- Email: [email protected]
Traffic noise survey and analysis in Singapore
Applied Acoustics 18 (1985) 115-125
Traffic Noise Survey and Analysis in Singapore H. K. Sy, P. P. Ong, S. H. T a n g a n d K. L. T a n Department of Physics, National University of Singapore, Kent Ridge (Singapore 0511) (Received: 26 January, 1984)
S UMMA RY A comprehensive survey and statistical analysis of daytime traffic noise in Singapore was carried out. The results are presented in terms of average Llo, Lso and L9ofor four different classes of sites. By clearly distinguishing between temporal and spatial noise fluctuations, it is possible, on the basis of the Gaussian noise distributions obtained, to verify that the overall noise fluctuation can also be derivable from the respective temporal and spatial noise fluctuations. The traffic noise index ( T N I ) and the noise pollution index ( LNp) are determined and a correlation is established between the traffic noise levels and the corresponding volume of traffic.
1.
INTRODUCTION
The island city-state of Singapore has a very intense population concentration, and an elaborate network of roads. This, accompanied by a p e r capita income fast approaching that of the developed countries, has resulted in a very high density of vehicles per unit area. Economic prosperity, sustained by a high level of noise-polluting socio-economic activities such as transportation and construction, has contributed to enhance the environmental noise level. The policy of the government to encourage more business activities while at the same time containing the population of private cars has resulted in a disproportionately large percentage of heavy vehicles on the roads. This situation is further compounded by the siting of a large number of noise-trapping high-rise ll5 Applied Acoustics 0003-682X/85/$03.30 © Elsevier Applied Science Publishers Ltd,
England, 1985. Printed in Great Britain
116
H. K. Sy, P. P. Ong, S. H. Tang, K. L. Tan
buildings near the arterial roads, not only in the business districts but also in the suburban public housing estates in which 80 ~o of the population resides. On the other hand, the rising standard of living among the population has brought about a steady increase in the appreciation of the deleterious effects of noise pollution. Notwithstanding these factors, systematic scientific surveys on environmental noise pollution have not kept up with the pace of economic development, and little information on noise pollution in Singapore is available in the literature. Mattar 1 studied the statistical noise levels in ten private housing estates, while Heng 2'3 has made some noise investigations on other selected isolated sites, but a more comprehensive and up-to-date survey is not yet available. In this paper we report an island-wide survey of traffic noise along main roads and expressways in Singapore. A statistical analysis is made and the major contributory factors are identified. The results are shown to obey a traffic noise model.
2.
THE SURVEY
The island-wide survey was conducted in two phases during the months of June and July 1983. As there are no seasonal fluctuations in the local weather or traffic, these months are expected to be representative of the whole year. In phase I an extensive study was made covering over 300 widely scattered sites along main roads. For each site, 40 A-weighted instantaneous noise levels were measured by survey teams using B & K sound level meters (SLM) over a period of 10min in the time interval between the hours of 4pm and 7 pm. This period corresponds to the normal peak noise period of the day. For practical reasons, as well as for the purpose of standardising the procedure, all the measurements were generally taken with the SLM placed at a height of I m above the ground, at a distance of 10 m from the middle of the road, and with the microphone pointed towards the road. However, earlier investigations made with variations of the microphone orientation and of its height above the ground did not yield significant changes in the readings as long as the microphone was not shielded from the noise source. The average noise data for each of the 300 sites were collated and
117
Traffic noise survey and analysis in Singapore EAST
COAST PARKWAY
90. 85.
8OO
80.
600 -T
75
500 >
< on 70 65.
400 o
700 w .J (J
LLJ
LL
3OO c5
/
Z
/
60 55 50
2OO
-100 :
:
:
:
:
:
:
o
o
o
o
o
:
:
:
cJ
:
o
:
:
:
o
o
:
:
:
:
:
0
TIME
Fig. !.
