Aviation Environmental Design Tool Research Articles

A large-scale validation study of aircraft noise modeling for airport arrivals.

In the U.S., the Federal Aviation Administration's Aviation Environmental Design Tool (AEDT) is approved to predict the impacts of aircraft noise and emissions. AEDT's critical role in regulatory compliance and evaluating the environmental impacts of aviation requires asking how accurate are its noise predictions. Previous studies suggest that AEDT's predictions lack desired accuracy. This paper reports on a large-scale study, using 200 000 flight trajectories paired with measured sound levels for arrivals to Runways 28L/28R at San Francisco International Airport, over 12 months. For each flight, two AEDT studies were run, one using the approved mode for regulatory filing and the other using an advanced non-regulatory mode with exact aircraft trajectories. AEDT's per aircraft noise predictions were compared with curated measured sound levels at two locations. On average, AEDT underestimated LAmax by -3.09 dB and SEL by -2.04 dB, combining the results from both AEDT noise-modeling modes. Discrepancies appear to result from limitations in the physical modeling of flight trajectories and noise generation, combined with input data uncertainties (aircraft weight, airspeed, thrust, and lift configuration) and atmospheric conditions.

Validating aircraft noise models: Aviation environmental design tool at Heathrow

Aircraft noise models are fundamental tools for noise abatement, control, enforcement, evaluation, and policy-making. Validation of aircraft noise models is necessary to ensure their reliability and credibility, particularly given their significant impact on society, the economy, and public health. However, validating such models is often a complex undertaking, and an acceptable validation methodology still needs to be developed. In this study, the Federal Aviation Administration's (FAA) Aviation Environmental Design Tool (AEDT) aircraft noise model is validated by correlating the calculated and measured noise levels for a specific aircraft flying in a particular flight path at Heathrow Airport. The validation results suggest that the AEDT noise model estimates the actual noise level quite accurately for landings, with a variation less than 2 dB(A), but might be inaccurate for takeoffs for certain aircraft types, with variations reaching 10 dB(A), resulting in a considerable difference between the measured and calculated noise levels.

Modeling the air quality impact of aircraft emissions: is area or volume the appropriate source characterization in AERMOD?

AbstractModeling dispersion of aircraft emissions is challenging because aircraft are mobile sources with varying emissions rates at different elevations depending on the operating mode. Aircraft emissions during landing and take-off cycle (LTO) influence air quality in and around the airport, and depending on the number of aircraft operations and location of the airport, this influence may be significant. AERMOD (v22112) incorporates a variety of conventional source types to characterize the intended emissions source, leaving the question of which conventional source type(s) best characterizes aircraft activities across the four modes of LTO cycle, unanswered. Currently, the publicly released version of FAA’s Aviation Environmental Design Tool (version 3e) models aircraft emissions as a set of AREA sources for all flight segments. A research version of AEDT allows users to model aircraft sources—both fixed wing and rotorcraft—as a series of VOLUME sources in AERMOD. However, both source treatments do not account for plume rise of aircraft jet exhaust. This paper compares AERMOD’s performance in describing SO2 concentrations associated with airport sources by comparing model results from the two source options during the summer campaign of the Air Quality Source Apportionment study conducted at the Los Angeles International Airport. We conclude that both VOLUME source and AREA treatments overestimate the highest observed SO2 concentrations despite not accounting for background sources. The VOLUME source option reduces this overestimation by using a higher initial plume spread than the AREA option does, and through the inclusion of meander. Our results suggest the need to include the plume rise of jet exhaust when using AERMOD for airport air quality studies.

The potential for spatiotemporal population data sets for aviation noise studies

Aviation noise analysis has traditionally focused on modeling the noise from an average day of operations. We investigate the potential of moving from this static approach to a dynamic method of assessing aircraft noise experienced by people where they are as they move about the day and night. In this research conducted on behalf of the National Academy of Sciences Airport Cooperative Research Program, we evaluated population data sets that account for the movement of people between their daytime versus nighttime location and assessed their applicability for aviation noise studies. We provided guidance on using these spatiotemporal data sets for aviation noise studies using the Aviation Environmental Design Tool, including sample maps and analyses. We also discussed the limitations of spatiotemporal population data, namely they only account for a person's location by time of day and not whether they are engaged in noise-sensitive activities. A fuller picture of noise impact by location and time of day may be achieved by developing an activity-based model, which combines data on location and level of noise sensitivity. We outline the basic elements of such a model.

