sensitivity analysis: highway noise level differences
TRANSCRIPT
Advancing transportation innovation for the public good
Sensitivity Analysis: Highway Noise Level Differences between Leq and LdnWilliam ChuppAaron HastingsGina Solman
Image Credit: Inhabitat.com
Background
• 23 CFR 772, “Procedures for Abatement of Highway Traffic Noise and Construction Noise” requires Leq(h) for peak noise hour
• Protects against short term effects of noise
• Practical for abatement and enforcement
• Usually similar values to Ldn with less measurement burden
• Question: How different are peak hour Leq(h) and Ldn?
• How big of a difference can we expect?
• What factors affect the difference?
Slide 2
LAeq (peak hour)
• Describes only loudest hour of noise
• Lower level of effort for accurate measurements
• Good descriptor for short term noise impacts
• May not account for nighttime noise impacts
Ldn
• Describes full day of noise exposure
• Requires longer duration measurements in day and night hours for accurate calculation
• Good descriptor for long term effects and land use planning
• May not account for significant peaks in hourly noise levels
LAeq (peak hour) and Ldn
646566676869707172737475
0 10 20 30 40 50 60
Nois
e Lev
el (d
BA)
Time (minutes)
70.072.074.076.078.080.082.084.086.088.090.0
0 5 10 15 20
Nois
e Lev
el (d
BA)
Hour of the day
Leq(h)
Ldn
Lnight +10 dB
Slide 3
Leq(h)
Sound of interest
Study Methodology
• Highway Noise Model: FHWA’s Traffic Noise Model (TNM)
• Artificial Analysis: • Experimental traffic parameter inputs
• Initial Analysis: Understand importance and trends with individual parameters
• In Depth Analysis: Predict the difference for ranges of parameter values
• Real world traffic patterns
• Model metric difference that may be observed in different regions
Slide 4
Noise Simulation in TNM – Initial Analysis
• Parameters Studied – changes from daytime to nighttime
1. Day and night traffic distributions, 𝑃𝑃𝑑𝑑𝑑𝑑𝑑𝑑, 𝑃𝑃𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛2. Peak hour volumes, 𝑋𝑋𝑝𝑝𝑝𝑝𝑑𝑑𝑝𝑝
• Simple setup: Single lane highway, 55 mph average speed, 4 receivers
• Calculated LAeq (peak hour) and Ldn for all scenarios
• 𝑉𝑉𝑝𝑝𝑒𝑒𝑒𝑒: Adjusts heavy duty and passenger vehicle traffic to equivalent noise levels with only passenger vehicles Simple Highway with Receivers
Slide 5
Noise Simulation in TNM – Results
• Overall difference is combination of both difference relationships: ∆𝐿𝐿= 𝐿𝐿𝐴𝐴𝑝𝑝𝐴𝐴(𝑛) − 𝐿𝐿𝑑𝑑𝑛𝑛 ∆𝐿𝐿= 𝑔𝑔 𝑃𝑃𝑑𝑑𝑑𝑑𝑑𝑑 + 𝑣𝑣 𝑋𝑋𝑝𝑝𝑝𝑝𝑑𝑑𝑝𝑝
• Peak hour and metric difference relationship is logarithmic: 𝑣𝑣 𝑋𝑋𝑝𝑝𝑝𝑝𝑑𝑑𝑝𝑝 = 10 ∗ log𝑋𝑋𝑝𝑝𝑝𝑝𝑑𝑑𝑝𝑝
• Obtain a more complete picture by generating 𝑔𝑔 𝑃𝑃𝑑𝑑𝑑𝑑𝑑𝑑 through simulation and shifting using 𝑣𝑣 𝑋𝑋𝑝𝑝𝑝𝑝𝑑𝑑𝑝𝑝
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
0 20 40 60 80 100 120
L Aeq
–L d
n(d
BA)
Day Volume Distribution (%)
Trend in Metric Difference with Day Volume Fraction
-7.0
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
1.0
0 1 2 3 4 5 6
L Aeq
–L d
n(d
BA)
Peak Hour Volume
Trend in Metric Difference with peak hour multiplier
Slide 6
In Depth Analysis Results
-12.0
-10.0
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
0 10 20 30 40 50 60 70 80 90 100
L Aeq
–L d
n(d
BA)
Day Volume Distribution, Pday (%)
Day Volume Percentage vs. Leq-Ldn Difference for Different Values of Peak Hour Multiplier.