Daytime variation of sound levels along a highway with very heavy traffic. , The number of vehiclecounts in a 3-min interval.
broadly identified with various environmental scenarios of noise sources. This procedure enabled a typical sample of 20 sites to be chosen which were sufficiently representative of the different scenarios in the proportion of the frequency of their occurrence. These 20 sample sites were subsequently chosen for the intensive daytime study carried out in phase II. In this phase the instantaneous SLM used in phase I was replaced by calibrated Nagra tape recorders and the noise level at each site was recorded on site. Typically recordings were made over a 3-min duration at regular half-hourly intervals from 9 am to 7 pm. The probabilistic consistency of this sampling technique had been checked in an auxiliary investigation involving noise collection at a particular site at irregular times. The resulting statistical predictability confirms the validity of the sampling method employed. The recorded tapes were brought back to the laboratory for detailed analysis with a B & K statistical noise analyser. Typical A-weighted noise level distributions are depicted in Fig. 1. The continuous measurements made in the second phase overcome the objection encountered in the first phase of this study where loud transient events occurring between successive measurements may have been omitted. The inclusion of such high noise pulses is especially important for a true determination of L10 noise levels. Notwithstanding
118
H. K. S£, P. P. Ong, S. H. Tang, K. L. Tan
this precautionary measure, comparisons of the L lo values obtained from the two phases did not show significant differences. The day-long measurements in the second phase also show that the overall diurnal fluctuations of noise levels are small. This justifies the confinement to the period from 4 pm to 7 pm during which all first phase measurements were made.
3.
ANALYSIS
The data collected for all the 300 sites surveyed were analysed with the aid of a computer. The sites were grouped into four classes of different scenarios as detailed in Table 1. F r o m the 40 SLM instantaneous readings at each site, the average noise level L~v and the corresponding standard deviation ~x are calculated. Normal distribution is formally tested and established for a sample of randomly selected sites using the chi-square test. This verification enables us to generalise that the sound level distribution function is normal for all sites. The standard deviation a T gives a measure of the short-term temporal fluctuation at a given site. Our analysis shows that, within a particular class, it is practically independent of site. Hence, an average a r for all subsequent calculations is adopted. In agreement with the normal distribution, the Llo, Lso and L 9 o values for every site in each class are found to satisfy the relationships Lso = L~v and AL = Llo - L9o =
2.56cr x
TABLE I The F o u r Classes of Traffic Scenario
Class
Description
TraJflc flow, N (rehicles/min)
I II III IV
M o d e r a t e traffic Busy traffic Very busy traffic D o w n t o w n busy traffic
N < 20 20 < N < 60 60 < N 20 < N _< 60
(1)
Traffic noise survey and analysis in Singapore
119 '100
10'
9O 80 ~
8.
.70 .~
23 c
,6O
6
g
• 50 "5 E
"5 .Q
• 30
20 10 56
58
Fig. 2.
60
62
64. 66 68 70 Sound Level in
Distribution
72 7z, dBA
o f S L at a site in class I.
A typical case of these results is illustrated in Fig. 2 in which both the differential and the cumulative distributions are shown. F r o m the values of Lay for each site within a particular class the overall average noise level and the spatial standard deviation a s for the class are calculated, where a s is a measure of the fluctuation from site to site in each class. The distribution of Lav for each class is again found to be Gaussian. As an example, the differential and the cumulative distributions for class I are given in Fig. 3. In a separate calculation all the individual instantaneous noise readings for a specific site at a specific time within a class are treated as independent TABLE 2
Summary of Noise Survey
Class
I II III IV
Moderate traffic Busy traffic Very heavy traffic Downtown busy traffic
Number oJ sites
Ll 0
Lso
Lgo
°1
Os
o-
j ( o -2 4- 0"~
80 120 20
68.9 77.4 84-12
64-5 72.3 79
60.1 67.2 73.9
3.4 4-0 4-0
2.3 3.0 1-7
4.3 5.6 5.1
4.1 5.0 4.4
80
77-4
73
68.6
3.4
2.3
3.9
4.10
H. K. Sy, P. P. Ong, S. H. Tang, K. L. Tan
120
100
18 80
14
:,5
12
g
•~
z
60
10
D
E
g8
z,0 20
59
60
64
62 Sound
Fig. 3.
