The response to railway noise in residential areas in Great Britain

Journal of Sound and Vibration (1982) G(2),

THE RESPONSE RESIDENTIAL

177-255

TO RAILWAY

AREAS

J. M. FIELDS? AND

IN GREAT

NOISE

IN

BRITAIN

J. G. WALKER

institute of Sound and Vibration Research, University of Southampton, Southampton SO9 SNH, England (Received 29 August

1981, and in revised form 16 February 1982)

The effects of railway noise on residents have been measured with a combined social survey (1453 respondents) and noise measurement survey (over 2000 noise measurements) at 403 locations in 75 study areas in Great Britain. In the analysis of the data methods have been used which take into account many typical noise survey problems including noise measurement errors, unique locality effects and the weakness of the noise annoyance relationship. Railway noise bothers 2% of the nation’s population. Approximately 170 000 people live where railway noise levels are above 65 dB(A) 24 hour L,,. Annoyance increases steadily with noise level; thus there is no particular “acceptable” noise level. Railway noise is less annoying than aircraft or road traffic noise of equivalent noise level, at least above 50 to 65L,,. Noise is rated as the most serious environmental nuisance caused by railways. Maintenance noise is rated as a bigger problem than passing train noise. Vibration is the most important non-noise problem. Reactions to vibrations are related to distance from route, train speed and number of trains. The railway survey’s highly stratified, probability sample design with many study areas makes it possible to evaluate the effects of area characteristics on reactions. The 24 h L,, dB(A) noise index is more closely related to annoyance than are other accepted noise indices examined. There is no support for ambient noise level or night-time corrections. Thirteen railway operation characteristics were examined. One, the type of traction, has a strong effect on reactions after controlling for L,, (overhead electrified routes are the equivalent of about 10 dB less annoying at high noise levels). Three indicators of railway ancillary noises and non-noise environmental nuisances affect annoyance but most operational characteristics have no effect. The effects of over 35 demographic, attitudinal and neighbourhood characteristics on annoyance are examined. Though most objective characteristics of neighbourhoods and respondents are not correlated with annoyance, three do decrease annoyance (older dwellings, older respondents, and life-time residence). The attitudes which affect annoyance with railway noise are not general ones about railways as transportation sources, but rather ones which are specific to the neighbourhood setting or to railways as environmental intrusions in the neighbourhood. Such attitudes often have less effect on annoyance at low noise levels. In such cases it is the reactions of the more annoyed types of people which are most closely related to noise level.

1. INTRODUCTION The potential importance of railway noise as an environmental nuisance was recognized in the Wilson Report [l] in 1963 but at that time little was known about the actual effects of railway noise. Since then two rounds of railway noise studies have been carried out. The first round started in the early 1970s when a number of studies were published on reactions to railway noise in Japan [2, Nimura et al. 1975; 3, Kumagai et al. 1975; 4, Tamura and Gotoh 19771, France [5, Aubree 1973; 6, Aubree 19751, England [7, Walters 19691 and Canada [8, Hemingway 19751. The British railway study in 1975 f Now at NASA Langley Research

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.I. M.

FIELDS

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J. G. WALKER

began a new round of large scale railway studies in the Netherlands [9, de Jong 19831, Germany [lo, Knall 1983; 11, Heimerl and Holzmann 19781, Denmark [12, Andersen 19831, and Sweden 113, Sorensen and Hammar 19831. In addition to these field studies, two laboratory studies have been completed [14, Kono et al. 1973; 15, Rice 19751. The British railway survey was explicitly designed to provide evidence on a number of research questions which had not been resolved by previous studies. The central questions for this study are as follows. 1. How important is railway noise as a problem? 2. Which noise index best describes railway noise? 3. How do reactions to railway noise and other noises compare? 4. Do types of railway operations, neighbourhood conditions or personal characteristics mediate the effects of railway noise? 5. How much of the population is affected by railway noise? 6. How does vibration from railways affect people? In this study an attempt has been made to overcome two major types of weaknesses found in some previous environmental noise studies; a lack of relevance for public policy and a lack of awareness of methodological uncertainties. Study results were not directed at public policy when (1) abstract annoyance indices were used which had no easily understandable meaning; (2) individual characteristics (attitudes) were studied which had no direct role in public policy; and (3) restricted localized areas were studied which were of doubtful relevance for the larger area to which policy would have to apply. The methodological uncertainties weakened studies in which there was not serious consideration of the extent of errors in physical noise data, the possibility of bias in subjective annoyance measurements, the unreliability of questionnaire survey data, the ordinal characteristics of annoyance scales, the existence of confounding local area characteristics, the importance of uncontrolled conditions in a non-experimental setting and the implications of violating assumptions contained in commonly used multiple regression methods. The mixture of study design principles, information gathering procedures and data analysis methods which were used in this study to attempt to eliminate or evaluate these methodological uncertainties while still providing useful information for public policy is described in section 2 and Appendix A.

2. STUDY METHODS

2.1. SAMPLE DESIGN The sample was designed to describe the population impacted by railway noise (by using probability selection techniques) and to analyze the effect of noise and other selected site characteristics on railway noise annoyance (by deeply stratifying the sample by analytically important variables). The sample is an unequal probability, stratified, clustered, multistage area sample in which the 75 Primary Sampling Units are systematically selected from a highly ordered list and single individuals are randomly selected from each of 2010 sampled addresses located in 403 compact segments. The study population consists of people over 18 years of age living in dwelling units within an estimated 65 peak dB(A) railway noise contour of railway routes in Great Britain which are estimated to have at least 20 passbys a day and to be at least 300 m from any of the country’s 41 marshalling yards. (Ten other criteria of lesser importance are listed in ISVR Technical Report No. 102 [16, Fields and Walker 19801.) The National Railway Proximity Cartographic Survey conducted in the planning stage for this study divided the entire 11 288 miles of railway routes into 3098 sections,

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classified each section according to 13 important characteristics, and estimated the population within a 200 m band either side of the route. This information was used to define the study population, form sample strata, and form a sampling frame. Unequal probability sampling techniques were used to select the 75 primary sampling units which are shown in Figure 1.

Figure 1. Railway noise study areas. (Booster sample study areas were chosen with probability techniques. They are not distinguished from other areas in the analysis in this article.)

selection

Each study area was visited and divided into noise strata on the basis of a railway noise prediction technique [17, Walker 19771. Each area was then divided into small clusters of 3-10 dwellings with homogeneous railway noise environments. A total of 403 of these clusters of addresses (total 2010 dwelling units) was selected into the sample. Each cluster became a single noise measurement site (Figure 2). A probability sampling procedure in which a Kish selection grid was used [18, Kish 19651 was followed to select one resident from each dwelling. Whether a particular resident was at home did not affect the selection.

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The 2010 addresses yielded 1919 sample addresses which were found to be inhabited dwellings. Of these 1919 sample addresses 1453 yielded interviews (response rate of 76%), 236 refused ail information or an interview, and 230 could not be contacted or were incapable of being interviewed. A study of this survey’s data on respondents and non-response produced no evidence that non-response would distort the findings reported here [19, Windle 19771. Much more detailed information is available about the rationale for and evaluation of the study design [20, Fields and Walker 1977; 21, Fields and Tomberlin 19781, the method of selecting the sample [16, Fields and Walker 1980, Appendix B] and the National Railway Proximity Cartographic Survey [16, Fields and Walker 1980, Appendix A]. 2.2.

DATA

COLLECTION

2.2.1. Social survey information Professional interviewers collected the social survey data in face-to-face interviews lasting approximately 45 min, utilizing a fixed format questionnaire which gathered approximately 280 pieces of information about each respondent. The interview emerged from a process which included a major literature search, consultation with previous researchers, 20 loosely structured interviews, two sets of pretests of over 70 interviews, and an examination of tape recorded interviews. The final questionnaire followed standard practices in being introduced as a neighbourhood survey, focusing on noise issues after about 10 minutes and on railway noise after 15 min. The interview has many noise annoyance questions including ones from other surveys which facilitate cross-survey comparisons (section 3.3). The questionnaire explored reactions to different types of railway noise, feelings about other aspects of the railway and most previously recognized, major noise-related attitudes. Two forms of the questionnnaire had different question positions and a few small differences in question wording. These questionnaire experiments produced some interesting findings but did not bias the results presented in this paper [22, Garnsworthy 19771. Seventy-four percent of the interviews were completed between 15 October and 18 December 1975 with 99% being completed by 31 January 1976. All interviews were completed in a study area before noise measurements were begun there. 2.2.2. Railway route characteristics’ information Information about railway traffic at each site was obtained in a matrix of 20 train types by five time-of-day periods. This information came largely from working time tables, supplemented in difficult cases by consultation with local railway personnel. About 20 other types of information about railway operations in each area were provided on special fixed format forms by British Railways. The most important information was on maintenance procedures, rail type and non-standard operations. Much of the information was verified by the acousticians on the site at the time of the noise measurement programme. None of the railway route data was collected from respondents or by interviewers. 2.2.3.

Noise measurements

Meeting the objectives of the study required a description of the railway noise environment at each of the 2010 sampled addresses. To describe this environment a three step programme was carried out. These steps comprised (1) collection of noise data on observed train passbys in all 75 study areas, (2) analysis of noise data to provide information about individual train passbys, and (3) the collation of individual passby

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information with information about railway traffic to provide summary noise indices for each area. Each step will be described briefly. The aim of the noise measurement survey was to measure the noise of trains passing the 403 sample clusters. Financial and time restraints made it impossible to measure the noise of all trains at each sample cluster. However, previous studies of railway noise at ISVR indicated that there is an approximately constant difference between the Aweighted peak levels measured at any two positions alongside a given length of railway line. This led to the development of the measurement strategy for this survey based on “reference” and “measurement” sites. One “reference” site was selected in each area for measuring all trains passing through the study area during the several hours of the noise survey. “Measurement” sites, one at one of the houses in each sample cluster, were selected at which a subset of the train passbys could be measured simultaneously at both the reference and measurement sites (Figure 2). One noise measurement team was thus located at the reference position; the other team moved sequentially through all the measurement sites during the several hour survey. Because of the constant difference in noise levels it was possible to estimate the levels at any measurement site for trains which were not measured there. In areas alongside very busy routes, a reference site was not always used because it was likely that all types of trains using the line would be measured at each measurement site in a relatively short period. Trains in all 75 areas were measured and all sites were visited. Adverse weather, time limitations and other factors meant that measurements were not made directly at 34 of the 403 sites. Noise levels at the omitted sites and the noise levels for missing train types at some sites were estimated from other measured levels. Noise levels from over 1750 train passbys were measured during the survey by the two persons comprising the measurement teams, the majority of which were recorded at both the reference sites (1311 noise measurements) and measurement sites (1748 noise measurements). In order to allow a complete analysis of the noise data each train passby was recorded on magnetic tape, with a system having a good frequency response (measurement site: flat from 0 Hz to 10 000 Hz; reference site: *2 dB from 50 Hz to 10 000 Hz). A radio-telephone system proved invaluable in maintaining good communication between the measurement teams. Very careful identification and documentation of each passby was necessary to allow the later analysis to be carried out correctly. 2.2.4. Observation data During the noise measurement programme at each site the acousticians collected about 130 additional pieces of information about eight aspects of the houses, study areas and noise measurement sites: (1) estimated railway noise attenuation to unmeasured sides of houses; (2) presence of other railway noise (stations, shunting, etc.); (3) character of train noise (smoothness, wheel squeal, etc.); (4) non-noise railway aspects (dirt, smell, etc.); (5) topographical and shielding information relevant for testing railway noise propagation models; (6) presence of neighbourhood amenities; (7) quality of neighbourhood housing, lawns, etc., and (8) non-railway noise sources. Short (approximately 10 min) ambient (non-railway) noise recordings from each site were analyzed with a graphic level recorder trace and a noise dosemeter to give ambient ,&, and L,,. Though reliability coefficients have not been computed for the observation data, confidence in the data is enhanced by the fact that the data are correlated with respondents’ descriptions of the areas. These data have been valuable for assessing the impact of environmental factors on individuals’ responses to railway noise because they provide a measurement of the

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neighbourhood environment which is uncontaminated by the respondent’s own subjective feelings about the neighbourhood environment (section 7.1). 2.2.5. Repeated noise measurement programme The noise data at any one site are samples from one of many possible microphone locations, from a few of all possible train passbys, and during one of many possible weather conditions. The data were then processed in a series of steps when errors could occur. The combination of sampling variability and possible errors means that the measured levels yield “estimates” of the actual long term noise environment. The reliability of these estimates would be best assessed by repeating all the steps in the entire estimation procedure without reference to knowledge about the first round’s site-specific measurement procedures or noise data. Insofar as was possible, and aided by a 2 year loss in memory, the acousticians did approach sites as if they were unfamiliar with them when they returned to 11 areas containing 59 measurement sites. These sites were chosen to represent a range of both easy and difficult to measure sites. The data were then processed without reference to the previous data to provide new values of the summary noise indices. The results of this programme are described in section 2.3.2. 2.3.

