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A method of traffic noise prognosis
Applied Acoustics 17 (1984) 21-31
A Method of Traffic Noise Prognosis
B. Buna and L. Vereb Institute for Transport Sciences, Budapest (Hungary) (Received: 15 November, 1982)
SUMMARY This paper describes a simple method for the calculation of changes in noise levels generated by the vehicle population of a country as a whole in future time related to present population. The changes of the total number of vehicles, the introduction of quieter vehicles and the condition of wear of the running stock are taken into account in the model and the change in Leq level is used as the output parameter. The calculated changes in Le~ values are about the same as those of L 1o. The application examples of the model show that this simple method seems to be helpful for decision makers. The examples also allow conclusions for noise control strategy to be developed.
INTRODUCTION To be able to assess the demand for and the choice of protection measures against traffic noise in any future time there is a need for noise forecasting methods. Although the reduction of traffic noise following the introduction of quieter vehicles has- already been satisfactorily investigated t,2 these prediction model applications take into account only the number of new quieter vehicles and the proportion of heavy vehicles. Another paper 3 has tried handling the noise output of the vehicle population as a system problem and developed a technique for calculating truck populations, using variable truck manufacturing and 21 Applied Acoustics 0003-682X/84/$03-00 © Elsevier Applied Science Publishers Ltd, England, 1984. Printed in Great Britain
B. Buna, L. Vereb
22
retirement rates. The real life situation, however, calls for a more complex treatment using more input parameters. On the other hand for the sake of simplicity the number of vehicles in a country should be taken as a whole. This means a representative traffic and vehicle allocation approach.
D E V E L O P M E N T OF THE M O D E L The parameters used in the m o d e P are as follows: (i) Change in vehicle population. (ii) Introduction of new quieter vehicles. (iii) State of wear of vehicle population. The traffic noise level arising at a certain time and place depends mainly upon the noise levels generated by individual vehicles in a traffic stream. The noise level detected by an observer from a single vehicle is determined by vehicle category and type, operating condition (velocity, engine speed, acceleration and driving attitude), state of wear, the vehicle/observer separation and the type of ground cover under the vehicle and between the vehicle and the observer. The overall noise level will also be influenced by factors such as the presence of barriers and buildings, and road geometry. The model described in this paper has been developed assuming an average type of vehicle in each category and by taking the noise influencing parameters not used in the model as constant during the period of investigation.
Change in vehicle population Assuming that the spatial distribution of vehicles in the country does not change during the period of prognosis, the change in traffic noise due to increasing number of vehicles can easily be estimated. Using the energy equivalent continuous sound level Leqfor the calculation of traffic noise, as is c o m m o n in many countries of Europe, the change of noise level is expressed by:
ALeq=
N 10 log - No
(1)
where N is the number of vehicles in the year forecast and N o is the same but in the reference year. The initial assumption has an important effect
A method of traffic noise prognosis
23
on the noise difference estimated. The increase of traffic volume on a single street also depends upon the initial volume on that street according to the capacity limit. Therefore it can happen that individual streets have changes in traffic noise other than those calculated. Introduction of new quieter vehicles
The noise limits of new vehicles are controlled by the method described in ISO Recommendation R 3625 for type approval testing. This method incorporates a vehicle operating condition which gives almost the highest noise level appearing in urban driving situations. The traffic noise immission is generally expressed by average values for longer terms. To be able to calculate the noise immission level in urban conditions, using the emission levels of vehicles, there is a need for a representative driving cycle for urban traffic. To avoid this, numerous studies have been undertaken to define the representative urban driving conditions 6 and to determine a new measurement procedure 7 to provide a better correlation with the equivalent urban noise level. Unfortunately, it is almost impossible at present to forecast the correct extent of change in Leq following the change of vehicle emission expressed by the ISO accelerating bypass test. We assume in this paper, that the decrease of noise level generated by individual vehicles appears to the same extent in the equivalent urban noise level. In that case the change in traffic noise depends only on the proportion of new quieter vehicles and the traffic composition. As a first step, two categories of vehicles are considered and the initial Leq value is expressed for the reference year by: Leq 0
=
10 log Q[(1 - p)10 °'1- L, + p . 10o.1. L2]
(2)
and after renewal of a part of the vehicle population in the future time in question: Leq z = lOlogQ[(1 - p ) ( 1 - z ) .