66 Level in
dBA
68
70
Distribution of average SL Lay from site to site for class I.
100 90 80 70
g 60
i
~ so ~
4o
~
2O 10 0
45
NOISE
Fig. 4.
50
60
70
80
90
dBA
Distribution of all SL in class I (moderate traffic).
g
Traffic noise survey and analysis in Singapore 100
-
:::==:=~-
121
. . . .
90 ~-
Lso: 72. 3 dBA
80 7O 60 5o
oIt.
20
~
,o
II
0 45 NOISE
Fig. 5.
I "-'"" 50 i5
I 60'
65
l/0
75
I 80
85---' -1---95 90.... dBA
Distribution of all SL in Class II (busy traffic).
data. This yields, for each class, a standard deviation a which measures noise fluctuations both in time as well as from location to location. Results for this method of calculation are shown in Figs 4--7, where the distribution is again found to be normal. Since the temporal, spatial and overall distributions are all Gaussian, their corresponding standard deviations satisfy the equation a2
= a~. + a2
(2)
The consistency of our data with eqn (2) is illustrated in Table 2. 100
::::--:::::====;:
-
I
90 80
I L50 = 79 dBA
60
30
20 10
45
I
50 NOISE
Fig. 6.
d5
I
60
05
70
75
80
85
I----=~5
90
dBA
Distribution of all SL in Class III (very heavy traffic).
122
H. K. Sy, P. P. Ong, S. H. Tang, K. L. Tan
80-
I
...............
L5o = 73 dBA
70-
c
o, 60 -
o-
u
so~
it_
40 -
302010 -
[
0 45
] 50
5]
5
I ill I 6s 60
75
I 80
70
t,
.
90
NOISE Fig. 7.
1__
8s'--T "-"9-s dBA
Distribution of all SL in class IV (downtown busy traffic).
The foregoing results are summarised in Table 2. For each class, the average L 10, Lso, L9o and the respective standard deviations aT, a s and a are given. The value x/(a~ + a ~ is shown to be consistent with a. The Lso values of 64.5, 72.3 and 79 dBA for moderate, busy and very heavy traffic and the value 73 dBA for downtown traffic are comparable to those obtained in other cities. The values of o-x are close to 4 dBA in all cases. In some studies aT was found to decrease with increasing traffic. The present study does not support such a trend. Based on our study the Noise Pollution Index (AL) 2
LNp=Lso+AL+
TABLE
6~
(3)
3
Noise Pollution Index and Traffic Noise Index
l II Ill IV
Class
Noise Pollution Index
Traj~c Noise Index
Moderate traffic Busy traffic Very heavy traffic Downtown busy traffic
74-5 84.3 91-0 82.9
64-9 78.2 84.9 73.4
Traffic noise survey and analysis in Singapore
123
and the Traffic Noise Index TNI = L 9 0 -t- 4AL -- 30
(4)
are calculated and presented in Table 3.
4.
TRAFFIC NOISE MODEL
A traffic noise model has been proposed and applied to G e r m a n 4 and Italian 5 towns. According to this model, the equivalent noise level is related tO the traffic and urban parameters by Leq = ~ nt-
10 log (N L + flNw) + 10 l o g ~
+ AL v + ' A L F + AL B + AL s + AL G + ALvB(dBA )
(5)
where N e (vehicles/h) is the flow of private cars, normal motor-cycles and light commercial vehicles; N w(vehicles/h) is the flow of heavy commercial vehicles, public transport vehicles and high noise level motor cycles; d is the distance from the centre of traffic, and is referred to a standard value of d o = 25 m; AL v accounts for the influence of flow velocity; AL r and AL B represent the correction parameters due to sound reflection by nearside faqades and by building fronts on the other side of the road (taken to be 2.5 and 1.5 dB, respectively); AL s is the correction relative to the road surface; AL G the correction due to road gradient; and ALvB accounts for extreme situations of traffic. In this survey the number of vehicles was counted over a period of 3 min at selected sites where the noise levels were being recorded simultaneously. A r a n d o m survey shows that the fraction of noisy heavy vehicle traffic in Singapore is typically 5~o of the total traffic. The value AL v = + 1.0 was chosen for the typical traffic speed of between 50 and 60km/h. The surface correction AL s was chosen to be - 0 . 5 for typical smooth asphalt Singapore roads. AL G was taken as zero since almost all the roads surveyed are horizontal. The corrections ALF and AL B for the presence of buildings were subtracted out from individual site measurements before analysis. The relation between Zeq and traffic flow rate N(in vehicles/min) for the first three classes is shown in Fig. 8. Using least squares fitting the best straight line is determined as Leq = 53"73 + 9.7 log N
(6)
124
H. K. Sy, P. P. Ong, S. H. Tang, K. L. Tan. 85 <
,,, . . . . . i .......... i....... ~....... i .......... ! . ^ ' v : ...... "O
,
7 5
.