NOISE

DATA

EVALUATION

The analogue tape recordings were analyzed and evaluated in the ISVR laboratory. 2.3.1. Noise data analysis All noise data were evaluated in the first year in a simple primary analysis and in a later year through a complex computer analysis. The primary analysis was based on the collation of reference site and measurement site data on four noise parameters from each passby. The train type, line used and direction of travel were added to the noise data. The noise measures (all in dB(A)) for each passby included the maximum sound level during the train passby, the mean sound level during the loudest part of the passby, the maximum sound level from the rail/wheel interaction and the energy emitted during the passby normalized to a standard time of 1 h. The first three measures were read from level recorder traces and the fourth obtained by using a noise dosemeter. From these four simple measures and information about the train movements, 13 summary noise measures for each site’s railway noise environment were derived. These noise measures included the logarithmic mean values of the individual event measures for all trains at each site, the 24 hL,,, the 18 h L,, (0600-2400), the day-night level (Ldn), the community noise equivalent level (CNEL), the number of trains exceeding a level of 68 dB(A) and their logarithmic mean noise level for an approximate evaluation of NNI (on the assumption that LA = LPN - 12), the number of trains exceeding the background level and their logarithmic mean level, the highest level recorded from any train, the number of passbys used in the calculations and the total number of trains per day. The noise measurement programme was designed also to allow the analogue recordings to be acquired directly and analyzed in a more comprehensive manner by using the ISVR computer. The analysis system included an interactive capability between the processor and the operator. Thus, whilst the precise calculation of noise levels was not influenced by the operator, the operator made decisions during the editing of the data, particularly when identification of train passbys was necessary at levels which were low compared to the site ambient noise. For 2213 of the 3059 recorded passbys over 100 pieces of information were derived from the computer analysis of l/3 octave band levels for 10 Hz to 10 kHz. These included

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maximum and integrated noise levels for each of the usual frequency weightings (unweighted, A, B, C, D, PNdB) and indicators of duration and rate of change of noise level with time. The reference site data, measurement site data and train operating information were again merged to provide summary noise measures for each site. The underlying principle was similar to that used in the earlier “primary” analysis, except that the individual passby data were acquired directly from magnetic tape. Most social survey analysis is based on the primary A-weighted analysis rather than the computer analysis except in a few highly specialized analyses involving other frequency weightings. The summary site-level noise data only became available after many social survey analyses had been completed. In view of the fact that the relative reliabilities of the two analysis techniques are unknown and the fact that the noise data from the original primary analysis were more highly correlated with annoyance, it was decided not to repeat all the former analyses with the computer analysed noise data. 2.3.2. Evaluation of noise data The reliability of the summary noise measures (from the primary analysis) was estimated by using the data from the noise measurements which were repeated at the 59 sites in the 11 areas. The variance of the pairs of repeated values of 24 h L,, dB(A) about their mean scores is approximately (T;= = 35.07. The standard deviation of the noise measurements is thus estimated to be uLL = 5.9 with a 95% confidence interval for gLL = 4 to 7. Given that the variance of the measured noise level is (+i = 151.99, the reliability coefficient for the noise level is (151*99-35.07/151*99) = 0.77. The method for correcting for noise measurement errors in the social survey analysis is described in Appendix A. 2.4.

SOCIAL

SURVEY

ANALYSIS

The analysis techniques used have been selected to provide information in a most useful form while at the same time assessing the effects of inaccuracies in interview data, adjusting for the effects of noise measurement errors, removing the effects of noise level, including area effects in sample variance estimates, and evaluating the weaknesses and strengths of alternative analysis methods. The various methods used in the analysis are described in the text when they are first used. The bases for the selections of the analysis methods are described in Appendix A. OF THE SURVEY METHODOLOGY 2.5. EVALUATION The large scale, complex design, large amount of data collected, and wide ranging concern with methodological issues made the survey process a lengthy and expensive one. The most critical decision may well have been to include a large number of study areas. This increased the expense of the noise measurement program and probably reduced the quality of the noise data to some degree. However, it was the inclusion of the large number of areas which has made it possible to study the critical area-level variables (the variables which are of the greatest policy relevance) with some assurance that area characteristics’ effects were not confounded with other variables. The questions about survey methodology which are reviewed here and in Appendix A may lead the naive reader to feel that this survey contained an unusually large number of methodological difficulties. However, most of these problems could have been raised with equal force about previous noise surveys.

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DOCUMENTATION

ISVR Technical Report 102 contains much more complete information on the study design and all data collection procedures [16]. All physical and social data collection forms are included in that report. 3. THE IMPACT OF RAILWAY

TRAIN NOISE

In this section the importance of railway noise in residential areas is evaluated. To address this issue, four separate questions are considered. (1) How does train noise affect people at their residences? (2) How do these effects vary with noise level? (3) Does an equal noise level from trains, airplanes, or road traffic have an equivalent effect on people? (4) How many people are impacted by railway train noise? 3.1.

THE

EFFECTS

OF TRAIN

NOISE

ON

RESIDENTS

Noise from trains affects people in at least three ways: (1) by directly interfering with certain activities, (2) by causing people to alter their behaviour, and (3) by influencing their general feelings about the quality of their environment. In Figure 3, four types of activity disturbances are reported: speech communication interference (inside and outside homes), television listening interference, sleep disturbance, and a severe measure of interference with concentration (being startled). Two different measures of speech and television interference are reported.

24 h L,

(dB(A))

Figure 3. Percentage of respondents reporting different types of -, Q21 ‘*. . . Stop talking or pause or speak louder. in the back hard to hear. . . TV. when the windows are open”; ---, Q20e, or speak louder.. . when the windows are open”; - - - -, Q18a (iii) ....‘..., Q18a TV”; --, Q18a (v) “. . . interfere with conversation”; startle you”. with sleep”; - ..’ -, Q18a (i) “.

activity interference from train noise. garden”; ---, Q19f, g, h “. . made it f, g “. . . make you stop talking, pause “. . . interfere with listening to radio or (ii, vii) “. . wake up. . . or. . interfere

Speech interference reports are strongly related to noise level. They increase from almost no reported interference below 40~5,~ to 48-88% at 75L,,. Sleep interference is less closely related over this noise level range since even at the lowest noise level (35~5,~) 12% report sleep interference while even at the highest no more than 35% report sleep interference. Because specific speech interference levels can be relatively objectively identified in a laboratory setting, it is sometimes assumed that they could be readily used to identify

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specific acceptable environmental noise limits. In fact, the steady increase in reported speech interference over the entire noise range in Figure 3 means that in complex living environments, there is no particular long-term noise level (at least above 45L_) where speech interference begins. This same steady increase was found for other noise indices (highest peak noise level, average peak noise level). Television listening interference is more often reported than speech interference at the same noise level in similar situations. The greatest communication interference, however, is reported for conversing outdoors where noise levels are higher and people may often be further apart. The impact of railway noise on behaviour is investigated with four behavioural reaction measures. On the most extreme behavioural reaction, less than 0.5% of the people at any noise level volunteered that the railway noise was related to their moving plans. Of the remaining three behavioural indicators, two others show very low effects: above 7OL,, less than 8% say they have complained to any authorities about the noise and less than 8% say that the railway noise had anything to do with a decision to install double glazing. (About half of the 8% say the railway noise was the “most important” reason for double glazing.) The most frequently reported behavioural response in Figure 4,

24 h L,

(dB(A))

Figure 4. Percentage of respondents reporting three behavioural reactions . . make you keep doors or windows shut”; --, Q30b “. . double glazed railway noise”; - -, Q46a “. complained about railway noise”.

“

to railway noise. -, at least partly because

Q27a of the

make you keep doors or windows shut more than you otherwise would. . .” is reported by about one-third of the respondents at the highest noise level. Follow-up questions showed that for about half of them the window closing is required during both the day-time and night-time. It seems unlikely that there are other more frequently occurring indoor behavioural indicators of noise effects. No one was found in the pretests who had consciously arranged interior living space to adapt to high railway noise levels. However, there may have been unmeasured inhibitions in the use of outdoor space such as were found in a Swiss Aircraft Study [23]. The activity interference and behavioural reaction results provide relatively limited but objectively definable indications of the effects of railway noise. More global, summary evaluations are available in Figure 5, which presents respondents’ overall feelings about railway noise. The results for the especially useful Verbal Rating Scale (Q17b) are presented in full with the cumulative percentages of respondents who say that the railway noise annoys or bothers them “very much”, “moderately”, or “a little”. Figure 5 provides some insights into the complexity of the response to railway noise and the meaning which should be attached to particular statements about the annoyance. hi

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24 h L,(dB(A))

Figure 5. Evaluation of railway noise according to nine criteria. -, QlOa: hear trains; -. --, Qllb: train noise is less than “definitely satisfactory” (less than 7 on 7 point scale); - -, Q42: would mind at least “a little” if twice as many trains; - ... -, Q17b: trains “bother or annoy” at least “a little” (4 point scale); - ‘- - -, Q17b: trains “bother or annoy” at least “moderately”; - - -, Qlb: without being prompted say that railway noise is something which “particularly dislike about the area”; ....... Q17b: trains “bother or annoy” . . “very much” (4 point scale); -- -, Q43b: railway noise is worst imaginable amount; - - -, Q40b: have not “got used to the noise from trains”.

There is not a single categorization of people into simply being affected or unaffected by the noise. Some people who say they are not bothered or annoyed “at all” (Q17b) still are not completely indifferent to railway noise because they also say that the noise is not “definitely satisfactory” (Qllb) and think they would be bothered if there were more trains (Q42). Though almost everyone reports that they have “got used to the noise from the trains” (Q40b), it is clear that this accommodation to the noise is far from satisfactory, since many more people still report that they are “bothered” and even “very” annoyed by the train noise (Q17b). Even Figure 5 understates the range in reactions to railway noise. That there are some people who enjoy railway noise, at least at a low enough level, has been shown in a study of noise in 10 small villages in Southern England (all more than 1 mile from a railway line). Of the 27% of that sample who said they could hear railway noise at home, no respondent disliked it and 37% said they actually like the sound (63% were indifferent) [24, Hawkins 19791. People in the British railway survey were not offered a positive scale for rating the railway noise they experienced. However, about hali’did indicate a preference for living where they could sometimes hear some sounds from a railway (presumably at much lower levels than many experience now) rather than in a place where there was no railway noise at all. Given the diversity of reactions evident in Figure 5 it seems clear that people’s reactions to noise cannot be adequately summarized by any simple, two-category dichotomy. From this survey’s analysis it appears to be more satisfactory to consider people’s reactions to railway noise as being arranged along a positive-negative continuum. For much of the rest of this article’s analysis, respondents are placed upon this continuum on the basis of the averages of their answers to five questions about their general evaluation of the railway noise they experience at home. This is labelled the Summed Annoyance Index and is described more fully along with the justification for the method of its construction in Appendices A and B. The Summed Annoyance Index is scored from 1 to 11. All 1453 respondents’ ratings on the index are plotted by noise level in Figure 6.

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The enormous variation in individuals’ reported responses to the same noise levels is especially obvious in Figure 6, though it has already been implicit in the dichotomizations in the earlier figures. The quadratic equation which regresses the Summed Annoyance Index scores on noise level shows that noise level explains only about 18% of the variance in the Summed Annoyance Index. This might lead to doubts about whether the annoyance by noise level relationship is of enough consistency to be of any use for public policy. The summary of these data in Figure 7 show that there is a strong, consistent relationship which can be the basis for policy: as noise level decreases, the average degree of noise impact steadily decreases.

