A COMPARATIVE ANALYSIS OF ANNOYANCE FROM AIRCRAFT NOISE
AT THREE EUROPEAN AIRPORTS
Abigail L. Bristow and Mark Wardman
Institute for Transport Studies, University of Leeds
Christine Heaver
FaberMaunsell
Elisabeth Plachinski
EUROCONTROL Experimental Centre
1. Introduction
This paper reports results from the 5A project (Attitudes to Aircraft Annoyance
Around Airports) funded by EUROCONTROL, the European organisation for
the safety of air navigation. The aim of the project was to gain a greater
understanding of how residents perceive and value annoyance from aircraft
noise. A large scale social survey including innovative application of stated
preference techniques to value noise and an extensive range of questions on
socio-economic characteristics of respondents and their response to noise
from aircraft and other sources was conducted in 2002 in three countries. A
companion paper (Bristow et al., 2004) reports the results of the study with
respect to the value of aircraft noise. This paper focuses on the findings from
the social survey on the factors that influence annoyance; the aim was to
determine attitudes to aircraft and other forms of noise, and identify the factors
that determine behavioural response to noise.
As the EU moves towards a standardisation of noise measures and with the
underlying principle of common standards across the community, (for
example, Directive 2002/49/EC (European Parliament and Council 2002)
relating to the assessment and management of environmental noise adopts
Lden and Lnight for the construction of strategic noise maps) it becomes
increasingly important to understand variation in annoyance levels within and
between countries.
Annoyance is a function of perceived noise which is itself a function of actual
noise. These relationships are modified by a range of factors relating to:
quality of life, other sources of noise, exposure to noise and activity patterns,
area type, country, personal and socio-economic characteristics and
confounding issues such as employment at the airport that influence attitudes.
The results presented in this paper include a discussion of descriptive
statistics and cross tabulations.
The survey work took place at the end of 2002 around the three airports at
Bucharest, Lyon and Manchester, achieving a total sample size of 647
respondents (with at least 200 respondents at each airport). A common
methodology was used at each airport with the aims of achieving a controlled
comparison of attitudes and valuations across countries and permitting
identification of any heterogeneity across locations. The design of the social
© Association for European Transport 2004
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survey was influenced by three key sources: 15 focus group analyses
undertaken earlier in this study (5 at each airport site), the body of literature
on variables that influence annoyance from noise, and guidelines on
standardised noise reaction questions for use in community noise surveys.
The paper is structured as follows. Section 2 describes the methodology and
the selected survey locations. Section 3 presents results and section 4
contains the conclusions.
2. Methodology and Locations
The social survey was intended to identify the key influential variables on the
value of noise nuisance from aircraft. The survey design was informed by a
wide range of sources which included:
•
•
•
Fifteen focus groups conducted in Manchester, Lyon and Bucharest for
this study, reported in Heaver (2002), and evidence from focus groups
conducted in earlier studies, including those carried out by Diamond et
al., (2000) for work on aircraft noise sleep and health.
The body of literature exploring the variables that influence annoyance
from noise and the value of noise from transport sources. Review
papers such as that by Miedema and Vos (1999) on the influence of
demographic and attitudinal factors and Fields (1998) on the role of
ambient noise were of particular assistance as were valuation studies
that identified key variables.
Guidance on standardised noise reaction questions for use in
community noise surveys (Fields et al., 2001) and previous
questionnaires such as that implemented in the large scale 1985 UK
study of aircraft noise (Brooker et al., 1985).
By drawing on earlier studies we endeavoured to ensure that no key influential
variables were omitted and that where appropriate questions were asked in
such a way as to make comparisons between studies possible.
The original intention was to conduct household interviews using a computer
based survey. However, as we wished to use aircraft noise simulation
software and use a range of different Stated Preference experiments, it was
ultimately decided that the best option was a paper based survey
implemented in hall test like conditions where staff could assist respondents
as necessary and explain each part of the survey before it started. Section
2.1 considers the selection of airports and survey areas around them. Key
areas covered in the survey are detailed in sections 2.2 onward.
2.1 The Airports
Manchester airport was selected as representative of a large regional airport
experiencing growth over time and with the recent (2001) opening of a second
runway. Lyon is also a large regional airport, though not as busy as
Manchester and in a much more rural setting. At Lyon two new runways are
planned. Bucharest was included as representative of relatively lightly used
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airport in a accession country. At each airport 5 or 6 locations were chosen to
give a range of levels of exposure to aircraft noise.