.
65
~
.
;
.
.
:
-
".'
"
.
":
-,
"""
:
" ""
'~"
' " Y - "
"
""
":
"
"
"
55 •
. . . . .
45
.
.
..
I 2
Fig. 8.
.
- . . . . . . . . . .
.
:. . . . . . . . . . . . . . .
:
i
i
i
. . . . . . . . . . . . . . . . . . . . . . . . .
i
i
5 10 20 50 100 VEHICLE COUNT PER MIN
200
Correlation between noise level and traffic volume•
This is in good agreement with the prediction according to eqn (5). The value of/~ was chosen to be 8; this is the typical value used in earlier studies. 4'5 A value of ~ = 30-2 (dBA) was finally obtained from eqns (5) and (6). This should be compared with ~ = 33.8 for German towns and = 35'1 for Italian towns. The parameter ~ is expected to be different from country to country as it is related to the noise level due to a single vehicle and depends on the type of vehicles and the average driving habits of the local people. In this connection, it is appropriate to point out that the majority of vehicles in Singapore are Japanese cars fitted with (1300-1600 cc) engines. The fourth class, namely downtown traffic, does not fit the model of eqn (5), and deserves special consideration. Here the scenario is made up of streets crowded with human activities and the traffic is slow-moving and congested. The observed Ls0 of 73 dB is about 8 dB higher than that of class II with a comparable volume of traffic. This difference comes from (i) the amount of human activity, which varies from time to time, (ii) ALvB which measures extreme traffic conditions (high vehicle density per unit area, traffic junctions, horning, etc.), and (iii) the high concentration of high-rise buildings. At the moment no simple model is available to explain this noise pattern. 5.
CONCLUSIONS
This paper represents part of the work done in a noise survey in Singapore. In this survey, we have carefully differentiated the fluctuations
Traffic noise survey and analysis in Singapore
125
of noise over time and over location. This distinction is often not duly appreciated. A similar survey on residential areas will be published elsewhere. A noise map is being prepared using eqn (5). Subjective tests of traffic noise interference with speech perception have been carried out and will be reported shortly. It is hoped that the present paper fills the gap on noise data and their analysis for modern Singapore.
ACKNOWLEDGEMENTS The authors wish to thank the Telecommunication Authority of Singapore for a grant without which this survey would not have been possible. We also thank the departmental technicians, S. Ratnam, T. M. Wu and B. H. Tay, and the students of the Physics Department for their assistance in carrying out this study.
REFERENCES I. A. M. Mattar, A statistical study of traffic noise in private housing estates in Singapore, Ph.D. Thesis, University of Singapore, 1977. 2. R. B. W. Heng, A noise survey of public housing estates in Singapore, Acoustics Letters, 1 (1979), pp. 198-203. 3. R. B. W. Heng, The acoustic environment of Singapore schools in relation to traffic noise. In Proceedings of the Second Symposium on Our Environment, Singapore, 1979, p. 27. 4. B. B. M. Miiller, Verkehrsl/irmprognoise bei Stadtral3en. Unver6ffentlichter Bericht des F.A. 4762 des Bundesverkehrs-ministers, Bonn, 1978. 5. B. G. Cannelli, K. Gliick, S. Santoboni, A mathematical model for evaluation and prediction of the mean energy level of traffic noise in Italian towns. Acustica, 53 (1983), pp. 31 6.
