Statistical model to simulate noise levels generated by vehicle traffic flow in the Caribbean Region of Colombia Edgar Quiñones-Bolañosa) Javier Mouthon-Bellob) Environmental Modeling Research Group, Faculty of Engineering, University of Cartagena Carrera 6 No 36 - 100, Centro, Cartagena de Indias, Colombia Ciro Bustillo-Lecomptec) Department of Chemical Engineering, Ryerson University 350 Victoria Street, Toronto, Ontario, M5B2K3, Canada The objective was to evaluate the applicability of a statistical model to simulate noise levels generated by vehicle traffic flow in the Caribbean region of Colombia. Noise levels were measured in rush hours during working and no working days in eight (8) vial intersections in urban areas in the city of Cartagena (Colombia). Vehicle counting was carried out simultaneously, recording flow directions, and vehicle class (Buses (B); light and heavy vehicles (LV, HV) and motorcycles (M)) and traffic flow. Noise measurements were realized with a sound level meter Type II, in the track of the 627 administrative act issued by the Ministry of Environment, Housing and Territorial Development of Colombia. Meteorological parameters such as temperature, relative humidity and wind velocities were also recorded. The highest average traffic flow was for the city of Cartagena with 11723 LV, 4540 B 459 HV and 9125 M per day. The highest noise levels was found to be 84,95 dB in the city of Sincelejo. The main cause of this noise level was the high motorcycle flow. The best fit to the experimental data was obtained with a modified version of the German Standard RLS-90 model, with a standard error of 3.0 %. a)
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b)
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c)
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1
INTRODUCTION
Vehicular traffic noise is one of the main sources of disturbance in urban environments. In large cities, it usually represents more than 70 % of the complaints presented to the environmental control agencies in developed and developing countries1,2. To design and implement appropriate prevention plans to minimize and control road traffic noise in urban areas, it is vital to understand the relationship between the road traffic and the noise. It has been reported that heavy vehicles are the most significant factor of urban traffic noise in Hong Kong 3. In that study, a multiple regression model for urban traffic noise was suggested. Li et al.4 proposed a Geographic information System (GIS) based road traffic noise prediction model in China. Similarly, Calixto et al.5 developed a statistical model for the measurement of traffic noise on avenues in the City of Curitiba, Brazil. Similar investigations have been presented for road traffic noise in Nigeria6 and Spain2. Despite these studies, there is not a universal accepted model yet to predict the road traffic noise. The complexity of modeling traffic noise relies not only on scientific and engineering principles, but also on social, economical, cultural and political factors that force researchers to obtain an experimental model for a specific city. Therefore, the objective of this study is to obtain an experimental model for the evaluation of noise pollution in vial intersections in the urban areas of the City of Cartagena de Indias, Colombia. Cartagena de Indias is located on the northern coast of Colombia, on coordinate 10° 26’ latitude north and 75° 33’ altitude west. The colonial walled city and fortress in Cartagena were designated a UNESCO World Heritage Site in 1984. It is the fifth largest urban area in Colombia. Nowadays the city is a center of economic activity in the Colombian Caribbean region and a popular tourist destination. Cartagena has a population of 895400 habitants over an extension of 609.2 km2, where about 94 % of the population lives in the urban area7 of 77.13 km2. Cartagena city has an extremely flat topography and there are no substantial hills in the city or its vicinity. Transportation network is constituted mainly by five avenues; Pedro de Heredia with an average length of 12 km, Transversal 54-Crisanto Luque with 8 Km, Santander with 5 km, Pedro Romero with 5 km, and Bosque-Corredor de Carga with 5 km as shown in Fig. 1. About 28 % of the roads are in good condition, 14 % in regular and 58 % in bad conditions. The average transportation speed is approximately 16 km/h, considering that there are approximately 150000 vehicles per month circulating in Cartagena8. This low speed transforms public transportation in the main cause of stress and noise emissions in the City. Therefore, there is an urgent need to understand the vehicular traffic flow and its impact on people health in Cartagena by evaluating the relationship between vehicle flow and noise. 2
MODEL DEVELOPMENT
As the main objective of this study was to relate vehicle traffic flow and noise, vehicle traffic flow (Q) was considered as the number of vehicles passing by a specific road sector in an hour. Traffic was classified in heavy (trucks, buses) and light (pickup trucks, vans, passenger cars) vehicle flow. However, because heavy vehicles produce stronger noise than light vehicles5, a heavy/light weighting factor (n) has been considered to obtain an equivalent number of light vehicles that can represent the same noise level generated by the counted heavy vehicles. In this study, buses have been considered as heavy vehicle because of the economic, social and cultural
aspects of Cartagena make them an important source of noise. Then, the equivalent traffic flow value (Qeq) given as the number of light vehicles per hour, can be determined as follows: (
