12010Study of Vehicular traffic noise andits effect 60 St. HillahVoluntary study

ByEng.Ahmed Sami Al-Khifaji

Shared in field work:Eng.Sadiq Khaleel Shadeed

Mr.Abbas Khudeir(environmentmanager-Babil)

2This study is a voluntary study and it is not financed fromany company or organization, it is an individual efforts from

the researcher, and it is a try to serve the Humanity, animprove the Iraqi people live and to save them from the

dangerousness

Ahmed Sami

3CHAPTER-1Introductions

Noise from transport has become a major pollutant of the outdoor urbanenvironment.The levels of noise cannot be any longer ignored by highwayengineers, developers and local authorities. High levels of noise may lead toa substantial change in the proposed construction plans and require noisecontrol measures such as barriers, absorbing road surfaces, buildinginsulation or restriction on vecular access to and speed in residential areas.These measures should be carefully examined and justified in terms of theiracoustic performance, costs, effectiveness, durability, visual intrusion andsafety.the general definition of noise is: the unwanted sound is typicallycharacterized by intensity, frequency, periodicity (continues or intermittent)and duration of sound. ( 1), the (dBA) is the unit of sound measurement.The ways of transporting of sound depend on the levels and distancebetween the road (source) and the receiver also the changes in the nature ofearth and the direction of winds. (2)

The major sources of noise are:1. Industrial noise2. Traffic noise3. Community noiseOut of above three parameters, the source that affects the most is Trafficnoise. In traffic noise, almost 70% of noise is contributing by vehicle noise.Vehicle noise, mainly, arises from two parameters i.e. Engine noise and Tirenoise. The major concern is to study the vehicular traffic noise and itsprediction.

:(3)mful Effects of Noise on Human Beings: Har)1-1.1(1-Reduces work efficiency.2- May cause Temporary Threshold Shift / Permanent Threshold Shift.3-Induces loss of hearing ability.4-May damage the Heart.5-Increases the cholesterol level in the blood.6-Dilates the blood vessels of the brain.7-Upsets the chemical balance of the body.

48- Causes headache, nausea and general feeling of uneasiness.9-Induces errors in motor performance, in visual perception.(1- 1-2) Useful Applications of NoiseNoise is not only has harmful affects but sometimes it is very useful. Someof The examples when noise is useful:1. Study of heart beats: Noise produced by the heart beats is very useful toDiagnose the persons health accordingly.2. Masking effects: Sometimes, it is necessary that nobody should hear theconversation between the two persons. For this, masking effect is used. Fore.g., In the doctors chamber, doctor wants that nobody should hear hisconversation with the patient so Dr. uses masking effect by putting a morenoisy exhaust fan which make noise outside the room.

(1-2) Physical Property of Sound:The definition of sound is: the difference in pressure (in air or water or anymedia) and the human ear can feel it (hear it).Undulation in an atmospheric pressure produced from vibration of atoms ofair, outcome a sound wave is called (sound pressure). Sound pressuremeasured by dBA (decibel)dBA is logarithmic ratio which defines the sound pressure level SPL asfollows:SPL=20*log (P/Po)In this formula (P) is the sound pressure measured and (Po) is the referencesound pressure 20 Pa.This logarithmic scale has several advantages over a linear scale. The mostimportant advantages are:

1. A linear scale would lead to the use of some enormous and unwieldynumbers.

52. The ear responds not linearly, but logarithmically to stimulus.Conversion from one scale to the other can easily be done by use of themathematical expression. (Table 1.1)

Table (1.1) Environmental conditions at different SPLSound Pressure(N/m2)

Sound Pressure Level(dB)

