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ARTICLES Table of Contents   
Year : 2002  |  Volume : 4  |  Issue : 15  |  Page : 45-55
Complaints and annoyance caused by aircraft operations: Temporal patterns and individual bias

Departments of Biological Sciences and Environmental & Geographical Sciences, Manchester Metropolitan University, United Kingdom

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The impact of aircraft movements on annoyance in the local community surrounding a major international airport was assessed for (a) patterns of complaints for the year, month, day-of­ the-week and time-of-day and (b) the frequency of complaining by individuals. Complaint data from Manchester Airport since 1991 and detailed analysis for 1998 were compared with associated information on noise monitoring and aircraft movements to investigate underlying biological and sociological patterns. The annual number of complaints peaked in 1996 when the 'Manchester Airport Second Runway Public Inquiry' was a major local issue and had a high profile in the local media. Since 1996 the number of flights has increased while the number of complaints has steadily fallen; from 50 to13 complaints per 1,000 movements from 1996 to 1999. Detailed inspection of the 1998 data revealed a total of 2072 noise complaints from 594 individuals but, while the majority of individuals complained once or twice, three individuals accounted for 41% of complaints. This introduced some bias into the results but there was; (a) a steady increase in complaints (per 1,000 movements) over the week from a low on Monday to a high on Saturday/Sunday; (b) a marked hourly variation over the 24 hours in both flight frequency (movements per hour) and complaints. However, the hourly patterns in flight frequency and complaints were clearly distinct. Calculations of the complaints per aircraft movement (a reflection of sensitivity) for each hour of the day showed a striking 24h pattern with twice as many complaints between 23.00 and 07.00 as the rest of the day (07.00­23.00). Late evening and night-time, particularly during the early hours of sleep, was the time of greatest sensitivity to aircraft, with or without the serial complainers. These results could be used to inform airport operations to minimize community disturbance.

Keywords: aircraft noise, community complaints, time-of-day, annoyance, sleep disturbance

How to cite this article:
Hume K, Terranova D, Thomas C. Complaints and annoyance caused by aircraft operations: Temporal patterns and individual bias. Noise Health 2002;4:45-55

How to cite this URL:
Hume K, Terranova D, Thomas C. Complaints and annoyance caused by aircraft operations: Temporal patterns and individual bias. Noise Health [serial online] 2002 [cited 2023 Nov 30];4:45-55. Available from: https://www.noiseandhealth.org/text.asp?2002/4/15/45/31789

  Introduction Top

The growth of the transport industry is placing increased pressures on the environment in developed and developing countries. Over the last decade the aviation industry has undergone rapid growth and this is predicted to continue for the foreseeable future at 5-7% per annum (Airbus 1997).

The disturbance caused by aircraft noise has been cited as the single most important environmental issue to affect the growth of airports in Europe (Berglund and Lindvall, 1995). Noise related operational controls and limits have already significantly constrained the growth of some major European airports (ICAO, 1993). This limit on growth prevents airports from meeting the demand for air travel in the region they serve and reduces the economic benefits to the regional and local economies which would have accrued (Goodwin, 1993; Button and Verhoef, 1998). Aircraft noise technology is improving, however these benefits are being offset by the growth in air traffic (DETR, 1997). At the same time, residents of communities near airports are becoming more sensitive to issues such as noise disturbance (Moss et al, 1997) and have increasing expectations in regard to the quality-of-life. Individuals and groups in the local community who complain about airport operations are the main drivers of the noise limitation and airport restrictions agenda.