100"l'L' +(1
+p(1 - z). 10 °'1"L2 + p . z . 10°'i'Ll]
-p)z.
100"l'L' (3)
where Q = the flow (vehicles/h); p = the composition of lorries; z = the proportion of new vehicles; L1, L'I = the Leqlevels of an average car for a period of 1 h at the reference distance in the reference and the chosen future year; and L2, L~ = the same as above but of an average lorry.
B. Buna, L. Vereb
24
Proportion of new vehictes
10 I I
20 I
30I
~0 I
50I
60 I
70 I
80 I
90 100 z[%] I I
.
tO
~2'--m
r..
3-
(2J
"~ 5=
d= ?..5 m x=55 dB (A)
&
8"7-
I,M
ALeql [dB(~] Fig. i.
Reduction
in
L~q
for various
proportions
of new quieter vehicles. Curve
1.
p = 0 - 4 , x 1 = 5, x 2 = 0 ; c u r v e 2, p = 0.1, x I = 0 , x 2 = 7; c u r v e 3, p = 0 . 1 , x 1 = 5, x 2 = 0 : c u r v e 4, p = 0.4, x 1 = 0, x 2 = 7: c u r v e 5, p = 0-1, x l = 4, x 2 = 7; c u r v e 6, p = 0-4, x I = 4, x 2 = 7; c u r v e 7, p = 0-1, x I = 5, x 2 = 10; c u r v e 8, p = 0 " 4 , x I = 5, x 2 = 10.
AL eq [ dB(A)] 6-
E _
t~.
p=0 xl = 6 dB (A] L2 = L1"10 dB (A) z = 0.75
tel
o " ,4,--
p=0.9
~
¢..
2
:=3
,,,
0
x2 [dB(/~]
Noise reduction of heavy vehicles F i g . 2.
Reduction
in L~q w i t h v a r i o u s n o i s e r e d u c t i o n v a l u e s f o r l o r r i e s .
A method of traJfic noise prognosis
25
F r o m eqns (2) and (3) the noise reduction for a future time can be given in closed form: 1
AL~ = 10log 1 + z E(1 - P ) " 10°~(L~-x~) + p . 10o.l(L, +~-x01
10ol,,+x)
L
(4)
/
where x = the difference between the noise emission of the average car and lorry; xl = the noise level reduction of new cars; and x 2 = the noise level reduction of new lorries. It can be seen that the attainable noise reduction is a function of the parameters p, x, x~ and x 2. The changes in Le~ over the proportion of the new vehicles calculated by eqn. (4) are depicted in Fig. 1. The eight curves represent various arrangements of the parameters p, x~ and x 2. In the year of introduction of quieter vehicles at realistic proportions there is only very little improvement in noise pollution and the change for the better becomes steadily favourable as the proportion of quieter vehicles increases. To have a sensible result, 70 per cent of the rolling stock at least has to be renewed (e.g. curve 7 at overall noise reduction of 3 dB(A)). When the percentage of heavy vehicles is higher, the reduction of car noise generation has little influence (see curve 1). The lowest curve in Fig. 1 (curve 8) represents the practical limits of noise reduction of vehicles. In that extreme case and supporting a rate of 10 per cent in yearly renewal of the population, in order to reach an overall reduction of 3 dB(A) one has to wait more than 5 years. Using the calculated result given in eqn. (4) some internal relationships can also be studied. According to the graphic presentation possibilities in a plane, two of the parameters have been kept constant and the changes in Le~ against the noise reduction of lorries have been plotted in Fig. 2. It can be seen that the evaluation x I = x 2 has particular importance, that is the change in Leq becomes independent of traffic composition when noise reduction values for cars and lorries are the same (the curves intersect at the same point). Thus the traffic, as far as noise generation is concerned, acts homogeneously. Equation (4) has no local end values as a function o f p (it has a point of inflexion at x~ = x2). The international standardization is intended to reduce noise emission of lorries to the level of cars. When the vehicle population is homogenous as regards noise generation, x and p are both zero in eqn. (4) and changes in Leq can be calculated very easily as follows: 1
L~q = lOlog 1 + z[lO - ° ' l ' x ' - 1]
(5)
26
B. Buna, L. Vereb