Environmental Conditions

102 134 dB Threshold of pain

10114 dB Loud Automobile horn

(distance 1m)1 94 dB Inside subway train

10-1 74 dB Average Traffic on streetcorner

10-2 54 dB Living room, Typicalbusiness office

10-3 34 dB Library

10-4 14 dB Broadcasting Studio

10-5 0 dB Threshold of Hearing

(1-3) Weight of sound measurement (Weighting Curves) (Weighting filters):There are three global scales for weighting curves are (A,B,C) differentaccording to the frequency that the ear can feel it. The most commonly usedof these curves is the (A- weighting curve) as it gives the best correlationbetween the measured values and the annoyance and the harmfulness of thesound signal that comes from vehicles. The (D- weighting curve) is usedwith used for aircraft noise, In addition to these weightings sound levelmeters usually also have a Linear or zero weighting.(Fig.1-1)

6Fig 1.1 Weighting Curves(1-4) Noise Levels:Percent Exceeded Sound Levels:L10 = 10 percent exceeded Sound level (av. Peak level)L90 = 90 percent exceeded Sound level (av. Background level)L50 = Median value of Sound levelL10 L90 = Noise climateAlso, Leq = the equivalent steady-state sound level which in a stated periodof time contains the same acoustic energy as a time-varying sound levelduring the same period. and can calculate by the following equation:

Leq=L50 + (L10 L90)2/ 56 . (42)

(1-5) NOISE MEASUREMENT TECHNIQUES & INSTRUMENTS:

7The all noise measuring device typically use sensor to receive thesignal from the source the signal consist of the noise from the Sourceand the background sound, and to reduce the background noise likethe friction of wear of the researcher and other noise we must applythe following instructions:

1- The minimum distance between the researcher and theinstrument is (0.5) meter.

2- The instrument must be at (1) meter from the wall ofneighboring house or building.

3- The instrument me be put on frame stand4- The height of instrument not less 1.2 m from the earth. See fig

(1-2)

Fig 1.2 Noise Measurement Procedures

8In this study we used (sound level meter) manufactured by Bruel & Kjear model2237 as shown in fig (1-3):

Fig (1-3): sound level meter

(1-6) the Parameters with affect on the traffic noise :The essential parameters that affect on traffic noise are:1- The flow of traffic.2- Traffic speed.3- The ratio of heavy vehicle in traffic flow.4- Elevation of road.5- The condition of surface of road.6- The distance from the source and the receiver.7- The partition and the buildings.The traffic noise is changed according to the changes of the number and typeand speed of vehicles in one section of road. (5)3

9Fig (1-4) the essential elements of traffic that affect on traffic noise.

1-6.1 Traffic Flow:Traffic volume is defined as the total number of vehicles flowing per hour.

The number of vehicles passing through a fixed point on the road is to becounted; we obtained the traffic flow in this study by video filming bycomputing the number of vehicles which passed the section through onehour for each section.1-6.2 Traffic speedTraffic speed is the distance which traveled by vehicle through unit time,and there are many method to compute the speed such as by radar or byelectronic sensors putted in the roads, we obtained the vehicles speed in thisstudy by video filming.1-6.3 Heavy Vehicles:Trucks and buses are contributing more noise to the environment, whencompared to automobiles. The ratio of heavy trucks and buses to total trafficis called truck traffic mix ratio. This is computed in terms of percentage. Anincrease in this ratio will increase the noise level.(6)4 , the Fig(1-5) showthe noise level which comes from private and heavy truck and medium truck

10

.

111-6.4 traffic density (K):Traffic density defined as the number of vehicles in a specific sectionof road in any period of time.We obtained the vehicles speed in this study by video filming, andusing the following equation (7)5

Where:K= mean traffic density (Veh/km/ln)n=number of observationsKi= number of vehicles/ length of section(m).

12

Chapter 2

13

Theories and method of work

This chapter contain explanation and definition to the region ofstudy and the ways of obtaining the data and analysis and thestatistic program that used for multilane road 60st. in Hilla city, andthis data consist methods of measuring the essential elements oftraffic (speed, density, flow) and effect of this elements on the levelsof noise (see Figure (1-4)).(2-1) defenition of study region:The 60 St. in Hilla is one of the main multilane highways in city (seeFig (2-1)).

