Atmospheric Effects On Traffic Noise Propagation Behind Noise Barriers

Transcription

1 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 1 Atmospheric Effects On Traffic Noise Propagation Behind Noise Barriers A. A. EL-Aassar, R. L. Wayson, J. MacDonald University of Central Florida Community Noise Laboratory Civil & Environmental Engineering Department P.O. Box Orlando, Florida Tel: (407) Fax: (407) aelaassa@pegasus.cc.ucf.edu Word Count Figures and Tables = 3000 Abstract = 213 Main body words = 3352 Total word count= 6565 ABSTRACT Several computer models are used to assess noise levels impacts, i.e. Standard Method In Noise Analysis (STAMINA), the Traffic Noise Model (TNM). These models calculate propagation losses for geometric spreading, diffraction, atmospheric absorption, and ground effects. Though, they have neglected the atmospheric effects of refraction effects on noise propagation. The main objective of this research was to evaluate the effectiveness of noise barriers. However, the data collected allowed evaluation of the meteorological effects on traffic noise propagation as well. The data collection for this study was carried out over three years and twenty sites (Site A-T) in the State of Florida. A comprehensive sound level database and corresponding meteorological data have been created for thirteen of these sites (Site G-S). Other data included site specific information such as geometries, and traffic data. Statistics were employed on this data in order to investigate relations between wind shear and lapse rate on traffic sound levels for first and second row homes behind the barrier. This research demonstrated that even on light wind days (necessary for barrier effectiveness evaluation), lapse rates might still affect the sound levels due to refraction. Additionally, it was found that using the Florida specific measured temperature and relative humidity values as input to TNM slightly reduced the predicted sound levels.

2 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 2 INTRODUCTION Several computer models are being used to predict noise from highways and to design barriers. These include two models promulgated by the Federal Highway Administration (FHWA): STAMINA 2.0,Standard Method In Noise Analysis, (1); and, TNM, Traffic Noise Model, (2). Many other models, such as the University of Central Florida CNM, Community Noise Model, (3) also have this prediction capacity. However, in most of these models, the effects due to atmospheric refraction have been ignored. Measurements were made at twenty barrier locations in Florida, with thirteen having sufficient weather data collected, to allow an analysis of the impacts due to refraction. These measurements were primarily conducted to assess the effectiveness of noise barriers already built and to compare to the model predictions, but the comprehensive database allows other effects to be explored as well, such as those due to refraction. Therefore, additional research was undertaken that focused on the understanding of the meteorological effects on traffic noise propagation due to atmospheric refraction. Meteorological data was collected concurrently with site specific parameters (geometries, etc), sound levels, and traffic (vehicle counts and speed). From this database, it was possible to evaluate the effects of low wind speeds and various lapse rates. These conditions are normally thought to not be important and no effort is usually made to correct for the refraction effects during low wind speeds. This is especially true for short distances, common to first row homes along heavily traveled highways, behind noise barriers. To allow the research to be more comprehensive of the effects due to weather, the impacts of using the FHWA policy inputs for temperature and relative humidity in TNM for atmospheric absorption were also explored. METHODOLOGY Sensor and Microphone Locations The data were collected as part of an in-situ barrier insertion loss project sponsored by the Florida Department of Transportation (FDOT), from January 1999 until May The detailed meteorological data were not collected until the seventh measurement site (Site G) due to equipment concerns and replacement. Only meteorology at a single height was measured for the first six sites. As such, these sites have not been used in the analysis. In addition, equipment problems for the upper location occurred for the last site measured (Site T) and this site was also not evaluated. This provided a total of thirteen sites (Site G S) that included details of both sound and meteorological data. Table 1 provides a description of each of the thirteen sites analyzed in this project. TABLE 1 Summary of Sites Used In the Meteorological Evaluations The actual height listed in Table 1 is the height above the base of barrier. The effective height is the height above the ground plane where the receivers are located. Any elevation increase due to berms or ground elevations is included in the effective height. Criteria used in the selection of these locations included accessability for the noise measurement van and