The problem of aircraft noise disturbance involves a complex interaction of a number of physical, biological, psychological and sociological processes (e.g. Hatfield et al 2001; Schultz, 1978). The relevant physical factors can be divided into those associated with the noise generation e.g. aircraft type, operation and noise level. Such data are automatically collected at major airports using sophisticated computer based monitoring systems (Thomas, 1996). Such monitoring is a prerequisite for airports to operate a viable financial penalty system for noisy and/or off-track aircraft. . These systems can track aircraft movements and associated noise production. In addition, most major airports operate complaint services to gather information about the disturbance caused by their operations to neighbouring communities. This information can give direct indications of the degree of annoyance in the local community and be used to refine or restrict operations so as to minimize disturbance and thereby facilitate growth. Community complaint data can feature prominently in public inquiries associated with planning approval for major airport developments. Therefore, a need exists to scientifically assess this data to support decision ­making by Government, planning authorities and airport operators. However, there has been apparently little effort to explore complaint data scientifically. The present authors consider that a well structured complaints system operating in parallel with a computerized noise monitoring system can provide useful data to explore the relationship between aircraft noise and community annoyance. We have demonstrated in a pilot study that the number of complaints about specific aircraft noise events are related to the noise level and the time-of-day of the event (Hume et al, 2002).

In this study we investigated airport data on complaints about specific aircraft noise events to explore two important aspects of annoyance due to aircraft noise;

  • temporal factors (yearly, monthly, day of-the-week and time-of-day) and
  • individual bias that serial complainers can introduce into the data.

  Method Top

The data used in this study were collected from Manchester Airport plc, the third busiest airport in the United Kingdom. The Airport has a Community Relations Department that deals with complaints via surface mail, e-mail, a dedicated phone line during office hours and an answer-phone at other times. There were two main data sets (a) annual total complaints and aircraft movement data from 1991 until 1999 and (b) a more detailed investigation for the calendar year 1998 when the monthly, day-of-the-week, hour-of the-day and individual complaint frequency for all complaints about specific aircraft movements were investigated.

Flight and noise information

Manchester Airport operates a computerized Aircraft Noise and Track Information System (MANTIS). MANTIS has links to nine remote noise monitors situated at strategic locations in the local community surrounding the airport that can be used to describe the local noise climate or the noise made by individual aircraft movements. Five of these monitors were situated 3.5 nautical miles from the start of the 'take-off roll' along the departure and arrival routes. The readings from these monitors are used to assess the outdoor noise levels on departure and arrival and routinely used to determine whether the aircraft is operating within the noise limits for that particular time of day and impose penalties upon aircraft which exceed locally agreed limits. The other four monitors record the noise on the airfield and in nearby densely populated areas. In this way, every individual aircraft movement could be associated with the noise generated in the community surrounding the Airport. Aircraft movements that led to a complaint were compared to the noise readings to obtain a noise level for that particular aircraft noise event (ANE). All aircraft movements (arrivals and departures) with associated information; flight number, aircraft type, airline, route, runway, time and date, were logged onto this system.

Complaints information

The complaints data had been processed by the Community Relations Department and initially logged and coded for a variety of factors, e.g. time and nature of the complaint, and further processed with the addition of flight and noise data onto the MANTIS system by the Environment Office. The current authors then carried out further specific analysis.

For the yearly patterns of complaints (1991­1999) all types of complaint were included, both non-specific and specific annoyance to specific aircraft noise events. All aircraft movements, which caused a specific complaint between 01/01/1998-31/12/1998, were retrieved from MANTIS and systematically analysed. This involved 2,072 complaints from 594 individuals. It should be stressed that for these specific complaints about aircraft noise events the time of day of the event was logged and not the time when the complaint was registered. The primary aim of the 1998 analysis was to investigate how complaints varied over the month, week-day and 24h day in comparison to the variation in flight frequency. The complaint data were all specific noise complaints that were directly compared to recorded movements from the Airport's monitoring system.

Complaints per Movement

In order to gain a clearer picture of noise disturbance due to aircraft movements for different years, months, days and times of day there was a need to control for the large variation in the number of movements. This was achieved by calculating a common metric of the number of complaints per unit movements (usually 1,000 movements). The complaints per movement represents a sensitivity scale as when the number of complaints per movement is high, it represents a high level of annoyance as each movement is generating a large number of complaints.

