various alternative road schemes under consideration by minimising the impact on air quality.
7. References
1 Central Bureau of Statistics, Luchtverontreiniging: Emissies door Wegverkeer, 1978-1984: Milieustatistieken. Staatsuitgeverij, Den Haag, 1986. 2 National Institute of Public Health and Environmental Protection, Luchtkwaliteit Jaarverslag 1986. RIVM, Laboratorium voor Luchtonderzoek, 1988. 3 J. den Boeft, Voorspellingssysteem Luchtkwaliteit voor Wegtrace-varianten (MI-OWo89-18). Rijkswaterstaat [Department of Public Works], Road and Hydraulic Engineering Division, 1989.