3 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 3 microphone and meteorological towers, limited obstruction, and a clear view from the microphone positions to the noise barrier. Sound levels were recorded at several microphone positions behind each barrier. Typically twelve measurement positions were used at each site. These positions included eight 1/3-octave band analyzers and four broad band (A-weight) sound level analyzers. In many cases, where possible, other microphone positions were also used. Figure 1 shows a typical monitoring array of microphones used at each location. FIGURE 1 Microphones Location Set-up at Different Sites This array is based primarily on the American National Standards Institute (ANSI) defined procedures, (4). Distances beyond 30 m (98 feet) were difficult to measure due to existing homes. The twelve typical microphone positions for all sites were the same except in cases when power lines or other obstacles inhibited tower placement. In Figure 1, the location marked 1 thru 8 were measured using 1/3-octave band analyzers. Locations labeled A thru D represent the location for the overall sound level analyzers which were 1.5 m (4.92 feet) above the ground. Multiple heights and distances behind the barriers were achieved by using portable towers. It should be noted that microphone positions 1 and 4 are the same as microphone positions B and D. This was done intentionally for quality control purposes. The 1/3-octave band analyzers 1, 2, and 3 were located on a tower 30 m (98 feet) from the barrier and at heights of 1.5 m (4.92 feet), 3.0 m (9.8 feet) and 6.0 m (19.7 feet) respectively. The 1/3-octave band analyzers 4, 5, and 6 were located on a tower 15 m (49 feet) behind the barrier and at the same microphone heights as the 30 m (98 feet) tower. Moreover, microphones positions 7 and 8 are always reference microphones and are always placed at 1.5 m (4.92 feet) directly above the top of the noise barrier as prescribed in the ANSI standard method. Meteorological Towers Locations and Sampling The meteorological instruments were situated in available open areas away from the microphones to avoid any interference but in the general vicinity as the microphone locations and at the same distances from the barrier. Wind speed, direction, and temperature were collected at two heights: 1.5 meters (4.92 feet) and 6.0 meters (19.69 feet), as shown in Figure 2. Wind speed and direction were measured by using U-V-W anemometers equipped with propylene propellers to allow very low stall speeds. The anemometers were oriented with the positive V-axis (Y in usual coordinate system) pointing to the north. The positive U-axis (X in a usual coordinate system) was oriented to the east. The W-axis (Z-axis) was perpendicular to the ground plane with the positive direction being upwards. Wind direction was an important parameter, because it is the perpendicular wind component to the noise barrier that has the largest impact on noise levels. Downwind propagation (i.e. positive from source to receiver) could increase noise levels at receivers while upwind propagation (i.e. negative from receiver to source) may cause attenuation at the microphones. In addition, the magnitude is important because small changes in the wind shear may have a measurable effect on noise propagation. Temperature data was collected using aspirated thermometers with an absolute precision of 0.5 degrees centigrade. Before and after sampling periods, the two thermometers, from both high and low towers were placed on the ground, side-by-side to assure that each thermometer indicated the same temperature and verified with mercury thermometers. If there was a

4 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 4 difference, this was noted and used during data reduction. The extreme linear output and the similar calibration allowed much smaller differences in temperature to be measured. The thermometers were mounted at the same height of the anemometers, as shown in Figure 2, on the same portable towers. FIGURE 2 Meteorological Towers Set-up The weather information from both towers was automatically recorded to a separate data recording system. The time base was synchronized to the sound level measurement system. In addition, relative humidity was recorded using sling psychrometers. Sound Level Data Collection and Recording The 1/3-octave band analyzers were part of the overall data acquisition system. The overall measurement system consisted of the microphones with associated preamplifiers connected to cables that were routed to a mobile lab that housed the actual analyzers and a microprocessor based data acquisition system. The van was carefully situated away from the microphone positions to avoid any propagation interference. The data collection system allowed direct recording to a laptop computer. The recorded data included time, calibration levels, frequency and amplitude data on a real-time basis. The data sampling period was 20 minutes with four sample periods at each site. This was more than required by the ISO standard (5) but done for quality control purposes. Moreover, the four samples runs helped to insure adequate number of samples were measured at each location and provided additional quality control features. The multiple sample periods permitted whole sample periods to be discarded if necessary. The overall A-weighted sound levels analyzers collected data for a longer period than the twenty minute sample, but only data collected during the sample period was used in this analysis. Calibration for all sound measurement support was conducted before the first 20 minutes sample and just after the fourth sample run. For the1/3-octave band analyzers, the calibration was verified for both amplitude and frequency. Site and Traffic Data During the sampling period, the traffic data were manually counted and classified for each sample period and each direction of travel. The vehicle classifications were done using the FHWA defined vehicle classes of cars, medium trucks, heavy trucks, buses and motorcycles. Speed data were collected using radar guns for accuracy. Speeds in both traffic directions were obtained and averaged for each 20 minutes sample. Care was also taken to measure site specific geometries very carefully. This information included actual barrier heights, ground elevations and changes in height, lane dimensions, medians, distances from the barrier for receivers and the roadways, obstructions, and other important characteristics. The sites measured were mostly flat and the ground cover varied between paved and grass.