Peak hour = 1Times Average
Peak hour = 2Times Average
Peak hour = 3Times Average
Peak hour = 4Times Average
Peak hour = 5Times Average
Slide 7
Real World Traffic Data – Traffic Monitoring and Analysis System (TMAS)
Slide 8
Location Category
Hourly Volume (# veh)Peak Hour Multiplier
Percent Daily Volume (%)
Peak Average Daytime
Average Nighttime Total Daytime
HoursNighttime
Hours
NJ (NYC) I-80 Urban 4931 3990 1648 3112 1.58 80.1 19.9
Atlanta, GA I-20 Urban 7849 5756 2050 4367 1.80 82.4 17.6
San Francisco, CA US101 Near SFO Urban 7547 6930 2598 5306 1.42 81.6 18.4
Waverly, NY I-86 Rural Highway 775 542 139 391 1.98 86.6 13.4
Shamrock, TX I-40 Rural Highway 412 335 137 261 1.58 80.3 19.7
Shelby, MT I-15 Rural Highway 100 75 16 53 1.89 88.8 11.2
Horseheads, NY RT 223
Rural Backroad 135 70 23 70 1.93 87.8 12.2
Shamrock, TX RT 83
Rural Backroad 106 75 11 51 2.08 91.6 8.4
Harlem, MT RT 241
Rural Backroad 17 11 1 7 2.38 97.0 3.0
Projected Differences From Noise Modeling
• Resulting projected differences shown as green triangles
• Ranges between -2.3 dB and +3 dB
• Differences depend on location
Slide 9
Truck Traffic Distributions
• Can change from day to nighttime hours and in peak hour independently
• More difficult to analyze, shifts inherently affect other variables
• Hourly truck distribution affects any hour’s noise level independently of day-night shifts in distribution
• Reduce Day–Night truck distributions to percent of overall truck traffic that occurs during the day
• Affects difference more or less depending on the percent of AADT that is trucks
Slide 10
74.0
76.0
78.0
80.0
82.0
84.0
86.0
88.0
0 10 20 30 40 50 60 70 80 90 100Ld
n(d
BA)
P trucks, day (%)
AADT = 2.5% Trucks AADT = 5% Trucks AADT = 10% Trucks
AADT = 20% Trucks AADT = 40% Trucks
Constant Ldn with 0% Truck AADT
Constant Ldn with 100% Truck AADT
Real World Truck Traffic Data
• Not from TMAS, from individual state databases (NY, GA, TX)• Simulated LAeq (peak hour) and Ldn for 7 locations• Key Conclusion: Difference depends mostly on 𝑃𝑃𝑑𝑑𝑑𝑑𝑑𝑑 (𝑅𝑅2 = 0.88)
Slide 11
Location Xpeak Pday Ptrucks,peak Ptrucks,day Ptrucks,aadt LAeq (Peak Hour) Ldn LAeq-Ldn
New York, I-95 in the Bronx
northbound 1.48 75.9 21.76 77.1 15.54 79.46 82.74 -3.28
New York Waverly I-86
Eastbound 1.65 78.33 24.31 75.16 28.5 72.38 74.84 -2.46
Georgia I-20 Eastbound Atlanta 1.66 81.97 3.58 80.89 3.97 79.14 81.12 -1.98
Georgia I-16 Eastbound Near
Dublin 1.59 79.05 26.1 76.62 32.1 73.83 76.36 -2.53
Georgia Route 85 Northbound in
Riverdale 1.7 83.89 3.09 88.24 3.17 71.08 72.69 -1.61
Texas, I-40 Westbound in
Shamrock 1.62 77.6 59.76 76.94 61.34 72.66 75.33 -2.67
Texas, US Route 35 northbound
outside of Austin 1.81 79.55 21.3 77.09 12.79 80.58 82.59 -2.01
New York, I-95 in the Bronx northbound
New York Waverly I-86 Eastbound
Georgia I-20 Eastbound Atlanta
Georgia I-16 Eastbound Near Dublin
Georgia Route 85 Northbound in
Riverdale
Texas, I-40 Westbound in Shamrock
Texas, US Route 35 northbound outside of
Austin
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
75 76 77 78 79 80 81 82 83 84 85
L Aeq
–L d
n(d
BA)
Percent Effective Volume Occuring During Day
Summary
• Use plot of differences for ranges of parameter values to estimate difference in specific situations
• Need hourly traffic data, including heavy duty classifications
• Calculate two parameters using Veff:
1. Xpeak
2. Pday
Slide 12
5 = Xpeak4.5 = Xpeak4 = Xpeak3.5= Xpeak3 = Xpeak2.5 = Xpeak
2 = Xpeak
1.5 = Xpeak
1 = Xpeak
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
60 65 70 75 80 85 90 95 100
L Aeq
–L d
n(d
BA)
Day Volume Distribution, Pday (%)
Day Volume Percentage vs. Leq-Ldn Difference for Different Values of Peak Hour Multiplier.
Example
• Example:
New York Waverly I-86 Eastbound
Result: Leq-Ldn = -2.5
Slide 13
5 = Xpeak4.5 = Xpeak4 = Xpeak3.5= Xpeak3 = Xpeak2.5 = Xpeak
2 = Xpeak
1.5 = Xpeak
1 = Xpeak
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
60 65 70 75 80 85 90 95 100
L Aeq
–L d
n(d
BA)
Day Volume Distribution, Pday (%)
Day Volume Percentage vs. Leq-Ldn Difference for Different Values of Peak Hour Multiplier.
Parameter Value
Xpeak (Veff) 1.65
Pday (Veff) 78.33%
Thank You!
AcknowledgementsThe authors thank Cecilia Ho and Aileen Varela-Margolles in FHWA’s Office of Natural Environment for sponsoring
and supporting this work.
Contact Information
William ChuppGeneral Engineer, [email protected]
Aaron HastingsPhysical Scientist, [email protected]
Gina SolmanEnvironmental Protection Specialist, [email protected]
USDOT Volpe Center
Slide 14