Field Evaluation of Reflected Noise from a Single Noise Barrier—Phase 1 (2016)

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1 E X E C U T I V E S U M M A R Y This research studied, through field measurements and audio recordings, the possible change in sound levels and sound characteristics caused by sound reflections off a reflective (non-absorptive) noise barrier on the opposite side of a highway. The analysis was done using: • a modification to a method in a Federal Highway Administration (FHWA) noise measurement manual in which simultaneous measurements were made at the Barrier site and at an equivalent adjacent site without a barrier under equivalent source and meteorological conditions (“FHWA Method”); • acoustical spectrograms, which show the frequency content of sound as a function of time; and • psychoacoustic measures of Loudness, Sharpness, Roughness, and Fluctuation Strength combined into metrics of Annoyance. Additionally, changes in the statistical exceedance (Ln) descriptors were also addressed. Broadband unweighted sound pressure levels and A-weighted sound levels were studied as well as 1/3 octave band sound pressure levels. Five locations were selected for data collection and analysis in this study: • I-24, Murfreesboro, TN • Briley Parkway, Nashville, TN • I-90, Rockford, IL • SR-71, Chino Hills, CA • MD-5, Hughesville, MD With one exception, six sound level analyzers were deployed at each location: three at the Barrier site and three at the adjacent No Barrier site. Each site had a reference microphone on the barrier side of the road and two pairs of “community” microphones on the opposite side of the road from the barrier. These microphones were positioned in terms of their distance from the road and height above the road such that the results from each pair were directly comparable. The I-24 and SR-71 locations also afforded the opportunity to place the Barrier reference microphone between the barrier and the road so that it could be compared to the No Barrier reference microphone as a primary point that might be affected by reflected noise. Evening measurements at the Briley Parkway and MD-5 locations were scheduled to capture isolated, single-vehicle passby events. A meteorological station collected simultaneous wind speed and direction, and a video camera and laser speed gun were used to collect traffic volume and classification data and travel speeds. Four hours of data were collected at each location, logged at one-second intervals, and processed in one-minute periods. The one-minute data blocks were examined to see if there was contamination from intrusive noise sources and eliminated these as necessary. They were then grouped into five-minute periods for comparability, For highway traffic, this amount of time averages the short-term vehicle passby and intervening lulls and allows for the same vehicles to be captured at both Barrier to No Barrier microphones, with only slight differences at the beginning and ending of the block. Broadband A-weighted sound levels and unweighted sound pressure levels were examined for the five-minute periods without consideration of the source and meteorological equivalence of the periods to each other. This analysis reveals evidence of sound level increases at the Barrier microphones, both for those positions in front of the barrier as well as across the road. The five-minute periods were tested for source equivalence—in terms of the reference sound level data and speed data—and for meteorological equivalence. The meteorological classes consist of a combination of wind direction (Upwind, Calm and Downwind) and temperature gradient (Lapse, Neutral and