The introduction of new quieter vehicles generally results in better improvement in traffic noise pollution in a homogenous population and in the case of x I = x z, eqns (4) and (5) both yield the same result (see also Fig. 2). In prognostic calculations, time (the year of prognosis) is the real variable instead of the percentage of the already quietened vehicles. Because of this, information about the change of vehicle population (injection and retirement) over the calender years is needed. Before starting calculations some other considerations have also to be made. It is known, for example, that when new limits come into force, the vehicles which complied with the previous ones are still allowed to be sold for a while. This causes delays in the effects of any new regulation and a certain time-shift must be included in the prognosis, that is the curves in Fig. 1 have to be shifted to the right by At. State of wear of vehicle population During the lifetime of vehicles in use the noise generated by them generally increases. The relationship between the growth in noise and the years of use depends on m a n y influencing parameters; it has not been published until now and seems difficult to present. As a first approximation it is assumed to be a linear relationship and the noise increase is characterized by the speed of vehicle deterioration, assumed to be constant: AL = c. t (6) where c = the 'speed' of noise increase (dB(A)/year) and t = time in use (years). The speed of deterioration is probably different for cars and heavy vehicles and it makes sense to choose different lifetimes for the representative vehicles of various categories. Building up of the model The basic parts of the model are described by eqns (1), (4) and (6). To bring these parts together a conversion of all variables to time is needed. To do this, the time history of vehicle population has to be expressed: N(t) = N O +
l(t) dt o
= N o+
R(t) dt o
I(t)dto
I(t)dt o
= N o+
I(t)dt -
T{k)
(7)
A methodof traffic noiseprognosis
27
where t = the year of prognosis; N o -- the vehicle population at the initial point of time; I(t) = the time history of introduction of new vehicles; R(t) = the time history of retirement of old vehicles; t o = the initial point of time (starting year); and T(k) = the average lifetime of the representative vehicle in the kth category. It can be seen that the time function which expresses the population dynamics is theoretically an integral equation. However, the data for the past and often also for the future are available in the form of time series. Therefore it is more practical to employ summation rather than integration. After combining the relationship discussed above and using more than two categories of vehicles, the future change in traffic noise, in comparison to the noise at a reference point of time, can be also expressed in the form of a time series as follows:
S(k, t) ALeq(t ) = 10log
k=l
(8)
Z S(k, t,eS) k=l
where k = the number of vehicle categories and 1
S(k, t)=
)'
q(k,j).
l O0" l[Ax(k,j)
+ ( t - j) .c(k)]
(9)
j = t - T(k)
t = year of prognosis; j = running year; t,eI = year of reference; q(k,j) = number o f new vehicles in the kth category introduced in t h e j t h year; Ax(k,j)=L(k,j)-L(1,to) (where L(k,j)=noise level of the representative vehicle of the kth category in the jth year, and L(1, to) = noise level of the representative vehicle of the first category (cars) in the starting year); and c(k) = yearly rate of noise increase caused by ageing of vehicle in the kth category. When the time series ofq(k,j) and L(k,j) are known, the total change in traffic noise level can be determined for any time using eqns (8) and (9). These equations are valid for the total population of vehicles in a country taken as a whole. When the local values, e.g. for a certain street, are needed they can be derived from eqn. (8) as follows:
ALeql(t )
Q,(t) Z pl(k,t) =
10log
S (k , t_~)
N(k, t) S(k, tr~I) Q~(tr~¢) Z Pl(k,t*e¢) k = 1 N(k, t, el) k=__1
(10)
B. Buna, L. Vereb
28
where Q l ( t ) = t h e local traffic volume in the year of prognosis; Q l(trey) = local traffic volume in the year of reference; pl(k, t ) = proportion of vehicles of the kth category in the local traffic volume at the year of prognosis; pl (k, trey ) = the same as above but in the year of reference; and N(k, t) = ~,~:,_ T(k)q(k,j) In eqn. (10) it is assumed that the wear of vehicles in use and the rates of introduction of new quieter vehicles for the total and local case are the same.
