Máster Universitario en Ingeniería Acústica
TRABAJO FIN DE MÁSTER
“Complementation of Faro’s Airport Noise Map with Listening Points”
Alice Segurado Ramos
September /2021
ii en
Ingeniería Acústica
Trabajo Fin de Máster
Título Complementation of Faro’s Airport Noise Map with Listening Points
Autor Alice Segurado Ramos Firma
Tutor / Co-Tutor Antonio Pedrero González Firma Director Externo Vítor Carlos Tadeia Rosão Firma
Tribunal Examinador Presidente/
Secretario/
Vocal
Fecha Calificación
Secretario
iii
List of Figures ... v
List of Tables ... x
List of Equations ... xii
Acknowledgments ... 2
1 Introduction ... 3
2 Fundamental Principles ... 7
2.1. Assessment of Environmental Noise ... 8
2.1.1. Noise Maps and European Normative ... 8
2.1.2. The use of listening Points to assess Environmental Noise ... 8
2.2. Characterization of Faro’s Airport ... 10
2.3. Simulation Software AEDT 3d ... 12
2.3.1. Simulation Parameters ... 13
2.3.2. Noise Level Calculations ... 16
2.4. Mathematical Equations for the changes to be applied in the audios ... 17
3 Methodology ... 22
3.1. Measurements ... 23
3.1.1. System and Equipment ... 23
3.1.2. Measurement Points ... 24
3.1.3. Data treatment ... 25
3.1.4. Data from Flight Radar to be included ... 34
3.2. Estimation of the Levels obtained ... 38
3.3. Software Simulation ... 41
iv
3.4.1. Airport’s Noise Maps in AEDT ... 48
3.5. Creation of the Listening Points ... 54
3.5.1. Arrivals and Departures... 54
3.5.2. Adaptation of the audios for the Listening Points ... 60
4.1.1. Creation of the simulation and data recollection ... 60
4.1.2. Adaptation of the Audios for the Listening Points ... 65
4 Analysis of the results ... 69
4.1. Mathematical Predictions ... 70
4.2. Simulations in AEDT ... 71
4.3. Analysis of the Listening Points ... 72
4.3.1. Analysis of the Arrivals and Departures ... 72
4.3.2. Analysis of the audios for the Listening Points ... 74
5 Conclusions ... 78
6 References ... 82
6.1. Annex 1 ... 1
6.1.1. Matlab Script for the change of parameters for adapting the departure to the arrival ... 1
6.1.2. Matlab Script to compare the envelopes of the original arrival with the envelope of the altered audio ... 3
6.1.3. Matlab Script for the predictive equations for the Listening Points ... 5
6.1.4. Matlab Script for the comparison between the original audio and the altered audios for the Listening Points ... 7
v
Figure 1: Location of Faro's Airport. ... 10
Figure 2: Number of passengers in the three main airports in Portugal. ... 11
Figure 3: Available municipal Lden noise map for Faro's district. ... 12
Figure 4: Available municipal Ln noise map for Faro's district. ... 12
Figure 5: User interface for the user to define the metrics... 15
Figure 6: Scheme for the line segments of the route. ... 18
Figure 7: Theoretical variation of the sound pressure levels in accordance of Lp maximum for a punctual noise source with constant velocity in a straight line. ... 18
Figure 8: Theoretical variation of the sound levels in accordance of the maximum Lp for a punctual noise source with constant velocity traveling in a straight line with time correction. ... 19
Figure 9: Mathematical example for the equations using the divergence only and the divergence and time adjustment. ... 21
Figure 10: Sonometer in measurement point 1. ... 24
Figure 11: Sonometers for measurements and recordings in Point 3. ... 24
Figure 12: The four recording points as seen in Google Earth. ... 25
Figure 13: LAeq levels measured each 125ms obtained for the passing of the flight one, Point 1. ... 27
Figure 14: LAeq levels measured each 125ms obtained for the passing of the flight two, Point 1. ... 27
Figure 15: LAeq levels measured each 125ms obtained for the passing of the flight three, Point 1. ... 28
Figure 16: LAeq levels measured each 125ms obtained for the passing of the flight five, Point 2. ... 28
Figure 17: LAeq levels measured each 125ms obtained for the passing of the flight six, Point 2. ... 29
vi
eight, Point 3. ... 29
Figure 19: LAeq levels measured each 1s obtained for the passing of the flight one, Point 1. ... 30
Figure 20: LAeq levels measured each 1s obtained for the passing of the flight two, Point 1. ... 30
Figure 21: LAeq levels measured each 1s obtained for the passing of the flight three, Point 1. ... 31
Figure 22: LAeq levels measured each 1s obtained for the passing of the flight five, Point 2. ... 31
Figure 23: LAeq levels measured each 1s obtained for the passing of the flight six, Point 2. ... 32
Figure 24: LAeq levels measured each 1s obtained for the passing of the flight eight, Point 3. ... 32
Figure 25: Recollection of speed and altitude data from the third flight in the point 1. ... 34
Figure 26: Recollection of the data from the point 2, flight 5. ... 34
Figure 27: Recollection from the data from the flight 8 in the third point. ... 35
Figure 28: Measurement of the horizontal distance from the measurement point 1 to the nearest point of passage of the aircraft in Google Earth. ... 36
Figure 29: Scheme for calculating the distances from points to the aircrafts. ... 37
Figure 30: Mathematical Prediction for Flight 1, Point 1. ... 38
Figure 31: Mathematical predictions for Flight 2, Point 1. ... 39
Figure 32: Mathematical Predictions for the Flight 3, Point 1 ... 39
Figure 33: Mathematical predictions for Flight 5, Point 2. ... 40
Figure 34: Mathematical prediction for Flight 6, Point 2. ... 40
Figure 35: Mathematical predictions for Flight 8, Point 3. ... 41
vii map). ... 42
Figure 37: Nearest flight segments for flight 5 in Point 2 from the simulation in AEDT. ... 46 Figure 38: Scheme for calculating the altitude for the flights in Point 2. ... 46 Figure 39: Definition of the noise mapping area in AEDT... 49 Figure 40: LASmax noise map obtained in AEDT for flight 1, point 1 with medium stage length (A320 departure). ... 50 Figure 41: LASmax noise map obtained in AEDT for the flight 2, point 1 with medium stage length (B738 departure). ... 50 Figure 42: LASmax noise map obtained in AEDT for flight 3, point 1 with medium stage length (A320Neo departure). ... 51 Figure 43: LASmax noise map obtained for the flight 5, point 2 (A321Neo arrival).