At Manchester to the north and east of the Airport are relatively high
population density suburbs while to the south and west there is more rural
aspect with farms, villages and commuter towns. The two parallel runways are
oriented NE to SW with the predominant winds (80%) coming from the SW
and consequently take-offs, and more noise disturbance, to the SW. The
selected areas are: to the north-west the main approach corridor to the airport
is over Stockport (11km), Cheadle Hulme (7km) and Heald Green (3km),
typical established home owning areas, affluent with semi-detached and
detached houses and little population mobility. To the immediate north and
north-west of the Airport is Wythenshawe which is one of the most deprived
areas in the country. In complete contrast the main departure routes to the
south-west cover the affluent town of Knutsford (10km). The development of
a second runway has brought the aircraft noise issue nearer to Knutsford.
Further away from the airport is the rural Lostock Gralam (20km).
In Bucharest the survey locations are areas of low income, although holiday
homes are starting to appear in Mogosoia and Buftea. The locations were as
follows: Mogosoia an attractive commune located around 5km south west of
the airport under the flight path; Buftea - 10km west of the airport, on the flight
path; Balotesti – 3km north of the airport a commune with poor basic
infrastructure; Tunari - 7kms east of the airport and highly agricultural; the city
of Otapeni lies around the airport.
At Lyon the area around the airport is made up of small rural communities that
have greatly increased in size over the last ten to fifteen years. They have a
very similar social and economic structure. The areas surveyed were as
follows: St Quentin Fallavier (10km) south of the airport a small town in a rural
setting; Grenay a small picturesque village perched on a hillside surrounded
by woods 6.5km south of the airport; Balan is a small village that has
experienced rapid growth in recent years 12 km north of the airport; Jons is an
attractive village 7.4km north of the airport and is also close to the TGV and
motorway; Pusignan is a half urban, half rural community 4km north of the
airport.
The surveyed areas around Manchester Airport exhibit a great variation in
both the nature of the area and socio-economic characteristics, whereas in
Lyon the small towns and villages surveyed are relatively homogenous and
this is probably true of Bucharest also. In all areas a good spread of age
groups and occupations was obtained. One aspect that proved problematic
was in finding recent incomers to the areas concerned. It was intended to
include recent movers to test whether acclimatisation to noise occurs as
people get used to it over time. However, at all locations the vast majority of
people had lived there for more than 5 years.
© Association for European Transport 2004
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2.2
Quality of Life
A key objective of the study was to obtain values for aircraft noise nuisance
and for one of our stated preference experiments we wished to ensure that
values were placed in a wider context and thus reduce the risk of respondents
focusing unduly on aircraft noise and reporting inflated values. In the focus
groups carried out as part of this study factors other than aircraft noise were
seen to be more influential in adversely affecting quality of life. These
included: crime, anti-social behaviour, air pollution, traffic congestion and lack
of local facilities. Evidence from an earlier study (Diamond et al., 2000)
involving four UK focus groups identified crime, parking, proposed new
developments and road traffic as important quality of life variables. A budget
allocation exercise undertaken within the 15 focus groups for this study
indicated that a quieter environment was a fairly low priority in Bucharest and
Manchester but was a high priority in Lyon.
This evidence underlined the need to place aircraft noise in context. The first
section of the questionnaire dealt with quality of life issues and avoided
alerting the respondent to the true purpose of the survey. Respondents were
therefore asked to rate 16 factors influencing quality of life in terms of, firstly,
importance and secondly, satisfaction.
2.3
Noise Awareness and Annoyance
Initial questions covered noises noticed, how noisy they were perceived to be
and overall noise levels in the area. Levels of annoyance from various noise
sources were next considered, where a numerical or verbal scale could be
used. Fields et al., (2001) suggest the use of two standardised questions on
annoyance using a five point verbal scale and a ten point numerical scale.
Given the length of the questionnaire and the range of issues to be covered,
we opted to use the five point verbal scale alone.
“Thinking about the last (…12 months or so), when you are here at home, how
much does noise from (…noise source…) bother, disturb or annoy you:
Extremely, Very, Moderately, Slightly or Not at all?” Fields et al., 2001.