A P P L I C A T I O N OF T H E M O D E L It was decided to investigate how the traffic noise level would change in this country (Hungary) up to the year 2000. To make the calculations easier, a simple desk computer program was developed. The initial data and assumptions used in the calculation were as follows: (i)
The vehicle population rapidly grows according to an optimistic prognosis variant valid for this country. (ii) The increase in noise generated by vehicles during their lifetime is 5dB(A) and the lifetime of the vehicles T(1)= 15 years and T(2) = 7 years for cars and lorries, respectively. The retiring of vehicles takes place immediately at the end of their lifetimes. (iii) The tightening of noise limits follows the values given in Figs 3 and 4. The time gap between the coming into force and the real operation of new limits is assumed to be 2 years. The calculated results are plotted in Figs 3, 4 and 5. The time scales of prognosis curves start with the year 1975 but the calculation of the values had to be commenced T(k) years earlier. In Figs 3 and 4 a certain noise increase for 1975 already appears, because special values of reference S(k, t) do not contain the last term of the exponent of 10. Therefore this is the noise increase characterisation for the average wearing condition of the vehicles at the reference year. It can be seen that it has to take into account an increase in noise level in the near future in this country, and a decrease in noise level, even under optimistic conditions, can only be expected about 1990. The curves in Fig. 5 are largely similar to those plotted in Fig. 3, i.e. the noise prognosis for the whole vehicle population is mainly determined by the noise generation of the car population.
A method of traffic noise prognosis
29
ALeq [dB(A)]
81'
1
p 61 I I
J
/
2
2!
~
•4....•
t--
I
! I
i
I !
"i
Ib
,//
1975
1980
i
i ..........
1985
1990
1995
2000
f[yead Fig. 3. Noise prognosis for car population. 1, Without any noise reduction; 2, with a noise reduction of 2 dB(A) for new cars introduced in 1983 and a further noise reduction of 2 dB(A) in 1993; 3, the same as above but with a further noise reduction of 2 dB(A) in 1988.
&Leq [da(A)]
,
"080
1985tIyead1990
1995
2000
Fig. 4. Noise prognosis for heavy vehicle population. 1, Without any noise reduction; 2, with a noise reduction of 5 dB(A) for new heavy vehicles introduced in 1985 and a further noise reduction of 2 dB(A) in 1990 and 1995; 3, the same as above but with a further noise reduction of 2dB(A) in 1990.
B. Buna, L. Vereb
30
AL eq [dB( A ®
O
.c
® Q m Q
-
Z
-
lg75
lg80
1985
1QeO t
lg95
2000
[yesr]
Fig. 5. Noiseprognosis for total vehicle population. 1, Without any noise reduction; 2, without any noise reduction and taking into account the ageing of the vehicles; 3, with a noise reduction of variant 2 in Figs 3 and 4; 4, the same as 3 but without taking into account the ageing of the vehicles; 5, the same as 3 but without any increase in the vehicle population.
The influence of the parameters discussed in this paper on the change in noise level at any future time can be compared with the help of various curves presented in Fig. 5. It can be stated that the deterioration of vehicles has less influence on noise level change, at least for the parameter allocation used in this paper.
CONCLUSION On the basis of the examples considered, the simple method for traffic noise prognosis described here seems to be a useful device for decision makers. The examples show the weights of the various noise influencing parameters and enable the user to make an effective noise control strategy. The figures show that noise reduction based on noise sources only is not sufficient to meet present public demands. The model is intended to increase the precision of relationships between noise emission and immission in urban conditions and noise increase and ageing of vehicles.
A method of traffic noise prognosis
31
ACKNOWLEDGEMENT The authors wish to express their thanks to Professor P. Lord for his encouragement in writing this paper.
REFERENCES 1. P. M. Nelson and J. Fanstone, Estimates of the reduction of traffic noise following the introduction of quieter vehicles, TRRL Laboratory Report 624, Crowthorne, 1974. 2. E.J. Rathe, Untersuchung fiber den Einfluss der Fahrzeugldrmemission auf die Ldrmimmissionen bei typischen Verkehrsverhdltnissen, Eidg. Amt fiir Umweltschutz, Bericht No. 51 u. 52, Bern, 1976. 3. C. T. Molloy, Noise control strategies for new and in-use trucks, Motor Vehicle Noise Control, Transportation Research Board, Special Report 152, Washington, 1975, pp. 72-6. 4. B. Buna and L. Vereb, Prediction of the change of traffic noise caused by the variations in the vehicle population features and noise limits, Proceedings of Inter-Noise 81 Conference, Amsterdam, 1981, pp. 541-4. 5. ISO R362. Measurement of noise emitted by vehicles, 1964. 6. CCMC Report. Proposals for a new test procedure for the measurement of exterior noise of passenger cars, 1977. 7. ISO/DIS 7188. Method for the measurement of the external noise level of passenger cars, 1981.