  Results Top

Yearly 1991-1999: There has been a steady progressive increase in the number of flights for the last ten years at Manchester Airport paralleling the global increase in aviation. The number of complaints showed a greater rate of increase up until 1996 followed by a steady fall. One would expect to see a positive association between the number of flights and the number of complaints, so in order to control for this association the number of complaints per 1000 flights was calculated [Figure1]. The peak in complaints in 1996 is associated with the Manchester Airport Second Runway Public Inquiry which received considerable cover in the local media and was a major local issue. The result was announced in January 97 - the first year with a fall in complaint numbers. This resulted in a fall from 50 to 13 per 1,000 movements from 1996 to 1999.

One issue that was considered by the enquiry was the level of complaints that the Airport received and the phenomenon of serial complainers (Thomas, 1996). Exactly how complaints by a core of individuals can bias the complaints profile was further investigated in the data for 1998 by constructing a frequency histogram of the complainers and the number of noise complaints made [Figure - 2]. There was an exponential decrease where most individuals complained once to individual complainers who complained about a dozen times and at the extreme end of the distribution are three individuals who complained about the noise levels of 141, 239 and 461 aircraft noise events. These three individuals accounted for 41% of specific complaints in 1998 and were identified as serial-complainers and appear as a separate group in some of the graphs to follow.

Month of the year: The monthly movements reflect the typical annual holiday cyclical pattern with a high season from May to September followed by a low season. The pattern of noise complaints follows this but with two peaks one at the start of the high season (May) one during the main holiday month (August) and a smaller peak in the low season (January). In order to control for the variation in movements over the year the complaints per 1,000 movements were calculated and showed the same pattern [Figure - 3] as for the raw complaint data with the serial complainers accentuating the three peaks.

Day of the week: The daily pattern of flights over the week shows a steady level with a fall on Friday and Saturday while the number of noise complaints rises steadily from a minimum on Monday to a maximum on Saturday/Sunday. This pattern is the same after calculating the complaints per 1,000 movements and is similar with or without the serial complainers [Figure - 4].

Time-of-day: Manchester Airport in common with many other airports operates a 'Night Noise Policy' which restricts the types and numbers of aircraft which can take-off and land between 23.00 and 07.00. With Chapter 2 (noisier) aircraft only allowed to land after 06.30. In addition, the Airport operates a 'Noise Penalty Scheme' the limits of which are lower at night (100 PNdB) than in the day (105 PNdB) to encourage airlines to operate quieter aircraft and pilots to fly more quietly, particularly at night. Therefore, the number of aircraft movements remains low at night between the hours of 23:00 and 06.00 when there are very few scheduled departures and arrivals and the majority of traffic is due to charter flights. Following the night restrictions the flight frequency rapidly rises between 06.00 and 09.00 with departure of many European business flights and arrival of transatlantic flights. There is a similar peak in aircraft movements between 17:00-19:00 which coincides with the return arrival of many of the European business flights.

The pattern of movements during the 24h day show two main peaks one in the morning at (07.00-10.00) and the other in the early evening (about 17.00-19.00) with a clear nadir at night time when the "Night flight policy" with financial penalties was acting [Figure - 5]. However, the complaint pattern does not follow this with high complaint levels during the early morning, midday and late evening (about 06.30, 12.00 and 24.00). Controlling for the variation in the movements per hour gives a very distinctive pattern of total complaints over the 24h with high levels in the late evening over the night and a second peak in the early morning with a minor peak at midday [Figure - 6].

Separation of the serial complainers [Figure - 7] from the moderate/low complainers [Figure - 8] seems to indicate that both are clearly disturbed at night but clear differences exist. Serial complainers are affected more at the start and the end of the night (and presumably sleep) while the moderate/low complainers are affected more evenly across the night with a peak between 02.00 and 03.00.