Fig (2-1) 60 Street image by satellite imaging60 St. start from the intersection of Nadir quarter (south) to the

intersection of Al-Thawra (north) its length is (8)km and it classify as 4lane multilane highway and it separate by intermediate with

14width (3)meter and the width of road in one direction is 10 meter andon its long therere many turning on left and right and there is a towcar bridge one the middle and the other at the end (north) underconstruction, and there are two pedestrians bridges.Along the street there are overlapping in traffic activities and the

movement of pedestrians and this overlapping is not regular thatscreate a random passing of pedestrians and that affect on speed andflow and density of traffic all that create a low level of service to theusers of road.In this study we take four stations along the direction of traffic thatcomes from Nadir intersection to Al-Thawra intersection (Up stream)(see Fig (2-2)).

Fig (2-2) location station (1)From these stations we calculate the elements of traffic (Flow, Speed,density) also the levels of noise. (L10, L50, L90, Leq).

15(2-2) survey stage:

In this stage we surveyed (observed) the state of traffic in studyregion 60 St. in Hilla city the condition of surface and the parameterswhich affect on traffic flow and the environmental affects, and wesuggest the locations of stations and the distance from the location ofcamera and road to ensure the evident distance is 50 meter withappear in camera to compute the speeds and flow and density oftraffic in each station, also specified the peak period of traffic .

(2-3) fixing stations stage:In this stage we shared opinion with our supervisor regarding the

locations of stations and by return to the global specifications wefixed the locations of stations also the location of camera.

(2-4) measuring stage (collecting data):In this stage we collected the data from the field using the instrument

of sound level meter and the video camera.(2-4.1) measuring the traffic volume:Is define as: the number of vehicles which pass specific section ofroad through specific period (8)6 , we calculate traffic volume be videofilming through the peak period (peak hour volume) for every stationand after that we analysis the data computerize by using (Excel)program and find the Harmonic mean flow(q) by the following equation:

Where:Q = mean traffic volume (veh/hr)n = number of observations , qi=traffic volume for (i) from observations.In this stage we followed-up the status of road along one week from

(4/4/2010) to (9/4/2010) and we concluded the peak hour and we found it

16was in work days (Sunday, Monday , Tuesday, Thursday) also we taken dataon holidays to give an approximate idea for the traffic situation on 60 St.

2-4.3 compute the mean traffic speed:We measured the mean traffic speed by taking specific section from the

road (50 meter) and calculated the absorbed time to pass vehicle that sectionfor many number of vehicles according to the sample size, and by dividingthe distance (50 meter) on time we obtain speed, and we can obtain meantraffic speed by:Vs=Vt (2/ Vt) ..(9)7

Where:Vs= mean traffic speed (km/hr)Vt= traffic speed (km/hr)2= standard deviationn= total observations

(2-4.4) Traffic density:Return to Chapter (1) item (1-6.4).

17(2-4.5) Sample size:We estimate the sample size by the following equation:N min= (SK/E) 2.. (10)

Where:N min= minimum sample size.S = standard deviation.K = constant, 1.96 for trust degree 95%.E = permissible error= 2.For example to compute minimum sample size for section in region of study(for speed):Standard deviation of speed is =12.48N min = ((12.48*1.96)/ (2)) 2

= 149.58= 150

Where, we take the mean speed (100) observation every (5) minutes for eachsection, therefore we conclude that the sample taken size is (300)observation for every (15) minutes and that is greater that the minimum sizesample (N min).(2-4.6) Noise levels:After calibrating the instrument (sound level meter) we were depend thefollowing instructions (comprehensive study of Baghdad):

1- Record the reading of instrument every (5) second.2- Used weight (A) which is suitable with traffic noise.3- The height of instrument is (1.20)m.4- Location of instrument beyond (1) meter from the fence of building.5- Distance from the researcher and the instrument is (0.5) meter.

And follow the following instruction in measuring:1- The surface of road sections is supposes a plains.2- Wind speed not more than (2 m/s).

183- The paving status is good.4- Temperature degree is 24.5- Neglect horns sound or friction of clothes sound.