Prediction of Noise-Power-Distance Data for Urban Air Mobility Vehicles

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations due to a combined lack of UAM aircraft flight performance model data and aircraft noise data. This paper addresses the latter by offering two prediction-based approaches for generation of noise–power–distance data for use within AEDT. One utilizes the AEDT fixed-wing aircraft modeling approach, and the other utilizes the AEDT rotary-wing aircraft modeling approach.

Characterizing temporal trends in populations exposed to aircraft noise around U.S. airports: 1995-2015.

Aircraft noise is a key concern for communities surrounding airports, with increasing evidence for health effects and inequitable distributions of exposure. However, there have been limited national-scale assessments of aircraft noise exposure over time and across noise metrics, limiting evaluation of population exposure patterns. We evaluated national-scale temporal trends in aviation noise exposure by airport characteristics and across racial/ethnic populations in the U.S. Noise contours were modeled for 90 U.S. airports in 5-year intervals between 1995 and 2015 using the Federal Aviation Administration's Aviation Environmental Design Tool. We utilized linear fixed effects models to estimate changes in noise exposure areas for day-night average sound levels (DNL) of 45, 65, and a nighttime equivalent sound level (Lnight) of 45 A-weighted decibels (dB[A]). We used group-based trajectory modeling to identify distinct groups of airports sharing underlying characteristics. We overlaid noise contours and Census tract data from the U.S. Census Bureau and American Community Surveys for 2000 to 2015 to estimate exposure changes overall and by race/ethnicity. National-scale analyses showed non-monotonic trends in mean exposed areas that peaked in 2000, followed by a 37% decrease from 2005 to 2010 and a subsequent increase in 2015. We identified four distinct trajectory groups of airports sharing latent characteristics related to size and activity patterns. Those populations identifying as minority (e.g., Hispanic/Latino, Black/African American, Asian) experienced higher proportions of exposure relative to their subgroup populations compared to non-Hispanic or White populations across all years, indicating ethnic and racial disparities in airport noise exposure that persist over time. Overall, these data identified differential exposure trends across airports and subpopulations, helping to identify vulnerable communities for aviation noise in the U.S. We conducted a descriptive analysis of temporal trends in aviation noise exposure in the U.S. at a national level. Using data from 90 U.S. airports over a span of two decades, we characterized the noise exposure trends overall and by airport characteristics, while estimating the numbers of exposed by population demographics to help identify the impact on vulnerable communities who may bear the burden of aircraft noise exposure.

Accounting for plume rise of aircraft emissions in AERMOD

The U.S. Federal Aviation Administration (FAA) uses the Aviation Environmental Design Tool (AEDT) to assess the impact of airport emissions on air quality in and around an airport. AEDT incorporates EPA's (Environmental Protection Agency) regulatory model, AERMOD. The area/volume source algorithm in AERMOD is currently used to treat most airport sources including aircraft, which contribute a major fraction of total airport emissions. Aircraft emissions have horizontal momentum corresponding to the forward thrust of the aircraft. In addition, they have buoyancy corresponding to the heat rejected from the aircraft engine. These plume dynamics are not included in the latest version (v22112) of the area/volume source algorithm in AERMOD; the effects of the plume on ground-level concentrations are accounted through an initial plume height and width based on LIDAR observations at the end of runways. Model predictions based on this approach are likely to lead to overestimates of ground-level concentrations because they do not account for the increase of plume height with distance from the source. This paper proposes a plume rise formulation for aircraft emissions modeled with AERMOD. Plume rise is modeled using the weighted average of the characteristics of the aircraft that pass through the area/volume source during 1 h, the averaging time used in AERMOD. The buoyancy parameter used to compute plume rise is estimated using the aircraft engine characteristics: thrust, fuel burn rate, the velocity of the aircraft, air-fuel ratio, and the engine bypass ratio. The proposed plume rise formulation for AERMOD is evaluated using SO2 observations from the 2012 Air Quality Source Apportionment Study (AQSAS) conducted at the Los Angeles International Airport (LAX). The results from the evaluation indicate that plume rise improves AERMOD's description of the qualitative behavior of concentrations measured in and around the airport.

Associations between Aircraft Noise Exposure and Self-Reported Sleep Duration and Quality in the United States-Based Prospective Nurses' Health Study Cohort.