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The importance of the variability in the measured responses (Figure 6) around the central tendency (Figure 7) depends very much upon both the purposes for which the data are to be used and the explanation for the scatter in reported scores. If the purpose were to predict one individual’s measured score on the scale, then the relationship is of little use. This is not, however, the goal. The purpose is rather to predict the true impact at particular noise levels. Some of the scatter in responses can be traced to simple errors in measuring reactions (e.g., not understanding questions, errors in recording responses). Inasmuch as these are “well behaved” random errors (the errors are not correlated with other variables of interest and the mean of errors’ deviations around the true score is zero), then the central tendency relationship is a good prediction of the average impact on all individuals at a given noise level. Inasmuch as the variability arises from differences in how annoyed any one individual actually feels at different times (a person may vary from day to day in how annoyed he is on a daily basis) then the central tendency is a good indication of how every individual feels on the average, over a long period of time. If the scatter is due to consistent, long-term differences in individuals’ feelings (sensitive or insensitive people), then the central tendency is obscuring the diversity in the noise impact even though it is still useful for indicating the average of the effect on the individuals at any one noise level. Recent studies of the reliability of noise annoyance measures give evidence for both the measurement error and diverse true reaction explanations [25, Griffiths, Langdon and Swan 1980; 26, Hall 19801. Inasmuch as the scatter in the responses is due to the above sources and the interest is in the averages of people’s reactions, then the variability in response is of no importance as long as enough individuals are sampled to obtain precise estimates of the mean scores. There are sources of the individual variability which, if present, could seriously affect the value of the central tendency relationships (e.g., people give falsely distorted high annoyance responses at high noise levels). In Appendix A there is no evidence for these types of problems. The individual variability in the measured annoyance scores does indicate that the analysis methodology must include inductive statistics to estimate the reliability of any finding. The data also suggest, however, that there are considerable differences in how different people feel about noise situations which can be characterised by the same L,, value. Much of the analysis in the remaining sections will be directed toward attempting to identify types of people or situations which may explain part of the variability in reactions to similar noise levels. The most important finding from Figures 3-7 is that the various indicators of noise effects are clearly related to noise level. In fact, noise level affects reactions more than any other variable. At the lowest noise levels present in these graphs (35L,,), three types of reactions have virtually disappeared: all the communication interference measures, startle reactions, and the most severe measures of overall annoyance. The 40 dB range in noise level changes the percentage in Figure 5 who are slightly annoyed by noise by more than 40%. We will see later that no other variable can create such a large change in annoyance reactions. It should be noted that people at the lowest noise levels can hear railway noise: 82% report they can hear railway noise. (In fact, this is probably an underestimate of the numbers who can hear the railway; some people in the pretest seemed to interpret “hear” as “bother”.) When Figures 3 and 5 are compared, it is clear that adverse reactions to railway noise arise from more than sleep or speech interference. Even though speech interference has virtually disappeared at the lowest noise levels and sleep interference is reduced to less than 12%, there are still a much larger 40% who still say that the railway noise is not “definitely satisfactory”. The residue of negative reactions even at the lowest noise levels

190

J. M. FIELDS

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may quite possibly be based on largely aesthetic grounds. The noise may then be disliked in the same way that the visual environment can be judged as unsatisfactory on aesthetic grounds. People rate a neighbourhood environment with dilapidated buildings as visually unsatisfactory, not because it interferes with their speech or sleep or concentration, but because it is not aesthetically pleasing. Part of the adverse reaction to the railway noise may be of the same type. 3.2. IMPLICATIONS OF THE NOISE REACTION CURVES FOR PLANNING Planners often hope to use noise reaction curves either to indicate a single “acceptable” noise level or to provide information about the benefits of various noise control measures. The data in Figures 3-6 do not support the concept of a single “acceptable” noise level. Some types of effects do not disappear at even 4OL,,. Departures from a linear relationship are so small that they provide no support for a “threshold-of-annoyance” which might be used as a “natural” value in noise regulations for noise insulation grants, environmental quality compensation grants, or absolute trackside noise limits. Most of the measures in Figures 3-7 show a roughly linear relationship above 45L,, with a lessening of the slope below roughly 45L,,. Even this weak pattern is not universal; the least severe annoyance measures in Figure 5 do not show the decreasing slope at lower noise levels. In addition, the shallower slope below 45L,, may be no more than a statistical artifact. It could arise if there were more measurement error in the physical noise variable at lower noise levels. While this seems plausible and is consistent with the limited noise reliability data collected there are not sufficient data on the variability of the noise estimates to discount the possibility that there is a real change in the shape of the reaction curve below 45L,,. A close examination of the curves in Figures 3-5 shows that the percentage counted as impacted as well as the shape of the curves depends on the activity considered, the question phrasing (the two television interference questions in Figure 3) and the point at which a particular question’s responses are dichotomized. There is no single, universal response pattern. As can be seen in Figure 5, though the Summed Annoyance Index is roughly linearly related to Leq, there is some lessening of the slope below 45L,,. The curve is best fit by a quadratic equation (Summed Annoyance Index = O-978 + 0*00139 x L,,+ 0.0008779 x LZJ,but in fact the regression coefficient for the Lzqterm is not statistically significant If the sample is split at 45L,, and separate in an equation which already includes L,,. linear regressions of the Summed Annoyance Index on L,,are calculated for each part, the difference between the two linear regression coefficients is statistically significant at only the p < 0.10 level. This sort of post hoc analysis is particularly suspect since a similar approach in which the sample is split at either 50 or 55L,, is even less statistically significant. In spite of the doubtful meaningfulness of the curvilinear trend, the remainder of the analyses proceeds with the quadratic relationship which fits the data best. This decision follows a general strategy in which priority is attached to the noise level variable in the analysis. With any other strategy one runs the risk of erroneously assigning part of the true noise level effect to other variables. Officials must often choose some type of measure which makes it possible to count people as either annoyed or not annoyed. Probably the single, most useful questionnaire item for these purposes is Q17b (Figure 5), which offers three different curves depending on whether a “very”, “moderately”, or “at all annoyed” curve is chosen. The choice between them is difficult to make on purely scientific grounds, but one major implication of the choice is clear. The more severe measure gives smaller absolute numbers of annoyed people impacted while completely ignoring any impact on people at low noise levels. Given the fact that many more people live at low rather than high noise levels,

RAILWAY

NOISE

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IN GREAT

191

BRITAIN

this is not a trivial point. In concrete terms, when compared with a low annoyance dichotomization, a severe annoyance measure shows relatively greater benefits from localized noise control schemes (noise barriers, local restrictions) than from noise control schemes which control the noise at its source. This is because the localized schemes can greatly reduce the exposure at very high levels, while having much less impact at the lower noise levels where moderately annoyed people can still be found. If a dichotomization must be chosen and if the arguments for the Summed Annoyance Index used in this paper are accepted then the dichotomization of the Verbal Rating Scale (Q17b in Figure 5) with the properties which most resemble the Summed Annoyance Index is the “at all annoyed” division. 3.3.

COMPARING

RAILWAY

AND

OTHER

SOURCES’

DOSE-RESPONSE

RELATIONSHIPS

Though railway noise can have many of the same effects on people as does other noise, the question still remains as to whether railway noise creates more, less or the same disturbance as other transportation noise at the same noise level. A detailed examination of this question in the British railway study has been reported earlier [27, Fields and Walker 19821. The results are summarized briefly here. Three Heathrow aircraft surveys and two English road traffic surveys were compared with the British railway noise survey. Most of the estimates suggest that at the noise levels at which many noise regulations are set (greater than 65L,, or 55NNI) the annoyance levels experienced with other noise sources are only experienced with railway noise at levels about 5-10 dB higher. It is not possible to provide a single estimate of how much less annoying railway noise is at all noise levels. At high railway noise levels (74L,, or 55NNI) railway noise is estimated to be less annoying by the equivalent of 4-15L,, for road traffic and 13-3ONiV1 for aircraft. Reactions to railway noise and other noises are more similar at lower noise levels and in some comparative analyses converge below 55-65L,, or 20-35NNI. The generally lesser annoyance with railway noise may be partially explained by characteristics of the railways’ sounds and partially by positive attitudes towards railways. Other European investigators have found that railway noise also is less annoying in France [29, Gilbert 19731, Denmark [12, Andersen 19811 and Germany [lo, Knall1983; 11, Heimerl and Holzmann 19781. It is not certain that this difference in reactions would be found under all cultural conditions. One Japanese study indicates that the noise from the high speed Shinkansen routes is more annoying than road traffic noise of the same noise level [4, Tamura and Gotoh 19771. Japanese data reviewed [28, Fields 19771 in a comparison of regular railway line and road traffic noise studies, suggested that the railway noise may be equally or more disturbing at the same noise level. 3.4. EXTENT OF RAILWAY NOISE IMPACT In spite of the fact that the size of the railway network has contracted in the last 50 years the existing railway network penetrates all the densely populated urban areas. It is quite likely that under favourable weather conditions, trains are audible at over half the country’s residences. 3.4.1. Extent of exposure The survey’s probability sample design makes it possible to estimate the number of people in Great Britain exposed to railway noise above certain levels. These estimates and their 95% confidence intervals are presented in Table 1. The estimates are based on (1) the National Cartographic Railway Proximity Survey’s measure of the amount of land near railways which is settled and (2) the measurement of noise levels in the social survey sample areas.

192

J. M. FIELDS AND J. G. WALKER TABLE

I

Number of dwelling units and residents at three levels of railway noise in Great Britain Dwelling

units

Residents

r No. of dwelling units

Standard deviation of estimate

60 and above

178 474

19 369

65 and above

59 667

9505

70 and above

17 834

4366

Noise level (24 h L,, dB (A))

,

\ 9.5% confidence interval 141 oooto 216 000

\

No. of residents

Standard deviation of estimate

95% confidence interval

491969

65 172

364 000 to 620 000

41000 to 78 000

171 184

29 730

112 913 to 229 455

9300 to 26 000

51167

13 018

25 649 to 76 685

The techniques used for making these estimates are described in more detail in Appendix K of ISVR Technical Report 102 [16]. In Table 1, it is estimated that 170 000 people live at railway noise levels above 65L,,. Thus in a country of about 54 million, less than 0.5% of the people are at railway noise levels exceeding 65L,,. It can be seen in the last column of Table 1 that this estimate is imprecise. On sampling grounds alone the 95% confidence interval for the 170 000 estimate is about *60 000. Non-sampling errors may also be important. Due to errors in specifying noise levels exactly (Appendix A), the data in Table 1 may somewhat overestimate the numbers of people exposed. 3.4.2. Extent of annoyance The best estimate of the proportion of the population annoyed by railway noise comes from an English road traffic survey which is based on a probability sample of England TABLE

2

Outdoor noises heard by people when indoors (% of households in England)t Noise source (% )

, Type of reaction

Road traffic

Aircraft

Hearing (95% confidence interval)

88.6 (*l.l)

83.6 (*2.1)

72

Being bothered, disturbed annoyed

22.9 (kO.4)

13.3 (+1.8)

14

Children

Animals

People

Trains

55

53

35.0 (*3.0)

13

12

16

8

1.9 (*0.4)

4

3

Factories

Construction

or

Being the most bothersome t Percentages are cumulative; e.g., This table is based on data from a in parentheses for the three sources technique. All other estimates come al. 19781.

the 88.6% hearing road traffic noise includes the 22.9% who are bothered. study of road traffic noise in England. 95% confidence intervals are given for which they were specially calculated using the successive differences from figure 7 of the road traffic survey report [30, Morton-Williams er

RAILWAY

NOISE

REACTIONS

IN GREAT

BRITAIN

193

[30, Morton-Williams et al. 19781. (The railway survey cannot provide this estimate because the evidence suggests that there are annoyed people who live outside of the boundaries included in the railway study population.) As can be seen in Table 2, the English road traffic survey estimated that 1.9% of the population of England would report they are bothered by railway noise and 0.8% would say railway noise is the biggest noise nuisance they can hear when they are at home. The 95% confidence intervals show that these estimates are sufficiently precise to indicate the relative importance of the different sources: about 12 times more people are bothered by road traffic than by railway noise and about seven times more are bothered by aircraft noise. Railway noise clearly affects a smaller proportion of the population than does road traffic noise or aircraft noise.

4. A NOISE INDEX FOR RAILWAY NOISE Many types of public policies require that the physical noise levels be numerically summarized in a noise index which is closely related to people’s response to the noise. In the analysis in this section noise indices are approached with two different strategies: an analytic strategy and a comparative strategy. The comparative strategy is simply to compare the relative predictive power of sets of existing indices, each of which already includes various components in a pre-existing model. The analytic strategy is to analyze each of the index components to determine which ones are related to annoyance and thus should be included. In the analytic strategy used here the five most frequently included noise index components are considered: noise levels of individual events, number of noise events, time of day of noise, ambient (non-train) noise levels, and spectral frequency weighting of noise levels. 4.1. NUMBER OF NOISE EVENTS The combined effect of number of events and average peak noise levels on annoyance (Summed Annoyance Index) is shown in Figure 8. Annoyance increases with both noise level and number of events. Though the number effect is fairly weak and subject to considerable variability in Figure 8, it is found to be statistically significant (p < 0.01) in a regression of the Summed Annoyance Index on average peak noise level and number of events. Thus number of noise events does affect annoyance.

2_

I. 50

60

Average Figure 8. Reactions in number x, 300-499; & 500 and over.

categories.

I 80

70

peak

Number

nme

level

I 90

I00

(dB(A))

of passbys per day: 0,

O-99;

0,

100-199;

+, 200.-299;

194

J. M. FIELDS

AND

J. G. WALKER

The form of the relationship between annoyance and number cannot be closely identified with these data. In Figure 9, the data have been normalized at a value of 80 dB(A) Leq, so that the Summed Annoyance Index score can be plotted by number of events (the plotted points come from a dummy variable regression procedure). The linear, logarithmic and cubic least squares solutions for the data set are also plotted.

100

200

300 Number

(Number

of interviews)

Figure

(119)

400

of tram possbys

(1571(77) (841 (2611 (3911 (1641

9. Form of the number

effect: -,

500

(621 linear;

I

600 (24

I 700

I BOO

900

h day)

(641

- - -, logarithmic;

(741 - - -, cubic.