(
)
)
(1)
where, HV is given in percentage of heavy over the total vehicle flow per hour. In the other hand, noise level was characterized using the equivalent continuous sound pressure level (Leq) parameter, given in dBA. It is the constant sound pressure level (SPL) which, under a given situation and time period, contains the same acoustic energy as the actual timevarying noise level. It is considered as the most important descriptor for road traffic noise surveys9, and is related to vehicle flow5 as shown in Eqn. (2): (
)
(2)
where a and b are empirical parameters determined using linear regression. Equations 1 and 2 represent a modified version of the German Standard RLS-90 model10. 3
METHODOLOGY
The process of data collection and analysis was carried out in three steps. In the first step, a 16-day monitoring campaign was conducted to measure the SPL and the vehicle flow in rush hours at eight vial intersections in the City of Cartagena; named India Catalina, Blas de Lezo, La Plazuela, Reloj Solar, San Felipe, Las Tenazas, María Auxiliadora, and Bomba El Amparo as shown in Fig. 2. The selected vial intersections represent the eight most critical intersections with the highest road traffic volume in the city11. In the second step, 1-day monitoring campaign was performed to determine the heavy/light vehicles weighting factor described in Eqn. (1). In the third step, a statistical analysis was conducted to determine the applicability of the model introduced in Section 2. 3.1
Noise Level and Vehicle Flow Monitoring Campaign
A total of 76800 traffic noise data was collected every two days between May 24th to June 25 (2009) using a sound level meter Type II (Extech Instrument, Model 407750) with a precision/resolution of ±1.5 dB/0.1 dB. SPLs were recorded between 06:00 am to 9:00 am, 11:00 am to 02:00 pm, and 05:00 pm to 07:00 pm during working and none working days. These time frames represent rush hours in Cartagena. At the same time, ambient temperature, relative humidity, and wind speed/direction were registered every five minutes with a portable meteorological station (Cross Technology). All measurements points were located at 1.2 m above the ground and within 7.5 m from the road edge according to MAVDT12. Vehicle traffic flow was determined by manually counting the numbers of vehicles passing by each lane approaching the monitored intersection, during the selected frame times described above. Vehicles were classified into four categories: cars (microcars, city cars, off-roaders, minivans, and campers); buses (minibuses and buses); motorcycles and trucks (trucks, ambulances and any other vehicle having more than four wheels). th
3.2
Noise Emission Generated by Heavy versus Light Vehicles
The heavy/light vehicle weighting factor, n, described in section 2, was experimentally determined by measuring the SPL generated by a heavy vehicle, alone, and by a light vehicle, alone, with an approaching traffic speed between 30 km/h and 50 km/h, according to the methodology presented by Li et al4. To carry out these measurements, two roadways (Miramar, and Mamonal Avenue) were selected in the city, one in which only light vehicles usually flow and other with only heavy vehicles. Both roadways were characterized having a traffic flow less than 60 vehicles per hour. Two sound pressure level meters were located across the selected road from each other at a distance of 15 m (as seen in Fig. 3). Both sound meters were located at 1.2 m above the ground level. The equivalent sound pressure level was estimated for each type of vehicle as the average of the readings on both sound level meters when their difference was less than 1 dB(A). The weighting factor, n, was estimated as difference between the sound pressure level produced by the heavy (LeqHV) and light (LeqLV) vehicles, Eqn. (3). [
4
]
(3)
RESULTS AND DISCUSSION
The results were divided in characterization of the traffic flow, traffic noise, weighting factor and climate effects on traffic noise. 4.1
Traffic Flow Characterization
Figures, 4 and 5, show the traffic flow on working and no working days for the eight selected vial intersections. It shows, in general, that on working days the traffic flow was higher than that found for no working days, these findings can be explained because people in Cartagena usually prefer to stay at home during no working days. The highest traffic flow was found at Bomba El Amparo intersection, during both working and no working days, this is probably because Bomba El Amparo is one of the main the entrance to the city; from one side it connects Cartagena to a bigger city called Barranquilla and from the other side, and it connects Cartagena to Medellin (the second city in Colombia). The highest passenger car flow, on working days, was found at India Catalina intersection this can be explained because this intersection is the entrance to the tourist area of Cartagena and where most of the main government institutions are present. Truck and buses were grouped as heavy vehicles representing from 12 to 26 % of the total traffic flow on working days and from 8 to 21 % on no working days. Passenger cars and motorcycles were grouped as light vehicles representing the main traffic flow in the city. Traffic flow at the intersections India Catalina, Blas de Lezo, La Plazuela, Reloj Floral, San Felipe, las Tenazas, and María Auxiliadora are controlled with traffic lights. Traffic at Bomba del Amparo intersections is controlled with a traffic roundabout. In all intersections, the approaching velocity ranged from 25 to 35 km/h. Table 1 summarizes other characteristics of the selected intersections.
