Prediction of LA10T traffic noise levels in the city of Visakhapatnam, India

Applied Acoustics 34 ( 19911 101-110

Prediction of LAIOTTraffic Noise Levels in the City of Visakhapatnam, India P. R a m a l i n g e s w a r a R a o * & M. G. Seshagiri R a o Department of Engineering Physics, College of Engineering, Andhra University, Waltair, 530 003 India (Received 3 September 1990; revised version received 6 February 1991;

accepted 12 February 1991)

A BSTRA CT The environmental noise level due to motor vehicle traffic to a first approximation is a function of traffic volume. The values of sound pressure level ( L Al ov) resulting from traffic noise measurements over one-hour periods have been correlated with the equivalent measured numbers of heavy~light vehicles per hour (traffic density). A statistical analysis of the data has been made to enable LAIOr tO be expressed in terms of the traffic densi O' in the city of Visakhapamam, India in 1986 and 1987. Plots of LAlov against logarithm N h (equivalent heavy vehicle density) and logarithm N 1 (equivalent light vehicle densio') fbr the different zones, as well as for the entire city. have been made. The validity of these equations is tested by computing the values of the noise indices from these equations, using the traffic density data and comparing them with the measured values. The difference between the measured and calculated values is very small.

INTRODUCTION A systematic and exhaustive noise measurement p r o g r a m m e throughout the City of Visakhapatnam, India, which has a population o f greater than one million, has been performed to assess the noise environment in typical * Present address: National Thermal Power Corporation Ltd, Environmental Engineering, Core-6, 7th Floor, Scope Complex, 7 Institutional Area, Lodhi Road, New Delhi 110003, India.

101 Applied Acoustics 0003-682X/91/$03.50 © 1991 Elsevier Science Publishers Ltd, England. Printed in Great Britain

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P. Ramalingeswara Rao, M. G. Seshagiri Rao

Indian cities; and also to develop models for predicting noise levels in different types of localities (zones) in the city. Accordingly, semi-empirical 1 and regression equations-' developed from experimental data to predict LACqr values are found to be in good agreement with experimental observations. As an extension of the study in the present paper, an attempt has been made to express the LA to-r values as a function of traffic density, by a statistical analysis method. In India, traffic noise studies are few and arbitrary. The earlier studies have measured only the traffic noise in some Indian cities and presented raw data only. Prabhu & Chakraborty 3 have presented a prediction model based on their measurements carried out at selected points in the city of Calcutta during 1977. This predictive equation for LAso-r is expressed as a linear combination of a number of parameters describing traffic density, road type and land use. The dependence of noise level on different parameters has been studied by a number of authors'*-15 in different countries. Delany'* and Delany et al. 5 in the UK have developed theoretical models for the prediction of LAbor noise indices due to motor vehicles. Jraiw t5 has developed a computer model for the prediction of Lalov, Lasor, LA90Tand La~qv based on field measurements made at a number of sites in Bath, U.K. Studies of noise level (kerbside values) emitted by seven different categories of motor vehicles travelling on the roads of Visakhapatnam city under actual conditions have been carried out and the average noise emission levels estimated.t 3 The same study has also shown that the average noise level of a particular type of vehicle is quite insensitive (within + 1 dB) to factors such as road width, condition of road surface and presence or absence of reflecting and absorbing surfaces. Because the average speed with which the vehicles move on inner city roads rarely exceeds 25-30 km/h, and because the average noise emission levels of mopeds, scooters and tempos (three-wheeled vehicles) rarely change by more than + 1 dB, and of cars, buses and trucks by more than ___6 dB, it is assumed that the traffic noise, to a first approximation, is a function of traffic volume only. Accordingly, regression equations connecting the LAto-r level and the traffic density are proposed. Their validities have been tested using the extensive data of LAbor for each hour and for corresponding values of motor vehicle traffic density.