Although the adjusted squared multiple correlation coefficients from the regressions on annoyance of each of the forms do differ (cubic = O-18, linear = O-16, loglo = 0.17), the differences are not statistically significant at the 0.05 level. The cubic form indicates that if there is a decreasing effect for numbers of events, it occurs for very high numbers of events (900 events per day) where there are insufficient observations to give reliable estimates. The effects of noise level and number do appear to interact in Figure 8; as noise level increases the effect of number increases. The interaction effect is not statistically significant when a multiplicative interactive term (loglo number multiplied by average peak noise level) is introduced into a multiple regression equation together with average peak level and loglo number. There is no support for the general pattern advocated for aircraft noise [31, Rylander et al. 19741 that peak noise level does not affect annoyance in low number groups until a threshold around 90 dB(A) is reached. Such an effect was not found for five alternative annoyance measures, different definitions of noise level (including peak of noisiest train), different forms of the noise level (including quadratic form), number (unlogged as well as logged) or different interaction terms (unlogged or logged number multiplied by noise level). The evidence available from this analysis is not sufficient to reject the most commonly held hypotheses that peak noise level and number effects are independent and that number can be represented by a logarithmic transformation. Nonetheless, it is also not inconsistent with linear forms for the number effect. 4.2. RELATIVE IMPORTANCE OF NOISE LEVEL AND NUMBER OF EVENTS Most of the debate on number effects has focused on the relative effect of noise level and number of events (logarithmically transformed). The relative importance of the two factors is represented by the ratio of the partial regression coefficient for log10 number t This is the same procedure used for measuring additional variables’ effects with the Decibel Equivalent Annoyance Units all through this article. No correction for noise measurement errors is made here since other surveys calculating this number effect ratio have not included such corrections.

RAILWAY

NOISE

REACTIONS

IN

GREAT

BRITAIN

195

divided by the partial regression coefficient for noise levelt (k). For the total British railway sample, the Summed Annoyance Index and A-weighted peak levels being used, the value of the ratio is k = 9.4 with a standard error of 5.5. The value of k = 9.4 indicates that a one unit change in the logi, number (a lo-fold increase in number) is estimated to be the equivalent in annoyance units to a 9.4 dB increase in noise level. This is consistent with the L,, ratio value of k = 10, but it is so imprecise as to not be significantly different (p < 0.05 level) from the NNI value of 15. 4.3. NIGHT-TIME NOISE EVENTS The same amount of noise is commonly assumed to be more annoying during the evening or nignt-time than it is during the day-time. When the respondents were directly asked “do you find the train noise is more annoying at certain times of the day or is it always the same?“, some 44% (of those who are ever bothered by railway noise) say that it is always the same, 25% say train noise is most annoying in the night (2100-0700) and 22% in the evening (1900-2100). Given the fact that day-time hourly L,, values average about 4 dB above night-time L,, values (day-time is about 1 dB above the evening L,,) and the fact that the day-time period is longer, there is some evidence that the same noise levels are more annoying at night or in the evening. This evidence is not, however, conclusive. People may rate night-time noise as a problem almost irrespective of level. What is needed is evidence that people’s reactions are very different in high and low night-time noise environments. The day-time and night-time peak noise levels are very similar, but there is considerable variation between study locations in the percentage of total traffic occurring at night (l-53%) and the average number of trains at night (less than 1 to over 100). However, there is no evidence that these variations in night-time traffic affect overall annoyance (Summed Annoyance Index) any more than do day-time noise events. In Table 3, including the number of events during the night in Regression 2 adds very little to the number effect of the day. In fact, in Regression 3 increasing the number of night events reduces annoyance (not increases it) after the effect of 24 h L,, is included. Similarly, in line 4, the night-time L,, contributes less on an hourly basis than does day-time L,, (the 14 h day-time period has about 0*089/0*035 = 2.5 times as much effect on annoyance as does the 8 h night-time perod). The negative coefficient for evening L,, in Regression 4 shows that there is no evidence for a heavy evening weighting. The effect of the night-time noise environment on night-time annoyance itself was measured with four questions: the spontaneous mention of railway noise as a cause of sleep disturbance (before railway noise is mentioned in the questionnaire), a direct question about being awoken by trains, a direct question about whether trains “interfere with your sleep in any other way” and a question about time of day when most disturbed by railway noise. All four questions were also weighted by their factor scores from a principal component factor analysis to make the Night-Time Disturbance Index. The four questions individually give similar results to those found in Part B of Table 3 for the Night-Time Disturbance Index: though the average peak level (Regression 5) and night-time L,, (R e gression 6) are significantly related to night-time annoyance, the number of trains at night are in both cases negatively related to night-t; ne annoyance. Parts C and D of Table 3 show that even when only light sleeperst were examined there is no stronger evidence for the effect of number at night. A large number of other analyses were carried out in which control variables, special subsamples, and noise measurement errors were considered, but no evidence was found for a special night-time t Reports of general sleep quality were obtained before respondents knew the questionnaire noise. “Do you sleep extremely well, very well, fairly well, rather badly or very badly?”

would concern

196

J. M. FIELDS

AND

J. G. WALKER

* :,

2B 00

Z% 00

00

06

RAILWAY

NOISE

REACTIONS

IN GREAT

BRITAIN

197

effect. While the lack of a night-time effect is contrary to most expectations, there are possible explanations: (1) some people may sleep through all night-time events and thus be less affected than during the day; (2) increasing the number of trains may aid adaptation to the night noise events. While there is no evidence that the number of night-time noise events has a special effect on annoyance beyond that already included in 24 hour Leq, it must also be noted that the statistical estimates are not precise enough to reject the possibility of night-time effects. The standard deviation of the estimates in Table 3 are sufficiently large that 95% confidence intervals for the partial regression coefficients would not reject positive effects, even the conventional 10 dB penalty, for the number of events at night. There may also be strong night-time peak level effects which these data could not explore. 4.4. AMBIENT NOISE LEVELS The effect of ambient noise levels on annoyance with the railway noise is explored with four different ambient noise level indicators in Table 4. The ambient noise level effect is estimated by grouping residual annoyance scores (i.e., the difference between observed annoyance scores and those predicted from the regression of annoyance on L,, and Lzq) into ambient noise level groups. These deviations from the regression line are labelled “Decibel Equivalent Annoyance Units” (dB(EAU)) in this report. A change of 1 unit dB(EAU) is equivalent to the amount of annoyance that a 1 dB increase in noise level would cause. (The calculation of the Decibel Equivalent Annoyance Unit and the Summed Annoyance Index are explained in more detail in Appendix A.3.) For the first indicator in Table 4, there is slightly less annoyance with train noise in low ambient noise situations. At the lowest ambient noise level (below 50 L,,) the average annoyance of the 97 respondents is less than would be expected on the basis of the railway noise level. The value of -3.4 dB(EAU) indicates that a 3.4 dB reduction in railway noise level would be needed to create this large an effect on annoyance. At higher ambient noise levels, railway noise reactions are slightly above or equal to those which would be expected on the basis of the railway noise alone. Thus, if there is any pattern at all it is for reduced, rather than enhanced annoyance reactions at low ambient noise levels. This is consistent with a theory that the presence of other noises sensitises people to new noises, but not with a theory that other loud noises will reduce the reactions to a less intensive noise. For Indicator 4, the respondents were grouped by the acoustical measurement team using the common area descriptors from British Standard 4142 [32, BSI 19671 based on the IS0 1996 Standards [33, IS0 19711. To compare the empirical findings with the IS0 regulations, the last part of Table 4 gives the IS0 decibel leniency to be allowed above the rural residential standard for each type of area. It can be seen that. the application of the standard to residences is not supported by the data. The type of area which has the lowest observed annoyance reaction (rural) has the strictest criteria. More importantly, the range in actual reactions to railway noise between the different areas (equivalent to 5.5 dB), is actually very small after railway noise level is controlled for relative to the range of the ISO: 1996 adjustments (15 dB). While the observed negative relationship for measured ambient noise level is not statistically significant, it does reject even moderate conventional positive adjustments. A 5 dB adjustment for areas with an ambient level 30 dB L,, below the railway noise can be rejected at the p < 0.001 level. The same conclusion was reached, when ambient Lgo was used rather than L,, and when the relationship was controlled for section of country and the overall environmental quality of the neighbourhood. The possibility that the relationship could have been

J. M. FIELDS AND J. G. WALKER

198

TABLE

4

Residual railway noise annoyance in ambient noise groups for four indicators of ambient noise level Contents

of row

Ambient Indicator 50-54 L,,


-3.4 (97)

-0.9 (351)

noise groups

1: Measured 55-59 L,,

ambient noise levels 65-69 L,, 60-64 L,,

0.3 (449)

Indicator 2: dB(L,,) by which railway exceeds ambient -24 to -5 -4 to 4 5 to 14 215 L,, (RW is higher)

< -25 L,,

-1.0 (285)

-0.8 (90)

dB(EAU) (N)

370 L,,

Indicator

3: Population

Rural

density

-3.4 (137) (map survey)

Suburban

Urban

-2.7 (296)

dB(EAU) (N)

Rural (residential) dB(EAU) (N)

-4.8 (106) Rural

Leniency (dB) a dB(EAU)-Decibel

0

Indicator 4: Type of area using BS 4142 definitions Suburban Urban’ (mostly (little road Urban residential) Mixedd traffic) (residential)

(607;

-0.9 (268)

Predominantly industrial

(301;)

Corrections given by IS0 1996 Standards (not survey data) Urban Urban’ City Industrial Suburban -5

-10

-15

-20

-25

Equivalent Annoyance Units. The number of decibels (24 h L,, dB(A)) which would

cause an equivalent amount of annoyance. b N = Number of respondents. ‘Predominantly residential urban, but with some light industry or main road. d Mixed areas are between the urban (mostly residential) and predominantly industrial e Not enough data to calculate values.

categories.

destroyed by poor quality ambient noise measurements (10 min noise samples) was considered but rejected for three reasons: no relationship was found in the better quality ambient noise measurement areas; the measurement of ambient noise levels is related to road traffic noise annoyance; and an instrumental variable based on predicted road traffic noise levels showed no relationship. (The first two of these analyses are reported in more detail in the ISVR Technical Report [16].) The British Survey did discover the relationship which Aubree [5] has reported: e.g., that the relative ranking of the railway and other noise annoyance is related to the relative noise levels from the railway and other noise source. This does not conflict with the major findings: the absolute level of annoyance with railway noise itself is not affected by the presence of other noises. There is ho support for an ambient level correction to a railway noise index.

RAILWAY

NOISE

REACTIONS

IN

GREAT

BRITAIN

199

WEIGHTINGS 4.5. SPECTRAL FREQUENCY While most surface transportation noise regulations are based on the A-weighted frequency spectrum, there is considerable discussion about the possible utility of other weightings. The railway survey’s linear analogue recordings from the field were later analyzed with A, B, C, D and PNL weightings. While the different frequency weightings are, of course, highly correlated, the indices are not perfect linear functions of one another. For example, the standard deviation of the difference between L,, dB(A) and Lecl dB(Linear) is 5 dB. Since L,, best represents the number effect, L,, is initially examined for different frequency weightings. The first four columns of Table 5 compare A-, Linear-, D- and B-weighted L,, for the Summed Annoyance Index (Panel A) and a “very” annoyed dichotomy (Panel B). Of the four weightings, the Linear L,, is slightly more highly correlated with annoyance and the A-weighting is the least highly correlated with annoyance. The other weightings all give somewha; greater weightings to the lower frequencies than does the A-weighting. The differences in correlations with annoyance are small. The significance levels show that the differences between Linear-, B- and D-weightings are inconsequential, but that though the A-weighting’s inferiority can never be established at the conventional p < 0.05 level, it does sometimes exceed a p < 0.10 level. More extensive analyses in the ISVR Technical Report 102 [16, Table 3.91 show that the relative explanatory powers of the different frequency weightings are unchanged when cubic equations are used and when the frequency weightings are applied to any of three different measures of peak noise level. The data have not provided a conclusive, powerful test of the relative value of A and other weightings. The situation will become more complex in section 6.3, where the weightings are found to be closely related to a traction type difference. The A-weighting will continue to be used in the remainder of this analysis. In short, the evidence is not strong enough to reject the A-weighting but it does suggest that other weightings should continue to be explored.

4.6.

COMPARISONS

OF ESTABLISHED

INDICES

We now turn away from an analysis in which we seek to understand human reactions to an analysis in which one simply compares the relative explanatory power of already accepted alternative noise indices. Table 5 compares the relative explanatory power of Leq, Ldn, CNEL, NNI, CNR and NEF. The commonly used 24 h L,, dB(A) is more highly related to annoyance than are any of the other noise indices, the only exception being that the NEF is marginally more highly correlated with the Summed Annoyance Index. In the last two columns of Table 5 one final piece of evidence is provided to show that the restraints imposed by L,, on the form (logarithmic) and weight (k = 10) given to the number variable are not severely reducing the correlations. These correlations based on loglo number (but allowing for this data set’s optimal number weighting) and number of events represented in a cubic form are both less highly related to annoyance than is L,,. While the superiority of L,, over the other indices is consistent in this set of data, the low statistical significance of the differences against both L,,(A) and L,,(Linear) are evident from Table 5. The data sugest that L,,(A) is more highly related with annoyance than any of the other established noise indices (with the possible exception of NEF) but that the difference cannot be specified precisely enough with these data to reject the other indices.