We used the standardised English wording given in Fields et al., (2001). The
French version was adapted slightly by changing one of the modifiers as the
French survey team felt that the sense was not best conveyed with the
standardised wording. The phrase chosen will have switched the fourth point
on the reaction modifier scale slightly closer to the extreme position (5) in
terms of intensity than the standardised wording. The words were translated
into Romanian, but it was not possible within the budget of this study to
attempt to test and standardise the wording in this language.
Levels of annoyance or disturbance reported are likely to be influenced by the
nature of the activities being undertaken at the time, which will themselves be
related to the time of day or day of week. Respondents were asked about a
range of activities and types of disturbance, largely derived from Brooker et
al., (1985), but also drawing on the focus group responses, especially with
© Association for European Transport 2004
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respect to the use of the garden. The question was asked with respect to
aircraft noise, road traffic noise and other sources.
2.4
Personal and Situational Factors Influencing Annoyance
Findings of particular interest from studies of annoyance and valuation studies
of aircraft noise informing our design are discussed below.
Individual variables such as noise sensitivity (Bullen et al., 1986; Job, 1988;
Miedema and Vos, 1999) and factors such as level of fear associated with the
mode (Miedema and Vos, 1999) have been found to have a greater influence
on levels of annoyance than demographic variables. Fear was identified in
our focus groups as were other adverse impacts of airports: air pollution, fear
of lower house or land prices, increased development and increased road
traffic (Heaver 2002). In the questionnaire we asked respondents whether
they felt they were more or less sensitive or about as sensitive to noise as
other people. Later in the questionnaire after the focus had switched to
aircraft noise and the valuation questions completed, we asked about adverse
impacts of airports other than noise and their level of concern with these. We
also asked explicit questions on the value of people’s homes and whether this
would be higher or lower in the absence of the airport.
Higher levels of education and occupational status are likely to be associated
with higher reported annoyance (Miedema and Vos, 1999). Faburel and
Luchini (2000) also found this effect in the values obtained from their CVM
study of Paris-Orly. Given the range of countries involved in this study and
the different types of qualifications available, the question on education was
simplified to the age at which the respondent completed full time education.
For similar reasons we used income as an indicator of social class and
occupational status. These variables are of course likely to be highly
correlated.
Owner occupiers appear to report higher levels of annoyance than those who
rent (Miedema and Vos, 1999) and to be willing to pay more to reduce noise
levels (Fietelson et al., 1996). In hedonic pricing studies Collins and Evans
(1994) found that detached houses had a higher discount than semi-detached
or terraced houses. While Uyeno et al., (1993) found a higher noise discount
for flats than for detached housing. In this study respondents were asked
about the type of house they lived in and the form of tenure. Housing type
could be capturing the influence of other correlated variables such as income.
Confounding factors such as employment at the airport or high levels of use
have been found to reduce annoyance levels (Miedema and Vos, 1999).
Brooker et al., (1985) reported dependency to be a major confounding factor.
The focus groups (Heaver 2002) identified important beneficial effects of the
airport to be jobs and economic development in Bucharest and in Manchester
use of the airport and economic development. In this survey we asked about
the perceived benefits of the airport, levels of use by the respondent and other
household members and whether the respondent was employed at the airport.
© Association for European Transport 2004
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The young and the old tend to be less annoyed than those in between
(Miedema and Vos, 1999). Questions on age were included, as were
questions on times of day when respondents were usually at home to
establish exposure to noise while at home.
2.5
Aspects of Noise Influencing Annoyance
Different aspects of noise also influence levels of response:
•
•
•
•
There is remaining disagreement on the relative weights of average
noise level, number of events and maximum noise levels.
Related to the above is the issue of time of day weightings, where
again, agreement is perhaps only that existing solutions are less than
optimal (Bullen and Hede, 1986; Porter, 1997). Although Miedema and
Vos (2000) suggest that a 10dBA night time penalty does reflect levels
of annoyance caused.
Low frequency noise from aircraft on the ground is linked to annoyance
from rattle and vibration (Fidell et al., 1999)
The role of ambient noise should be considered. Fields (1998)
suggests that levels of ambient noise from road traffic may have little
effect on reactions to a target noise, say from aircraft. Nevertheless the
responses from the focus groups in this study (Heaver, 2002) and
those of Diamond et al., (2000) suggest that those in areas with fairly
high noise levels from other sources are less annoyed by an additional
source than those in an otherwise quiet environment. However, it is
possible that the Lyon focus groups were overstating their response
due to the influence of plans to build an additional runway.