5 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 5 Data Reduction During data sampling, field notes were taken to identify any noise interference from sources other than traffic (e.g. jet flyover, etc.), in order to remove them during analysis. The data reduction process, using a custom developed program, used the 1/3-octave band data to calculate the overall A-Weighted sound levels for each of the 20 minutes runs. The meteorological data collected for each tower was used to calculate the wind shear, lapse rate, standard deviations of the wind, and Richardson number, where the Richardson number is defined as: Ri = (g/t A ) {(γ - Γ) / [(du/dz) 2 ]} where: Ri = Richardson number g = gravitational acceleration γ = true lapse rate Γ = adiabatic lapse rate T A = absolute ambient temperature du/dz = Wind shear component These calculations were accomplished using another custom computer program that allowed combination of the noise and meteorological data. The perpendicular wind components to the roadway were determined and used during this data reduction process. RESULTS Atmospheric Refraction Measured and calculated meteorological data for sites G through S were used during this evaluation. Wind speed, wind direction, and temperature were recorded at the low and the high anemometer positions. Wind speed and directions are shown in Tables 2 and 3. The component perpendicular to the wall was calculated for both positive (P) and negative (N) wind directions. Positive (P) wind direction corresponds to conditions when the wind is blowing from the source (roadway) to the receivers, while negative (N) wind is from the receivers to the source. TABLE 2 Summary of Meteorological Data TABLE 3 Calculated Meteorological Parameter Table 2 also includes the percentage of the perpendicular wind component as compared to the total magnitude of the wind. This percentage specifies how much of the total wind magnitude is perpendicular to the wall. It should be noted that because the primary purpose of the measurements was to determine noise barrier effectiveness, the measurements were purposely taken at low wind speeds. Table 2 indicates that the maximum wind perpendicular component speeds during positive conditions were 1.6 m/s (Site R) and 1.5 m/s (Site G), which accounts for 63.4% and 78.4% from the magnitude respectively; while the minimum was 0.1 m/s (Site K). The maximum wind perpendicular component speeds during negative conditions were 1.8 m/s (Site K) and 1.3 m/s (Site G), which accounted for 84.6% and 78.6% from the magnitude