A Method of Traffic Noise Prognosis
B. Buna and L. Vereb Institute for Transport Sciences, Budapest (Hungary) (Received: 15 November, 1982)
SUMMARY This paper describes a simple method for the calculation of changes in noise levels generated by the vehicle population of a country as a whole in future time related to present population. The changes of the total number of vehicles, the introduction of quieter vehicles and the condition of wear of the running stock are taken into account in the model and the change in Leq level is used as the output parameter. The calculated changes in Le~ values are about the same as those of L 1o. The application examples of the model show that this simple method seems to be helpful for decision makers. The examples also allow conclusions for noise control strategy to be developed.
INTRODUCTION To be able to assess the demand for and the choice of protection measures against traffic noise in any future time there is a need for noise forecasting methods. Although the reduction of traffic noise following the introduction of quieter vehicles has- already been satisfactorily investigated t,2 these prediction model applications take into account only the number of new quieter vehicles and the proportion of heavy vehicles. Another paper 3 has tried handling the noise output of the vehicle population as a system problem and developed a technique for calculating truck populations, using variable truck manufacturing and 21 Applied Acoustics 0003-682X/84/$03-00 © Elsevier Applied Science Publishers Ltd, England, 1984. Printed in Great Britain
B. Buna, L. Vereb
22
retirement rates. The real life situation, however, calls for a more complex treatment using more input parameters. On the other hand for the sake of simplicity the number of vehicles in a country should be taken as a whole. This means a representative traffic and vehicle allocation approach.
D E V E L O P M E N T OF THE M O D E L The parameters used in the m o d e P are as follows: (i) Change in vehicle population. (ii) Introduction of new quieter vehicles. (iii) State of wear of vehicle population. The traffic noise level arising at a certain time and place depends mainly upon the noise levels generated by individual vehicles in a traffic stream. The noise level detected by an observer from a single vehicle is determined by vehicle category and type, operating condition (velocity, engine speed, acceleration and driving attitude), state of wear, the vehicle/observer separation and the type of ground cover under the vehicle and between the vehicle and the observer. The overall noise level will also be influenced by factors such as the presence of barriers and buildings, and road geometry. The model described in this paper has been developed assuming an average type of vehicle in each category and by taking the noise influencing parameters not used in the model as constant during the period of investigation.
Change in vehicle population Assuming that the spatial distribution of vehicles in the country does not change during the period of prognosis, the change in traffic noise due to increasing number of vehicles can easily be estimated. Using the energy equivalent continuous sound level Leqfor the calculation of traffic noise, as is c o m m o n in many countries of Europe, the change of noise level is expressed by:
ALeq=
N 10 log - No
(1)
where N is the number of vehicles in the year forecast and N o is the same but in the reference year. The initial assumption has an important effect
A method of traffic noise prognosis
23
on the noise difference estimated. The increase of traffic volume on a single street also depends upon the initial volume on that street according to the capacity limit. Therefore it can happen that individual streets have changes in traffic noise other than those calculated. Introduction of new quieter vehicles
The noise limits of new vehicles are controlled by the method described in ISO Recommendation R 3625 for type approval testing. This method incorporates a vehicle operating condition which gives almost the highest noise level appearing in urban driving situations. The traffic noise immission is generally expressed by average values for longer terms. To be able to calculate the noise immission level in urban conditions, using the emission levels of vehicles, there is a need for a representative driving cycle for urban traffic. To avoid this, numerous studies have been undertaken to define the representative urban driving conditions 6 and to determine a new measurement procedure 7 to provide a better correlation with the equivalent urban noise level. Unfortunately, it is almost impossible at present to forecast the correct extent of change in Leq following the change of vehicle emission expressed by the ISO accelerating bypass test. We assume in this paper, that the decrease of noise level generated by individual vehicles appears to the same extent in the equivalent urban noise level. In that case the change in traffic noise depends only on the proportion of new quieter vehicles and the traffic composition. As a first step, two categories of vehicles are considered and the initial Leq value is expressed for the reference year by: Leq 0
=
10 log Q[(1 - p)10 °'1- L, + p . 10o.1. L2]
(2)
and after renewal of a part of the vehicle population in the future time in question: Leq z = lOlogQ[(1 - p ) ( 1 - z ) .