... 51 Figure 44: LASmax noise map obtained in AEDT for flight 6, point 2 (A320 Arrival).
... 52 Figure 45: LASmax noise map obtained in AEDT for the flight 8 point 3 with minimum stage length (A321Neo departure). ... 52 Figure 46: LASmax noise map for the total of flights measured ... 53 Figure 47: Audio envelopes of the flight 3, P1, flight 6, P2 and the theoretical equation for the flight 6. ... 55 Figure 48: Superposition of the mathematical prediction with the audio envelope of the audio from flight 6. ... 56 Figure 49: Original arrival, predictive equation and altered departure to match the arrival. ... 56 Figure 50: Superposition of the original audio with the predictive equation and the altered audio. ... 57 Figure 51: Audio envelopes obtained for the departure of the flight 8 in point 3, the arrival of flight 6 in point 2 and its mathematical prediction. ... 58
viii Figure 53: Audio of the flight 8, point 3 before (above) and after (below) the audio level change. ... 59 Figure 54: Process of adjusting the time of decay. ... 59 Figure 55: Audio envelopes of the altered audio and original arrival and of the predictive equation. ... 59 Figure 56: Superposition of the envelopes of the altered audio from flight 8, the original audio from the flight 6 and its predictive equation. ... 60 Figure 57: Total LASmax noise map in Google Earth with pinned places of interest.
... 61 Figure 58: Point of data recollection for the Listening Point 1. ... 62 Figure 59: Flight performance points for the arrival of the flight 6. ... 63 Figure 60: Points considered for the horizontal distances for the listening points 2 and 3... 63 Figure 61: Close up of the Listening Points 2 and 3 for their points for the horizontal distance. ... 64 Figure 62: Predictive equations for the 3 listening points. ... 65 Figure 63: Superposition of the original audio of the flight 8, the predictive equation and altered audio for the Listening Point 1... 66 Figure 64: Superposition of the original audio of the flight 8, the predictive equation and altered audio for the Listening Point 2... 67 Figure 65: Superposition of the original audio of the flight 8, the predictive equation and altered audio for the Listening Point 3... 67 Figure 66: Spectrogram of the original arrival (flight 6, Point 2)... 73 Figure 67: Spectrogram of the altered departure. ... 73 Figure 68: Spectrogram of the altered Flight 8, point 2 to match the arrival of the flight 6 in Point 2. ... 74
ix Beach). ... 75 Figure 70: Spectrogram of the audio obtained for the Listening Point 2 (Faro's downtown). ... 75 Figure 71: Spectrogram obtained for the Listening Point 3 (Joaquim Magalhães School). ... 75 Figure 72: Spectrogram of the original flight 8 in point 3. ... 76
x Table 1: Stage lengths and the trip length associated (from the AEDT user manual)... 14 Table 2: Noise metrics available (default) in AEDT (from AEDT technical manual).
... 15 Table 3: Total of airport movements from the 1st of June 2021. ... 26 Table 4: Maximum levels obtained for each passage in the measurements (Time ponderation Slow). ... 32 Table 5: Maximum Levels obtained for each passage in the measurements (time ponderation Fast). ... 33 Table 6: Altitude registered from the flights in the measurement points ... 35 Table 7: Speeds registered from the flights in the measurement points. ... 36 Table 8: Horizontal distances measured from the measurement points to the nearest aircraft route. ... 37 Table 9: Distance from measurement point to aircraft. ... 37 Table 10: Resume of the operations created. ... 43 Table 11: Comparison of the levels measured with AEDT for the maximum stage length available. ... 44 Table 12: Comparison of the levels measured with AEDT for the medium stage length. ... 44 Table 13: Comparison of the levels measured with AEDT for the minimum stage length. ... 44 Table 14: Comparison of the altitudes obtained in Flight Radar and in AEDT. . 47 Table 15: Comparison between altitudes in the different stage lengths. ... 47 Table 16: Comparison between the speeds obtained in Flight Radar and in AEDT.
... 48 Table 17: Receptor set created for the Listening Points. ... 61
xi
Table 19: Horizontal distances for the listening points. ... 64
Table 20: Altitudes obtained for the listening points ... 64
Table 21: Speeds obtained for the listening points... 65
Table 22: Distances from listening points to aircrafts. ... 65
xii
Equation 1: Definition of time-averaging constant in AEDT. ... 16
Equation 2: Equation for the LASmax noise metric in AEDT. ... 16
Equation 3: Noise Pressure Level in order of the distance. ... 17
Equation 4: Equation for the sound pressure level for the line segments. ... 18
Equation 5: Lp level assuming the time for sound propagation. ... 19
Equation 6: Initial equation for the noise levels using only geometric divergence. ... 20
Equation 7: Equation for the noise levels considering only geometric divergence. ... 20
Equation 8: Initial equation for the deduction of the time interval for the decay of the 10 decibels. ... 20
Equation 9: Equation for the time variance of the 10 decibels below the maximum level obtained (based on Equation 7). ... 21
Equation 10: Equation for distance from point to aircraft. ... 37
Equation 11: Base formula for the calculations of the altitudes for the flights 5 and 6 (measurement point 2). ... 47
Equation 12: Formula for the altitudes of the arrivals of flights 5 and 6 measured in point 2. ... 47
El presente trabajo de fin de máster tiene como objetivo realizar la caracterización acústica del aeropuerto de Faro, Portugal a través de la realización de un mapa de ruido de LAFmax con puntos de escucha. Esto constituye un método de caracterización diferente al visto normalmente ya que este tipo de mapas de ruido no son muy utilizados para hacer la caracterización de los niveles de ruido emitidos por la actividad del aeropuerto.
Para realizar la caracterización acústica del aeropuerto, se harán diversas grabaciones audio y mediciones de niveles de ruido de despegues y llegadas al aeropuerto en diversos puntos relevantes cerca del aeropuerto. Los ficheros audio obtenidos serán procesados de acuerdo con su duración y nivel máximo obtenido para que se puedan adaptar a otros puntos de escucha de interés.
El mapa de ruido será desarrollado en el software AEDT 3D (Aviation Environmental Tool) y los puntos de escucha serán añadidos con los audios procesados para que se pueda hacer una mejor caracterización del impacto sonoro del aeropuerto.