In this study, time of day and day of week were important segmentations in
exploring annoyance from noise and valuations. This exploratory study did
not include resources for a significant noise measurement exercise or detailed
noise modelling. The survey samples were selected to give a range of levels
of exposure to aircraft noise. As a first step in linking noise measures to
levels of annoyance and valuation, we used the location of the household as a
proxy for aircraft noise exposure.
2.6
Adaptation and Acceptance
We might expect self-reported noise sensitive people to – if possible – avoid
noisy residential areas. This should be picked up by the sensitivity questions.
Adaptation to and acceptance of noise is expected to increase with length of
residence and this message certainly came through in the focus groups
(Heaver 2002) and those of Diamond et al., (2000). In our survey we
established length of residence and asked for motives in moving to the areas
and if the respondent was thinking of moving away, why this might be.
The presence of double glazing or other forms of noise insulation influences
the levels of noise experienced indoors (with the windows shut).
Respondents were asked whether they have any form of insulation, the type,
why it was installed and whether it was installed by them or by the previous
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occupant. Households may modify their behaviour as part of their adjustment
and our questions asked if respondents avoid certain rooms or the garden or
close windows in response to noise nuisance.
3. Results
3.1 Quality of Life
Responses on the importance of different factors to quality of life are shown in
Figure 1. A five point unipolar scale is used (ranging from 1 not at all important
to 5 extremely important) such that the closer the value is to five, the higher
the priority given to it. When considering the relative importance of broader
quality of life issues, crime and personal security are consistently highly rated
across the three countries. Local environmental issues, road traffic and
aircraft noise and air pollution are seen as very important in France. Air
pollution is the top concern in Romania, but noise much less so. In the
English sample noise is given a fairly low priority.
In the Manchester sample residents of Knutsford rate aircraft noise as their
top priority and looking at the standard errors their rating is higher than the
other areas. The Lyon sample exhibits a high degree of homogeneity. In the
Bucharest sample, aircraft noise is of greatest importance in Tunari and the
lowest rating is in Mogosaia.
Figure 1 - Quality of life: Importance
Amount of local council tax
Access to green spaces/countryside
Access to jobs
Access to public transport
Feelings of personal security
Level of local crime
Availability of local shopping facilities
Availability of local GP
Availability of local recreation facilities
Condition of roads and pavements
Aircraft noise
Neighbourhood air quality
Road traffic noise experienced at home
Amount of road traffic in area
Quality of local schools
Street cleanliness
1
Not at all
2
3
Slightly
Manchester
© Association for European Transport 2004
4
Moderately
Lyon
5
Very
Extremely
Bucharest
7
Figure 2 - Quality of life: Satisfaction
1
2
3
4
5
Amount of local council tax
Access to green spaces/countryside
Access to jobs
Access to public transport
Feelings of personal security
Level of local crime
Availability of local shopping f acilities
Availability of local GP
Availability of local recreation f acilities
Condition of roads and pavements
Aircraft noise
Neighbourhood air quality
Road traffic noise experienced at home
Amount of road traffic in area
Quality of local schools
Street cleanliness
Very satisfied
Satisf ied
Manchester
Lyon
Neither
Dissatisfied
Bucharest
Levels of dissatisfaction with aspects of quality of life are shown in Figure 2.
In this case a score close to five indicates a high level of dissatisfaction and
lower scores indicate satisfaction. Overall, respondents are fairly satisfied with
local facilities. The lowest levels of satisfaction are found in Bucharest,
reflecting the state of the local infrastructure. Aircraft noise is the aspect
causing most dissatisfaction in Lyon, followed by access to jobs, reflecting the
rural nature of the area, and the perceived lack of public transport which rates
fourth. In Manchester the main problem is the state of the roads and
pavements, closely followed by crime, with aircraft noise third. In Bucharest
the aspect respondents are most dissatisfied with is the level of local tax with
aircraft noise is rated tenth. Given that the number of aircraft movements in
Bucharest is much lower than in Lyon and Manchester it is not surprising that
aircraft noise generates less dissatisfaction in Bucharest than elsewhere.