Traffic Noise Survey and Analysis in Singapore H. K. Sy, P. P. Ong, S. H. T a n g a n d K. L. T a n Department of Physics, National University of Singapore, Kent Ridge (Singapore 0511) (Received: 26 January, 1984)
S UMMA RY A comprehensive survey and statistical analysis of daytime traffic noise in Singapore was carried out. The results are presented in terms of average Llo, Lso and L9ofor four different classes of sites. By clearly distinguishing between temporal and spatial noise fluctuations, it is possible, on the basis of the Gaussian noise distributions obtained, to verify that the overall noise fluctuation can also be derivable from the respective temporal and spatial noise fluctuations. The traffic noise index ( T N I ) and the noise pollution index ( LNp) are determined and a correlation is established between the traffic noise levels and the corresponding volume of traffic.
1.
INTRODUCTION
The island city-state of Singapore has a very intense population concentration, and an elaborate network of roads. This, accompanied by a p e r capita income fast approaching that of the developed countries, has resulted in a very high density of vehicles per unit area. Economic prosperity, sustained by a high level of noise-polluting socio-economic activities such as transportation and construction, has contributed to enhance the environmental noise level. The policy of the government to encourage more business activities while at the same time containing the population of private cars has resulted in a disproportionately large percentage of heavy vehicles on the roads. This situation is further compounded by the siting of a large number of noise-trapping high-rise ll5 Applied Acoustics 0003-682X/85/$03.30 © Elsevier Applied Science Publishers Ltd,
England, 1985. Printed in Great Britain
116
H. K. Sy, P. P. Ong, S. H. Tang, K. L. Tan
buildings near the arterial roads, not only in the business districts but also in the suburban public housing estates in which 80 ~o of the population resides. On the other hand, the rising standard of living among the population has brought about a steady increase in the appreciation of the deleterious effects of noise pollution. Notwithstanding these factors, systematic scientific surveys on environmental noise pollution have not kept up with the pace of economic development, and little information on noise pollution in Singapore is available in the literature. Mattar 1 studied the statistical noise levels in ten private housing estates, while Heng 2'3 has made some noise investigations on other selected isolated sites, but a more comprehensive and up-to-date survey is not yet available. In this paper we report an island-wide survey of traffic noise along main roads and expressways in Singapore. A statistical analysis is made and the major contributory factors are identified. The results are shown to obey a traffic noise model.
2.
THE SURVEY
The island-wide survey was conducted in two phases during the months of June and July 1983. As there are no seasonal fluctuations in the local weather or traffic, these months are expected to be representative of the whole year. In phase I an extensive study was made covering over 300 widely scattered sites along main roads. For each site, 40 A-weighted instantaneous noise levels were measured by survey teams using B & K sound level meters (SLM) over a period of 10min in the time interval between the hours of 4pm and 7 pm. This period corresponds to the normal peak noise period of the day. For practical reasons, as well as for the purpose of standardising the procedure, all the measurements were generally taken with the SLM placed at a height of I m above the ground, at a distance of 10 m from the middle of the road, and with the microphone pointed towards the road. However, earlier investigations made with variations of the microphone orientation and of its height above the ground did not yield significant changes in the readings as long as the microphone was not shielded from the noise source. The average noise data for each of the 300 sites were collated and
117
Traffic noise survey and analysis in Singapore EAST
COAST PARKWAY
90. 85.
8OO
80.
600 -T
75
500 >
< on 70 65.
400 o
700 w .J (J
LLJ
LL
3OO c5
/
Z
/
60 55 50
2OO
-100 :
:
:
:
:
:
:
o
o
o
o
o
:
:
:
cJ
:
o
:
:
:
o
o
:
:
:
:
:
0
TIME
Fig. !.