100"l'L' +(1
+p(1 - z). 10 °'1"L2 + p . z . 10°'i'Ll]
-p)z.
100"l'L' (3)
where Q = the flow (vehicles/h); p = the composition of lorries; z = the proportion of new vehicles; L1, L'I = the Leqlevels of an average car for a period of 1 h at the reference distance in the reference and the chosen future year; and L2, L~ = the same as above but of an average lorry.
B. Buna, L. Vereb
24
Proportion of new vehictes
10 I I
20 I
30I
~0 I
50I
60 I
70 I
80 I
90 100 z[%] I I
.
tO
~2'--m
r..
3-
(2J
"~ 5=
d= ?..5 m x=55 dB (A)
&
8"7-
I,M
ALeql [dB(~] Fig. i.
Reduction
in
L~q
for various
proportions
of new quieter vehicles. Curve
1.
p = 0 - 4 , x 1 = 5, x 2 = 0 ; c u r v e 2, p = 0.1, x I = 0 , x 2 = 7; c u r v e 3, p = 0 . 1 , x 1 = 5, x 2 = 0 : c u r v e 4, p = 0.4, x 1 = 0, x 2 = 7: c u r v e 5, p = 0-1, x l = 4, x 2 = 7; c u r v e 6, p = 0-4, x I = 4, x 2 = 7; c u r v e 7, p = 0-1, x I = 5, x 2 = 10; c u r v e 8, p = 0 " 4 , x I = 5, x 2 = 10.
AL eq [ dB(A)] 6-
E _
t~.
p=0 xl = 6 dB (A] L2 = L1"10 dB (A) z = 0.75
tel
o " ,4,--
p=0.9
~
¢..
2
:=3
,,,
0
x2 [dB(/~]
Noise reduction of heavy vehicles F i g . 2.
Reduction
in L~q w i t h v a r i o u s n o i s e r e d u c t i o n v a l u e s f o r l o r r i e s .
A method of traJfic noise prognosis
25
F r o m eqns (2) and (3) the noise reduction for a future time can be given in closed form: 1
AL~ = 10log 1 + z E(1 - P ) " 10°~(L~-x~) + p . 10o.l(L, +~-x01
10ol,,+x)
L
(4)
/
where x = the difference between the noise emission of the average car and lorry; xl = the noise level reduction of new cars; and x 2 = the noise level reduction of new lorries. It can be seen that the attainable noise reduction is a function of the parameters p, x, x~ and x 2. The changes in Le~ over the proportion of the new vehicles calculated by eqn. (4) are depicted in Fig. 1. The eight curves represent various arrangements of the parameters p, x~ and x 2. In the year of introduction of quieter vehicles at realistic proportions there is only very little improvement in noise pollution and the change for the better becomes steadily favourable as the proportion of quieter vehicles increases. To have a sensible result, 70 per cent of the rolling stock at least has to be renewed (e.g. curve 7 at overall noise reduction of 3 dB(A)). When the percentage of heavy vehicles is higher, the reduction of car noise generation has little influence (see curve 1). The lowest curve in Fig. 1 (curve 8) represents the practical limits of noise reduction of vehicles. In that extreme case and supporting a rate of 10 per cent in yearly renewal of the population, in order to reach an overall reduction of 3 dB(A) one has to wait more than 5 years. Using the calculated result given in eqn. (4) some internal relationships can also be studied. According to the graphic presentation possibilities in a plane, two of the parameters have been kept constant and the changes in Le~ against the noise reduction of lorries have been plotted in Fig. 2. It can be seen that the evaluation x I = x 2 has particular importance, that is the change in Leq becomes independent of traffic composition when noise reduction values for cars and lorries are the same (the curves intersect at the same point). Thus the traffic, as far as noise generation is concerned, acts homogeneously. Equation (4) has no local end values as a function o f p (it has a point of inflexion at x~ = x2). The international standardization is intended to reduce noise emission of lorries to the level of cars. When the vehicle population is homogenous as regards noise generation, x and p are both zero in eqn. (4) and changes in Leq can be calculated very easily as follows: 1
L~q = lOlog 1 + z[lO - ° ' l ' x ' - 1]
(5)
26
B. Buna, L. Vereb