Abstract
This project aims to acoustically characterize Faro’s airport (Portugal) through a development of a LAFMax noise map with sound listening points. This is a different approach as normally seen with noise maps, as LAFMax noise maps, and listening points, are not commonly used to describe the noise related to the airport’s activity.
To achieve this goal, several recordings of landings and take offs will be made in several points surrounding Faro’s airport. The recordings will be processed in time duration and maximum sound level so that they can be adapted to several other points of interest.
The noise map will be developed with the software AEDT 3D (Aviation Environmental Design Tool) and the listening points with the recordings and adapted audios will be added so that a better characterization of the sound impact of the airport’s activity can be made.
2
Acknowledgments
During the period in which I have been writing my master thesis there have been several people that have impacted me not only professionally but also personally that I would like to take the opportunity to thank for all the support.
Firstly, to the person that without which the project would not have happened, to my thesis director, Vítor Rosão for the opportunity of working under his valuable guidance and for the opportunity to develop his previous work. I would like to thank you for going on and beyond in all your support, not only by passing over your extensive knowledge but also for being an example of courage and motivation that I followed during the whole period.
Secondly, to my Tutor in Universidad Politécnica de Madrid, Profesor António Pedrero González for being there and keeping an eye on my thesis during this period, for making any corrections he deemed valuable, for all the support during this one year of master and for ensuring that the project could reach its final potential.
Now, on a more personal note, I could not let this opportunity go by without thanking my family. In these extraordinary times, when so many have to overcome not only a pandemic but also major life changes alone, I am blessed with a family that has shown me unconditional support, inspiration and motivation that helped me overcoming these challenging times.
Furthermore, to my colleagues in Universidad Politécnica de Madrid I would take the opportunity to acknowledge their patience and support, not only in putting up with my
“portuñol” but also for always making me feel at home even if I was one country and several kilometres away.
And finally, to my dearest friends who have been there for me all over the years helping and inspiring me to become the woman I am today. To Daniela, to João, to Beatriz, to Laura, to Tari, to Miguel, to Pajo and to Nelson, I have no words to describe my gratitude.
3
1 Introduction
4 We define noise as sound especially when it is unpleasant, loud or unwanted.
Then sounds of what we consider noise has been changing throughout the times.
Schafer (Schafer 1994) describes the change of scenery throughout the times, giving a unique perspective on the change of the definition of noise and the soundscapes people used to hear with the passing of the years. The arise of the human species starts to change the audio panorama as it starts to change the environment around them. As the species develop, we begin assisting to the passage of only natural sounds to the beginning of sounds provoked by the human’s activity. And so, we begin to hear the sounds of hunting, the sounds of pasture and farming. The sounds of brass and iron, as described by the author start in the rural soundscapes as the roman wars begin in the third century before Christ. Later with the development of the first mediaeval cities we start to hear noises such as clocks, bells from churches and mills.
Moving in the times, music starts to fill the streets. Work is accompanied by chants and the noise of people talking begins to dominate the streets of the cities. By the 19th century in Weimar, we have the first noise laws motivated by the conflict between indoor and outdoor music, and they stated that music should always be made behind closed doors. By 1864, as the result of agitation in the streets there are laws passed all around Europe that took around a century to be effective.
Inarguably, one of the biggest changes in the acoustic scenery occurs after the industrial revolution. The industrial revolution takes place from the 18th to the 19th centuries. The introduction of new machinery, factories and changes in the lifestyle of the general population, such as the increment of working hours brings a profound change in the soundscape as well. The sounds provoked by the factories and the machinery are at first, as noted by Schafer, upsetting to the general population but later accepted as inevitable and “blended” in the old soundscape.
By 1825 in England surges the first railway that was designed to carry coal from mines to waterways. The system has become popularized being spread to the United States of America in 1828 and to Russia in 1837, for example. By 1872 it had spread to Japan as well. Only around a century later, by 1920 the railway tracks begin to be electrified. Other important mark in the change of the soundscapes begin with the wide spreading of personal vehicles as a result of the growth in population and their transportation needs. By the year 1970 America was already mass-producing cars (Schafer 1994).
5 Other important mark was the growth of the aviation industry. By 1943 the civil flights begin gaining popularity (Mackenzie 2010) and its growth continued.
It also can be noted how the noise laws were directed to the human voice and how the change of panorama and evolution of knowledge now makes them directed to more objective parameters in general, such as measurements in decibels (Schafer 1994).
It comes as no surprise following the amount of legislation of environmental noise that today exists it can affect people’s lives in several ways including physical health, hence the need of legislation to regulate it. There have been studies showing the effects of the exposition to environmental noise. The Guideline Develop Group, for example, relates to noise exposure health problems such as cardiovascular diseases, annoyance, effects on sleep, cognitive and hearing impairment and overall critical outcomes in quality of life, well-being and mental health (World Health Organization for Europe 2018).
Several more studies have taken place relating exposure to environmental noise to these health problems. Gupta and Ghatak concluded based on a survey that communities that were regularly exposed to traffic noise reported suffering health conditions such as headaches, anxiety, high blood pressure and irritability and other more severe such as hearing loss and cardiovascular problems (Gupta and Ghatak 2011).
With the increase of aviation traffic there have also been studies showing how aviation noise can influence in one’s health. Ozkurt and Hamamci have noticed how the population with more proximity to the airport can be more affected by the noise produced by its activity. Problems such as sleep disturbances and hypertension were more significant nearby the area of the airport (Ozkurt, Hamamci and Sari 2015).
In this master’s thesis we will study the importance of adding other parameters such noise maps made with the parameter of LAFmax to complement the noise maps nowadays legislated, as it will give a better perception of the impact of a passage of an aircraft. The maps will be complemented with listening points made by synthetizing an audio recording of a passage of an airplane so that a better understanding of the impact of the passage of an airplane can be shown for non-acoustician people who may not be so familiarized with noise maps. This synthesis will be made via altering an audio so that the duration of the passage corresponds to the time the airplane would take in the place to be synthetized in, and also by adjusting the maximum level of the passage accounting for the distance to the aircraft rout.