Respondents in Knutsford are more dissatisfied with aircraft noise, than are
others in the Manchester sample. This probably reflects the fairly new nature
of the disturbance from the second runway at Manchester Airport. The
Manchester sample shows that those most concerned with crime are the rich
and the poor presumably because the former have the most to lose from it
and the latter more frequently experience it. When reporting levels of
satisfaction, the Lyon sample exhibits a little more variation than on
importance. Respondents from St Quentin and Jons are relatively content with
road traffic and road traffic noise compared with those elsewhere and
particularly Pusignan. On aircraft noise most respondents are fairly
© Association for European Transport 2004
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Very
dissatisfied
dissatisfied, but those from St Quentin are less concerned. In the Bucharest
sample, the greatest variations between areas are related to aspects of public
services: street cleanliness, public transport and schools. There is also
variation on crime, with those in Mogosaia and Balotesti being very
dissatisfied, while in Otapeni, it does not seem to be such a problem.
Considering road traffic and related noise, respondents in Mogosaia are the
most dissatisfied, those in Otapeni the least. On aircraft noise: Tunari,
Balotesti and Otapeni report below average levels of satisfaction.
3.2 Noise awareness and annoyance
Respondents were asked which noises were noticed on a scale ranging from
never (1) to all the time (5). Figure 3 shows the overall results. In the UK and
France aircraft noise was that noticed most often: while in Romania dogs
barking were the most frequently noticed noise, followed by road traffic noise
and aircraft noise.
Figure 3 - Noticing Noise
Factories/construction
Emergency vehicles/sirens
Aircraft
Trains
Road traffic noise
Rowdy people late at night
Motorbikes/mopeds
Children playing
Dogs barking
Neighbours
Burglar and car alarms
1
Never
2
Rarely
Manchester
3
Sometimes
Lyon
4
Often
Bucharest
Location clearly influences response. Around Manchester the highest reported
levels of noticing aircraft noise at Knutsford. The next highest was Heald
Green which is directly under the flight path and very close to the airport. In
Lyon the highest scores were Pusignan, which is the nearest to the airport of
the survey areas, but also at Balan, which is the most distant location. Around
Bucharest, aircraft noise is most likely to be noticed at Tunari, 7kms away
from the airport, with Otapeni, which is very nearby second. Location
influences response, but there is not a clear decay with distance. This reflects
the importance of flight paths and that some populations may be more
sensitive than others, either because they have a higher proportion of noise
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sensitive people or because noise has become an issue heavily discussed in
local media and or politics.
Figure 4 reports noisiness of different sources of noise. The top ranked
source in the UK and France was again aircraft noise, while in Romania it was
again third behind barking dogs and road traffic noise. This consistency is
also found in responses reflecting levels of annoyance from different sources
which are shown in Figure 5.
Respondents in Manchester rate aircraft to be the most annoying noise
source and this is higher than traffic noise which is itself higher than
annoyance from other noise sources. In Lyon aircraft noise and mopeds
receive the top ratings which are higher than those for other sources. French
law allows 14 year olds to drive mopeds, so these vehicles are very popular
with younger age groups who would not be permitted to drive a motor vehicle
in the UK or Romania. These vehicles are therefore likely to be more
prevalent in Lyon than in the other areas. Results in Bucharest are more
mixed but dogs barking are the most disturbing noise nuisance. This is partly
due to the high level of dog ownership in the area, but also the roaming packs
of dogs found locally.
Respondents in Knutsford were again reporting levels of annoyance higher
than in other locations around Manchester airport, this appears to be a
consistent “second runway effect”.
Figure 4 - Perception of how noisy each source is
Fact ories/construct ion
Emergency vehicles/sirens
Aircraf t
Trains
Road t raf f ic noise
Rowdy people late at night
M ot orbikes/mopeds
Children playing
Dogs barking
Neighbours
Burglar and car alarms
1
Not at all
2
3
Slightly
Manchester
© Association for European Transport 2004
4
Very
Moderately
Lyon
Bucharest
10
Figure 5 - How Much Does Noise Bother, Disturb or Annoy?
Factories/construction
Emergency vehicles/sirens
Aircraft
Trains
Road traffic
Rowdy people late at night
M otorbikes/mopeds
Children playing
Dogs barking
Neighbours
Burglar and car alarms
1
2
Not at all
Slightly
Manchester
3
Moderately
Lyon
4
Very
Bucharest
3.3 Personal and situational factors influencing annoyance
Table 1 shows annoyance segmented by a range of personal and situational
factors. There are no clear relationships between length of time at address or
the presence/absence of double glazing and annoyance. This is largely
because most respondents had lived in the area for more than 5 years and
most had some form of double glazing.