4.2
Meteorological Conditions
According to the ISO 9613, noise attenuation by meteorological conditions can be neglected when wind speed is less than 4 m/s in any direction and when the temperature and relative humidity range from 20 to 40 oC, and 60 to 80 %, respectively. During the two sound pressure level monitoring campaigns, the average temperature was 30.8 oC, the relative humidity 67 % and the average wind speed of 1.4 m/s north, this means that sound propagation was not affected by the meteorological conditions under which all sound pressure level data was obtained. 4.3
Traffic Noise
Figure 6 shows the sound pressure level variation for heavy and light vehicles when they were individually monitored. It shows that the SPL for heavy vehicles was always higher than those generated by light vehicles. The average SPL for HV and LV were 73.8 (± 3.1) and 64.0 (± 2.7) dBA, respectively. A heavy/light weighting factor, n, of 9.46 was found using Equation 3. This is in agreement with the data reported by Calixto et al5 in 2003. Based on the methodology, the data for eight sites were analyzed, from which data was put into a matrix in order to calculate and determine the factors involved in the process. The mean values of the noise results were calculated per fringes as well as percentile L90, and thus Leq values were determined and correlated with vehicles flow, the percentage of heavy vehicles, and the heavy vehicles weighting factor, as shown in Fig. 7. Therefore by means of the regression squared minimum method, the process parameters were obtained, it was found that the values for the constants a and b in Eqn. (2), are a = 1.63 dBA; b = 64.1 dBA. In this case, the expression that mathematically represents the adjusted curve and can predict the equivalent levels for the road noise is: ( (
))
(4)
Table 2 2 presents the average, standard deviation, maximum positive variation, and maximum negative variation of the calculated and measured values for Leq. Fig. 88 shows a comparison between measured and numerical estimated sound pressure level data. The error between estimated and measured data is negelible as seen in Fig. 8. This fact allows us to affirm that the mathematical model described by Eqn. (2) is able to satisfactorily predict the equivalent sound pressure noise levels generated by the vehicle flow in urban roads for the city of Cartagena de Indias. 5
CONCLUSIONS
It was concluded that none of vial intersections complies the standards, issued in 627 administrative act issued by the Ministry of Environment, Housing and Territorial Development of Colombia, 2006. Furthermore, it was determined that María Auxiliadora was the noisiest vial intersection with 79.69 dB as average sound pressure level on working days, and India Catalina
was the noisiest vial intersection on none working days with 77.66 dB. In contrast, the vial intersection with the highest vehicle flow was Bomba del Amparo with 44502 vehicles/day on working days and 24352 vehicles/day on none working days. San Felipe had the lowest vehicle flow with 14423 vehicles/day on working days and 9011 vehicles/day on none working days. As a result, San Felipe was the vial intersection with the lowest amount of noise. The proposed mathematical model represents well the behavior of noise generation in urban roads for Cartagena de Indias.