We conclude noise levels (L10,L90,L50,Leq) by using the statistical analysisfor the sound pressure levels which obtained from the field see Table (2-1),(2-2) also Fig (2-3),(2-4),(2-5),(2-6).

First StationTrafficnoise obser. obser.100% accumulative64 0 0 10065 1 1 9966 3 2 9867 2 1 9768 1 1 9669 3 2 9470 7 4 9171 9 5 8672 7 4 8273 10 6 7674 14 8 6875 19 11 5876 17 9 4877 21 12 3778 12 7 3079 9 5 2580 11 6 1981 4 2 1782 11 6 1183 6 3 784 7 4 385 3 2 286 3 2 0

Table (2-1) method of calculation the Traffic noise levels statisticaly.Second station

Traffficnoise obser. obser.100% accumuative64 0 0 100

1965 2 1 9966 2 1 9867 4 2 9668 2 1 9469 2 1 9370 7 4 8971 8 4 8572 6 3 8273 11 6 7674 13 7 6875 25 14 5476 12 7 4877 24 13 3478 11 6 2879 8 4 2480 9 5 1981 3 2 1782 14 8 983 5 3 784 5 3 485 4 2 286 3 2 0

Table (2-2) method of calculation the Traffic noise levels statisticallyThird Station

Traffficnoise obser. obser.100% accumuative64 0 0 10065 1 1 9966 3 2 9867 3 2 9668 4 2 9469 4 2 9270 6 3 8871 6 3 8572 7 4 8173 12 7 7474 11 6 6875 24 13 5576 13 7 4877 23 13 3578 12 7 2879 8 4 2480 8 4 1981 4 2 1782 13 7 1083 6 3 784 5 3 485 4 2 286 3 2 0

Table (2-3) method of calculation the Traffic noise levels statistically

20

Fourth StationTraffficnoise Obser. obser.100% accumulative64 0 0 10065 2 1 9966 1 1 9867 4 2 9668 5 3 9369 3 2 9270 7 4 8871 7 4 8472 6 3 8173 11 6 7474 12 7 6875 23 13 5576 14 8 4777 23 13 3478 11 6 2879 9 5 2380 9 5 1881 4 2 1682 12 7 983 6 3 684 4 2 485 4 2 286 3 2 0

Table (2-4) method of calculation the Traffic noise levels statistically

21

Table (2-5) the noise levels and mean speeds and traffic densities and theratio of heavy vehicles and traffic flow in study region.

Site: 60 St.,Measurement period: 15 min.

Microphone at 8.5m (1 meter from the building) from the centre of the Inner lane & at height of 1.1 m

Station Time Density Traffic Flow. QVeh/hr

HeavyvehicleH.V%

Avg. speedKM/hr

Sound Pressure level dB (A)L10 L50 L90 Leq.

First station7:45-8:00 39 562 6.4 76 82.1 75.75 70.1 78.38:00-8:15 39 538 8.2 73 81.8 75.6 69.8 78.28:15-8:30 40 490 11.4 69 82 75.8 69.5 78.68:30-8:45 41 452 10.6 69 81.8 75.6 69.4 78.3

SecondStation

7:45-8:00 24 355 10.3 69 84 75.5 67 80.668:00-8:15 40 400 11.81 81.92 86.25 76.5 68.5 82.138:15-8:30 36 390 9.64 76 87.5 76.7 67.5 83.848:30-8:45 38.5 316 10.15 79.41 85.75 74.3 68 79.93

Third Station7:45-8:00 39.8 370 9.62 76 83.5 76.4 69 80.158:00-8:15 41.5 366 11.5 78.6 86.52 75.4 68.5 81.208:15-8:30 34.6 358 9.48 77.5 86.4 75.5 66.5 82.578:30-8:45 33.8 362 10.71 76 84.5 76 67.5 81.16

FourthStation

7:45-8:00 29 402 11.61 79.40 83.80 75.60 67.60 80.298:00-8:15 31 340 9.67 77.50 85.00 77.20 68.65 81.978:15-8:30 34 378 10.21 76.00 84.50 77.61 68.30 82.308:30-8:45 41 350 9.16 79.92 84.75 79.70 64.30 87.17