Daytime variation of sound levels along a highway with very heavy traffic. , The number of vehiclecounts in a 3-min interval.
broadly identified with various environmental scenarios of noise sources. This procedure enabled a typical sample of 20 sites to be chosen which were sufficiently representative of the different scenarios in the proportion of the frequency of their occurrence. These 20 sample sites were subsequently chosen for the intensive daytime study carried out in phase II. In this phase the instantaneous SLM used in phase I was replaced by calibrated Nagra tape recorders and the noise level at each site was recorded on site. Typically recordings were made over a 3-min duration at regular half-hourly intervals from 9 am to 7 pm. The probabilistic consistency of this sampling technique had been checked in an auxiliary investigation involving noise collection at a particular site at irregular times. The resulting statistical predictability confirms the validity of the sampling method employed. The recorded tapes were brought back to the laboratory for detailed analysis with a B & K statistical noise analyser. Typical A-weighted noise level distributions are depicted in Fig. 1. The continuous measurements made in the second phase overcome the objection encountered in the first phase of this study where loud transient events occurring between successive measurements may have been omitted. The inclusion of such high noise pulses is especially important for a true determination of L10 noise levels. Notwithstanding
118
H. K. S£, P. P. Ong, S. H. Tang, K. L. Tan
this precautionary measure, comparisons of the L lo values obtained from the two phases did not show significant differences. The day-long measurements in the second phase also show that the overall diurnal fluctuations of noise levels are small. This justifies the confinement to the period from 4 pm to 7 pm during which all first phase measurements were made.
3.
ANALYSIS
The data collected for all the 300 sites surveyed were analysed with the aid of a computer. The sites were grouped into four classes of different scenarios as detailed in Table 1. F r o m the 40 SLM instantaneous readings at each site, the average noise level L~v and the corresponding standard deviation ~x are calculated. Normal distribution is formally tested and established for a sample of randomly selected sites using the chi-square test. This verification enables us to generalise that the sound level distribution function is normal for all sites. The standard deviation a T gives a measure of the short-term temporal fluctuation at a given site. Our analysis shows that, within a particular class, it is practically independent of site. Hence, an average a r for all subsequent calculations is adopted. In agreement with the normal distribution, the Llo, Lso and L 9 o values for every site in each class are found to satisfy the relationships Lso = L~v and AL = Llo - L9o =
2.56cr x
TABLE I The F o u r Classes of Traffic Scenario
Class
Description
TraJflc flow, N (rehicles/min)
I II III IV
M o d e r a t e traffic Busy traffic Very busy traffic D o w n t o w n busy traffic
N < 20 20 < N < 60 60 < N 20 < N _< 60
(1)
Traffic noise survey and analysis in Singapore
119 '100
10'
9O 80 ~
8.
.70 .~
23 c
,6O
6
g
• 50 "5 E
"5 .Q
• 30
20 10 56
58
Fig. 2.
60
62
64. 66 68 70 Sound Level in
Distribution
72 7z, dBA
o f S L at a site in class I.
A typical case of these results is illustrated in Fig. 2 in which both the differential and the cumulative distributions are shown. F r o m the values of Lay for each site within a particular class the overall average noise level and the spatial standard deviation a s for the class are calculated, where a s is a measure of the fluctuation from site to site in each class. The distribution of Lav for each class is again found to be Gaussian. As an example, the differential and the cumulative distributions for class I are given in Fig. 3. In a separate calculation all the individual instantaneous noise readings for a specific site at a specific time within a class are treated as independent TABLE 2
Summary of Noise Survey
Class
I II III IV
Moderate traffic Busy traffic Very heavy traffic Downtown busy traffic
Number oJ sites
Ll 0
Lso
Lgo
°1
Os
o-
j ( o -2 4- 0"~
80 120 20
68.9 77.4 84-12
64-5 72.3 79
60.1 67.2 73.9
3.4 4-0 4-0
2.3 3.0 1-7
4.3 5.6 5.1
4.1 5.0 4.4
80
77-4
73
68.6
3.4
2.3
3.9
4.10
H. K. Sy, P. P. Ong, S. H. Tang, K. L. Tan
120
100
18 80
14
:,5
12
g
•~
z
60
10
D
E
g8
z,0 20
59
60
64
62 Sound
Fig. 3.
66 Level in
dBA
68
70
Distribution of average SL Lay from site to site for class I.