Respondents were asked whether the area was noisy and this acts as a proxy
for ambient or background noise. In Manchester those who said the area was
noisy were more annoyed than those who said it was moderately noisy who
were themselves more annoyed than those in self reported quiet areas. The
same pattern is found in Lyon where the obvious difference is between quiet
areas and the rest. In Bucharest those in noisy areas are less annoyed by
aircraft noise than those in moderately noisy or quiet areas. This may be
related to the frequency of departures, where in Manchester and to a lesser
extent Lyon at certain times of the day aircraft movements are every few
minutes and therefore viewed as part of the noise landscape. In contrast
departures are less frequent at Bucharest and aircraft noise may still be
viewed as an aberration and an incursion on an otherwise quiet area.
We might have expected incomers to an area to notice aircraft noise more
than those who have lived in an area for a long time and in theory become
acclimatised to it. In reality the patterns are far from clear, largely because it
proved impossible to obtain an adequate sample of people who had recently
moved into the areas surveyed due to very low levels of turnover. It could of
course be that incomers are less sensitive to noise and this has affected their
choice of home location. Another possibility for long term residents is that
they perceive increased disturbance over time as the number of movements
at the airport has risen.
© Association for European Transport 2004
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Table 1: How Much Does Noise Bother, Disturb or Annoy You
Manchester
Air Traffic
3.03 90.11) 198
3.09 (0.23) 35
3.52 (0.19) 52
4.68 (0.12) 22
1.96 (0.23) 26
2.64 (0.37) 14
2.39 (0.20) 49
3.19 (0.13) 137
3.13 (0.29) 30
2.33 (1.33) 3
2.76 (0.23) 37
3.25 (0.18) 69
3.17 (0.27) 35
2.69 (0.43) 13
2.84 (0.29) 31
3.00 (0.62) 7
4.11 (0.20 35
3.25 (0.17) 71
2.36 (0.15) 84
2.13 (0.55) 8
2.13 (0.40) 8
2.18 (0.35) 11
2.68 (0.35) 19
3.22 (0.12) 152
2.38 (0.25) 34
3.01 (0.15) 87
3.35 (0.20) 65
3.07 (0.14) 116
3.03 (0.18) 71
2.33 (0.19) 52
3.01 (0.16) 86
3.67 (0.19) 57
2.87 (0.16) 84
2.86 (0.21) 50
3.91 (0.28) 22
Lyon
Air Traffic
3.33 (0.08) 210
3.62 (0.17) 45
3.53 (0.19) 34
3.46 (0.21) 26
3.64 (0.17) 44
2.74 (0.17) 61
Bucharest
Air Traffic
2.61 (0.08) 235
2.24 (0.17) 51
2.25 (0.18) 40
2.03 (0.20) 34
3.00 (0.16) 58
3.21 (0.18) 52
Overall
CHEA
BALA
BALO
HEAL
GREN
BUFT
KNUT
JONS
MOGO
LOST
PUSI
OTOP
STOC
STQU
TUNA
WYTH
Full Double Glazing
3.37 (0.10) 158
2.66 (0.09) 159
Part Double Glazing
3.46 (0.24) 26
2.69 (0.20) 51
No Double Glazing
2.91 (0.23) 23
2.08 (0.22) 24
0-2km
3.83 (0.32) 12
3.23 (0.16) 52
3-5km
3.60 (0.18) 40
2.71 (0.13) 98
6-10km
3.32 (0.17) 50
2.16 (0.16)
11-15km
3.03 (0.16) 67
1.40 (0.22) 10
16-25km
3.41 (0.22) 37
1.60 (0.40) 5
26km+
Noisy Area
4.09 (0.20) 35
2.23 (0.14) 69
Moderately noisy area
3.61 (0.13) 74
2.79 (0.12) 115
Quiet area
2.85 (0.12) 100
2.79 (0.22) 42
Less than 1 year
3.00 (0.58) 6
3.50 (0.43) 6
1-2 years
2-3 years
2.73 (0.25) 15
1.75 (0.48) 4
3-5 years
3.16 (0.22) 31
3.11 (0.45) 9
Over 5 years
3.41 (0.10) 155
2.58 (0.08) 216
Time < 60%
3.17 (0.28) 23
2.59 (0.17) 58
Time 61-80%
3.42 (0.12) 101
2.62 (0.13) 95
Time 81-100%
3.30 (0.14) 77
2.64 (0.15) 77
Female
3.11 (0.13) 99
2.54 (0.11) 142
Male
3.53 (0.11) 111
2.75 (0.14) 88
Age under 35
3.14 (0.18) 49