22

23

Foreword:In this chapter we were concluded relationships between the essential trafficelements and its affections on the traffic noise levels for the region of studyby statistical analysis using (SPSS ver.14)(Statistica 2005) also (Excel2003).(3-1) traffic speed:We took (100) random sample from the mean traffic speed for different

types of vehicles for period (10) minutes for a section from study region toexplain how concluded the mean traffic speed and the other types of speed(P15,P50,P85) through the statistical program (SPSS) we conclude the (P50)(average traffic speed) have strong correlation with the other traffic elementscharacters and the traffic noise levels ( give a bigger value of (adj.R2). thetable(3-1) and Fig(3-1) show the methods of calculation of the mean speedin a section in study region.

Table (3-1) Sample from the calculations of mean speed in a section of 60 St.

GroupSpeed Mean

SpeedVeh.Frequency(F)

Cumulativepercent oftotalobservation

20-30 25 0 030-40 35 8 840-50 45 7 1550-60 55 11 2660-70 65 22 4870-80 75 18 6680-90 85 7 7390-100 95 5 78100-110 105 10 88110-120 115 6 94120-130 125 3 97130-140 135 3 100

24

0

10

20

30

40

50

60

70

80

90

25 35 45 55 65 75 85 95 105 115 125 135

Series1P50=67

P15=46

P85=107

Fig(3-1) method of caculation the (P15,P50,P85)

0

5

10

15

20

25

25 35 45 55 65 75 85 95 105 115 125 135

Series1

Fig (3-2) method of calculation the mean speed

25

(3-2) relationship between mean speed and traffic density:For find a statistical model explain the relationship between the mean

traffic speed (km/hr) and traffic density (Veh/km) we chooses the speed as(dependent variable) and the traffic density as (independent variable) andtried use correlation equations (Linear, Log, Quadratic, Cubic) we find thatthe best correlation equation is (Cubic) because it gives a greater(R2)(Table(3-2),Fig(3-3)).

Table (3-2) correlation between traffic density and the traffic speedEquation Model Summary Parameter Estimates

Sta.Error

RSquare F df1 df2 Sig.

Constantb1 b2 b3

Linear .023 .324 1 14 .578 71.529 .120 4.09Logarithmic .033 .480 1 14 .500 58.691 4.799 4.07Quadratic .158 1.217 2 13 .328 9.098 3.920 -.056 3.97

The independent variable is K.

Best correlation is Vs= 9.09+3.92(K)-0.056(K)2

26

Fig (3-3) correlation between speed & traffic density

(3-3) relationship between L10 and mean speed (Vs) :From following table and figure we concludes that the linear equationrepresent the top correlation between L10 & Vs because it give a high (R2)and low (Error), that mean the noise level increase by increase the \vehiclespeed and that is logical because when the speed increase the speed of crashof the air with the engine will increase also the sound of engine will increasetoo. (Table (3-3), Fig (3-4))

(Table (3-3) Correlation between (L10) & speed.Equation

Model Summary Parameter Estimates Sta.R

Square F df2 Sig. Constant b1 b2 b3 ErrorLinear 0.408 9.64 14 0.008 62.352 0.29 1.451Log. 0.407 9.606 14 0.008 -9.086 21.597 1.453

Quadratic 0.408 4.479 13 0.033 71.268 0.051 0.002 1.452Cubic 0.408 4.48 13 0.033 71.624 0 0.003 -7.4E-06 1.505

The best correlation is L10=62.352+0.290(Vs)

27

Fig (3-4)(3-4) relationship between traffic flow (Q) and Noise levels :The following table and graph refer to that (L10) give a bigger value of (R

square) and low (error) compare with the other noise levels, also the linearequation is best correlation relationship between (L10) and (traffic flow)(table (3-4), Fig(3-5),(3-6),(3-7),(3-8).