Sleep disruption is linked with chronic disease, and aircraft noise can disrupt sleep. However, there are few investigations of aircraft noise and sleep in large cohorts. We examined associations between aircraft noise and self-reported sleep duration and quality in the Nurses' Health Study, a large prospective cohort. Aircraft nighttime equivalent sound levels (Lnight) and day-night average sound levels (DNL) were modeled around 90 U.S. airports from 1995 to 2015 in 5-y intervals using the Aviation Environmental Design Tool and linked to geocoded participant residential addresses. Lnight exposure was dichotomized at the lowest modeled level of 45 A-weighted decibels [dB(A)] and at multiple cut points for DNL. Multiple categories of both metrics were compared with dB(A). Self-reported short sleep duration ( h/24-h day) was ascertained in 2000, 2002, 2008, 2012, and 2014, and poor sleep quality (frequent trouble falling/staying asleep) was ascertained in 2000. We analyzed repeated sleep duration measures using generalized estimating equations and sleep quality by conditional logistic regression. We adjusted for participant-level demographics, behaviors, comorbidities, and environmental exposures (greenness and light at night) and examined effect modification. In 35,226 female nurses averaging 66.1 years of age at baseline, prevalence of short sleep duration and poor sleep quality were 29.6% and 13.1%, respectively. In multivariable models, exposure to Lnight dB(A) was associated with 23% [95% confidence interval (CI): 7%, 40%] greater odds of short sleep duration but was not associated with poor sleep quality (9% lower odds; 95% CI: , 19%). Increasing categories of Lnight and DNL dB(A) suggested an exposure-response relationship for short sleep duration. We observed higher magnitude associations among participants living in the West, near major cargo airports, and near water-adjacent airports and among those reporting no hearing loss. Aircraft noise was associated with short sleep duration in female nurses, modified by individual and airport characteristics. https://doi.org/10.1289/EHP10959.

Land use compatibility and aircraft noise impact assessment at Sphinx International Airport

Aircraft noise is one of the main causes of health problems in the cities surrounding airports, this study used Sphinx International Airport (HESX), west of Cairo, Egypt, as a case study. Adopting a multidisciplinary approach that encompasses both urban planning and aviation disciplines, We have used the Aviation Environmental Design Tool (AEDT) software in Geographic Information Systems (GIS) and Remote Sensing (RS) environment. Onscreen digitizing of land-use areas, compared with the reference points observed directly on the field found out that around 80% of the researched area is subjected to aircraft noise of less than 65 dB(A). Therefore, HESX operations have almost no significant noise impact on the surrounding environment. We aim to provide recommendations to decrease the potential effects of aircraft noise levels, and enhance future urban planning and land use compatibility, which ultimately reduce noise-related diseases. According to the Egyptian Environmental Law, the noise contour line 65 dB(A) is the undesired noise threshold.

Closed-Form Analytical Approach for Calculating Noise Contours of Directive Aircraft Noise Sources

This paper extends the simplified airport noise model Rapid Aviation Noise Evaluator (RANE) [Torija et al., Journal of the Acoustical Society of America, Vol. 141, No. 2, 2017, pp. 981–995], adding capability of including fully nonisotropic noise sources. This extended tool, RANE v2, is developed as a part of multidisciplinary acoustic assessment of novel aircraft, in order to produce ground contours around airports and helipads. Version 2 extends the capability of RANE to accommodate predictions of future air vehicles implementing propulsion systems solution with inherent directional properties. The model uses three-dimensional noise emission surfaces around a series of discretized segments that represent the aircraft flightpath. The main inputs are the sources’ sound power level, the distance from the flightpath at which a level is observed, and the source three-dimensional directivity. The directivity function may take analytical or numerical form, allowing for experimental data inputs. This paper demonstrates the use of spherical harmonics as a form of directivity function with a closed-form analytical solution for calculating the noise exposure contours. Results and comparison against the Federal Aviation Administration’s Aviation Environmental Design Tool module for helicopter community noise indicate that exposure contour coordinates can be estimated for high and low noise exposure levels. The incorporation of source directivity allows for the assessment of lateral attenuation, engine installation effects, and transition operations (for vertical to horizontal flight and vice versa) via the assumption of individual source directivities and, therefore, complex noise surfaces. As a consequence of the analytical nature of the model, low computational requirements allow for fast exploration of the design space and parametric studies, with minimal input requirements. The capabilities of RANE v2 are demonstrated by predicting noise footprints for three helicopters, each of different size, performance, and directivity characteristics.