0.439

Quadratic

0,464

0.449

0.185

Quadratic

5

0.216

0.205

0.4441 >dB(A) 0.457* >dB(A)

Index

o-433

0.431

0.190

0.185 0.195

0.188 0.181

0.180

on verbal rating scale

0.444: >dB(A)h 0-453

Lcin

correlation

dB(B)

Multiple

0.176

0,173

O-429

0.424

CNEL

coefficients

Other

0.147”
0.381*
NNI

standard

0.163*
0.412*
CNl?

indices

and tests for differences

indicesh

0.176*
O-45.5? >dB(A)

0.436

NEF

between

0.164’i
0.429’
0.423

log N

Average

Optimal

0.176

0.169

0.430

0.422

N+N2+N3

and

indices peak dB(A)

number

\

\

a Only the 1351 interviews with valid data on all frequency weightings and on the verbal rating scale are included in this table. All noise level indices are derived from the computer analysis of the analogue tape recordings. b Each correlation has been tested for its difference from the L,, dB(A) and L,, dB(LIN) weightings. Where there is a significant difference the weighting (A) or (LIN) with which it significantly differs is indicated. * Difference significant at p ~0.05. t Difference significant at p < 0.10.

0.181

Linear

dB(D) Annoyance

scale is “very annoyed”

O-432

Panel B: Annoyance

dB(LIN)

24 h L,, weightings

scale is Summed

dB(A)

Linear

Panel A: Annoyance

Noise level represented in linear or quadratic equation

TABLE

Comparisons of 11 noise indices’ correlations with two annoyance scales”

$

E

0

$ 5

6 VJ

a

2

RAILWAY

NOISE

REACTIONS

IN GREAT

5. EFFECTS OF RAILWAY OPERATIONS CHARACTERISTICS ON ANNOYANCE

BRITAIN

AND OTHER RAILWAY WITH TRAIN NOISE

In this section we consider the possibility that annoyance with noise from trains may be greater than would be expected from the noise level alone under types of less desirable railway environmental conditions. The conditions are grouped under three headings in Table 6: types of railway route, characteristics operating conditions and proximity to railway. 5.1.

ROUTE

201

passing certain loosely of local

TYPES

Four route-type characteristics have been examined. The night-time and traffic density variables are included in Table 6 for purposes of comparison, though they were discussed in earlier sections. For both of these variables, it is again clear that the variable has an unimportant effect on annoyance after the effects of 24 h L,, dB(A) have been removed. The results for the traction type analysis in Table 6 show that people on routes with overhead electrification are the equivalent of about 10 dB less annoyed than are people on the third rail electrified or exclusively diesel routes. This effect is important enough for all of section 6 to be devoted to its analysis. 5.1.1. Type of service

When respondents were asked on open ended interview questions to describe types of trains which were most bothersome, freight tranins were explicitly mentioned about three times more often than passenger trains. On a question about particular types of railway noises which are most annoying “banging and clanging” was most often mentioned. Though the answers to these questions show that respondents are more likely to single out freight traffic as a problem, other evidence is needed to determine whether reactions to railway noise are actually modified by differing amounts of freight traffic. 5.1.2. Regression technique analysis: the type of service example The analysis continues to be focused on the statistics of regression rather than on the statistics of correlation. The focus is thus on the change in annoyance (expressed in Decibel Equivalent Annoyance Units) which can be associated with the effects of other variables. The regression statistics in Tables 6, 7 and similar tables in section 7 present a large amount of information on over 50 variables. In this section the ways in which that information can be extracted for one variable, the service type, are illustrated. After reading this section, readers who have a particular interest in one of the other variables will be able to apply the same techniques to that variable, even though the information has not been presented verbally in the text. In Column 3 of Table 6, the results of the analysis of the annoyance residuals (the technique was described in section 4.4) make it possible to examine the annoyance in specific service-type categories after the effects of noise level are removed but before any assumptions are made about the form of the service-type variable’s effect. For service-type there is clearly not the linear relationship which originally had been hypothesized. Any post hoc non-linear relation may simply capitalize on random sampling variability; thus the originally hypothesized linear scoring of service-type (percentage of the traffic which is freight) is analyzed beginning in Column 4. The best estimation of this variable’s impact on overall annoyance is the partial regression coefficient (Column 6), which shows that a 1% increase in the freight traffic is associated with a change in annoyance which is equivalent to O-058 dB.

Traffic density

Night usage

Service (freight usage)

Traction (electrification)

Part A: route types

(1)

(Information comes from railway records or the acousticianobservers)

Characteristic

dB(EAU) (N)

dB(EAU) W)

dB(EAU) (N)

dB(EAU) (N)

(2)

Contents of row

associated

with railway

TABLE

6

characteristics

0.7 (501)

10-99

2.0 (173)

<4%

-3.3 (261) 0.1 (371)

-1.0 (382)

-2.1 (425)

Number loo-199

-1.0 (440) -3.8 (288)

;;

0.5 (234)

-0.4 (194)

of trains per 24 h day 200-299 300-549

2.1 (458)

at night 30-39%

$4;)

of trains which are freight lo-19% 20-39% 40-59%

Percentage of movements 4-9% lo-19% 20-29%

(:y26)

.

Percentage 4-9%

(&

-6.8 (332)

<4%

Third-rail electrification

Overhead electrification

550+

-0.1 (41)

40-53%

(12063)

80-100%

(725183

Diesel only

noise level

loglrr number (1.0-2.6)

% of trains at night (O-25)

“10of freight (O-50)

0 = Overhead 1 = Other (0, -1)

Coding of variable (90% range) (4)

1 dB

1 dB

3dB

10 dB

Approx. dB effect for 90% range (5)

~-0.84 13.09)

0,030 (0.082)

0.058 (0.045)

-9.58** (2.21)

Partial Regression Coeff. B,. (G\ ) (6)

N.S.

N.S.

N.S.

cl.64

> ?

P m

i:

BIIOB, (7)

Y

Interaction (I) Test Statistic

Control for noise by including railway characteristic in a regression equation with L,, and L&

controlled for railway

Control for noise through analysis of residuals Average residual annoyance (Annoyance is measured in the decibel equivalent of the annoyance scores on all columns of the table) (3)

Annoyance

(source: records)

Rate of train noise onset

Speed (source: acousticians measured or observed)

Maintenance maintenance

Non-noise impact (acoustician) observation)

Ancillary operation noises (sitting trains shunting, horns, etc)

Rhythmic noise from wheels crossing joints in rails

dB(EAU) 0’)

dB(EAU) (N)

dB(EAU) (W

dB(EAU) (N)

dB(EAU) (N)

dB(EAU) (N)

Part B: local operating characteristics

-0.6 (462)

0.44 (404)

-0.26 (348)

-0.14 (429)

Highest speed (km/h) 43-74 75-104 105-144

-2.11 (99)

145-200

0.02 (656)

0.12 (383)

-2.02 (236)

2.35 (178)

Average of measured trains’ rise rates (m/s) >4~6 >6 <2 ~2~4

(173)

1.05

25-42

0.89 (371)

-3.46 (133)

-1.76 (360)

4.74 (238)

1.79 (114)

-2.78 (222)

High

operations

Definitely noticeable

heard”

(:O:)

Index of frequency of maintenance Low

-2.0 (726)

is

(Z)

Some ancillary noise is: “Barely” heard “Definitely

-0.7 (383)

rated rhythmic noise from joints as: “Slight” “Very marked”

Fumes, dust, dirt, vibration Slightly noticeable Not noticed

-2.3 (651)

Not heard

-1.6 (715)

Acoustician None

(O-7)

m/s

km/h (30-140)

From 1 to 6 with 6 high (l-6)

O=Not 1 = Other (0-l)

O=No, barely 1 = Definite (O-1)

0 = None, slight, 1 = Marked (O-1)

2dB

1 dB

1 dB

5 dB

7 dB

6dB

0.26 (0.48)

-0.01 (0.02)

-0.21 (1.17)

4.95** (1.69)

6.80** (2.02)

6.10** (2.44)

N.S.

N.S.

N.S.

N.S.

N.S.

Distance

Visibility

Distance

to station

to track

Part C: Railway proximity

Duration

(1)

(Information comes from railway records or the acousticianobservers)

Characteristic

dB(EAU) (N)

dB(EAU) 0’)

dB(EAU) (N)

dB(EAU) 0’)

(2)

Contents of row

6 (cont.)

-2.61 (29)

Driving
-2.53 (356)

0.07 (322)

0.76 (359)

distance to nearest railway 100-499 500-999

-0.38 (322)

-0.3 1 (702)

station (m) SlOOO

1.34 (765)

is

-1.59 (62)

2200

6.43 (108)

aspect (train, bldg, property) Clearly Barely visible visible

-2.53 (134)

-2.21 (353)

2.87 (454)

-3.16 (205)

from tracks to house (m) SO-99 100-149150-199

2.25 (145)

Distance 25-49

-0.14 (308)

of day (24 h) could hear trains >3% 2% 1%

Most visible railway Not visible

2.42 (243)

<25

-1.10 (892)

Percentage < 1%

Control for noise through analysis of residuals Average residual annoyance (Annoyance is measured in the decibel equivalent of the annoyance scores in all columns of the table) (3)

TABLE

Distance in km (0*02-7.0)

1 = Clearly visible 0 = Else (O-I)

metres (l-2.2)

log10

Percent (O-3)

Coding of variable (90% range) (4)

1 dB

4dB

14 dB

4dB

Approx. dB effect for 90% range (5)

-0.0 1 (0.49)

3.69* (1.72)

-11*79** (2.84)

1.21 (1.13)

Partial Regression Coeff. B, ((+Rv1 (6)

N.S.

N.S.

N.S.

2*54*

(7)

B,lUB,

Interaction (Z) Test Statistic

Control for noise by including railway characteristic in a regression equation with L,, and Ls,

RAILWAY

NOISE

REACTIONS

IN GREAT

BRITAIN

205

Column 5 provides a much rougher, but more readily scanned indicator of a variable’s effect: the increase in noise annoyance (expressed in Decibel Equivalent Annoyance Units) associated with the observed range of the variable. (The range is defined in terms of the 90% range in the variable’s value in order to help guard against extrapolating beyond the available data.) For the service-type variable the 90% range (from 0% to 50% freight) increases annoyance by about the equivalent of 3 dB (50x0.058 = 2.9). Service-type is thus estimated to have a rather small effect on annoyance. A conceptually quite separate issue is whether the estimated effect of the variable could have arisen from chance variations in the sampling of individuals’ responses. The statistical significance of the findings is indicated by both the standard deviation of the partial regression coefficient qBV for variable V and, for rapid scanning, by “*‘s” for three conventional significance levels. The service-type partial regression coefficient of O-058 with a standard deviation of 0.045 is thus found to not be statistically significant at even the p < 0.05 level. Noise level/third variable interaction effects (i.e., the possibility that the variable’s influence changes with noise level), are tested for in Column 7. The test is to determine whether the partial regression coefficient BLxV for a multiplicative term (noise level multiplied by, in this case, service-type) is significant in a regression equation which also includes noise level and the variable. The test statistic used as an indicator is the ratio of the partial regression coefficient for the multiplicative term (BLxV) divided by its variance (oBLXV). (To reduce the amount of computing when using the pseudo-replication programs exact values of this ratio were calculated only when simple random sampling estimates indicated that BLxv/~s~xv was greater than 164.) Statistical significance levels are again indicated by “*” or “N.S.” (Not Significant). For the service-type variable, interaction effects were also examined visually with a graph of annoyance by L,, within three percentages of freight groups. Again there was no evidence for interaction effects. There was no strong a priori theory to suggest that the percentage freight must be linearly related to annoyance as is assumed in the last half of Table 6. In fact the best, admittedly post hoc, information which the data provide about the service-type suggests a different coding, one which is used in Table 7. Table 7 provides detailed information about the effect of all variables after they are controlled for the effects of other variables in multiple regression equations. Part A of the table repeats the partial regression coefficient for the variable from Table 6 (controlled only for noise level). (NOTE: Only for the service-type variable was there a change in the coding such that the partial regression coefficients in Tables 6 and 7 differ.) By reading down a column it is possible to determine whether the introduction of other variables has weakened or strengthened a particular variable’s effect. For the service-type variable, the introduction of additional variables has little effect on its coefficients. It is also still statistically significant. Part B of Table 7 attempts to better control for noise levels by using not only the measured noise levels but also the noise levels predicted with a technique in which one uses topographical information about the site and train operations [17, Walker 19771. The addition of the predicted noise levels does not lessen the effect of the service-type variable. The effect of the type of service is shared to some extent with the other variables, but the partial regression coefficient always remains great enough to be potentially important (given the range of the scores from 1 to 3, the partial regression coefficient in line 7 of 3.20 Decibel Equivalent Annoyance Units gives a range of effects of more than the equivalent of 6 dB). The service-type effect also remains statistically significant.

R2

0.18 (for L,

LL)

0.25

0.23 0.24

7

8 9

6.80** (R’=0.20)

l= Definite 0 = Else

routes.

The value of

4.74% 4.66*

4.32*** 4*69***

electric

3.19

4.36 5.06*

5.12**

-0.04 0.55

2.63

2.82 2.01

3.89*

4*95** (R’=0.19)

1 = Some 0 = None

-9.44* -3.33

-6.35

-11.79** (R”=0.21)

metres)

mhl

R' for l.,,,,, L&‘,, L,,,,. I~&, is R' = 0.22.