6 This study will be made regarding Faro’s Airport, one of the three main airports of Portugal continental (along with Lisbon’s and Porto’s airport). This airport is chosen as it serves the region of Algarve a mostly touristic region of Portugal and the airport is nearby Faro’s city centre. This situation is problematic as it places the airport near historical places. Due to the location of the airport and also the routes that the airplanes do, there will be impacts associated. There have been reports and news associated regarding complaints due to the airport’s activity noise. In April 2019 there was announced a new flight path to reduce aviation noise in the nearby city of Quarteira due to complaints about the noise (Portugal Resident 2019). In Quinta do Lago, a residential and touristic zone known for its golf courses there have also been complaints about the noise from both tourists and residents, especially during the summer during the peak of the airport movements (Couto N 2019; Revez 2005). To understand better the impacts of the airport and aid the general population to understand them as well, several recordings will take place in the surrounding area of the airport and aided of mathematical and computational simulations, the audios recorded will be synthetized so that the impacts of the airport’s activity can be better understood as the passage of a plane in several other locations of interest will be simulated.
7
2 Fundamental
Principles
8
2.1. Assessment of Environmental Noise
2.1.1. Noise Maps and European Normative
It is estimated that in the European Union around 100 million people are exposed to traffic noise (World Health Organization for Europe 2018). It is known that the rapid increase in population has result in an increase of use of transportation and so, an increase of noise is also expected. This calls for measures to protect the population to take place.
By the June 25th of 2002 the directive 2002/49/EC relating to the assessment and management of environmental noise is passed. This European normative states that the European member states must have by 2007 strategic noise maps approved by competent authorities. These maps must be made with the selected indicators, Lden and Lnight to assess annoyance and sleep disturbance, respectively. As included in legal legislation, Lden and Lnight noise maps have become increasingly common and part of the law to assess environmental noise («Directive 2002/49/EC OF THE EUROPEAN PARLIAMENT AND THE COUNCIL relating to the assessment and management of environmental noise» 2002).
Following this normative, by 19th May 2015 the commission directive (EU) 2015/996 establishes common noise assessment methods in order to normalize the methods for assessing and managing environmental noise from the previous stated European normative (the directive 2002/49/EC) («Common noise assessment methods in Europe (CNOSSOS-EU) : to be used by the EU Member States for strategic noise mapping following adoption as specified in the Environmental Noise Directive 2002/49/EC.» 2012).
2.1.2. The use of listening Points to assess Environmental Noise
Schafer introduces the concept of Soundscape in 1969 in the book “The New Soundscape”. The concept has its basis on rather than characterizing an environment through noise levels, describe it via the sounds a person is listening to (Schafer R. Murray 1969). This concept has become more popular with several in-situ methods being perfected so that soundscapes can be more included in the routine of the general population to the point of developing mobile applications so that people can submit freely
9 sounds and their impact on the persons psychological part (Craig, Moore and Knox 2017).
The term Auralization refers to rendering sound fields by modeling methods (Kleiner, Dalenbäck and Svensson 1993). This method, however, has always been more applied to room acoustics and its use on environmental acoustics is relatively new, being mostly used to analyze the general population response to new projects. With the premise that annoyance is a combination of perceptual factors and not only based on energetic levels, in 2013 Ruotolo et all study the combination of virtual reality and renderization techniques to help evaluate the potential negative effects of traffic noise of a future project by exposing a population group to reconstructions of a scenario via virtual reality without versus with the projected motorway and studying the population’s reactions to the noise (Ruotolo et al. 2013). In 2015 Dincer and Yilmaz intend to build annoyance models based on listening tests from traffic noise. This is made by recording several vehicle types and adapt them to simulate sound propagation in several city environments. The listening tests take place and the people’s annoyance response is analyzed (Dincer and Yilmaz 2015)).
It is also in 2015 that these kinds of studies begin to include air traffic. Arntzen explores the auralization of an aircraft so that the general population from the Lelystad, Netherlands can be aware of the possible impacts from the Lelystad airport expansion.
The problematic introduced was that, when confronted with the noise maps, the general population could not associate the presented levels with the real experience of the passing of the airplanes. The combination of the aircraft passages was allied to videos of rendered google street view images and exhibited to the general public (Arntzen 2015). By 2018 Santos and Rosão start studying as well ways to better raise awareness to the sound impacts of projects and so, start studying the application of recordings of a passing of an airplane to different points of an airport’s noise map in order to give a better understanding to the general population of the levels expected in said point of the noise map (Santos and Rosão 2018). This work is later developed in 2020 as Rosão, Bakirci and Roque continue studying further techniques of audio adaptations by adjusting both the time of the variation of the levels caused by the passing of the airplane and the maximum level expected based on mathematical models and computational simulations (Rosão, Bakirci and Roque 2020).
In the 29th volume of the Noise/News international (March 2021) ANIMA starts studying as well the reduction of airport’s noise impacts by addressing annoyance by working with communities to better understand the present problems caused by the noise
10 and/or the areas not being addressed that could be suffering from its problems as well.
ANIMA does this by releasing a virtual community tool that helps people predict, experience and evaluate the noise predictions of different scenarios («INTERNATIONAL NOISE/NEWS» 2021).
2.2. Characterization of Faro’s Airport
In this chapter we will proceed to describe Faro’s airport including facilities, location and movements. Faro’s Airport has opened to activity in 1965 and it is distanced around 4 kilometres from Faro’s city centre. Its location can be seen pinned in the following image:
Figure 1: Location of Faro's Airport.
As we can see, Faro’s airport is mostly surrounded by Ria Formosa, a Portuguese natural park and reserve which contains important vegetation and places for a variety of species of birds to nest (Costa and Dalila Espírito-Santo 1996).
According to the website Chegadas e Partidas no Aeroporto de Faro («Chegadas e Partidas no Aeroporto de Faro» [sin fecha]) Faro’s airport terminal has only one terminal that operates as both departures and arrivals, with an area of around 68 500 m2. The airport counts with a single runway with a lenght of 2,490 meters («Private Jet Faro Airport — Central Jets» 2021) that, depending on the direction of the wind, can be used in two different directions. There is the runway 10, that counts with landings and take offs in the West – East directions. The runway 28 is the opposite as it counts with landings and take offs in the East – West direction, as it can be observed in Faro’s Airport navigation cards («Aeroporto de Faro, Portugal | LPFR | Informações para pilotos»
2021).