Long-term aircraft noise exposure and risk of hypertension in postmenopausal women

BackgroundStudies of the association between aircraft noise and hypertension are complicated by inadequate control for potential confounders and a lack of longitudinal assessments, and existing evidence is inconclusive. ObjectivesWe evaluated the association between long-term aircraft noise exposure and risk of hypertension among post-menopausal women in the Women's Health Initiative Clinical Trials, an ongoing prospective U.S. cohort. MethodsDay-night average (DNL) and night equivalent sound levels (Lnight) were modeled for 90 U.S. airports from 1995 to 2010 in 5-year intervals using the Aviation Environmental Design Tool and linked to participant geocoded addresses from 1993 to 2010. Participants with modeled exposures ≥45 A-weighted decibels (dB [A]) were considered exposed, and those outside of 45 dB(A) who also did not live in close proximity to unmodeled airports were considered unexposed. Hypertension was defined as systolic/diastolic blood pressure ≥140/90 mmHg or inventoried/self-reported antihypertensive medication use. Using time-varying Cox proportional hazards models, we estimated hazard ratios (HRs) for incident hypertension when exposed to DNL or Lnight ≥45 versus <45 dB(A), controlling for sociodemographic, behavioral, and environmental/contextual factors. Results/discussionThere were 18,783 participants with non-missing DNL exposure and 14,443 with non-missing Lnight exposure at risk of hypertension. In adjusted models, DNL and Lnight ≥45 db(A) were associated with HRs of 1.00 (95% confidence interval [CI]: 0.93, 1.08) and 1.06 (95%CI: 0.91, 1.24), respectively. There was no evidence supporting a positive exposure-response relationship, and findings were robust in sensitivity analyses. Indications of elevated risk were seen among certain subgroups, such as those living in areas with lower population density (HRinteraction: 0.84; 95%CI: 0.72, 0.98) or nitrogen dioxide concentrations (HRinteraction: 0.82; 95%CI: 0.71, 0.95), which may indicate lower ambient/road traffic noise. Our findings do not suggest a relationship between aircraft noise and incident hypertension among older women in the U.S., though associations in lower ambient noise settings merit further investigation.

Improved Framework for Classification of Flight Phases of General Aviation Aircraft

Flight data mining enables airport owners, operators, and governmental entities to explore more intelligent management strategies; in particular, cost-effectively obtaining accurate operational data is beneficial for general aviation (GA) airports and their associated communities. The current data collection modus operandi, however, does not meet future needs, as aircraft operations are counted manually or estimated by sampling methods. The increasing traffic flow and limited available personnel at most GA airports make it unrealistic to continue using traditional methods to analyze aircraft operational statistics; therefore, a customized approach is needed to address this problem. Since different flight phases have different levels and types of impact on the environment, acquiring information related to the duration of each flight phase at the airport and within its surrounding airspace is critical to the assessment of emissions and noise pollution from aircraft. The primary goal of the research is to provide quantified inputs for the environmental evaluation model, such as the Aviation Environmental Design Tool (AEDT). This paper demonstrates a programmed framework that successfully achieves satisfactory performance in solving flight phase identification problems by testing the synthetic flight data as well as validating the empirical Automatic Dependent Surveillance-Broadcast (ADS-B) data. The experimental results suggest that the proposed methods achieve promising classification accuracy, leading to feasible deployment in airport operations.

Developing a Cost-Effective Assessment Method for Noise Impacts at Non-Towered Airports: A Case Study at Purdue University

Aircraft noise is considered as one of the environmental impacts that most adversely affects airport development. Aircraft noise estimation tools such as the Aviation Environmental Design Tool (AEDT) are widely used by airports to mitigate local concerns for airport development. Aircraft operations and fleet mix information play important roles in aircraft performance modeling for noise prediction. However, such information is difficult to obtain at almost 85% of the 3,348 National Plan of Integrated Airport Systems (NPIAS) airports, which lack full-time air traffic control facilities and personnel. Given the increasing percentage of equipped automatic dependent surveillance-broadcast (ADS-B) aircraft in the U.S. national airspace, this paper presents a cost-effective noise estimation approach for non-towered general aviation (GA) airports. Instead of deploying physical sound meters or relying on the local air traffic control facilities, the authors collected aircraft positional data and fleet mix information based on ADS-B broadcasts. Advanced aircraft performance model parameters are constructed using four-dimensional aircraft position and a kinematic point-mass model. Aircraft-specific noise levels are interpolated based on the EUROCONTROL Aircraft Noise and Performance (ANP) database. To obtain the final noise level, two adjustments are applied to the interpolated noise values. The test results show the proposed approach can help non-towered airports predict the noise impact on any selected locations near the airport cost-effectively. Recommendations and opportunities for future investigation are also included.