2.44 (0.13) 97
Age 35-54
3.42 (0.12) 96
2.77 (0.13) 92
Age over 54
3.35 (0.16) 65
2.64 (0.20) 42
Income 1 (low)
3.11 (0.17) 62
2.52 (0.25) 27
Income 2
3.46 (0.17) 48
2.49 (0.13) 103
Income over 3 (high)
3.40 (0.12) 97
2.75 (0.19) 48
4
2.77 (0.19) 47
Employed at airport – yes
3.50 (0.96) 4
2.67 (0.33) 3
2.63 (0.10) 182
Employed at airport - no
2.97 (0.14) 196
3.35 (0.09) 188
3.08 (0.38) 12
Environmental org - yes
3.55 (0.43) 11
3.78 (0.21) 27
2.60 (0.09) 216
Environmental org - no
2.99 (0.11) 187
3.24 (0.09) 178
3.10 (0.38) 10
More sensitive
3.24 (0.42) 17
3.41 (0.23) 34
2.76 (0.19) 51
About the same
3.15 (0.12) 138
3.41 (0.10) 150
2.77 (0.12) 106
Less sensitive
2.55 (0.23) 42
2.81 (0.22) 26
2.27 (0.15) 73
Flights: zero
3.06 (0.27) 31
3.48 (0.13) 90
2.60 (0.09) 212
1-2
2.90 (0.14) 119
3.29 (0.13) 87
2.74 (0.25) 23
3-4
3.16 (0.28) 32
2.86 (0.42) 14
5+
3.63 (0.33) 16
3.25 (0.25) 8
Each column contains mean, standard error in brackets and sample size.
Age does not seem to affect levels of annoyance in Lyon or Bucharest, but in
Manchester the young (under 35) are clearly less annoyed than older people
(over 54).
© Association for European Transport 2004
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There are few variables where clear differences in annoyance are identified.
This is perhaps to be expected as many influences form an individual’s
response to noise.
The amount of time spent at home is fairly strongly related to annoyance in
Manchester, less so in Lyon and Bucharest. Note, however, that a number of
assumptions have been made in estimating the proportion of time spent at
home and this could have influenced the relationship between annoyance and
exposure. Respondents who stated that they are more sensitive or averagely
to noise are more annoyed by noise than those who report that they are less
sensitive than the average.
Confounding factors include use of the airport by respondents which is highest
at Manchester and lowest for Bucharest. People who do not use the airport
do report higher levels of annoyance than infrequent users, but annoyance
increases again for frequent users. This effect may be further complicated by
location and income effects. A very small proportion of respondents work at
the airports concerned so segmentation is not really meaningful in this
dimension.
3.4 Aspects of Noise and Exposure influencing annoyance
Figure 6 shows annoyance from aircraft noise by time period. Annoyance is
worse during the time periods when people are likely to be at home and
relaxing: evenings, weekends and at night. The variation is clearest in Lyon.
When split further by exposure to aircraft noise, there is in most cases a clear
positive relationship between time spent at home and annoyance levels.
Figure 6- Aircraft noise annoyance by time period
Sundays
Saturdays
Night 10p.m. to 6a.m.
Evening 6p.m. to 10p.m.
Daytime 9a.m. to 6p.m.
Early mo rning 6a.m. to 9a.m.
1
2
Not at all
3
Slightly
Manchester
Lyon
Moderately
Bucharest
In both Lyon and Manchester respondents were most annoyed when
socialising or relaxing in the garden and this annoyance is higher than for
© Association for European Transport 2004
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other impacted activities. Tables 2 and 3 illustrate reported disturbance and
annoyance.
Table 2: Percentage Disturbed at Home by Noise from Different Sources
(standard error).