The introduction of new quieter vehicles generally results in better improvement in traffic noise pollution in a homogenous population and in the case of x I = x z, eqns (4) and (5) both yield the same result (see also Fig. 2). In prognostic calculations, time (the year of prognosis) is the real variable instead of the percentage of the already quietened vehicles. Because of this, information about the change of vehicle population (injection and retirement) over the calender years is needed. Before starting calculations some other considerations have also to be made. It is known, for example, that when new limits come into force, the vehicles which complied with the previous ones are still allowed to be sold for a while. This causes delays in the effects of any new regulation and a certain time-shift must be included in the prognosis, that is the curves in Fig. 1 have to be shifted to the right by At. State of wear of vehicle population During the lifetime of vehicles in use the noise generated by them generally increases. The relationship between the growth in noise and the years of use depends on m a n y influencing parameters; it has not been published until now and seems difficult to present. As a first approximation it is assumed to be a linear relationship and the noise increase is characterized by the speed of vehicle deterioration, assumed to be constant: AL = c. t (6) where c = the 'speed' of noise increase (dB(A)/year) and t = time in use (years). The speed of deterioration is probably different for cars and heavy vehicles and it makes sense to choose different lifetimes for the representative vehicles of various categories. Building up of the model The basic parts of the model are described by eqns (1), (4) and (6). To bring these parts together a conversion of all variables to time is needed. To do this, the time history of vehicle population has to be expressed: N(t) = N O +
l(t) dt o
= N o+
R(t) dt o
I(t)dto
I(t)dt o
= N o+
I(t)dt -
T{k)
(7)
A methodof traffic noiseprognosis
27
where t = the year of prognosis; N o -- the vehicle population at the initial point of time; I(t) = the time history of introduction of new vehicles; R(t) = the time history of retirement of old vehicles; t o = the initial point of time (starting year); and T(k) = the average lifetime of the representative vehicle in the kth category. It can be seen that the time function which expresses the population dynamics is theoretically an integral equation. However, the data for the past and often also for the future are available in the form of time series. Therefore it is more practical to employ summation rather than integration. After combining the relationship discussed above and using more than two categories of vehicles, the future change in traffic noise, in comparison to the noise at a reference point of time, can be also expressed in the form of a time series as follows:
S(k, t) ALeq(t ) = 10log
k=l
(8)
Z S(k, t,eS) k=l
where k = the number of vehicle categories and 1
S(k, t)=
)'
q(k,j).
l O0" l[Ax(k,j)
+ ( t - j) .c(k)]
(9)
j = t - T(k)
t = year of prognosis; j = running year; t,eI = year of reference; q(k,j) = number o f new vehicles in the kth category introduced in t h e j t h year; Ax(k,j)=L(k,j)-L(1,to) (where L(k,j)=noise level of the representative vehicle of the kth category in the jth year, and L(1, to) = noise level of the representative vehicle of the first category (cars) in the starting year); and c(k) = yearly rate of noise increase caused by ageing of vehicle in the kth category. When the time series ofq(k,j) and L(k,j) are known, the total change in traffic noise level can be determined for any time using eqns (8) and (9). These equations are valid for the total population of vehicles in a country taken as a whole. When the local values, e.g. for a certain street, are needed they can be derived from eqn. (8) as follows:
ALeql(t )
Q,(t) Z pl(k,t) =
10log
S (k , t_~)
N(k, t) S(k, tr~I) Q~(tr~¢) Z Pl(k,t*e¢) k = 1 N(k, t, el) k=__1
(10)
B. Buna, L. Vereb
28
where Q l ( t ) = t h e local traffic volume in the year of prognosis; Q l(trey) = local traffic volume in the year of reference; pl(k, t ) = proportion of vehicles of the kth category in the local traffic volume at the year of prognosis; pl (k, trey ) = the same as above but in the year of reference; and N(k, t) = ~,~:,_ T(k)q(k,j) In eqn. (10) it is assumed that the wear of vehicles in use and the rates of introduction of new quieter vehicles for the total and local case are the same.