6
REFERENCES
1. Establecimiento Público Ambiental (E.P.A.) de Cartagena-Colombia. Propuesta de Monitoreo y Control de la Contaminación por ruido en la ciudad de Cartagena de Indias D. T y C, Departamento de Planeación, EPA, 2004. 2. J.M. Barrigón Morillas, V.G. Escobar, J.A.M. Sierra, R.V. Gómez and J.T. Carmona, An environmental noise study in the city of Cáceres, Spain, Applied Acoustics, Volume 63, Issue 10, pp 1061-1070, 2002. 3. W. M. To, Rodney C. W. Ip, Gabriel C. K. Lam and Chris T. H. Yau, A multiple regression model for urban traffic noise in Hong Kong, J. Acoust. Soc. Am., Vol. 112, No. 2, pp 551556, 2002. 4. B. Li, S. Tao, R.W. Dawson, J. Cao and K. Lam, A GIS based road traffic noise prediction model, Applied Acoustics, Volume 63, Issue 6, 2002, pp 679-691, 2002. 5. A. Calixto, F. B. Diniz, P. H. T. Zannin, The statistical modeling of road traffic noise in an urban setting, Cities, Volume 20, Issue 1, pp 23-29, 2003. 6. M.U. Onuu, Road traffic noise in Nigeria: measurements, analysis and evaluation of nuisance, Journal of Sound and Vibration, Volume 233, Issue 3, 8 June 2000, pp 391-405, 2000. 7. Alcaldia Mayor de Cartagena de Indias. Plan de Ordenamiento Territorial – POT Cartagena de Indias. Decreto 0977 de 2001. Cartagena. 2001. 8. Alcaldía Mayor de Cartagena de Indias. Proyecto Cartagena como Vamos. Como Vamos en Movilidad. Cartagena, 2010. 9. D. Haling, H. Cohen, Residential Noise Damage Costs Caused by Motor Vehicles, Transportation Research Record: Journal of the Transportation Research Board, Transportation Research Board of the National Academies, Energy and Environment, Volume 1559 / 1996, pp 84-93, 2007.
10. RLS-90 Richtlinien fur den Larmschutz an Strasen,1990. Bonn: Der Bundesminister fur Verkehr, Abteilung Strasenbau. 11. M. Dagobert Narvaez and G. Gonzalez Grey. Modelos para evaluar la contaminación atmosférica por gases y ruido producida por el tráfico vehicular. Trabajo de grado presentado como requisito para optar el título de Ingeniero civil en la Universidad de Cartagena. Noviembre 1995. 12. Ministerio de Ambiente, Vivienda y Desarrollo Territorial (MAVDT). Resolución 0627 de 2006. República de Colombia. 2006.
Table 1 - Physical characteristics of the measured vial intersections (2009) Intersections India Catalina Las Tenazas San Felipe Reloj Solar María Auxiliadora Blas de Lezo Bomba el Amparo La Plazuela
Number Driving Lanes Seven Six Six Four Five Five Six Six
Pavement Surface Texture Concrete Asphalt Concrete Concrete Concrete Asphalt Asphalt Asphalt
Table 2 - Statistics of the Calculated and Measured Values for Leq en dBA Statistical Parameter Average
Model Measurement 0.0046
Standard Desviation
1.40
Maximal Positive Variation
3.11
Maximal Negative Variation
1.90
Fig. 1- Transportation network in the City of Cartagena, Colombia. Image Date: 12/28/2009.
Fig. 2 - Locations of the selected vial intersections.
Sound pressure level meter Roa
7.5 m
7.5 m
Sound pressure level meter
Fig. 3 - Schematic diagram of the traffic noise survey of individual vehicles.
Fig. 4 - the traffic flow on working days for the eight selected vial intersections.
Fig. 5 - the traffic flow on no working days for the eight selected vial intersections.
Fig. 6 - Sound pressure level variation for heavy and light vehicles.
75.0
Experimental Leq (dBA)
74.0
73.0 72.0 71.0 70.0 69.0 68.0 67.0 30.0
32.0
34.0
36.0
38.0 40.0 10 Log(Qeq)
42.0
44.0
Fig. 7 - Linear regression for experimental versus traffic flow data.
76.00
Leq [db(A)]
74.00
72.00 70.00
Leq(Exp) Leq(Teo)
68.00 66.00 64.00 1
21
41
61 81 Data number
Fig. 8 – Estimated versus Measured Values for Leq.
101
121
46.0