11 In the website PORDATA - Ambiente de Consulta ((«PORDATA - Ambiente de Consulta» 2019)) we can consult public data regarding the number of passengers using the Portuguese airports since 1970 until 2019. This website collects its data from INE (Instituto Nacional de Estatísticas – Statistics Portugal). It can be easily seen the consistent increase in the number of passengers, especially since 2014 to 2019, where we obtain a record level of 9 010 860 passengers. Even though the number of passengers has been growing, Faro’s airport still accounts for a relatively small number of passengers, especially when compared to the other two main Portuguese airports:
Figure 2: Number of passengers in the three main airports in Portugal.
Regarding the airplanes that mostly use the airport, using the public data available in https://www.flightradar24.com/ ((«Faro Airport (FAO/LPFR) | Arrivals, Departures & Routes | Flightradar24» 2021)) we can observe that the mostly registered flights are commercial, and the most observed aircarfts are the Airbus 320 family, the boeing 787 and the Embraer 190.
A municipal Lden and Lnight noise map can be consulted on Faro’s city website (Mapas de Faro (cm-faro.pt) («Mapas de Faro» 2021)), however the municipal noise maps do not discriminate against the environmental noise sources (eg.: If the source is traffic, railway or aviation noise). And so, Faro’s district provides the following noise maps:
0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 30,000,000 35,000,000
1970 1972 1974 1976 1978 1980 1982 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018
Number of Passengers in the three main Portuguese Airports
Faro's Airport Lisbon's Airport Porto's Airport
12 Figure 3: Available municipal Lden noise map for Faro's district.
Figure 4: Available municipal Ln noise map for Faro's district.
Even though the noise originated by the airport’s activity is not discriminated in the previous maps, it’s impacts can still be seen south of Montenegro’s city, where the airport is located.
2.3. Simulation Software AEDT 3d
In this thesis for computational simulations, we will use the software AEDT 3D (Aviation Environmental Design Tool, version 3d), a software developed by the Federal Aviation Administration Office of Environment and Energy (FAA-AEE) with the purpose of simulation the environmental consequences of the operations of the commercial aviation, namely noise, emissions and fuel consumption («Aviation Environmental
13 Design Tool (AEDT)» 2021). This software will be used in order to simulate the LAmax
levels to be obtained. With this software we aim to create simulations that will simulate the best possible way the maximum noise levels obtained in the listening points to better create the synthetized audios. Firstly, we have to consider that the LAMAX measured by AEDT has a slow time weighting (1s): LASMAX.
2.3.1. Simulation Parameters
For the simulations in the software AEDT we will define a certain number of parameters used in the simulations in this chapter.
The receptor defines the locations for where the noise metrics are calculated. The receptors can be defined to be single points or a grid. The set of receptors chosen to be evaluated in the simulation is called receptor set in AEDT.
The operation, as defined in AEDT, consists on the definition of the flight itself. In the aircraft operation certain parameters must be elected such as:
1. The operation type and airport layout;
In this panel the operation type (arrival/departure) is chosen, the airport layout, the operation count (that represents the total annual account)
1. The equipment;
In this menu the aircraft is chosen. There are several options depending on the model, the manufacturer or the motor type.
2. Time of the operation;
3. Flight profile;
Depending on the operation involved, there are several profile types to choose from.
In this work only the standard will be used. The stage length in departures is also chosen in this step. The stage length consists on the distance where in the stage the aircraft will depart. The further is the trajectory of the airplane from airport of origin to airport of destination, the bigger will be the stage length. This affects the noise as the bigger stage length is, the more fuel is needed for the flight distance and so, the airplane departs heavier, causing higher levels of noise. The AEDT user manual specifies the following stage lengths and the trip length (in International Nautical Miles, corresponding to 1.852 meters) corresponding to them:
14 Table 1: Stage lengths and the trip length associated (from the AEDT user manual).
4. Track of the operation.
After defining the operation, we define the annualization. The annualization consists of a hierarchical grouping of operations associated with the operations included, time period to be analysed, weighting of the operations (percentage of time the operation uses) and modelling operations.
With both the receptor sets and the annualizations ready, the next and last step of the simulation would be to define the metrics to calculate. AEDT has a range of emissions and noise metrics available to choose from. In this case only the noise metrics will be used. AEDT provides several choices in noise metrics based on exposure, maximum level, time above and time audible. It provides A-weighted, C-weighted and tone corrected perceived noise metrics. The noise metrics available in AEDT are:
15 Table 2: Noise metrics available (default) in AEDT (from AEDT technical manual).
AEDT also provides the option of creating a user defined noise metric according to the following parameters:
Figure 5: User interface for the user to define the metrics.
The noise metrics provide the option to choose the from the metric type to the frequency type to the weighting and time-averaging constant. The weighting factor is a numerical value that multiplies the sound exposure ratio associated with the time period,
16 in this case, defined by the user. The time-averaging constant is a constant decibel value given by the following equation:
𝑇𝑖𝑚𝑒 − 𝑎𝑣𝑒𝑟𝑎𝑔𝑖𝑛𝑔 𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡 = 10 log10[ 𝑇𝑖 𝑇𝑟𝑒𝑓]
Equation 1: Definition of time-averaging constant in AEDT.
Where:
• Ti is a time interval associated with the metric in seconds (s);
• Tref is the reference time interval of 1 second (s).
2.3.2. Noise Level Calculations
According to its Technical manual, AEDT computes noise from a series of single- event noise operations (individual aircraft operations) and then accumulates these single noise level events into the global noise level required. This process is made by following a series of steps:
1. With the specific aircraft data (equipment, noise, position and operational data) and environmental conditions (weather, terrain, boundary or ambient data) as input, calculate the “unadjusted” noise values at the receptor;
2. Apply the adjustments to account for the environmental and weather conditions and for operational and position effects.
3. Repeat the previous steps for each aircraft operation in the study;
4. Accumulate the noise output and compute the noise metrics;
5. Annualize the noise results.
The theoretical basis for the software to obtained the LASmax levels can also be found in the technical manual. For this particular noise measurement there is no Noise- Power-Distance (NPD) data existent, and the metric is calculated using empirical equations expressed in function of distance and sound exposure. The LASMAX metric for a civil aircraft in the AEDT simulations is obtained with the following equation:
𝐿𝐴𝑆𝑚𝑎𝑥= 𝐿𝐴𝐸− 7.19 − 7.73 log10[𝑆𝐿𝑅𝑝𝑡ℎ
1000 ] [𝑑𝐵𝐴]
Equation 2: Equation for the LASmax noise metric in AEDT.