6 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 6 respectively; while the minimum was 0.1 m/s (Site P). Table 3 illustrates that most of the calculated Richardson number values were below Richardson number, which is a dimensionless parameter that incorporates both thermal and mechanical forces, is a method for quantifying turbulence. Values of the Richardson numbers can be interpolated as shown in Table 4 (6). This indicates that the thermal effects dominate the wind effects. Only site H has values larger than 0.25, which indicates no vertical mixing. This shows that the stability of the atmosphere was primarily affected by the lapse rate and wind shear was less important. TABLE 4 Turbulence Characteristics for Various Richardson Number Wind shears (the difference between the low (1.5 meter) and the high (6 meter) anemometer positions) and lapse rates (temperature difference between the two thermometers (1.5 and 6 meter) were plotted against the difference between the reference and the microphone positions behind the barrier at for the various 1/3-octave bands. Examples are shown in Figures 3 and 4 for one kilohertz. The difference in sound levels show how changes occur and were normalized for various traffic conditions. FIGURE 3 Atmospheric Effects (Wind difference) Vs. 1 KHz at Site K FIGURE 4 Atmospheric Effects (Temperature difference) Vs. 1 KHz at Site K Figure 3 shows a very weak correlation for the wind shear, while Figure 4 shows a stronger correlation for the lapse rate at 1 KHz. In some cases, much stronger correlations were demonstrated at other frequencies than the 1 KHz. Table 5 summarizes the maximum correlation (R 2 ) between the calculated effects due to atmospheric refraction and the traffic noise level differences. Also shown in Tables 3 and 5 is that the dominant atmospheric parameter was the lapse rate, where it is obvious that greater correlations occur with increased lapse rates (Site G, K and P). This is considered to be an important finding. In most cases, on low wind speed days, refraction is ignored. The data indicate that the results could be significant, even at very short distances due to thermal refraction (that are caused by lapse rates). TABLE 5 Summary of Maximum R 2 For Refraction Effects and Primary Effect However, very strong correlations were not shown in this database. Only a few sites have attained an R 2 above 0.6 (Site G and K), while the lowest maximum R 2 was 0.2 and 0.18 for Site M and N respectively. This is in agreement with the literature (7 and 8), which indicates that higher frequencies are more affected. The correlations achieved at the lower frequency range are thought to be due to changes in ground effects caused by refraction. The small correlation impacts are thought to be due to the relatively small distances (maximum 30 meter behind the noise barrier) for thermal refraction over which effects were measured and the low wind speeds. Atmospheric Absorption The FHWA Traffic Noise Model (TNM) does include an atmospheric absorption algorithm. This algorithm was tested as part of this research. FHWA policy for input into TNM

7 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 7 recommends using 68 Fahrenheit and 50% relative humidity. However, the actual weather conditions over Florida test sites had higher values than the default values used in TNM. Table 6 presents the measured values for each site. The information in Tables 7 and 8 illustrate that the difference between the use of the measured inputs resulted in a very small change in the predicted noise levels. When applying the specific values for each site, TNM predicted sound levels tend to be 0.1 db(a) less than the originally predicted sound levels when using the FHWA default values. Site M was the only exception, since its temperature and relative humidity were similar to TNM default values. The reader is reminded that this analysis was for fairly short distances typical of the first and second row of homes behind the barrier. This does indicate however, that use of FHWA policy introduces only a small error into the predictions TABLE 6 Measured Temperature and Relative Humidity for Each Site TABLE 7 TNM Sound Levels in (db) for Position 1, Using FHWA Policy and Actual Inputs for Temperature and Relative Humidity TABLE 8 TNM Sound Levels in (db) for Position 2, Using FHWA Policy and Actual Inputs for Temperature and Relative Humidity CONCLUSIONS To date there has been only limited research conducted on the effect of atmospheric refraction for traffic noise propagation behind noise barriers at relatively short distances. The more recent Traffic Noise Model (TNM) does not calculate atmospheric refraction due to wind speeds and temperature gradients and has only included atmospheric absorption. This research has allowed a beginning to the better understanding of the meteorological effects on traffic noise propagation behind noise barriers. This research has demonstrated that even under conditions where refraction is thought to be minimal, correlation for the meteorological data still occurs. As such, impacts occur (even under low wind speeds during daytime hours) due to effects of the lapse rates. Stronger lapse rates had greater correlations at higher frequencies (e.g., R 2 = 0.77, 0.6). The small distances (maximum 30 meter behind the noise barrier) over which effects were measured tended to limit the effects due to thermal refraction and in these calm conditions the refraction due to wind shear was very minimal. More data is needed for higher wind speeds, greater lapse rates, and further distances to determine potential impacts and this research is being continued. However, the fact that the impacts occur even at relatively calm conditions, usually thought to be insignificant for refraction, is an important finding. The FHWA Traffic Noise Model (TNM) has been developed to predict traffic sound levels and barrier effectiveness. Policy recommended values for temperature and relative humidity have been determined by the FHWA in an effort to allow comparison of results from location to location. Applying the Florida specific measured values for temperature and relative humidity only slightly reduced the predicted sound levels compared to the same levels using the default values. This reduction was quite small due to the relatively short source-receiver