Manchester
Lyon
Bucharest
Reading/writing/concentrating
41 (3.5)
34 (3.1)
32 (3.1)
Watching TV
44 (3.6)
37 (2.7)
34 (3.1)
Listening to radio/stereo
34 (3.5)
33 (3.1)
30 (3.0)
Conversation
46 (3.6)
44 (4.2)
31 (3.1)
Socialising or relaxing in garden
73 (3.2)
75 (3.2)
38 (3.2)
Sleeping
35 (3.4)
39 (2.8)
41 (3.3)
Table 3 Mean Aircraft Noise Annoyance in Different Activities (standard
error)
Manchester
Lyon
Bucharest
Mean
Mean
Mean
Reading/writing/concentrating
2.16 (0.09) 2.42 (0.08) 1.97 (0.07)
Watching TV
2.17 (0.09) 2.25 (0.08) 2.17 (0.07)
Listening to radio/stereo
2.03 (0.09) 2.16 (0.09) 2.06 (0.07)
Conversation
2.34 (0.10) 2.39 (0.09) 2.03 (0.08)
Socialising or relaxing in the
2.90 (0.11) 3.27 (0.10) 1.92 (0.12
garden (those with a garden
only)
Sleeping
2.11 (0.09) 2.25 (0.09) 2.12 (0.08)
Figure 7 - Aircraft noise annoyance by aircraft type
Very
4
Moderately3
Annoyed
Slightly
2
Not at all 1
Manchester
Lyon
Bucharest
747 or other large four engine plane
737/Airbus or other tw o engine plane
Smaller aircraft/propeller/turbo prop
The reported annoyance from different types of aircraft is shown in Figure 7.
In Manchester and Bucharest, annoyance is clearly perceived to be a function
of the size of the plane. The relationship is also there in Lyon, although it is
© Association for European Transport 2004
14
less strong with no clear difference between aircraft types. Although the
relationships appear strong the only differences where the confidence
intervals do not overlap are between four engined planes and the rest in
Bucharest and Turbo props and the rest at Manchester. This may in part
reflect the nature of the traffic at Lyon Airport which consists almost entirely of
medium sized aircraft. Although Bucharest too has a small absolute number
of large aircraft movements, these are likely to be more noticeable as the total
number of movements is also relatively low.
4. Conclusions
A common feature across all three countries is the importance of crime and
personal security in determining quality of life. In Lyon there is an emphasis
on local environmental issues where road traffic and air pollution are rated to
be more important than aircraft noise. Air pollution is the top concern in
Bucharest where aircraft noise has the lowest importance rating.
In
Manchester noise is given a fairly low importance rating. Aircraft noise was
the aspect that caused most dissatisfaction in Lyon. In Manchester it rated
third and lower down the list in Bucharest. Importance and satisfaction ratings
also varied by specific location.
Aircraft noise was the most frequently noticed noise at Lyon and Manchester
and the third most frequently noticed in Bucharest.
Responses were
influenced by specific location and distance from the airport, exposure to
noise (time spent at home), the respondent’s view of the noisiness of the area
and their own sensitivity to noise. There is a high degree of consistency
between rating of the noisiness of noise sources and the frequency of
noticing.
This consistency in response carried over into responses on levels of
annoyance from different noise sources. Aircraft noise is the most annoying
source in Manchester followed by road traffic noise. In Lyon aircraft noise and
mopeds are the most annoying sources of noise. In Bucharest barking dogs
create the most annoyance. Annoyance levels appear to be influenced by
such factors as specific location, double glazing, noisiness of the area, length
of residence, exposure, sensitivity and income.
The most severe disturbance from aircraft occurred when using the garden in
both Lyon and Manchester. The ratings at these locations were much higher
than for any other activity. Aircraft noise was perceived to be most disturbing
during weekends, at night and during the evenings. There is clearly a
correlation between annoyance at weekends and during the evenings and
annoyance when using the garden.
Large 747 planes were consistently rated as more annoying than 737/airbus
or equivalent planes, which in turn were rated more annoying than smaller
turbo-prop aircraft. However, the response seems to be in part conditioned by
the air traffic experienced, respondents in Lyon where most planes are two
engined were the least discriminating.
© Association for European Transport 2004
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Confounding factors included easy access to the airport when flying, which is
seen as a key benefit of living near an airport in both Lyon and Manchester.
In Bucharest access to jobs is seen as the key advantage.
The data should be able to support further analysis, which we intend to
commence once we have noise data for the airports concerned. It is our
intention to use ordinal logit to model influences on reported levels of
annoyance from aircraft noise.
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