2 Inversion). When three or more equivalent periods were identified based on source and meteorological class, they were grouped together and their broadband and 1/3 octave band sound level differences, in terms of the five-minute equivalent sound level, Leq(5min), were examined. Additionally, the one-second data were processed to determine statistical exceedance descriptors ranging from L1 to L99, both for the broadband levels and the 1/3 octave band levels. From the above data, the following findings were developed: 1. Measured broadband unweighted sound pressure levels and A-weighted sound levels are generally higher at the Barrier microphones than at the No Barrier microphones. 2. The differences in Barrier and No Barrier levels are frequency-specific and vary by location and site. There are clear examples of enhanced levels opposite the barrier compared to the corresponding No Barrier position. 3. Sound levels are higher and spectral content changes at a position between the barrier and the road, compared to the No Barrier site, as evidenced at I-24 and SR-71. 4. The background sound pressure level is elevated in the presence of the noise barrier at the microphone position between the barrier and the road. 5. Even at the reference microphone position atop the barrier the level can be slightly higher than at the equivalent No Barrier position, as evidenced at I-90. However, little difference was seen at MD-5. 6. Near the edge of the road for the lower-height microphones, the Barrier levels are roughly the same as the No Barrier, being slightly higher in the very low frequency bands, as evidenced at SR-71. 7. Near the edge of the road for the lower-height microphones, there is some evidence of an increase in the background A-weighted sound level on the order of 1 dB to 1.5 dB at BarCom03, as seen at SR-71. 8. Farther back from the road, but still within 100 ft, the Barrier levels are higher than No Barrier levels by 0.5 to 1.5 dB and the spectrum is changed by even more in some of the frequency bands between 250 Hz and 630 Hz and in some of the bands at and above 1 kHz, as evidenced at I-24, I-90, and MD-5. 9. Farther back from the road, but still within 100 ft, the background level increases in the bands from 630 Hz up through 3.15 kHz, as evidenced at I-90 and MD-5, but not I-24. 10. Back at 400 ft from the road, the Barrier levels are typically 1 dB to 4 dB higher than at the No Barrier site, as evidenced at SR-71. 11. Back at 400 ft from the road, all of the Ln descriptors were higher at the Barrier site, not just the background levels, as evidenced at SR-71. 12. The increase in levels due to reflections decreased by 1 dB to 2 dB going from a lower-height microphone to a higher microphone, as evidenced at I-24, I-90, and MD-5. 13. No effect on sound level differences was seen as a function of traffic volume, as evidenced at all microphone pairs at all locations. 14. There are slight differences in the sound level differences for different meteorological classes, however there are no clear trends, as evidenced at I-90, I-24, and MD-5. Data collected at greater distances from the road might tell more. Spectrograms were generated for individual and groups of vehicle passby events, as well as samples of highway traffic for each of the measurement sites. The spectrograms compare data collected at the Barrier site and at an equivalent position at the No Barrier site. This comparison allows for a visual examination of the effect of barrier-reflected noise. The spectrogram data reveal that the presence of a reflective noise barrier causes sound levels to increase over a broad range of frequencies and causes higher sound levels to be sustained for a longer period of time. The increased sound levels include frequencies that dominate highway traffic noise. These observations apply to vehicles traveling on either side of the road, for a range of distances from the road and heights above the road, and for the vehicle types examined (autos, heavy trucks, and motorcycles).

3 An additional observation is that there is evidence that the barrier effect is more pronounced at farther distances from the road. It is assumed that the path length difference between direct and reflected sound is one of the variables controlling the strength of the effect seen from barrier reflections (smaller difference = greater effect). At each site, the signal from each sound level meter’s microphone was digitally recorded. These audio recordings were filtered and post-processed to extract basic psychoacoustic metrics as a function of time. In turn, these were combined into three different measures of psychoacoustic annoyance: Unbiased Annoyance, Psychoacoustic Annoyance, and Category Scale of Annoyance. Descriptive statistics for the annoyance metrics were compiled for each site. The statistics were investigated as indicators of whether the received sound from Barrier sites would be significantly different from those at No Barrier sites. Our findings of the psychoacoustic assessment were that: 1. Unbiased Annoyance and Psychoacoustic Annoyance yield similar results, while Category Scale of Annoyance does not yield useful indications. 2. Annoyance metrics show differences between Barrier and No Barrier sites at moderate distances, but the results are contra-indicative. 3. Annoyance metrics are less effective in heavy, constant traffic, but show differences in lighter traffic with separated passbys. The research team found several applications of this research. The most immediate application is for traffic noise analysis and abatement practitioners: traffic sound levels and sound characteristics for receptors across from a proposed single reflective noise barrier can change after the installation of the barrier. This understanding can lead to the appropriate specification of sound-absorbing surfaces on these single barriers, especially for highway widenings where the roadway already exists. In addition, the study found spectrograms to be very useful in identifying the change in sound characteristics due to barrier reflections in both the time and frequency scales. Spectrograms could help policy makers provide guidance on when it may be effective to use sound-absorbing barriers and help in showing the public what an absorptive barrier could provide. It was also found that psychoacoustic metrics of annoyance are not effective for looking at subtle changes in constant traffic, but are helpful to provide insights into increased annoyance at lower traffic levels. Finally, the research team made several recommendations and considerations for future research. In summary, these included: 1. Creating a screening tool to determine when sound absorption may be appropriate. 2. Conducting before/after studies to assess the effect of the barrier in situ, using techniques developed in this project and others, as needed. 3. Developing a layman’s guide to improve understanding of barrier reflections. 4. Incorporating some of these findings into various courses on highway traffic noise. 5. Studying sound reflections off of sound-absorbing barriers. 6. Evaluating Time-Based and Time-Above metrics to help understand other drivers of adverse community perception. 7. Using TNM to further investigate why the barrier reflection effects are greater closer to the ground by studying the frequency ranges being affected by shielding from median barriers and highway vehicles and also ground effects, which may show that sound-reducing propagation effects help to “expose” barrier-reflected noise. 8. Conducting listening trials to directly assess human reaction to reflected noise.