Long-term aircraft noise exposure and incident hypertension in National U. S. Cohort Studies

Few cohort studies have examined relationships between aircraft noise and health, none in the United States. We evaluated associations between aircraft noise and incident hypertension in three national cohorts of women, the Nurses’ Health Studies (NHS/NHSII) and the Women’s Health Initiative (WHI). Noise levels around 90 airports for 1995–2015 (in 5-year intervals) were modeled using the Aviation Environmental Design Tool and assigned to participants’ geocoded addresses over time. Hypertension risks were estimated using time-varying Cox proportional-hazards models for day-night average sound level dichotomized at 45 and 55 decibels (dB), adjusting for fixed and time-varying covariates. Hypertension cases were 33,190, 28 256, 5299 over 0.7M,1.3M, and 0.09M person-years in NHS, NHSII, and WHI, respectively. In combined NHS/NHSII, we observed adjusted hazard ratios (HRs) of 1.03 (95% CI: 0.99, 1.07) for 45dB and 1.07 (95% CI: 0.98, 1.15) for 55 dB cut-points. In WHI, we observed preliminary HRs of 1.03 (0.94, 1.16) for 45 dB and 0.93 (0.83, 1.05) for 55 dB cut-points. Overall, in these cohorts, we did not find clear evidence of a positive association between aircraft noise exposure and hypertension.

Associations between nighttime aircraft noise exposure and insufficient sleep in the US-based prospective Nurses’ Health Study cohort

BACKGROUND AND AIM: Chronic sleep disturbances leading to short sleep duration have been linked to chronic diseases (e.g., cardiovascular disease, hypertension). Aircraft noise may contribute to sleep disruption, indicating a potential pathway to chronic disease. However, multivariable-adjusted and longitudinal relationships have infrequently been studied in a large sample of adults. This study investigates associations between nighttime aircraft noise and insufficient sleep in the US-based Nurses’ Health Study (NHS). METHODS: Nighttime aircraft noise levels (LAeqN) were modeled for 90 U.S. airports from 1995-2015 in 5-year intervals using U.S. Federal Aviation Administration’s (FAA) Aviation Environmental Design Tool (AEDT) and linked to geocoded participants’ residential addresses for 2000, 2002, 2008, 2012, and 2014 (years when self-reported habitual sleep duration was available). Participants were classified as exposed if they lived at addresses with modeled LAeqN ≥45 decibels (dB). Sleep duration was classified as insufficient if ≤6 hours per night. A repeated measures analysis was conducted using generalized estimating equations. Multivariable models adjusted for participant-level demographics, behaviors, comorbidities, and ambient fine particulate matter. RESULTS:In 2000, the 35,226 female participants were on average 66.1 years old. The proportion of participants with insufficient sleep varied from 29.6% in 2000 to 37.0% in 2014. The percent exposed to nighttime aircraft noise varied from 1.5% to 0.6%. In age-adjusted longitudinal models the odds of insufficient sleep were 33.1% higher (95% CI: 17.0%, 51.6%) for those exposed to nighttime aircraft noise compared with those not exposed, and the association remained after multivariable adjustment (25.3% higher odds; 95% CI: 10.1%, 42.7%). CONCLUSIONS:Elevated nighttime aircraft noise was associated with shorter sleep duration in the NHS cohort. The relationship was robust after controlling for multiple confounders and with increased insufficient sleep and decreased aircraft noise exposure over time. Future research will investigate sleep quality as an additional sleep outcome. KEYWORDS: noise, epidemiology, environmental epidemiology

Community noise assessment of urban air mobility vehicle operations using the FAA Aviation Environmental Design Tool

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate in communities close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration's Aviation Environmental Design Tool (AEDT), does not support analysis of such operations due to a combined lack of a UAM aircraft performance model and aircraft noise data. This paper discusses the initial development of a method to assess the acoustic impact of UAM fleet operations on the community using AEDT and demonstrates its use for representative UAM operations. In particular, methods were developed using fixed-point flight profiles and user-supplied noise data in a manner that avoids unwanted behavior in AEDT. A set of 32 routes in the Dallas-Ft. Worth area were assessed for single and multiple (fleet) operations for two concept vehicles.