M E T H O D OF C A L C U L A T I O N A N D M E A S U R E M E N T For measurement of traffic noise, 65 locations spread over the entire city of Visakhapatnam were chosen. These locations are divided into four groups (zones), as follows:

Prediction Of LAIoT traffic noise levels

103

(1) Residential (2) Commercial (3) Residential and commercial (4) Industrial At each of these locations, measurements were made when there was reasonable traffic activity (in general from 8.00 a.m. to 21.00p.m.). LAL0r values (in dB) for each hour were obtained from the integrating sound level meter. The sound level meters used in the noise survey were: (1) Precision Integrating Sound Level Meter Type CEL 193 (an IEC-651, B.S. 5969 type-I Instrument), and (2) Integrating Sound Survey Meter Type CEL 283 (an IEC-651 B.S. 5969 type-II Instrument). The measurements in the present investigation were carried out during 1986 and 1987. The sound level meter was mounted on a stand at a height of 1.2 m above ground level and was located at the side of the road as per ISO R-362 regulation. During the time interval T of noise measurement (20-30 min in each hour), the vehicles of different categories that passed the point of observation were counted. The time-varying sound levels were recorded manually by taking readings from the sound level meter at intervals of 10 s. From these data, which are taken as representative for the 1-h interval, noise indices LAbor, LASOV, LA9Or, LNp, traffic noise index (TNI) and noise climate (NC) have been evaluated. In earlier studies L2 statistical regression equations for the LAoqV value with traffic density have been derived. A similar analysis for LA~o'r versus logarithm of the traffic density is attempted in the present study. Here, LAbor indicates the sound pressure level which exceeded for 10% of the time of the recording interval. The average noise emission levels of/7.pA, emitted by the seven categories of motor vehicles on the roads of Visakhapatnam, have been determined in previous work ~z by studying a total of 4994 vehicles. From this study, the equivalent number of vehicles of a particular category whose total noise emission level equals that of a single vehicle of another category has been computed. Thus, the total traffic density consisting of different types of vehicles can be converted to an equivalent density of a particular category. Statistical analysis carried out on the extensive data obtained at different locations in different zones of the city yielded statistical mean noise level (LAtoT) values for the city and for different zones of the city, as well as the statistical mean for the logarithm of equivalent heavy/light vehicle density. (N,, N 0. Standard deviations for these quantities, as well as the standard errors of estimates, have been computed. Correlation analysis between the LAbOr value for different locations in a

104

P. Ramalingeswara Rao, M. G. Seshagiri Rao

zone and the corresponding logarithms N, or N 1 yielded correlation coefficients (r) for the different zones in the city and for the combined city. The regression analysis has been carried out using correlation coefficient (r) and the regression equation is given by Y - F = r ~Y(X-)~)

(1)

O" x

where X is the logarithm of traffic density (heavy/light per hour) Y is the LAt0T value ax is the standard deviation of the logarithm of traffic density a~ is the standard deviation of the LAIOT values .~ is the mean of the logarithm of traffic density is the mean of LAt0T values This yields regression equations LAtOT versus logarithm of traffic intensity for both cases of equivalent numbers of heavy/light vehicles per hour. The equation then can be rewritten in the form LAt0- r =

a log.~ + b

(2)

where a is the regression coefficient (slope) obtained from the analysis of the data and b is the intercept, while Nx is the equivalent number of vehicles per hour of a particular category corresponding to the total mixed traffic density. A plot of Lator measured against the logarithm of the equivalent number of vehicles of a particular category should be a straight line. The regression equations for the different zones can be obtained by substituting the corresponding values of a and b in eqn (2).

RESULTS A N D DISCUSSIONS Table 1 presents the average of noise emission levels, E,pA, for different categories of vehicles on the roads of the city, and the equivalent number of light vehicles (scooters) and the equivalent number of heavy vehicles (trucks) in terms of the average noise emission levels. It can be seen from the table that scooters (light vehicles) with a mean emission level of 73.20 dB(A) are the least noisy vehicles, while trucks (heavy vehicles) with a mean emission level of 87.42dB(A) are the noisiest. Table 2 presents the values of the statistical analysis data for the correlation between the L AtOT value and the logarithm of equivalent density for the different zones and for the entire city. The correlation coefficient (r) is better in all cases. Table 3 presents the values of a and b for different zones and for the combined city, the intercept and

105

Prediction of L,to v traffic noise levels

TABLE I /7.p, Values for Different Categories of Vehicles and Conversion Factors for Equivalent Numbers of Light Vehicles (Scooters) and Heavy Vehicles (Trucks) Serial no.