The best equation is :L10=91.676-0.018(Q)

28

(Table (3-4) the correlations between (Noise Levels and traffic flow)

noiselevel Equation

model summery Parameter Estimates ErrorR square F df1 df2 Sig. Constant b1 b2 b3

L10Linear 0.510 14.571 1.000 14.000 0.002 91.676 -0.018 1.320Logarithmic 0.503 14.148 1.000 14.000 0.002 130.966 -7.786 1.329Quadratic 0.510 6.773 2.000 13.000 0.010 90.378 -0.012 -6.9E-06 1.396Cubic 0.510 6.773 2.000 13.000 0.010 90.378 -0.012 -6.9E-06 0 1.400

L50Linear 0.035 0.509 1.000 14.000 0.487 77.479 -0.003 1.241Logarithmic 0.030 0.434 1.000 14.000 0.521 83.834 -1.277 1.242Quadratic 0.055 0.377 2.000 13.000 0.693 70.335 0.030 -3.8E-05 1.247Cubic 0.050 0.345 2.000 13.000 0.715 73.186 0.012 0 -2.6E-08 1.277

L90Linear 0.430 10.544 1.000 14.000 0.006 62.837 0.013 1.127Logarithmic 0.425 10.345 1.000 14.000 0.006 34.225 5.668 1.132Quadratic 0.430 4.895 2.000 13.000 0.026 62.930 0.013 4.92E-07 1.170Cubic 0.430 4.896 2.000 13.000 0.026 62.523 0.014 0 -1.9E-09 1.170

Leq.Linear 0.377 8.472 1.000 14.000 0.011 89.154 -0.020 1.924Logarithmic 0.365 8.035 1.000 14.000 0.013 132.357 -8.577 1.943Quadratic 0.383 4.028 2.000 13.000 0.044 81.805 0.014 -3.9E-05 1.988Cubic 0.383 4.028 2.000 13.000 0.044 81.805 0.014 -3.9E-05 0 1.990The independent variable is (Q) traffic flow.

29Fig (3-5) correlation between L10 and traffic flow (Q)

Fig (3-6) correlation between L90 and traffic flow (Q)

30Fig (3-7) correlation between L50 and traffic flow (Q)

Fig (3-8) correlation between Leq. and traffic flow(Q)

31

(3-5) relationship between traffic Density (K) and Noise levels :According to the following statistical results in Table (3-5) we concludesthat the (L50) give a best correlation relationship with the traffic density,comparing with the other noise levels, the quadratic equation represent thebest statistical relationship between (L50) and traffic density because it give ahigher value of (R square) and low value of (Standard error) the Figure (3-9)refer to that the (L50) will increase if the traffic density.

Figure (3-9) the best correlation between L50 and traffic density

Quadratic equation

The best correlation equation is: L50=71.762 +0.243(K) - -0.00326(K)2

32

noiselevel Equation

model summery Parameter EstimatesErrorR square F df1 df2 Sig. Constant b1 b2 b3

L10Linear 0.010 0.141 1.000 14.000 0.713 85.702 -0.036 1.876Logarithmic 0.006 0.089 1.000 14.000 0.769 87.805 -0.954 1.879Quadratic 0.068 0.476 2.000 13.000 0.632 67.055 1.099 -0.017 1.888Cubic 0.068 0.471 2.000 13.000 0.634 72.874 0.552 0 -0.00017 1.889

L50

Linear 0.009 0.121 1.000 14.000 0.734 75.381 0.022 1.258Logarithmic 0.010 0.140 1.000 14.000 0.714 73.336 0.799 1.257Quadratic 0.013 0.088 2.000 13.000 0.916 71.762 0.243 -0.00326 1.302Cubic 0.013 0.088 2.000 13.000 0.916 71.762 0.243 -0.00326 0.00E+00 1.303

L90

Linear 0.067 0.999 1.000 14.000 0.334 65.439 0.074 1.442Logarithmic 0.069 1.032 1.000 14.000 0.327 59.228 2.485 1.44

Quadratic 0.071 0.497 2.000 13.000 0.619 61.362 0.322-3.68E-

03 1.493

Cubic 0.072 0.503 2.000 13.000 0.616 62.395 0.214 0-4.01E-

05 1.492

Leq.