Comparison of two community noise models applied to a NASA urban air mobility concept vehicle

Predictions of community noise exposure from the NASA urban air mobility (UAM) concept vehicles have been conducted for representative operations using the FAA Aviation Environmental Design Tool (AEDT) in order to demonstrate modeling tool interoperability and assess applicability, capabilities and limitations of integrated noise modeling tools. To both quantify limitations and highlight other capabilities, a comparative analysis is performed using a time simulation method, in particular, using the Volpe Advanced Acoustic Model (AAM). Starting with the same source noise model, the 3D directivity of a UAM concept vehicle is predicted in terms of aeroacoustic pressure time histories at a sphere of observers near the vehicle. In addition to distilling those data to a set of noise-power-distance data for input to AEDT, the data are processed preserving directivity, into narrowband, one-twelfth and one-third octave bands for input to AAM. Results from AEDT and AAM modeling are provided for a variety of metrics to demonstrate the effect that source noise and propagation modeling fidelity have on predicted results at receptors over a study area.

Validation of the aviation environmental design tool's noise model using high fidelity weather

To enable sustainable aviation growth, mitigation of environmental effects must be developed in parallel. To further this effort, these effects are modeled using capabilities such as the Aviation Environmental Design Tool (AEDT), a program that is able to model aircraft performance, fuel burn, emissions, and noise. Past and current projects are performed with the intent of improving the accuracy of the models within AEDT to capture various real-world effects. This paper targets the sensitivity of the noise prediction and propagation by varying multiple assumptions within AEDT. To validate the noise capabilities, multiple streams of real-world data will be used to accurately model actual flights to and from SFO airport. This data includes High-Fidelity weather data,detailed flight performance characteristics from airline flight data records and noise monitoring data obtained from stations around the airport. The results from this study are expected to offer recommendations and help users prioritize and more accurately quantify community noise exposure using AEDT.

Parametric optimization of aircraft arrival trajectories for aviation noise mitigation using BADA4 performance model

Successful mitigation of aviation noise is a key enabler for sustainable aviation growth. A key focus of this effort is the noise arising from aircraft arrival operations. Arrival operations are characterized by the use of high-lift devices, deployment of landing gear, and low thrust levels, which results in the airframe being the major component of noise. In order to optimize for arrival noise, management of the flap schedule and gear deployment is crucial. This research aims to create an optimization framework for evaluating various aircraft trajectories in terms of their noise impact. A parametric representation of the aircraft arrival trajectory will be created to allow for the variation of aircraft's flap schedule. The Federal Aviation Administration's Aviation Environmental Design Tool will be used to simulate the aircraft trajectory and performance, and to compute the noise metrics. Specifically, the latest performance model from EUROCONTROL called "Base of Aircraft Data - Family 4" will be used. This performance model contains higher fidelity modeling of aircraft aerodynamics and other characteristics which allows for better parametric variation.

Subtraction Analysis for Predicting the Propagation Effects of Aircraft Noise

In 2013, the Federal Aviation Administration and Volpe National Transportation System Center conducted a series of acoustic measurements with a propeller driven aircraft operating in the regions near Houston, Texas. The recorded data on octave band sound levels, aircraft locations, temperature and wind speed profiles were used in the current study to quantify the uncertainties for predicting the propagation effects of aircraft noise. Use of the Aviation Environmental Design Tool (AEDT) was explored for its accuracy and validity in real world scenarios offered by the dataset. The sound exposure level (SEL) data for each section of a flight path was used instead of the time history data for reducing the directivity effect of the sound source due to the change in its relative positions with the receivers. A subtraction-based method was introduced to analyze the propagation effect in which the SELs between two receiver locations were compared. The use of the subtraction method reduces the possible influences of the sound power variations along the flight paths. The measured data for a spiral and a level flight event were presented and the AEDT predictions on the propagation effects were examined in this paper.