Where:
• LAE is the A-weighted sound exposure level (dB);
17
• SLRpth is the length (ft) of the perpendicular vector from the receptor to the perpendicular closest point of approach on the flight path segment, or the extended flight path segment.
The LAE levels in AEDT are estimated based on Noise-Power-Distance (NPD) Data computations that are stored in AEDT data base and are dependent on aircraft type, aircraft operation and noise metric.
2.4. Mathematical Equations for the changes to be applied in the audios
For the changes in the audios that will be made in this thesis the two main parameters that will be subjected to changes are:
• Maximum level;
• Time of passage of the aircraft.
For the maximum level, we will use the values given by the AEDT 3d simulation.
However, for the time of passage we will determine with basis on a mathematical model.
According to («International Organization for Standardization - ISO 9613-2:1996:
Acoustics: Attenuation of sound during propagation outdoors: Part 2: General method of calculation» 1996) the noise pressure level Lp in a given point due to the noise originated from a punctual source in a distance d (in meters), from that point is given by:
𝐿𝑝= 𝐿𝐴𝑊− 11 − 20 log(𝑑) − 5
1000𝑑 − 𝐴𝑜𝑡ℎ
Equation 3: Noise Pressure Level in order of the distance.
Where:
• LAW is the power level of the source (dB);
• d is the distance (m);
• Aoth is the attenuation due to other sources of attenuation;
In this equation −11 − 20 log(𝑑) is the attenuation due to the spherical divergence and −10005 𝑑 is the attenuation due to the atmospheric absorption, which is variable with the sound frequency and with the atmospheric conditions. With the typical aircraft’s frequency spectrum and to normal temperature and relative humidity (15ºC and 80%), it assumes the simplified expression. Aout is due to other sources of attenuation such as the barrier effect, soil, among others which will not be accounted for.
18 As the routes of the arrivals and departures may be decomposed in several line segments where the velocity of movement and the dislocation of the noise source (the aircraft) and its emissions are relatively constant, we can deduce the following equation with the following scheme.
𝐿𝑝= 𝐿𝐴𝑊− 11 − 20 log (√𝑑⊥2+ (𝑣𝑡)2) − 5
1000√𝑑⊥2+ (𝑣𝑡)2
Equation 4: Equation for the sound pressure level for the line segments.
Figure 6: Scheme for the line segments of the route.
In Figure 7 we have the graphic for the variation of the noise levels regarding the maximum Lp when d= d ⊥ between -5 and 5 seconds (where t=0 is the moment when the noise source passes in the minor perpendicular distance d ⊥ to the receptor point). This graphic was made for a distance of 10 meters and velocity of 25 m/s (or 90 km/h).
Figure 7: Theoretical variation of the sound pressure levels in accordance of Lp
maximum for a punctual noise source with constant velocity in a straight line.
As the last equation does not account for the time the sound will take to arrive at the receptor point, d= d ⊥ will not be the exact instant when the sound level will be
19 maximum at the receptor. We can adjust Equation 4 for the time at the receptor assuming a sound velocity of 340 m/s:
𝐿𝑝= 𝐿𝐴𝑊− 11 − 20 log (√𝑑⊥2 + (𝑣(𝑡 − 𝑑
340))2) − 5
1000√𝑑⊥2+ (𝑣(𝑡 − 𝑑 340))2
𝐿𝑝= 𝐿𝐴𝑊− 11 + ⋯
…-20 log (√𝑑⊥2+ (𝑣(𝑡 −√𝑑⊥
2+(𝑣𝑡)2
340 ))2) −10005 √𝑑⊥2+ (𝑣(𝑡 −√𝑑⊥
2+(𝑣𝑡)2 340 ))2
Equation 5: Lp level assuming the time for sound propagation.
In Figure 8 we have the corresponding graphic of the variation of the sound levels considering the maximum Lp (𝑡 −340𝑑 = 0 𝑠), between -5 and 5 seconds for a distance of 10 meters and a velocity of 25 m/s (or 90 km/h) considering the time adjustment.
Figure 8: Theoretical variation of the sound levels in accordance of the maximum Lp for a punctual noise source with constant velocity traveling in a straight line with time correction.
We can observe that the symmetry between the growth and decay of the sound levels that was observed in Figure 7 no longer exists. We can see that now we have a bigger inclination in the approach of the noise source and less inclination in the distancing of the noise source (Rosão, Conceição and Házyóvá 2010).
20 According to («International Organization for Standardization - ISO 9613-2:1996:
Acoustics: Attenuation of sound during propagation outdoors: Part 2: General method of calculation» 1996) it is considered that the passing of a noise source corresponds to the time interval between the decay of 10 decibels before and after its maximum level.
To simplify, considering only the geometric divergence, without the time adjustment for the receptor, we have that:
𝐿𝑝𝑀𝑎𝑥= 𝐿𝐴𝑊− 11 − 20 log(𝑑⊥)
Equation 6: Initial equation for the noise levels using only geometric divergence.
𝐿𝑝𝑀𝑎𝑥− 𝐿𝑝= 20 log (√𝑑⊥2+ (𝑣𝑡)2
𝑑⊥ )
Equation 7: Equation for the noise levels considering only geometric divergence.
For the deduction of the time interval of interest of the decay of the 10 decibels is:
10 = 20 log (√𝑑⊥2+ (𝑣𝑡)2
𝑑⊥ )
Equation 8: Initial equation for the deduction of the time interval for the decay of the 10 decibels.
10 = 20 log (√𝑑⊥2+ (𝑣𝑡)2 𝑑⊥ )
10𝑑⊥2 = 𝑑⊥2+ (𝑣𝑡)2
9𝑑⊥2 = (𝑣𝑡)2
𝑡2=9𝑑⊥2 𝑣2
𝑡 = ±3𝑑⊥ 𝑣
∆𝑡 =3𝑑⊥
𝑣 −−3𝑑⊥ 𝑣
21
∆𝑡 =6𝑑⊥ 𝑣
Equation 9: Equation for the time variance of the 10 decibels below the maximum level obtained (based on Equation 7).