3.24 2.98

2.66

5.02* 4.30

5.73**

noise levels (L,, + L& + Leq,+ L&J

6.10** (R’=0.19)

3,20**

3.43** 3.69***

5.02***

and predicted

4.03** (R’= 0.19)

noise level (L,, + L&)

variablesh

L,, LZq L‘l, LZ L,,, Z,, Leq,, LL, (separate o/head electric)’ L., G,, L,,,, L& (separate o/head electric) Lq, L:q Leq, L$, LID, LS,,

for indicated

LZq,

for both measured

only for measured

1 = Marked 0 = Other

1 = O-3% freight 2 = 4-39% freight 3 = 40-100% freight

Distance to track

(not standardized)

Non-noise RW impact

coefficients

Ancillary RW noise

regression

Rhythmic noise

Partial

Service-type”

I

“,Service type was coded differently in table 6. In Part C each line represents a single multiple regression equation. kL,,, = L,, for overhead electric routes. L,,,, = L,, for non-overhead

0.21 0.23 0.22

controlled

Part C: Characteristic

4 :

L,, LZq, L,,

controlled

L,, LZq

controlled

Noise level is controlled by inclusion in regression of: L,,= 24 h L,,dB(A), or L,,,= predicted value of L,,,or L,,, = overhead electric route Lq, or L,,"= non-overhead electric L,,

0.20 (for

3

Part B: Characteristic

1 2

Part A: Characteristic

Row

Squared multiple correlation coefficient,

7

Railway characteristics’ effects controlled in multiple regression analyses (dependent variable is Summed Annoyance Index expressed in Decibel Equivalent Annoyance

TABLE

2.35

3.69* (R’=0.19)

Visibility of RW l= Clearly visible, 0 = Other

for:

Units)

-0.09

1.21 (R*=0.18)

% of day trains audible

Duration

RAILWAY

NOISE

REACTIONS

IN GREAT

207

BRITAIN

Type of service does seem to have an effect which is not greatly weakened by the introduction of third variables. It must be remembered, however, that the strength of this effect is dependent on the post hoc coding of the form of the effect. Neither the linear nor logarithmic representations of percentage freight traffic is significantly related to annoyance. If, however, there is actually this levelling off of annoyance (or possibly even a decrease in annoyance) with very high proportions of freight traffic then servicetype does affect annoyance. 5.2. LOCAL OPERATING CHARACTERISTICS The evidence in Table 6 suggests that four local operating characteristics (maintenance work, train speed, rise rate, duration) do not increase annoyance directly beyond any effects they may have on noise level. Only the duration effect interacts with noise level. A graphical analysis showed that longer durations increased annoyance above 55L,,. The duration effect is not further considered because, as can be seen in Table 7 for the additive model, the duration effect completely disappears when predicted noise levels are introduced. Thus it seems likely that this duration measure may do little more than compensate for errors in measurements. The three remaining local operation variables (rhythmic rail-joint noise, ancillary operation noises, and non-noise nuisances) all have statistically significant and substantively important effects (the equivalent of 5-7 dB) when they are controlled for only noise level in Table 6. Their effects are only slightly reduced but still statistically significant when the predicted noise level is introduced in Part B of Table 7. The effects of the three variables are not, however, independent of each other. In Table 7, when the three variables are simultaneously controlled for each other, their effects are reduced (line 4). When the freight service and the traction type variables are also added, the three local characteristic effects are reduced by more than half and are no longer statistically significant. Though no single effect remains significant the pattern of relationships does suggest that the combined effects of these other unfavourable environmental aspects of the railway may increase annoyance. 5.3. RAILWAY PROXIMITY Being close to railway facilities or the railway line itself might be thought to mediate the perceived impact of railway noise. The convenience of having a station nearby (Table 6, Part C) does not however reduce negative reactions to the noise significantly. Being near to the railway tracks is associated with a considerable increase in annoyance when only the measured noise level is controlled for in Table 6. There is more annoyance when the railway is visible (-3.69 dB(EAU)) or nearby (-11.79 dB(EAU) for a lo-fold increase in distance). These variables are, however, just the types of variables which are so closely related to noise level that their observed effects could be due to their correlations with actual noise levels in instances where the measured noise data contain errors. When the visibility and distance variables are controlled in Table 7 for both predicted and measured levels, the partial regression coefficients are substantially reduced and are no longer statistically significant. The addition of the local operation variables further weakens the distance effect, thus again suggesting that it is the correlation of distance with railway environmental effects and not distance itself which was responsible for the originally large distance effect. 6. THE EFFECT

OF TRACTION

TYPE

ON RAILWAY

NOISE

ANNOYANCE

The three types of traction available on the British Railway System differ from each other in several ways. Table 8 shows that although 20% of the route miles are electrified,

208

J. M.

FIELDS AND J. G. WALKER TABLE

8

Residential exposure to three types of traction

Traction type Electric: overhead Electric: third-rail Diesel Total

Percentage of route mileage

Percentage of track side land within 200 m which is residential

Percentage of population above each noise level r z=60 L,,

\ a65 L,,

270 L,,

Number of interviews

10

16

20

23

27

332

10

21

30

35

44

323

80

63

50

42

29

798

100

100

100

100

1453

100

they contain over half of the population exposed to high noise levels. This is chiefly because electrification is most easily justified in the densely settled areas where there are many customers. Diesel trains run on all routes; even on electrified routes they make up between 10% and 60% of the traffic. The third rail electrified routes (with a live third rail on the ground) are almost entirely in the southern part of the country. They were established before the overhead electrified routes which draw their power from a wire suspended above the train. Diesel trains at low speeds have a peak noise level for the locomotive which is clearly above the rest of the passby. Diesel noise is more impulsive and has more low frequency content. The noise level from the diesel locomotive varies depending upon whether or not it is under power. The traction types differ from one another in a variety of other respects which will be examined in the course of this discussion. 6.1. DIFFERENCES IN REACTIONS In Figure 10, overhead electrified routes are considerably less annoying than either of the other two types above 45L,,. The relationship is summarized above 45L,, by linear regression equations in Figure 11 (non-linear relations give virtually.the same estimates). The differences in reactions can then either be quantified in terms of the difference in annoyance scores at a particular noise level or the difference in decibels at a particular annoyance level (Figure 11). For the Summed Annoyance Index, the overhead-diesel reaction difference is the equivalent of approximately 13-14 dB at high noise levels (Tables 9 and 11). The third rail-overhead difference is the equivalent of about 10 dB. The differences in the slopes of the three lines are not statistically significant at even the p = 0.20 level. The differences in reactions to the overhead electrified and the other two route types are significant beyond the O-02 level (e.g., at 6OL,, in the first line in Table 11, the differences in predicted scores of 1.60 and 1.26 are significant beyond p ~0.02). The differences in the reactions to third-rail electric and diesel routes never obtain even a p ~0.20 level. The differences in reactions are found for all 13 annoyance measures in Table 9. (The linear regression equations in Table 9 are calculated only on the data above 55 dB since some questions showed distinct curvilinear trends between 45 and 55L,,.) All but the first three measures in Table 9 are expressed in percentages; thus it is possible to compare reactions easily, either in terms of percentage differences in reactions (Columns 8 to 13) or decibel gaps between equal reactions (Columns 14

RAILWAY

NOISE

REACTIONS

IN tiREAT

BRITAIN

209

questions* 9a* 't 6-

24 h Leg (dB(A)l Diesel mterwews Nz 70 3rd~roll mtervlews N= 8 Overhead mterwews N= 17

37 21 0

114 164 III 112 7060 8 3048428861 22 37 26 33 66 54

38 27 17 0 54 38

Figure 10. Effect of traction type on annoyance. -, Diesel; - - - -, overhead electric; - - --, third-rail electric. *This scale is very similar to the Summed Annoyance Index except that this scale scores people as less than “not annoyed” if they report that they cannot “hear” the railway.

40

50

60

24 h L,

Figure 11. Effect of traction type electric. *See note for Figure 10.

on annoyance.

-,

70

(dB(A))

Diesel;

---,

overhead

electric;

--,

third-rail

and 15). The third rail estimates are about half as precise, probably because of the lesser variance in noise levels (note the number of interviews below Figure 10). Even if only the more reliable overhead/diesel comparison is focused upon there are still differences in the estimates provided by different questions. Questions with lower partial regression coefficients (shallower slopes) in Columns 3, 5 and 7, estimate smaller traction effects on percentages annoyed but greater traction type effects on the decibel gap (e.g., “very” annoyed and the three sleep interference questions). The two very specifically phrased speech interference questions have the lowest estimates of the decibel gap and steepest slopes but this pattern does not carry over to the two more conventionally phrased

- 108.8 -34.7

2.21 1.41

0.90

0.37

-21.2

-9.1

“Bother, disturb, or annoy at all”

“Very”

annoyed

giving the listed response)

scales (scores are percentage

Part B: Dichotomous

-1.68

0.095

0.064

-78.2

-109.1

-3.21

0.61

1.99

0.059

0.139

-1.19

-4.35

0.147

Score on Guttman activity interference scale (range 1 to 7) used in Heathrow Survey

-3.53

0.105

0.160

-0.45

Summed index

Score on 5 item general annoyance indexb

-6.77

0.180

Slope (5)

C

13.5 4.3

22.6 11.5

9.2

11.8

12.3

15.7

0.92

0.82

0.57

0.78

1.38

1.50

1.30

1.84

1.69

3rd minus overhead (11)

1.70

1.49

2.23

Diesel minus overhead (10)

70 L,

8.0

6.4

0.85

1.33

1.43

16.3

16.9

1.10

1.42

1.79

3rd minus overhead (13)

7.5 L, Diesel minus overhead (12)

Difference between overhead and other traction response 60 L,, \_W, Overhead Diesel 3rd minus minus Interoverovercept Slope head head (6) (7) (8) (9)

(~5.5 L,,)”

0.106

-6.48

indices (scores are index scores)

Intercept (4)

3rd-rail

equations

-1.32

annoyance

Part A: Annoyance

Response measure (1)

Regression

Diesel -Fe Intercept Slope (2) (3)

I

9

Traction type effects for different measures of response to noise

TABLE

21 dB

7dB

13 dB

13 dB

13 dB

12 dB

8dB

12dB

10dB

10dB

Difference in noise level for equal response (Overhead L,, = 75) Overhead minus ,’ Diesel 3rd rail (15) (14)

+ E p

E

b

LI

a

7

F U ;

k 2

LI

1.91

1.95

2.13

0.68

0.27

0.38

-74.0

-75.4

-73.6

-16.4

-3.5

-6.0

Trains ever made “Stop talking, pause, or speak louder” in home

“Interfere listening to radio or TV”

Trains ever made it hard to hear something on TV

Trains ever wake up

Trains ever disturb sleep in other ways

Spontaneously volunteer railway disturbs sleep

“RIIS index was used in eariier

-54.5

1.16

0.18

l-03

-40.3 -4.7

2.93

2.80

2.06

2.80

1.63

4.04

-127.8

-132.3

-87.1

-146.2

--76.6

-222.4

publications.

It is similar

electric,

0.56

0.04

0.60

2.51

1.61

2.87

1.58

1.56

1.63

Annoyance

208 are third-rail

-28.3

-6.2

-26.9

-113.1

-68.9

-149.1

-79.4

-87.2

-87.9

to the Summed

55 L,,, 235 are overhead

1.72

-73.0

“Interfere conversation”

at or above

0.99

-38.4

Say railway noise is biggest noise nuisance in neighbourhood

‘Of the 745 interviews

0.91

-18.3

Spontaneously mention railway noise as thing “particularly dislike about living in this area”

9.9

9.5

5.6

16.1

12.7

17.2

8.0

16,3

8.5

19.2

18.9

-0.7

19.0

16.6

25.6

1.2

24.2

15.4

46.5

who report

8.6

6.6

16.5

10.8

18.9

3.2

17.0

5.6

15.6

for peop!e

15.9

-1.4

16.9

14.5

19.7

5.3

18.9

15.1

34.4

for its lower scoring

302 are diesel. Index except

electric,

11.4

-2.8

12.5

15.3 3.4

10.3

7.8

13.4

6.0

14.5

10.3

16.6

13.8

17.6

14.9

14.3

26.4

“nnt hearing

23 dB

25 dB

24 dB

5 dB

10dB

2dB

1OdB

6dB

17dB

the ratlway”

16dB

-4 dB

18 dB

6dB

9dB

1dB

9dB

9dB

11 dB

t3 L +

10

-3.63

-3.69

Correction lb (when three separate instrumental variables)

Correction 2h (when single instrumental variable correction)

0.145

0.147

0.132

Slope

-3.26

-5.05

-3.99

Intercept

0.130

0.163

0.142

Slope

3rd-rail (N = 284)

equations

-4.20

-4.04

-3.57

Intercept

0.132

0.123

0.114

Slope

Overhead W = 283)

(345 L,,)

1.30

1.86

1.63

head

Dieseiover-

em

“These uncorrected values arc slightly different from those appearing elsewhere because no;-acoustic noise prediction variables. For correction 2 one equation to predict measured noise level from the non-acoustic procedure was carried out independently in each electrification group.