100 90 80 70
g 60
i
~ so ~
4o
~
2O 10 0
45
NOISE
Fig. 4.
50
60
70
80
90
dBA
Distribution of all SL in class I (moderate traffic).
g
Traffic noise survey and analysis in Singapore 100
-
:::==:=~-
121
. . . .
90 ~-
Lso: 72. 3 dBA
80 7O 60 5o
oIt.
20
~
,o
II
0 45 NOISE
Fig. 5.
I "-'"" 50 i5
I 60'
65
l/0
75
I 80
85---' -1---95 90.... dBA
Distribution of all SL in Class II (busy traffic).
data. This yields, for each class, a standard deviation a which measures noise fluctuations both in time as well as from location to location. Results for this method of calculation are shown in Figs 4--7, where the distribution is again found to be normal. Since the temporal, spatial and overall distributions are all Gaussian, their corresponding standard deviations satisfy the equation a2
= a~. + a2
(2)
The consistency of our data with eqn (2) is illustrated in Table 2. 100
::::--:::::====;:
-
I
90 80
I L50 = 79 dBA
60
30
20 10
45
I
50 NOISE
Fig. 6.
d5
I
60
05
70
75
80
85
I----=~5
90
dBA
Distribution of all SL in Class III (very heavy traffic).
122
H. K. Sy, P. P. Ong, S. H. Tang, K. L. Tan
80-
I
...............
L5o = 73 dBA
70-
c
o, 60 -
o-
u
so~
it_
40 -
302010 -
[
0 45
] 50
5]
5
I ill I 6s 60
75
I 80
70
t,
.
90
NOISE Fig. 7.
1__
8s'--T "-"9-s dBA
Distribution of all SL in class IV (downtown busy traffic).
The foregoing results are summarised in Table 2. For each class, the average L 10, Lso, L9o and the respective standard deviations aT, a s and a are given. The value x/(a~ + a ~ is shown to be consistent with a. The Lso values of 64.5, 72.3 and 79 dBA for moderate, busy and very heavy traffic and the value 73 dBA for downtown traffic are comparable to those obtained in other cities. The values of o-x are close to 4 dBA in all cases. In some studies aT was found to decrease with increasing traffic. The present study does not support such a trend. Based on our study the Noise Pollution Index (AL) 2
LNp=Lso+AL+
TABLE
6~
(3)
3
Noise Pollution Index and Traffic Noise Index
l II Ill IV
Class
Noise Pollution Index
Traj~c Noise Index
Moderate traffic Busy traffic Very heavy traffic Downtown busy traffic
74-5 84.3 91-0 82.9
64-9 78.2 84.9 73.4
Traffic noise survey and analysis in Singapore
123
and the Traffic Noise Index TNI = L 9 0 -t- 4AL -- 30
(4)
are calculated and presented in Table 3.
4.
TRAFFIC NOISE MODEL
A traffic noise model has been proposed and applied to G e r m a n 4 and Italian 5 towns. According to this model, the equivalent noise level is related tO the traffic and urban parameters by Leq = ~ nt-
10 log (N L + flNw) + 10 l o g ~
+ AL v + ' A L F + AL B + AL s + AL G + ALvB(dBA )
(5)
where N e (vehicles/h) is the flow of private cars, normal motor-cycles and light commercial vehicles; N w(vehicles/h) is the flow of heavy commercial vehicles, public transport vehicles and high noise level motor cycles; d is the distance from the centre of traffic, and is referred to a standard value of d o = 25 m; AL v accounts for the influence of flow velocity; AL r and AL B represent the correction parameters due to sound reflection by nearside faqades and by building fronts on the other side of the road (taken to be 2.5 and 1.5 dB, respectively); AL s is the correction relative to the road surface; AL G the correction due to road gradient; and ALvB accounts for extreme situations of traffic. In this survey the number of vehicles was counted over a period of 3 min at selected sites where the noise levels were being recorded simultaneously. A r a n d o m survey shows that the fraction of noisy heavy vehicle traffic in Singapore is typically 5~o of the total traffic. The value AL v = + 1.0 was chosen for the typical traffic speed of between 50 and 60km/h. The surface correction AL s was chosen to be - 0 . 5 for typical smooth asphalt Singapore roads. AL G was taken as zero since almost all the roads surveyed are horizontal. The corrections ALF and AL B for the presence of buildings were subtracted out from individual site measurements before analysis. The relation between Zeq and traffic flow rate N(in vehicles/min) for the first three classes is shown in Fig. 8. Using least squares fitting the best straight line is determined as Leq = 53"73 + 9.7 log N
(6)
124
H. K. Sy, P. P. Ong, S. H. Tang, K. L. Tan. 85 <
,,, . . . . . i .......... i....... ~....... i .......... ! . ^ ' v : ...... "O
,
7 5
.