  Discussion Top

Temporal patterns of noise complaint: yearly, monthly and daily

It is important to note that the number of complaints concerned only a very small fraction of the total number of movements that occurred in the period of the study.

There was a clear sustained increase in movements from 1991 to 1999 at Manchester Airport compared to a more rapid rise in complaints from 91 to 96. The peak in 96 may indicate the sensitization of the local community as a result of the "Manchester Second Runway Inquiry" augmented by the increased media attention. It is likely that the decline in complaints after 1996 (the 2nd runway was approved in January 1997) was due to a combination of 'complaint fatigue' with acceptance of the inevitable 2nd Runway development and the loss of media interest. It will be interesting to appraise the complaint data following the opening of the 2nd Runway in 2001.

There are two main peaks in the monthly complaint data when the variation in flights over the year is controlled for by calculating the complaints per 1,000 movements. The rise in complaints in May is likely to be due to the increase in flights at the start of the peak summer season following the relatively quiet low winter season. The complaint rate then seems to habituate over June and July before another rise in August which is most likely due to the main UK summer holiday month with time spent at home with windows open and in the garden and more time to complain.

There is a very distinctive pattern of complaints per 1,000 movements across the week with substantially higher values at the weekend. Possible explanations for this elevated weekend levels pattern are: (a) the residents of the local community are spending more time at home and are therefore subjected to more aircraft noise (b) the weekend is most likely perceived as having greater intrinsic value for rest and relaxation, important factors in the quality of life, and therefore more annoying when the peace and tranquility are disturbed by aircraft noise. These explanations could equally apply to the August peak indicated above.

Time-of-day of Complaints

A general assumption could be made that the number of complaints over the day was directly related to the number of aircraft movements. However, [Figure - 5] reveals a lack of such a simple direct relationship between the daily pattern of complaints and movements. The results agree with earlier an earlier pilot-study (Hume et al 2001a) carried out on a six month period in 1999.

Consideration of the raw data of the hourly number of movements and complaints [Figure - 5] revealed a lack of a direct relationship between flight movements and complaint level. A very distinct pattern emerged when the distribution of complaints to specific ANE over the 24h in terms of complaints per 1,000 movements was analysed. A substantial night-time sensitivity was revealed [Figure - 6] which was considerably greater than the rest of the day. The tolerance towards aircraft is lowest between 23:00-07:00 [Figure - 6] and one could assume that this is when people become the most annoyed when disturbed. These eight hours are the main time for normal sleep. This clear circadian variation in complaining should not be too surprising as it has been clearly established that most physiological, psychological and behavioral variables express circadian variability as a result of internal clocks (Moore Ede et al, 1982).

One explanation of the data could be that there is more chance of most individuals being at home at night than at any other time of the day and therefore there is more chance of complaints at night. However, there is little difference in the data between the evening (e.g. 18.00-22.00) and the afternoon (e.g. 13.00-17.00) when one would predict far more people at home in the evening compared to the afternoon. To further investigate this issue we analysed the 24h patterns for all the weekends (Saturday and Sunday) in the year and found the same as when week-days and weekends were analysed [Figure - 6] indicating that when more people are at home over most of the day the 24h pattern is still apparent.

It could have been predicted that aircraft noise in the late evening/night when we are trying to go to sleep, during sleep and in the early morning before we wish to be awakened are times that generate the most complaint because it is a reasonable expectation that individuals in their own homes could expect to be allowed a 'good nights sleep' without the intrusion of loud external noise. The increased tendency to complain about night flights would be even more apparent if the 'Night noise policy' was not in operation which does reduce the noise load during the night. However, fewer aircraft at night at a time when the background noise is at its lowest of the day may well accentuate the effect of aircraft noise with the loss of habituation one might expect with more frequent flights.