8 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 8 distances and usually was on the order of 0.1 db(a). This tends to indicate that the FHWA policy for temperature and humidity has only very small effects on model accuracy. This research has concluded that the meteorological effects could be significant at short distances and that effects occur in cases of stronger lapse rates. This most likely also occurs during cases of stronger wind shear, but data collected during this project were not sufficient to allow speculation of these cases. The correlation was generally found at higher frequencies. In the case of correlation at low frequencies, it was thought that a change in ground effects occurred due to refraction changing the angle of the wave propagation. More work is needed on this important issue, which is thought by the authors to be the greatest source of errors still in the models.

9 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 9 REFERENCES (1) Bowlby, W., Higgins, J., Reagan, J. Noise Barrier Cost Reduction Procedure: STAMINA2.0 /OPTIMA: User s Manual. FHWA-DP-58-1, U.S. Department of Transportation, Federal Highway Administration, (2) Anderson, G.S., Lee, C.S.Y., Fleming, G.G., Menge, C.W. FHWA Traffic Noise Model, User s Guide. FHWA-PD-96-09, U.S. Department of Transportation, Federal Highway Administration, (3) Wayson, R.L., Macdonald, J.M., El-Aassar, A. Continued Evaluation of Noise Barriers in Florida. FDOT Project No. BD Florida Department of Transportation, (4) American National Standards Institute Method for Determination of Insertion Loss of Outdoor Noise Barriers of All Types, ANSI S , New York, (5) International Organization for Standardization In-Situ Determination of Insertion Loss of Outdoor Noise Barriers of All Types, ISO 10847:1997(E), Geneva, (6) Wark, L. and Warner, C.F. Air Pollution: Its Origin and Control. Harper Row, New York, (7) Parkin, P.H. and Scholes, W.E. The Horizontal Propagation of Sound From A Jet Engine Close to the Ground at Hartfield, Journal of Sound and Vibration, vol. 2(4), pp , 1965 (8) Piercy, J.E., Embleton, T.F.W., Sutherland, L.C. Review of Noise Propagation In Atmosphere, Journal of the Acoustical Society of America, vol. 61(6), pp , 1977

10 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 10 LIST OF FIGURES AND TABLES FIGURE 1 Microphones Location Set-up at Different Sites FIGURE 2 Meteorological Towers Set-up FIGURE 3 Atmospheric Effects (Wind Difference) Vs. 1 KHz at Site K FIGURE 4 Atmospheric Effects (Temperature Difference) Vs. 1 KHz at Site K TABLE 1 Summary of Sites Used In the Meteorological Evaluations TABLE 2 Summary of Meteorological Data TABLE 3 Calculated Meteorological Parameter TABLE 4 Turbulence Characteristics for Various Richardson Number TABLE 5 Summary of Maximum R 2 For Refraction Effects and Primary Effect TABLE 6 Measured Temperature and Relative Humidity for Each Site TABLE 7 TNM Sound Levels in (db) for Position 1, Using FHWA Policy and Actual Inputs for Temperature and Relative Humidity TABLE 8 TNM Sound Levels in (db) for Position 2, Using FHWA Policy and Actual Inputs for Temperature and Relative Humidity

11 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 11 FIGURE 1 Microphones Location Set-up at Different Sites

12 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 12 FIGURE 2 Meteorological Towers Set-up

13 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 13 Ivy 1 (positive) Difference Between Reference and Ivy for 1 KHz (db(a)) R 2 = Difference Between Towers at 6.0 m and 1.5 m Windiff (m/s) FIGURE 3 Atmospheric Effects (Wind difference) Vs. 1 KHz at Site K

14 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 14 Ivy 4 (positive) Difference Between Reference and Ivy for 1 KHz (db(a)) R 2 = Difference Between Towers at 6.0 and 1.5 m Tempdiff (deg.c) FIGURE 4 Atmospheric Effects (Temperature difference) Vs. 1 KHz at Site K