.
65
~
.
;
.
.
:
-
".'
"
.
":
-,
"""
:
" ""
'~"
' " Y - "
"
""
":
"
"
"
55 •
. . . . .
45
.
.
..
I 2
Fig. 8.
.
- . . . . . . . . . .
.
:. . . . . . . . . . . . . . .
:
i
i
i
. . . . . . . . . . . . . . . . . . . . . . . . .
i
i
5 10 20 50 100 VEHICLE COUNT PER MIN
200
Correlation between noise level and traffic volume•
This is in good agreement with the prediction according to eqn (5). The value of/~ was chosen to be 8; this is the typical value used in earlier studies. 4'5 A value of ~ = 30-2 (dBA) was finally obtained from eqns (5) and (6). This should be compared with ~ = 33.8 for German towns and = 35'1 for Italian towns. The parameter ~ is expected to be different from country to country as it is related to the noise level due to a single vehicle and depends on the type of vehicles and the average driving habits of the local people. In this connection, it is appropriate to point out that the majority of vehicles in Singapore are Japanese cars fitted with (1300-1600 cc) engines. The fourth class, namely downtown traffic, does not fit the model of eqn (5), and deserves special consideration. Here the scenario is made up of streets crowded with human activities and the traffic is slow-moving and congested. The observed Ls0 of 73 dB is about 8 dB higher than that of class II with a comparable volume of traffic. This difference comes from (i) the amount of human activity, which varies from time to time, (ii) ALvB which measures extreme traffic conditions (high vehicle density per unit area, traffic junctions, horning, etc.), and (iii) the high concentration of high-rise buildings. At the moment no simple model is available to explain this noise pattern. 5.
CONCLUSIONS
This paper represents part of the work done in a noise survey in Singapore. In this survey, we have carefully differentiated the fluctuations
Traffic noise survey and analysis in Singapore
125
of noise over time and over location. This distinction is often not duly appreciated. A similar survey on residential areas will be published elsewhere. A noise map is being prepared using eqn (5). Subjective tests of traffic noise interference with speech perception have been carried out and will be reported shortly. It is hoped that the present paper fills the gap on noise data and their analysis for modern Singapore.
ACKNOWLEDGEMENTS The authors wish to thank the Telecommunication Authority of Singapore for a grant without which this survey would not have been possible. We also thank the departmental technicians, S. Ratnam, T. M. Wu and B. H. Tay, and the students of the Physics Department for their assistance in carrying out this study.
REFERENCES I. A. M. Mattar, A statistical study of traffic noise in private housing estates in Singapore, Ph.D. Thesis, University of Singapore, 1977. 2. R. B. W. Heng, A noise survey of public housing estates in Singapore, Acoustics Letters, 1 (1979), pp. 198-203. 3. R. B. W. Heng, The acoustic environment of Singapore schools in relation to traffic noise. In Proceedings of the Second Symposium on Our Environment, Singapore, 1979, p. 27. 4. B. B. M. Miiller, Verkehrsl/irmprognoise bei Stadtral3en. Unver6ffentlichter Bericht des F.A. 4762 des Bundesverkehrs-ministers, Bonn, 1978. 5. B. G. Cannelli, K. Gliick, S. Santoboni, A mathematical model for evaluation and prediction of the mean energy level of traffic noise in Italian towns. Acustica, 53 (1983), pp. 31 6.