-3.07

Intercept

No correction” (only areas with valid noise prediction variables)

Noise measurement adjustment

Diesel (A’ = 565) W-Y

Regression

0.82

1.38

1.28

head

3rdover-

variables

70 L,

0.80

1.79

1.56

head

3rdover-

1.50

2.22

1.91

overhead

Diesel-

for the entire

\

1OdB

6dB

12dB

12dB

14dB

15dB

3rd-rail

Overhead m Diesel

minus

Difference in noise level at annoyance score for overhead noise level 0 75 L,,

Index)

For correction

1 this estimation

I 245 L,,) with valid data on all the

0.78

1.99

3rdoverhead ____ 1.70

75 L,

sample.

on only the respondents

1.43

2.10

1.81

head

Dieselover-

was solved

they are based

60 L,

Difference between overhead and other traction type annoyance score at:

Traction type effects after adjusting for random errors in noise measurements (dependent tiariable is the Summed Annoyance

TABLE

k ;a

z

$ I0

E

i: ?I E

.-

td

2

RAILWAY

NOISE

REACTIONS

IN GREAT

BRITAIN

213

speech interference questions. In the absence of other strong patterns, the single best estimate for the overhead-diesel annoyance gap is about 13 dB. By summarizing the data here with linear rather than curvilinear relationships it is much easier to determine whether there are changes in slopes between questions (Table 9) or when third variables are introduced (Table 11). When the responses to the Summed Annoyance Indices were also summarized with curvilinear relationships over the entire sample [16, Fields and Walker 19781 virtually identical conclusions were reached. The possibility that noise level measurement errors may affect these findings is examined with an instrumental variable technique using two-stage least squares regression in Table 10. (The technique is described by Johnston [34].) When the possibility of different degrees of accuracy for different traction types is allowed for in the second line of Table 10 the decibel equivalent values remain virtually unchanged and the annoyance score gaps widen. If the entire sample is assumed to be subject to the same degree of noise measurement accuracy then the lowest line in Table 10 shows that all differences are considerably reduced. Given the greater difficulties inherent in sampling the more variable diesel noise, the independent error assumption would appear to be more valid. CONDITIONS AND AREA CONDITIONS EFFECTS 6.2. OPERATING The heavier usage and higher speeds found on most electrified routes might be expected to create generally more favourable noise environments (after railway L,, is controlled for) because there would be expected to be more continuously welded rail (less impulsive noise), lower proportions of freight traffic, higher ambient noise levels (more likely to be in urban areas) and a greater distance from the railway for the same noise level (because of higher speeds). If these variables explained the annoyance, then the overhead electrification effect might be concluded to be spurious. Each of these variables is introduced into a multiple regression equation in which the three traction types and their noise levels are represented by dummy variables. However, when the results are examined in Part B of Table 11, there is no evidence that the traction type difference is any less after the variables were controlled for than before they were introduced in Part A. Other analyses could find no evidence that the third-rail estimates were being distorted by the fact that London Transport (subway) trains also operated on some third-rail routes. There is no evidence that the lower overhead electric reactions could be explained by the distinction between the suburban, local service overhead routes and the mainline, inter-city overhead routes. Reactions might also be thought to be altered by the electrified routes’ higher speeds, greater numbers of trains, Southern Region location (for third-rail route) or greater visibility (for the overhead electric wires). In Table 11 these variables again have no effect, except for the Southern Region control which suggests that the third-rail-overhead differences in reactions are even greater than they were estimated to be before being controlled.

6.3. UNDERSTANDING TRACTION TYPE DIFFERENCES The analyses all suggest that there are real differences in reactions to different traction types. How are these differences to be explained, especially since the two types of electrified routes are reacted to so differently? Several possible explanations have been examined and rejected. Third-rail electrified routes are not viewed as being any more dangerous by residents (even residents with children) than are other routes in spite of the live third-rail. A careful analysis of the annoyance residuals could find no evidence that the heightened third-rail reaction could be explained by generally more annoyed responses in the South (the region in which

11

0.13 0.13 0.13 0.13 0.11 0.14

C: Possible confounding variables Speed Number of trains Region (South = 1; Else = 0) Visibility

Part 8. 9. 10. 11.

Part D: Possible explanatory variables 12. Bothered by standing trains 13. Uneven noise levelsd 0.11 0.14

0.14 0.13 0.14 0.13

0.14 0.14 0.14 0.14 0.14 0.11

0.14

-

Third-rail I (3)

0.09 0.12

0.11 0.11 0.11 0.10

0.11 0.11 0.11 0.11 0.11 0.07

0.11

Overhead (4)

0.96 1.60

1.39 1.45 1.40 1.33

1.33 1.23 1.15 1.38 1.45 1.07

1.38

0.83 1.25

1.03 0.99 1.94 0.94

0.78 1.04 1.08 0.99 1.02 0.75

1.00

L,, = 50 -We D-E0 E3-EO (6’) (5)

l-15 1.80

1.61 1.63 1.60 1.56

1.51 1.53 1.44 1.59 1.67 1.42

1.60

D-E0 (7)

1.00 1.50

1.30 1.20 2.20 1.21

1.04 1.36 1.37 1.25 1.35 1.23

1.26

E3-EO (8)

L,, = 60

Index) (only

143 1.90

1.95 1.89 1.90 1.91

1.79 1.98 1.88 1.92 2.00 1.95

1.93

dB dB dB dB 13dB 14dB

15 15 14 15

14dB 14dB 14 dB 14dB 15dB 18dB

14dB

12dB 12dB

12dB 1ldB 19dB 12dB

10dB 13dB 13dB 12dB 13dB 15dB

12dB

with the third variable.

1.25 1.62

1.71 1.52 2.59 1.61

1.44 1.85 1.81 1.65 1.84 1.68

1.66

Difference in noise level for \ equal annoyance (Overhead L,, = 75 L,, = 75) D-E0 E3-EO e (12) (11) (9) (10)

at

a Variables are scored as described in Tables 6. 13 or 14. ‘This service type variable is coded: 1 = O-3% freight; 2 =4-39X freight, 3 = 40-100% freight. ‘These come from the regression of intercept and slope dummy variables for each traction type when they are included in a single equation d Uneven noise levels = peak from noisiest measured train -average peak level of trains. ’ This estimate is slightly different from the one in Table 8 because this table includes all respondents at or above 45 L,,.

0.13 0.14 0.14 0.13 0.13 0.11

Part B: Chailenges to traction type effects 2. Rhythmic noise from wheels crossing joints 3. Service type (% freight) 4. Service type (three categories)’ 5. Ambient noise 6. Population density (1 = Urban; 0 = Else) 7. Distance from railway (log,,)

Diesel (2)

0.13

I

Part A: No control’

Variable” controlled for: (1)

Partial regression coefficients when controlled for variable in Column 1

Difference in annoyance scores (D - EO = Diesel-overhead) (E3 - EO = 3rd-rail -overhead)

Differences between reactions in traction type areas after controlling for conditions (dependent variable is Summed Annoyance respondents 345 L,, are included; N = 1161)

TABLE

2

$ tJ Z0 < P 2

k

3

3

+

t4 z.

RAILWAY

NOISE

REACTIONS

IN GREAT

215

BRITAIN

third-rail routes are located); people near diesel routes in the South are not any more annoyed than people near diesel routes in other parts of the country. Dust or dirt, or fumes or smells are not any more often noticed along diesel routes (nuisances which people could associate with diesel exhaust) than along electrified routes. People living near overhead routes are less likely to report noticing or being bothered by noise from trains which are standing. The introduction of this control in Table 11 only slightly changes the decibel gap in annoyance reactions but reduces the noise level partial regression coefficients (slopes) as well as the annoyance gap by about 20-30%. While this is consistent with the possibility that standing diesels’ motors are responsible for the different reactions, the fact that the standing train description is an annoyance measure which may not be causally prior to the overall annoyance reaction means that the standing train noise hypothesis cannot be uncritically accepted. The three major obvious acoustical differences between the two traction types are the prominence of the diesel locomotive noise, the relatively unpredictable, uneven and often impulsive noise from diesel trains (depending upon whether or not they are operating under power) and the greater low frequency content of the diesel noise. The uneven, unpredictable nature of the diesel noise has not been carefully quantified acoustically in this study. A somewhat indirect indicator of the variability of the train noise levels, the difference between the logarithmic average of the peak levels and the single highest peak level is introduced as a control in Table 11. This does not reduce the diesel-overhead electric difference. To examine the effect of differences in spectral content, noise levels are expressed in dB(Linear) in Figure 12. The differences between the traction types are very considerably reduced.

7-

6-

Linear

Figure 12. Reduced diesel-overhead electric; A---A, third-rai! electric.

effect

weighted

for linear

24

h Leq

weighting.

O----O,

Diesel;

W.

-.

?? , overhead

Table 12 presents the numerical estimate of the effects of the different weightings on the diesel-electric differences. First it should be noted that just changing from the primary to the computer analysis of the A-weighted levels decreases the diesel-overhead traction gap at low and moderate levels, but while considerably reducing it (by 5 dB) at the highest levels still leaves a large gap (9 dB). It is the Linear-weighting which goes on to

216

J. M.

FIELDS AND J. G. WALKER TABLE

12

Differences in reactions to traction types for spectral frequency weightings of 24 h L,, Regression Weighting (sample used

in analysis)

equations

for each traction

Diesel

Third-rail

type Overhead

YPI R2

Intercept

Slope

Intercept

Slope

Intercept

Slope

0.17

-3.24

0.135

-3.85

0.139

-3.53

0.113

L,, dB(A) (a46.5 dB(A)) (N= 1155)

0.17

-3.55

0.137

-4.34

0,144

-5.66

0.148

L,, dB(LIN) (256.5 dB(LIN)) (N = 1146)

0.18

-9.07

0.199

-5.47

0.147

-9.78

0.197

L,, dB(D) (2 52 dB(D)) (N = 1143)

0.17

-5.24

0.153

-4.68

0.140

-6.73

0,154

Primary

noise analysis”

L,, dB(A) (245 dB(A)) (N= 1161) Computer

noise analysis”

a The distinction between the primary and computer in this paper use the primary analysis unless otherwise

analysis is discussed indicated.

in section

2.3.1. A-weighted

tables

reduce the gap to only 4 or 5 dB. The D-weighting has no more effect than the A-weighting. In separate analyses it was found that the Linear-weightfng effect is not eliminated within traction types: separate analyses in reference [16] showed that even within traction type groups, the Linear-weighting explains more of the variance in annoyance than does the A-weighting. While the data do, on the balance, give evidence for a Linear-weighting explanation, the acoustical basis is not at all clear because the puzzling overhead electric-third-rail electric reaction differential remains and throws some doubt on the significance of any acoustical explanation. With the Linear-weighting, the reactions now tend to converge at higher noise levels so that the diesel-overhead electric difference is significant beyond the p ~0.01 level at around 65 dB(LIN) but not above 75 dB(LIN). The percentage of the traffic which is diesel does increase annoyance on the electrified lines by the equivalent of about 5 dB over the O-40% diesel traffic range (p -C0.01). The percentage of diesel traffic does not reduce the overhead-third-rail electric difference. 6.4. SUMMARY OF TRACTION TYPE FINDINGS After carefully examining a variety of methodological issues and the many nonacoustical differences between the three types of routes it has been concluded that people are less annoyed by the noise from overhead electrified routes than by the noise from diesel or third-rail electrified routes. Some limited evidence suggests that this may be partially due to differences in the noise made by standing trains and to acoustical characteristics which are better represented by a linear than an A-weighting. The puzzling

217

RAILWAY NOISE REACTIONS IN GREAT BRITAIN TABLE 12 (cont.) Difference in summed annoyanceb index scores when overhead electric is: (D - EO = Diesel-overhead) (E3 - EO = 3rd-rail-overhead)

Difference in noise levels at annoyance score of -\

fl EO= 3.235

EO = 2.108

EO = 4.948

>FF

r

~~--D-E0

4.948

3.235 E3-EO

D-E0

E:3--EO

12dB

9dB

14 dB

12 dB

1.02

10 dB

7dB

9dB

7dB

0.82

0.54

4dB

7dB

4dB

4 dB

1.41

1.01

9dB

8dB

9dB

7 dB

D-E0

E3-EO

E-E0

E3-EO

D-E0

E3-EO

I .38

1.00

1.60

1.26

1.94

1.63

1.50

1.09

1.41

1.07

1.27

O-80

1.27

0.81

0.98

1.43

1.26

1.42

1.16

-

h These are the overhead electric annoyance scores actually used for the comparisons in Table 11; i.e., the annoyance predicted for overhead electric routes at 24 h L,, dB(A) (primary analysis) for SO, 60, 75 L,,

similarity in reactions for the third-rail electrified routes and diesel routes which could not be explained with the available variables leads to the speculation that there may be a generally more positive reaction toward the more modern overhead electrification programme. There is no firm evidence to explain why the reactions to the routes differ.

7. INDIVIDUAL AND NEIGHBOURHOOD CHARACTERISTICS WHICH MEDIATE ANNOYANCE The enormous variation in individuals’ responses to the same level of environmental noise (Figure 6) leads to a consideration of non-acoustical explanations. Most of the explanations fit into five broad categories: neighbourhood characteristics, housing characteristics, respondent-specific noise exposure, demographic characteristics and personal attitudes. While most previous work has been focused on the last two types of individual characteristics, the first three are of greater potential significance for noise policy.