15 A. A. EL-Aassar, R.L. Wayson, J. Macdonald 15 TABLE 1 Summary of Sites Used In the Meteorological Evaluations Site City Highway Actual Barrier Effective Barrier Height Height G St. Petersburg S.R H Ft. Lauderdale I I Deerfield Beach I J Miami I K Tamiami U.S L Hialeah S.R M Wildwood S.R N Maitland S.R O Ft. Lauderdale I P Boynton Beach I Q Palm Beach Gardens I R Palm Harbor S.R S New Port Richey S.R

16 A. A. EL-Aassar, R. L. Wayson, J. MacDonald 16 TABLE 2 Summary of Meteorological Data Site G H I J K L M N O P Q R S Wind No. Data Wind at 1.5 m Wind at 1.5 m Perpendicular Wind at 6.0 m Wind at 6.0 m Perpendicular Direction Points (mag.) (m/s) (Perp.) (m/s) % of Mag. (mag.) (m/s) (Perp.) (m/s) % of Mag. N P N P N P N P N P N P N P N P N P N P N P N P N P

17 A. A. EL-Aassar, R. L. Wayson, J. MacDonald 17 TABLE 3 Calculated Meteorological Parameter Site G H I J K L M N O P Q R S Wind Direction Richardson # Average Lapse Rate (C/m) N P N P N P N P N P N P N P N P N P N P N P N P N P

18 A. A. EL-Aassar, R. L. Wayson, J. MacDonald 18 TABLE 4 Turbulence Characteristics for Various Richardson Number (Wark, 1976). Richardson Number Turbulence Characteristics Ri > 0.25 No vertical mixing 0 < Ri < 0.25 Mechanical turbulence, weakened by stratification Ri = 0 Mechanical turbulence Only < Ri < 0 Mechanical turbulence dominates convective mixing Ri < Convective mixing dominates mechanical mixing

19 A. A. EL-Aassar, R. L. Wayson, J. MacDonald 19 TABLE 5 Summary of Maximum R 2 For Refraction Effects and Primary Effect Site Max. R 2 Microphone Frequency Effect G 0.60 (N) Ivy 5 20 KHz Temperature H 0.26 (P) Ivy 3 20 KHz Temperature I 0.57 (P) Ivy 1 63 Hz Temperature J 0.32 (P) Ivy 3 20 KHz Temperature K 0.77 (P) Ivy 4 10 KHz Temperature L 0.44 (N) Ivy 3 12 KHz Temperature M 0.20 (N) Ivy 4 20 KHz Temperature N 0.18 (N) Ivy 4 8 KHz Temperature O 0.30 (N) Ivy 1 25 Hz Temperature P 0.58 (N) Ivy Hz Temperature Q 0.53 (P) Ivy Hz Temperature R 0.47 (N) Ivy Hz Temperature S 0.53 (P) Ivy Hz Wind

20 A. A. EL-Aassar, R. L. Wayson, J. MacDonald 20 TABLE 6 Measured Temperature and Relative Humidity for Each Site Site Temperature ( F) Relative Humidity (%) Site M Site N Site O Site P Site Q Site R 85 NA Site S N.B: TNM default values (50% RH and 68 F)

21 A. A. EL-Aassar, R. L. Wayson, J. MacDonald 21 TABLE 7 TNM Sound Levels in (db) for Position 1, Using FHWA Policy and Actual Inputs for Temperature and Relative Humidity Site TNM Using Policy TNM Using Measured Recommended db(a) Value db(a) Site M No change No change Site N Site O Site P Site Q Site R NA NA Site S

22 A. A. EL-Aassar, R. L. Wayson, J. MacDonald 22 TABLE 8 TNM Sound Levels in (db) for Position 2, Using FHWA Policy and Actual Inputs for Temperature and Relative Humidity Site TNM Using Policy TNM Using Measured Recommended db(a) Value db(a) Site M No change No change Site N Site O Site P Site Q Site R NA NA Site S