Category of vehicles

ff.PA value

Equivalent number of scooters

Equivalent number of trucks

I 2 3 4 5 6 7

Scooters Mopeds Tempos Motor cycles Cars Buses Trucks

73.23 74.30 76"28 78.43 79-28 86"00 87"42

1.00 1"20 2.00 3"30 4.03 18.90 26"20

0"038 0-048 0-073 0"126 0"153 0"714 1'000

slope of the regression equation connecting the LAIOT value and the equivalent traffic density. Different regression equations for different zones can be obtained by substituting the corresponding values of a and b in the equation. The equation for the entire city can be written as: LAIOT = 7"59 log N h + 62"56 LAIOT = 7"73 logN I + 52-75

(3) (4)

Hourly LA~0Tvalues computed from experimental observations are plotted for the different locations in a zone against the logarithm of equivalent heavy/light vehicle density for the different zones as well as for the entire city. Figure 1 represents the plot for the entire city for equivalent heavy vehicles versus the LAtOT value; Fig. 2 represents the plot for the entire city for equivalent light vehicles versus the LAIOT value. Figure 3 represents these plots for all the individual zones in the city for equivalent heavy vehicle density while Fig. 4 represents the plots for all the individual zones in the city for equivalent light vehicle density. The validity of these equations was tested by predicting LAIOT using the equations and the mean equivalent vehicle density (obtained from measured values by conversion using the conversion factors) for the different locations in the different zones, and comparing them with the LAIOT values computed from measured A-weighted sound pressure levels. Computed m e a n LAI0T values from actual measurements and the p r e d i c t e d LAt0T values from the proposed equations using equivalent heavy/light vehicle densities are in good agreement. The standard deviation for the differences in values for the different zones is much less. The present study also indicates that there is better agreement between p r e d i c t e d LAIOT values and those computed from measurement, compared

O

TABLE 2 Statistical Analysis Data for Correlation Between Measured Values and Logarithm of Equivalent Traffic Density for the Different Zones and for the Entire Visakhapatnam City

Serial mJ.

Zone

Equivalent vehich, catego O'

Correhttion coejfieient (r)

Mean noise level L^ l or (dB)

Standard devkttion (dB)

Mean ~] Iogttrithm ~71"equiwth'nt trtt.ffic dettsity

Stamho'd deviation

Stamhtrd error o f estimate

I 2 3 4 5 6 7 8 9 10

All zones (combined) All zones (combined) Residential Residential Commercial Commercial Residential/commercial Residential/commercial Industrial Industrial

Heavy Light Heavy Light Heavy Light Heavy Light Heavy Light

0-507 9 0-524 0 0.627 0 0.620 0 0.5500 0'4700 0.581 0 0"5500 0"493 0 0-5600

78.43 78.43 78-40 78"40 78.50 78-50 79.00 79"00 78.26 78.26

+ 3"53 +__3'53 + 5-37 + 5.37 +3'23 + 3.23 ___3"36 +3"36 + 3"15 +3"15

2'09 3.32 1.89 3.30 2.10 3.42 2" 17 3.46 2.22 3-46

+__0.24 + 0.24 -t-0.26 -I-0.29 +0-24 _+0.25 + 0.26 +0.26 + 0.20 +0.19

3.08 3.00 4-18 4.21 2.69 2"85 2.73 2.79 2.73 2.61

Of LAIoT traffic noise levels

Prediction

107

TABLE 3 Values of a and b for Different Individual Zones, and for All Zones Combined. for the Regression Equation Correlating LA,OT and Equivalent Traffic Density Serial no.

Zones

1 2 3 4 5 6 7 8 9 10

Equiralent vehicle category

Intercept b (dB)

Slope a

Heavy Light Heavy Light Heavy Light Heavy Light Heavy Light

62.56 52.75 53"92 41-09 63-15 57-56 63'00 54.10 60-72 47.45

7.59 7.73 12'94 11"30 7.31 6-12 7.37 7.19 7-89 8-90

All zones (combined) All zones (combined) Residential Residential Commercial Commercial Residential/commercial Residential/commercial Industrial Industrial

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Prediction of LAtoT traffic noise levels

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to the agreement between predicted and measured LAeqT values proposed earlier. L2 As such, regression equations for the prediction of LA~0T values can be used with slightly more reliability compared to the corresponding equations for the prediction of LAeqT. The regression equations for predicting LAbor values can be used for quick prediction of LAbor from the equivalent traffic density and also serve to plan noise control measures• ACKNOWLEDGEMENT The authors record their grateful thanks to the Ministry of Environment and Forests, Government of India, New Delhi, for financial assistance to a project of which the present work forms a part.

110

P. Ramalingeswara Rao, M. G. Seshagiri Rao REFERENCES

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