Serial-complainers and bias

The frequency histogram of complaints [Figure - 2]indicates that the vast majority of complainers do so only once a year but at the other extreme a few individuals complain most days of the year. This contribution of 41% to the complaint data from the serial-complainers has the potential to bias the results. However, the series of graphs indicated that, compared with the low/moderate complainers, the serial-complainers:

  1. Simply accentuated the underlying trend in the daily plot[Figure - 4]]
  2. Presented a slightly more complex effect on the monthly plot [Figure - 3] but maintained the essential features.
  3. The 24h pattern shows that both types of complainers have a major problem at nighttime but the serial-complainers seem to have a particular problem with going to sleep, early sleep and early mornings while the low and moderate complainers have a more consistent nighttime problem with a peak at 02.00-03.00 and much less of a problem in the morning.

Complaining can be considered as part of a coping mechanism to a stress situation that provides an index of annoyance. However, many factors (e.g. assertiveness) come into play to determine who is annoyed and if that annoyance finds expression as a complaint to the Airport. It is quite likely that many individuals are disturbed by aircraft noise but choose to cope by direct action e.g. installing or improving sound insulation or taking on a positive mental attitude after balancing the disturbance with positive benefits of the Airport being nearby. A social survey (Hume and Thomas, 1993) indicated that many individuals cope or 'put-up-with' the disturbance, rather than complain, because they assumed that their complaint would not change significantly the airports operations.

It is difficult to determine whether serial­ complainers; (a) have a problem with their coping mechanism for dealing with stress or (b) find an outlet for expression of a personal political feud or crusade? Important to identify and investigate as great ability for a few individuals to bias the complaint data. Interestingly, there is a wide variation in how serial-complainers are viewed from "cranks" to "champions of the community" i.e. no need to complain as he/she will have done it for me! Further work needs to be done to determine if a certain personality type predisposes an individual to become a serial-complainer. It is plausible that they are linked to vulnerable groups e.g. noise sensitive, poor sleepers, chronically ill, or high neuroticism.

It is well known that individual and community reaction to aircraft and environmental noise are not fully explained by acoustic variables and a wide individual variation in sensitivity to noise exists (Job 1996). There has been an inability of acoustic variables, on their own, to satisfactorily predict self reported annoyance (Fidell, 1999). A complex interaction exists between annoyance and stress in noise affected residents living near airports. If an individual is already stressed, they may find an aircraft disturbance more annoying and therefore more likely to lodge a complaint. An unanswered question is why individuals differ in their responsiveness to environmental stressors (Winneke et al 1996).

Thomas (1996) noted a number of cases of serial complainers who seem to be more active when there is increased sensitivity e.g. during planning proposal inquiry for a second runway or after an aircraft crash. Despite the difficulties of understanding the motivation behind complaints, they are recorded and used to help determine planning applications that can have major financial, environmental and social consequences. Complaint statistics are frequently considered during the planning process to expand or build a new airport. Noise related operational controls and limits have already significantly constrained the growth of some major European airports (ICAO, 1993). It is a difficult challenge to arrive at a balance between the 'good' an airport development does in terms of transport, travel, increased commerce and employment for a region, and the 'bad' environmental and putative health effects of noise disturbance, increased road traffic and loss of green field.

The work reported here indicates that complaints depend in part not only on the noise level (Hume et al, 2001) but also airport expansion plans; media interest and temporal factors including the month of the year, day of the week and time of day that the noise occurred. And finally who heard the aircraft noise. It is a reasonable assumption that levels of complaint would be different from different airports because of e.g. different efficiency of systems used to log complaints, different levels of community awareness, cultural and socioeconomic differences, the local track record of air/ground accidents and the relationship of local communities with the airport. This again suggests further work.