For example, for values considered more approximated to the real conditions like v= 78 m/s and 𝑑⊥=230 m, we have that ∆𝑡 ≈ 18 𝑠. In the graph from Figure 9 we have the graphs for both Equation 5 and Equation 7 for the same values:
Figure 9: Mathematical example for the equations using the divergence only and the divergence and time adjustment.
It is verified that the time interval is smaller for the variation considering the time attenuation than for the variation considering only the geometrical divergence. It is expected that these results are more similar to the reality. Accounting for these results, the determination of the time intervals will be given by Equation 5 instead of Equation 8
22
3 Methodology
23
3.1. Measurements
3.1.1. System and Equipment
For the recordings and measurements made two type I NSRTW_mk3 sonometers were used. These sonometers are equipped with a recorder which also allows them to be used to record sound. The first sonometers was used to recording the airplane’s passing’s and the second one was used to measure the Leq levels. The time ponderation used was fast (125ms), and the frequency weighting was A-weighting. The fast noise levels variation (each 125ms) was converted (energetic average) in slow noise levels variation (each 1 s) The slow calculation ponderation was used with the sole purpose of compatibility with the computational simulations with the software AEDT which specifies in its user manual that all the noise metrics calculated are slow. Video was also recorded with a smartphone.
Although the present work uses the 1 s variations of noise levels (slow time weighting) it was decided to carry out measurements of 125ms in 125ms (Fast time weighting) and convert these results into variations of 1 s in 1 s, as more information is available, which can be used in future works, for example works comparing the values of LAFmax and LASMax.
The equipment for the measurements is listed below:
1. 2x type I NSRTW_mk3 sonometers (audio recordings and noise level measurements);
2. Computer;
3. Smartphone (for video recordings);
4. Software:
a. Instrument Manager (NSRT) for measurements;
b. REAPER for audio treatment;
Due to the weather conditions, the measurements and recordings were made with a windshield in both sonometers.
24 Figure 10: Sonometer in measurement point 1.
Figure 11: Sonometers for measurements and recordings in Point 3.
3.1.2. Measurement Points
The set measurements took place in the first of June 2021. They took place in four distinct places of interest considering the routes of the aircrafts arriving and departing to/from Faro’s airport:
• Point one: point nearby the end of the stage 10 of Faro’s airport;
• Point two: point nearby both Faro’s downtown and the industrial area;
25
• Point three: located nearby a golf course and several housings in a luxury habitation zone;
• Point four: opposite side of Faro’s airport (according to point one);
The points and its locations can be seen in the following image:
Figure 12: The four recording points as seen in Google Earth.
3.1.3. Data treatment
Due to the restrictions placed on tourism in Portugal due to the covid-19 pandemic, the number of movements on the airport at the previous and following months of the recordings and measurements was severely impacted and so, there weren’t as many flights as usual. The number of flights recorded was lower what could have been obtained in any other regular occasion. In the spam of around 4 hours, being limited as well because of the time for travelling around the four recording points, there was a total of nine flights recorded. In the point one there was a total of four flights recorded. In the second point there were a total of two flights recorded, on the point three there was a total of two more flights recorded and in the point four, one flight recorded.
In the following table, with public information regarding the day’s flights (from Flightradar24: Live Flight Tracker - Real-Time Flight Tracker Map) we can see the flights predicted for the day, and the flights recorded signalled in colours:
26 Table 3: Total of airport movements from the 1st of June 2021.
In the previous table we have the following colour code:
• Yellow: Recordings in point 1;
• Blue: recordings in point 2;
• Green: recordings in point 3;
• Orange: recordings in point 4.
Some details to be added are the existence of eight flights instead of the nine that were recorded. This is due to the fact that in the point 1, the last flight recorded was a jet with no public information regarding which made the flight be discarded.
The LAEQ levels were measured each 125ms. The following registrations were obtained from the passing of the flights:
Flight code Day Hour Aircraft Stage Way Flight Code Day Hour Aircarf Stage way FR4088 01-Jun 9:05 B738 E-O FR7417 01-Jun 6:45 B738 E-O U21879 01-Jun 9:25 A320 E-O FR5140 01-Jun 7:00 B738 E-O
FR9142 01-Jun 9:45 B738 E-O FR7455 01-Jun 7:00 73H E-O