A P P L I C A T I O N OF T H E M O D E L It was decided to investigate how the traffic noise level would change in this country (Hungary) up to the year 2000. To make the calculations easier, a simple desk computer program was developed. The initial data and assumptions used in the calculation were as follows: (i)
The vehicle population rapidly grows according to an optimistic prognosis variant valid for this country. (ii) The increase in noise generated by vehicles during their lifetime is 5dB(A) and the lifetime of the vehicles T(1)= 15 years and T(2) = 7 years for cars and lorries, respectively. The retiring of vehicles takes place immediately at the end of their lifetimes. (iii) The tightening of noise limits follows the values given in Figs 3 and 4. The time gap between the coming into force and the real operation of new limits is assumed to be 2 years. The calculated results are plotted in Figs 3, 4 and 5. The time scales of prognosis curves start with the year 1975 but the calculation of the values had to be commenced T(k) years earlier. In Figs 3 and 4 a certain noise increase for 1975 already appears, because special values of reference S(k, t) do not contain the last term of the exponent of 10. Therefore this is the noise increase characterisation for the average wearing condition of the vehicles at the reference year. It can be seen that it has to take into account an increase in noise level in the near future in this country, and a decrease in noise level, even under optimistic conditions, can only be expected about 1990. The curves in Fig. 5 are largely similar to those plotted in Fig. 3, i.e. the noise prognosis for the whole vehicle population is mainly determined by the noise generation of the car population.
A method of traffic noise prognosis
29
ALeq [dB(A)]
81'
1
p 61 I I
J
/
2
2!
~
•4....•
t--
I
! I
i
I !
"i
Ib
,//
1975
1980
i
i ..........
1985
1990
1995
2000
f[yead Fig. 3. Noise prognosis for car population. 1, Without any noise reduction; 2, with a noise reduction of 2 dB(A) for new cars introduced in 1983 and a further noise reduction of 2 dB(A) in 1993; 3, the same as above but with a further noise reduction of 2 dB(A) in 1988.
&Leq [da(A)]
,
"080
1985tIyead1990
1995
2000
Fig. 4. Noise prognosis for heavy vehicle population. 1, Without any noise reduction; 2, with a noise reduction of 5 dB(A) for new heavy vehicles introduced in 1985 and a further noise reduction of 2 dB(A) in 1990 and 1995; 3, the same as above but with a further noise reduction of 2dB(A) in 1990.
B. Buna, L. Vereb
30
AL eq [dB( A ®
O
.c
® Q m Q
-
Z
-
lg75
lg80
1985
1QeO t
lg95
2000
[yesr]
Fig. 5. Noiseprognosis for total vehicle population. 1, Without any noise reduction; 2, without any noise reduction and taking into account the ageing of the vehicles; 3, with a noise reduction of variant 2 in Figs 3 and 4; 4, the same as 3 but without taking into account the ageing of the vehicles; 5, the same as 3 but without any increase in the vehicle population.
The influence of the parameters discussed in this paper on the change in noise level at any future time can be compared with the help of various curves presented in Fig. 5. It can be stated that the deterioration of vehicles has less influence on noise level change, at least for the parameter allocation used in this paper.
CONCLUSION On the basis of the examples considered, the simple method for traffic noise prognosis described here seems to be a useful device for decision makers. The examples show the weights of the various noise influencing parameters and enable the user to make an effective noise control strategy. The figures show that noise reduction based on noise sources only is not sufficient to meet present public demands. The model is intended to increase the precision of relationships between noise emission and immission in urban conditions and noise increase and ageing of vehicles.
A method of traffic noise prognosis
31
ACKNOWLEDGEMENT The authors wish to express their thanks to Professor P. Lord for his encouragement in writing this paper.
REFERENCES 1. P. M. Nelson and J. Fanstone, Estimates of the reduction of traffic noise following the introduction of quieter vehicles, TRRL Laboratory Report 624, Crowthorne, 1974. 2. E.J. Rathe, Untersuchung fiber den Einfluss der Fahrzeugldrmemission auf die Ldrmimmissionen bei typischen Verkehrsverhdltnissen, Eidg. Amt fiir Umweltschutz, Bericht No. 51 u. 52, Bern, 1976. 3. C. T. Molloy, Noise control strategies for new and in-use trucks, Motor Vehicle Noise Control, Transportation Research Board, Special Report 152, Washington, 1975, pp. 72-6. 4. B. Buna and L. Vereb, Prediction of the change of traffic noise caused by the variations in the vehicle population features and noise limits, Proceedings of Inter-Noise 81 Conference, Amsterdam, 1981, pp. 541-4. 5. ISO R362. Measurement of noise emitted by vehicles, 1964. 6. CCMC Report. Proposals for a new test procedure for the measurement of exterior noise of passenger cars, 1977. 7. ISO/DIS 7188. Method for the measurement of the external noise level of passenger cars, 1981.