Linear 0.004 0.050 1.000 14.000 0.827 82.061 -0.028 2.434Logarithmic 0.002 0.033 1.000 14.000 0.859 83.732 -0.749 2.453

Quadratic 0.018 0.119 2.000 13.000 0.889 70.082 0.701-1.08E-

02 2.507Cubic 0.016 0.107 2.000 13.000 0.900 74.302 0.328 0.00E+00 -0.0001 2.509

The independent variable is (K) traffic Density.

Tab(3-5) statistical results show the correlations between noist level and traffic density.

33

(3-6) relationship between Noise levels and the ratio of heavy vehiclesfrom the traffic volume:The following statistical results (Table (3-6)) are refer to that (L90) representthe best level to mention the relation with the percentage of heavy vehiclesfrom the traffic flow and the quadratic equation represent the best correlationthe Figure (3-10) explain the quadratic equation .

Figure (3-10) the relationship correlation between L90 and the percentage ofheavy vehicles

Quadratic equation

%

34

noiselevel Equation

model summery Parameter EstimatesErrorR square F df1 df2 Sig. Constant b1 b2 b3

L10

Linear 0.092 1.426 1 14 0.252 80.367 0.401 1.796Logarithmic 0.108 1.700 1 14 0.213 75.363 3.931 1.78Quadratic 0.154 1.186 2 13 0.336 65.847 3.589 -0.171 1.799Cubic 0.154 1.186 2 13 0.336 65.847 3.589 -0.171 0 1.8

L50

Linear 0.017 0.249 1 14 0.625 77.369 -0.117 1.252Logarithmic 0.010 0.145 1 14 0.710 78.055 -0.809 1.256Quadratic 0.090 0.644 2 13 0.541 66.829 2.198 -0.124 1.25Cubic 0.086 0.608 2 13 0.559 70.325 1.043 0 -0.004 1.233

L90

Linear 0.018 0.259 1 14 0.619 69.545 -0.141 1.479Logarithmic 0.033 0.484 1 14 0.498 72.102 -1.729 1.467Quadratic 0.222 1.852 2 13 0.196 90.400 -4.721 0.245 1.366Cubic 0.222 1.852 2 13 0.196 90.400 -4.721 0.245 0 1.37

Leq.

Linear 0.007 0.098 1 14 0.759 79.625 0.142 2.249Logarithmic 0.016 0.232 1 14 0.638 76.521 1.973 2.418Quadratic 0.174 1.365 2 13 0.290 48.813 6.909 -0.362 2.3Cubic 0.174 1.365 2 13 0.290 48.813 6.909 -0.362 0 2.302

The independent variable is (H.V) ratio of heavy vehicles to that traffic flow

Table (3-6) correlation between the percentage of heavy vehicles and the noise levels in study region.

35

36

(4-1) Conclusions:1-We concluded that the linear equation represent the best correlationbetween (L10) and traffic flow in study region (60 St.) through the uppervalue of (R square) and the lower value of (STD, Error) comparison with theother relationships.2- According to the field studies and the analysis of results we found that ifthe percentage of heavy vehicles in traffic flow increased the traffic noisewill increases too.3- If we applied the top correlation equation which we got it from statisticalanalysis, we can compute the traffic noise as follow:

L10 (predicted)= 91.676-0.018(Q)And if we make comparison betweenthe predicted L10 and the actual L10we find the deferent between them isvery small.The % Error values are very small thatprove the study is successful because thereare very small difference between(predicted L10) and the (actual L10).