  Acknowledgements Top

The authors would like to thank Manchester Airport for access to data and provision of office facilities and the staff of the Community Relations Department Office, in particular, Wendy Sinfield, Helen Collins, Jonathan Challis and David Ashworth; Alan Melrose in Business Development and David Foote in the Environment Office for all their help and support in gathering and analyzing the data.[16]

  References Top

1.Airbus Industries. (1997) Global market forces 1997-2016, confirming very large demand. Airbus Industries, Blagna, France.  Back to cited text no. 1    
2.B.Berglund and T. Lindvall. (1995) (eds.) Community Noise, Archive of the Centre for Sensory Research - Stockholm. 2(1): 86-104.  Back to cited text no. 2    
3.K. Button and E. Verhoef . (1998) 'Transport at the edge of mobility and sustainability' (in) K. Button, P. Nijkamp and H. Priemus (eds.) Transport Networks in Europe, Edward Elgar, Cheltenham.  Back to cited text no. 3    
4.DETR (previously, DoE) (1997) 'Decision letter on the proposed second runway at Manchester Airport' PNW/5082/219/23, Government Office for the NorthWest, Manchester.  Back to cited text no. 4    
5.S. Fidell (1999) Assessment of the effectiveness of aircraft noise regulation. Noise and Health, 3: 17-25).  Back to cited text no. 5    
6.P. Goodwin. (1993) 'Efficiency and the environment: Possibilities of a green-gold coalition' (in) Banister, D and K Button (eds.) Transport, the Environment and Sustainable Development, Spon, London.  Back to cited text no. 6    
7.J. Hatfield, R.F.S. Job, N.L. Carter, P. Peploe, R.Taylor and S. Morrell (2001). The influence of psychological factors on self-reported physiological effects of noise. Noise and Health 3(10: 1-14  Back to cited text no. 7    
8.K.I. Hume and C.S.Thomas. (1993) Sleep disturbance due to aircraft noise at a rapidly expanding airport (Manchester Airport). In, Noise as a public health problem. Vol 2, Ed. Vallet M. Inrets(France) p563-567.  Back to cited text no. 8    
9.K.I. Hume, M. Gregg, D. Terranova and C.S.Thomas. (2002) A pilot study into complaints caused by airport operations: noise level and time of day. Transportation, Planning and Technology (In press).  Back to cited text no. 9    
10.ICAO. (1993) International standards and recommended practices - environmental protection. Annex 16, Vol II Noise (3rd edition) International Civil Aviation Organisation, Montreal.  Back to cited text no. 10    
11.R.F.S.Job. (1996) The influence of subjective reactions to noise on health effects of noise. Environment International, 22 (1), 93-104.  Back to cited text no. 11    
12.M. Moore-Ede, F. Sulzman and C. Fuller. (1982) The clocks that time us. Harvard, Cambridge (USA).  Back to cited text no. 12    
13.D. Moss, G. Warnaby, S. Sykes and C.S. Thomas. (1997) Manchester Airport's Second Runway Campaign: The boundary spanning role of public relations in managing environmental organisational interaction. Journal of Communication Management. 2(4), 320-334.  Back to cited text no. 13    
14.T.J. Schultz. (1978) Synthesis of social surveys on noise annoyance. J.Acoust.Soc.Am. 64, 377-405.  Back to cited text no. 14    
15.C. S. Thomas. (1996), in Environmental Management at Airports. N.T. Pedoe, D. Raper and J. Holden (Eds) Thomas Telford, London.  Back to cited text no. 15    
16.Winneke, M. Neuf, and B. Steinheider. (1996) Separating the impact of exposure and personality in annoyance response to environmental stressors, particularly odours. Environment International, 22 (1) 73-81.  Back to cited text no. 16    

Correspondence Address:
Ken Hume
Dept of Biological Sciences, Manchester Metropolitan University, Chester St, Manchester, M1 5GD
United Kingdom
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Source of Support: None, Conflict of Interest: None

PMID: 12678948

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  [Figure - 1], [Figure - 2], [Figure - 3], [Figure - 4], [Figure - 5], [Figure - 6], [Figure - 7], [Figure - 8]

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