U27193 01-Jun 9:55 A20N E-O U21166 01-Jun 7:00 A320 E-O BA2620 01-Jun 10:05 A20N E-O FR3712 01-Jun 7:35 B738 E-O TP1907 01-Jun 10:30 E190 E-O FR9221 01-Jun 8:00 B738 E-O U21461 01-Jun 11:15 A320 E-O FR2451 01-Jun 8:10 73H E-O U28931 01-Jun 11:25 A21N E-O FR4087 01-Jun 9:30 B738 E-O U27199 01-Jun 11:55 A20N E-O U21880 01-Jun 10:05 A320 E-O U23503 01-Jun 12:00 A320 E-O FR9143 01-Jun 10:15 B738 E-O FR7418 01-Jun 12:25 B738 E-O U27194 01-Jun 10:25 A20N E-O FR7456 01-Jun 12:45 73H E-O BA2627 01-Jun 11:00 A20N E-O LH1786 01-Jun 12:50 A20N E-O TP1902 01-Jun 11:15 E190 E-O FR5139 01-Jun 13:00 B738 E-O U21462 01-Jun 11:45 A320 E-O U21165 01-Jun 13:10 A320 E-O U28932 01-Jun 12:10 A21N E-O FR3711 01-Jun 13:40 B738 E-O U27200 01-Jun 12:25 A20N E-O LH1162 01-Jun 14:15 A20N E-O U23504 01-Jun 12:40 A320 E-O FR2452 01-Jun 14:25 73H E-O FR2504 01-Jun 13:35 B738 E-O U22023 01-Jun 14:50 A320 E-O LH1787 01-Jun 13:40 A20N E-O FR9222 01-Jun 15:15 B738 E-O FR9948 01-Jun 14:05 73H E-O TP1903 01-Jun 15:35 E195 E-O LH1163 01-Jun 15:10 A20N E-O BA2696 01-Jun 16:20 A21N E-O FR2365 01-Jun 15:15 B738 E-O FR6826 01-Jun 16:45 B738 E-O U22024 01-Jun 15:25 A320 E-O FR4160 01-Jun 17:15 B738 E-O U28928 01-Jun 16:10 A320 E-O FR5099 01-Jun 17:15 B738 E-O FR9371 01-Jun 16:20 B738 E-O FR2911 01-Jun 17:50 B738 E-O TP1904 01-Jun 16:20 E195 E-O HV6093 01-Jun 17:55 B738 E-O FR652 01-Jun 16:35 B738 E-O FR9282 01-Jun 18:10 B738 E-O FR6827 01-Jun 17:10 B738 E-O WK298 01-Jun 18:20 A320 E-O BA2697 01-Jun 17:15 A21N E-O EI496 01-Jun 18:45 A320 E-O FR4170 01-Jun 17:40 B738 E-O FR4052 01-Jun 18:50 B738 E-O FR5098 01-Jun 17:40 B738 E-O HV5357 01-Jun 19:00 B738 E-O FR9225 01-Jun 17:55 B738 E-O U22019 01-Jun 19:15 A20N E-O FR2912 01-Jun 18:15 B738 E-O FR9947 01-Jun 19:45 73H E-O FR9283 01-Jun 18:45 B738 E-O FR2503 01-Jun 19:55 B738 E-O HV6094 01-Jun 18:45 B738 E-O FR8248 01-Jun 20:40 B738 E-O WK299 01-Jun 19:10 A320 E-O U26009 01-Jun 21:30 A21N E-O FR4051 01-Jun 19:15 73H E-O
FR9370 01-Jun 22:25 73H E-O EI497 01-Jun 19:35 320 E-O
U28927 01-Jun 22:30 A320 E-O U22020 01-Jun 19:45 A20N E-O FR2364 01-Jun 22:40 73H E-O HV5358 01-Jun 19:50 B738 E-O
FR5486 01-Jun 22:55 73H E-O OR698 01-Jun 19:50 73H E-O
FR651 01-Jun 23:15 73H E-O FR5487 01-Jun 20:20 73H E-O FR9226 01-Jun 23:15 73H E-O FR8249 01-Jun 21:05 73H E-O TP1909 01-Jun 23:50 E90 E-O U26010 01-Jun 22:10 A21N E-O
Arrivals Departures
27 Figure 13: LAeq levels measured each 125ms obtained for the passing of the flight one, Point 1.
Figure 14: LAeq levels measured each 125ms obtained for the passing of the flight two, Point 1.
60.0 65.0 70.0 75.0 80.0 85.0 90.0 95.0
10:11:44 10:11:44 10:11:45 10:11:46 10:11:47 10:11:47 10:11:48 10:11:49 10:11:50 10:11:50 10:11:51 10:11:52 10:11:53 10:11:53 10:11:54 10:11:55 10:11:56 10:11:56 10:11:57
LAeq(dB)
Time (s)
Flight 1, Point 1
60.0 65.0 70.0 75.0 80.0 85.0 90.0 95.0
10:22:1 10:22:1 10:22:2 10:22:2 10:22:3 10:22:4 10:22:4 10:22:5 10:22:6 10:22:6 10:22:7 10:22:7 10:22:8 10:22:9 10:22:9 10:22:10 10:22:11 10:22:11 10:22:12 10:22:12 10:22:13 10:22:14 10:22:14
LAEQ(dB)
Time (s)
Flight 2, Point 1
28 Figure 15: LAeq levels measured each 125ms obtained for the passing of the flight
three, Point 1.
Figure 16: LAeq levels measured each 125ms obtained for the passing of the flight five, Point 2.
60.0 65.0 70.0 75.0 80.0 85.0 90.0
10:24:40 10:24:41 10:24:42 10:24:43 10:24:44 10:24:45 10:24:46 10:24:47 10:24:49 10:24:50 10:24:51 10:24:52 10:24:53 10:24:54 10:24:55 10:24:56 10:24:58 10:24:59 10:25:0 10:25:1 10:25:2 10:25:3 10:25:4 10:25:5
LAEQ(dB)
Time (s)
Flight 3, Point 1
55.0 60.0 65.0 70.0 75.0 80.0 85.0
11:6:19 11:6:20 11:6:21 11:6:22 11:6:23 11:6:24 11:6:25 11:6:26 11:6:28 11:6:29 11:6:30 11:6:31 11:6:32 11:6:33 11:6:34 11:6:35 11:6:37 11:6:38 11:6:39 11:6:40 11:6:41 11:6:42 11:6:43 11:6:44
LAEQ(dB)
Time (s)
Flight 5, Point 2
29 Figure 17: LAeq levels measured each 125ms obtained for the passing of the flight six, Point 2.
Figure 18: LAeq levels measured each 125ms obtained for the passing of the flight eight, Point 3.
As it was previously stated, the software AEDT has its noise levels with the slow time ponderation instead of the fast, the following graphs convert the previous 125ms LAeq values to 1s LAeq values:
55.0 60.0 65.0 70.0 75.0 80.0 85.0
11:9:11 11:9:12 11:9:13 11:9:14 11:9:15 11:9:16 11:9:17 11:9:18 11:9:20 11:9:21 11:9:22 11:9:23 11:9:24 11:9:25 11:9:26 11:9:27 11:9:29 11:9:30 11:9:31 11:9:32 11:9:33 11:9:34 11:9:35 11:9:36
LAEQ(dB)
Time (s)
Flight 6, Point 2
60.0 65.0 70.0 75.0 80.0
12:13:23 12:13:24 12:13:24 12:13:25 12:13:26 12:13:26 12:13:27 12:13:28 12:13:28 12:13:29 12:13:29 12:13:30 12:13:31 12:13:31 12:13:32 12:13:33 12:13:33 12:13:34 12:13:35 12:13:35 12:13:36 12:13:36 12:13:37
LAEQ(dB)
Time (s)
Flight 8, point 3
30 Figure 19: LAeq levels measured each 1s obtained for the passing of the flight one, Point 1.
Figure 20: LAeq levels measured each 1s obtained for the passing of the flight two, Point 1.
60 65 70 75 80 85 90
LAEQ(dB)
Time (s)
Fight 1, Point 1
60 65 70 75 80 85 90 95
LAEQ(dB)
Time (s)
Flight 2, Point 1
31 Figure 21: LAeq levels measured each 1s obtained for the passing of the flight three, Point 1.
Figure 22: LAeq levels measured each 1s obtained for the passing of the flight five, Point 2.
60 65 70 75 80 85 90
LAEQ(dB)
Time (s)
Flight 3, Point 1
60 65 70 75 80 85
LAEQ(dB)
Time (s)