Note: % Error=(L10 act. L10 pred.)/ L10 act.)*100%.................(11)

TrafficFlow. QVeh/hr

L10actual

L10predicted Error %

562 82.10 81.56 0.66538 81.80 81.99 -0.235490 82.00 82.86 -1.044452 81.80 83.54 -2.127355 84.00 85.29 -1.531400 86.25 84.48 2.057390 87.50 84.66 3.250316 85.75 85.99 -0.278370 83.50 85.02 -1.816366 86.52 85.09 1.655358 86.40 85.23 1.352362 84.50 85.16 -0.781402 83.80 84.44 -0.764340 85.00 85.56 -0.654378 84.50 84.87 -0.440350 84.75 85.38 -0.739

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4- The survey form of the citizens view points to that they were disturbedfrom the traffic noise in region of study especially in daytime of work days,that need to put a studies and researches to produce a new environmentalwithout traffic noises.(4-2) Health review:The evidence for a cause-effect relationship between noise and hearing lossis considered sufficient in the scientific community. There is consensus thatsound levels less than 75 dBA are unlikely to cause permanent hearing lossand that sound levels about 85 dBA with exposures of 8 hours per day willproduce permanent hearing loss after many years (12)

According to data from the Workers Compensation Board (1998) in BritishColumbia, almost thirty percent of young adults entering the workforce havealready suffered some hearing damage due to noise.Noise has been reported to lessen the quality and the duration of sleep. Manystudies have focused on the impact of noise on individuals such as patientsin hospital and the impact of particular sources of noise (e.g., aircraft) onsleep. The Health Council of the Netherlands (1996) has considered theevidence to be sufficient for a causal relationship between the long-termeffects of noise-related sleep disturbances, with changes in sleep patterns,awakening, sleep stages, and subjective sleep quality. Susceptible personsmay be affected by noise occurring during sleep, as well as the waking state,with day and night noise being a significant problem for night workers,mothers with babies, elderly persons (Horne et al., 1994), persons who areespecially vulnerable to physical or mental disorders, and other individualswho experience sleeping difficulty (Berglund & Lindvall, 1995.(13)

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Table (4-1) the noise values and its effect on human health

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According to Table (4-1) we can classify the noise in (60) street is veryannoying and its causing a dozing and may be causes a fail in hear operationin future if there is along periods exposure to noise source.

(4-3) Recommendations:There are many recommendations and instructions must be applied to avoidthe harms of the traffic noise:1- To avoid the dangerousness of traffic noise we must use a special

material in construction which reduces the noise like thick glass.2- Specifying the uses of areas in sides of road. Not allow the variable uselike commercial and residential and industrial use in one time for one sectionfrom the street.2- Specifying the path of heavy vehicles, also specifying the periods of

passing for heavy vehicles to reduce the traffic noise and the smoke anddust that generated from passing of heavy vehicles.

3- Advertence with afforestation in sides of road is an active factor to suckthe sounds and protect the region from dust and toxic gases.

4- Use a suitable environmental design factor in future designs of roads inHilla city.

5- Protect the primary schools and the kids parterre from thedangerousness of noise by using the afforestation and construct asuitable fence according a special specification to prevent the noise.

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References(1)-Toronto Public HealthHealth Promotion and Environment Protection Office research 2000.(2)-Paulik,K.(1975)noise and urban environmental road research Paris.(3)-STUDY OF VEHICULAR TRAFFIC NOISE AND ITS PREDICTION(NAROTAM KUMAR) Master letter 2009.(4) - Federal highway administration(1980).(5)- Kim, Y: Online Traffic Flow Model Applying Dynamic Flow-DensityRelations, PhD thesis, University of Technology, Munich, Germany, 2002.(6)- NAROTAM KUMAR (master letter 2009) India.(7) -R.J.slter(1985)highway analysis and design 2nd edition MacmillamEducation,LTD Houndmills.(8)- R.J.slter(1985)highway analysis and design 2nd edition MacmillamEducation,LTD Houndmills.(9) -R.J.slter(1985)highway analysis and design 2nd edition MacmillamEducation,LTD Houndmills(10)-Pignatara reference(11) - STUDY OF VEHICULAR TRAFFIC NOISE AND ITSPREDICTION, NAROTAM KUMAR master letter 2009 Delhi UniversityIndia 2009.(12)- (United States Institute of Health Consensus Statement on Noise andHearing Loss, 1990).(13) -Dr. Sheela V. Basrur Medical Officer of Health March, 2000.