7.1. THE NEIGHBOURHOOD CONTEXT Individuals experience railway noise as a neighbourhood environmental nuisance within the context of other objective characteristics of the area and the context of individual subjective feelings about the neighbourhood. Three objective characteristics are considered: ambient noise level, section of the country, and quality of neighbourhood. In section 4.4 ambient noise level was shown to be unrelated to railway noise annoyance.

of country

Neighbourhood organization (source: respondent’s self-report)

Region

Visual quality of neighbourhood (source: observers’ ratings)

Part A: neighbourhood

Characteristic (1)

Annoyance

dB(EAU) (N)

dB(EAU) (N)

dB(EAU) (N)

context

Contents of row (2)

Units)

associated

of British vicinity

-0.53 154)

-0.3 1 (889)

Yes, in last year -___ 1.16 (403)

any local

-1.57 (124)

Scotish

0.38 (361)

about

-0.48 (708)

Rail Midlands

done anything problems

Yes, in past

that local groups

1.15 (330)

Region London

-0.41 (923)

of quality and upkeep of houses and gardens Middle High

None known

Know

0.55 (291)

South /West

2.04 (137)

Low

of 5 ratings

and exposure

characteristics

1 = Yes, last 0 = Other yr (O-l)

0 = Other (O-1)

1 = Scotland

1 = High 0 = Other (O-l)

2dB

2dB

1 dB

Approx. decibel effect (90% range) (5)

1.61 (1.37)

-1.77 (3.58)

0.50 (1.65)

(Z’

Partial regression coefficient B,

N.S.

N.S.

N.S.

Interaction (I) test statistic, Brlas, (7)

Control for noise by including the characteristic in a regression equation with L,, and JT.~~

housing

Coding of variable (90% range) (4)

I

with neighbourhood,

13

Average residual annoyance score is given for each category (annoyance is measured in Decibel Equivalent Annoyance Units in all columns of the table) (3)

Control for noise through analysis of residuals

Annoyance

Average

(dB Equivalent

TABLE

~

5

Z k ?

0

!? *

3 -0 i;j E; in

feelings

House

type

Part C: Housing

Non-noise neighbourhood rating index (source: selfreport)

dB(EAU) (N)

dB(EAU) (N)

dB(EAU) (N)

-1.72 (224)

Believe -0.66 (1143)

nothing

2.78 (606)

Fairly

Respondent’s

1.16 !215)

Flats

-6.5 (169)

-1.21 (398)

8.54 (122)

Yes, been complaints

about railway

12.23 (53)

0.33 (21)

0.61 (185)

13.14 (62)

0.64 (509)

unit Semidetached

1.40 (146)

Detached

aspects of neighbourhood Low rating

5.96 (120)

satisfaction with area Don’t Rather Very dissatis. know dissatis.

-1.27 (183)

Don’t know

Type of dwelling Terraced/ Terraced/ middle end

-2.2 (423)

14.32 (83) done anything noise

Average rating of 8 non-noise High rating

(644)

-5.00

Very Satis.

done

Know that neighbourhood

-1.32 (1085)

tried

to get rates (tax) reduced because railway noise? -Tried/ unsuccessful Don’t know Successful

anyone

No

Has

about the neighborhood

dB(EAU) (N)

dB(EAU) (N)

characteristics

Overall satisfaction with neighbourhood (source: self report)

Part B: personal

Neighbourhood railway complaints (source: self-report)

Reduction of taxes due to railway noise (source: self-report)

Flats = 1 Other = 0 (O-l)

Standard deviation units (-2 to 1.5)

Standard deviation units (-2 to 0.8)

1 = Complaints 0 = Other (O-1)

1 = Tried or succeeded 0 = Other (O-1)

2dB

13dB

13 dB

9dB

15 dB

2.45 (5.56)

(0.65)

_3.69***

(0.51)

_4.55***

9.43*** (2.18)

15.47*** (1.79)

N.S.

2.01*

N.S.

N.S.

1.45

type

living

glazing

Outdoor area

Double

Part D: Respondent-specific

House age (observer rated)

Tenure

Characteristic (1)

dB(EAU) (N)

dB(EAU) (N)

exposure

dB(EAU) (N)

dB(EAU) (N)

Contents of row (2)

13 (cont.)

Estimated 1915-44

-0.83 (313)

-8.04 (49)

For heat

1.66 (235)

3

2.22 (30)

15.50 (47)

Reason for double Done bv For RW others noise

2.35 (150)

unit

5.43 (163)

1970+ (2)

0.52 (874)

Owner occupied

1.49 (19)

glazing Other noise

-0.32 (1290)

-0.34 (1306)

No double glazing

owned garden/yard Yes

2.78 (89)

date of construction 1945-59 1960-69 (25) (7)

-0.29 (249)

of dwelling Rent/ private

Does dwelling have own privately No

indicators

-3.18 (552)

Pre-1914 (74)

-5.41 (13)

Type of tenure Rent/govt supported Rent free

Average residual annoyance score is given for each category (annoyance is measured in Decibel Equivalent Annoyance Units in all columns of the table) (3)

Control for noise through analysis of residuals

TABLE

O=Nodbl glazing 1 = Other o-1

l=Yes O=No (O-1)

Years since built (2-74)

Own=1 Other = 0 (O-1)

Coding of variable (90% range) (4)

3 dB

3 dB

8dB

1 dB

Approx. decibel effect (90% range) (5) -

2.53 (2.41)

-2.95 (2.63)

(0.02)

_0.11***

1.31 (1.52)

(UB,) (6)

Partial regression coefficient B,

N.S.

N.S.

N.S.

2.93**

(7)

BIl UB,

Interaction (I) test statistic.

Control for noise by including the characteristic in a regression equation with L,, and Li,

g

RAILWAY

% iz

OCF’ “0,

0 r ,-

; II

/

,

NOISE

REACTIONS

IA-

OPJ 4.4 I-

IN GREAT

BRITAIN

221

222

J.

M. FIELDS

AND

J. G. WALKER

The region of the country was hypothesized to affect annoyance because the climate in the North would be more likely to discourage outdoor activities and opening windows. Table 13, however, shows that any regional effects are small and not statistically significant. The quality of the neighbourhood environment was rated by the acoustician-observer on 16 items covering the general topics of upkeep of streets, extent of trees or green spaces, appearance of housing, neatness of area, fumes in area, presence of retail business, frequency of bus services, and the proximity of stores, bus-stops, parks and open spaces. The relationships between each of these environmental characteristics and railway noise annoyance (controlled for railway noise level) were examined in tables which are not shown here. The objective characteristics are generally unrelated to noise annoyance. The few weak relationships are as likely to indicate that better environments generate less noise annoyance as to indicate the opposite. As an example the visual quality index in Table 13 is unrelated to railway noise annoyance. Other analyses show that people are aware of the environmental quality: the observer’s measurement of each environmental characteristic is related to the respondents’ rating of that particular characteristic. However, the objective characteristics of one aspect of the neighbourhood do not bias the respondents’ perceptions of other characteristics. While the actual non-noise characteristics are not related to people’s annoyance with the railway noise, people’s subjective attitudes towards those non-noise area characteristics are related to annoyance with railway noise. In Part B of Table 13, railway noise annoyance is closely related to a direct question about “satisfaction with this area” as well as to an index based on ratings of eight non-noise aspects of the neighbourhood (closeness to shops, quality of local schools, upkeep of streets, appearance of buildings, nice neighbours, presence of parks, convenience of location and availability of public transport). The strength of the relationship is evident in Column 3 of Table 13 where the difference in railway noise annoyance for being “very satisfied” or “very dissatisfied” with the neighbourhood is the equivalent of 18 dB. In Column 6 it is seen that one standard deviation on the neighbourhood attitude question is the equivalent of about 4.55 dB. Thus, with a normal distribution assumed, about one-third of the sample would be expected to have their annoyance scores either increased or decreased by the equivalent of more than k4.55 dB because of their overall attitudes toward the neighbourhood. Column 5 shows that there was a roughly 13 dB effect over the range of scores which included 90% of the sample. As in an earlier road traffic survey [35-37, Langdon 19761, it is found that it is the ratings of the neighbourhood appearance and of the presence of parks which are most closely related to the rating of the neighbourhood as a whole. Since that aspect of the respondents’ attitudes toward the neighbourhood which is related to railway noise annoyance is not caused by the objective neighbourhood characteristics, the relationship must be explained in some other way. The explanation may be more complex than the simple one that feelings about the neighbourhood cause railway noise annoyance. Other possible explanations may be that either railway noise annoyance itself increases annoyance with other aspects of the neighbourhood or, as Weinstein suggested [38], a response bias leads some people quite independently of their own true attitudes, to be more willing to espress their own critical feelings in an interview situation. Perhaps the most likely explanation is that there are basic attitudes or personality traits which lead to a critical stance toward many aspects of a neighbourhood. Inasmuch as this represents a generalized critical-uncritical dimension [38, Weinstein 19801 then the possibility that some of the other noise related attitudes may also be a function of this general outlook must be considered when attitudinal effects are discussed in section 7.5.

RAILWAY

NOISE

REACTIONS

IN GREAT

BRITAIN

223

The neighbourhood also provides a social setting for feelings about railway noise. Some neighbourhoods might share a heightened awareness of the neighbourhood environment because of neighbourhood groups or individuals who have previously dealt with a neighbourhood problem. However, when this is tested in Part A of Table 13, knowledge of “. . . any people or local groups around here who have ever tried to do something about any neighbourhood problems” is not significantly related to railway noise annoyance (only 32 people mentioned railway complaints on this question). Two indications of knowledge of actions specifically about railway noise are, however, related to annoyance: knowledge of neighbours’ railway complaints and knowledge of attempts to obtain a reduction in “Rates” (local tax relief) because of railway noise (Part A of Table 13). These effects are not independent of one another. In Table 17 (see section 7.5), it is seen that when both variables are simultaneously considered their independent effects are reduced by 1 or 4 dB. Some caution must be exercised in interpreting the answers to these questions since these reports which are based on memories of neighbours’ actions may be partially contaminated by the respondent’s own feelings. Nevertheless, it does appear that knowledge of actions of others towards railway noise does increase people’s own annoyance with the noise. The weakening of the knowledge variable when preventability is introduced in line 6 of Table 17 suggests that the increased annoyance may be partly explained by the belief that the noise can be controlled or prevented. 7.2.

HOUSING

CHARACTERISTICS

The type of housing unit does not have an important or statistically significant relationship with annoyance (Part C of Table 13). Whether house tenure is based on ownership, private rental or government rental (council housing) seems to be of little or no importance. The statistically significant interaction effect for house tenure (Column 8) was found to indicate that council housing tenants were slightly more annoyed than others at lower noise levels (less than 50 dB) but that owners were slightly more annoyed above 60 dB. Unlike the other two housing characteristics, the house age (observer-rated) affects feelings about railway noise. Even after the age of the respondent and length of residence are controlled for in Table 15 (see sections 7.3 and 7.4) it is seen that increased annoyance equivalent to 5 dB(70 years x 0.07) is associated with new as opposed to 70 year old housing. The apparently non-linear relationship (Column 3 of Table 13) becomes more nearly linear when other variables are controlled for in the analysis in section 7.4. 7.3. RESPONDENT-SPECIFIC EXPOSURE INDICATORS Up to this point, the noise levels have been outdoor noise exposures at one metre from the facade of the noisiest (for railway noise) side of the house. Individuals with similar outdoor noise levels have different individual exposures depending on such factors as time spent out-of-doors, usage of rooms in the home and amount of time at home. Five variables are now examined which are related to the individual’s actual noise exposure. In Table 13, Part D, the presence of private outdoor space (an indication of out-of-doors noise exposure at home) has no important or statistically significant effect on annoyance. Double glazing which on the average reduces noise levels indoors, does not by itself reduce annoyance. While there are not enough interviews to draw firm conclusions, the data in Part D of Table 13 support the speculation that the reasons for having double glazing installed are important. People who have had double glazing installed at least partly because of railway noise are more annoyed than people with no double glazing

224

J. M. FIELDS

AND J. G. WALKER TABLE

Annoyance

(Decibel Equivalent Annoyance

Control

Characteristic (1) Part A: Demographic

for

14

Units) associated with

noise through analysis of residuals

Average residual annoyance score is given for each category (annoyance is measured in Decibel Equivalent Annoyance Units in all columns of the table) (3)

Contents of row (2) characteristics

Sex of respondent

Sex

dB(EAU) (N)

Female

Male

-0.74 (790)

0.88 (663)

18-29

30-39

Age (years) 40-49 SO-59

60-69

270

6.90 (331)

3.61 (227)

1.82 (226)

-4.17 (244)

-8.48 (210)

Age dB(EAU) (N) Marital status

Single dB(EAU) (N)

1 dB(EAU) (N)

-4.40 (253)

Education <15 dB(EAU) (N)

Prof/ mgr 0.42 (215)

Length of residence
7.00 (128)

Married 0.94 (991)

-4.87 (258) Number of people in household 3 2 4 -1.81 (475)

0.61 (235)

2.72 (279)

Years of education of respondent 16-19 15 5.24 (328)

-3.89 (676)

Occupation

dB(EAU) (N)

Marital status Separated/widowed/divorced

1.72 (203)

Household size

-3.33 (215)

0.15 (448)

5.07 (211) 220 5.25 (104)

0.82 (323)

Occupation of head of household White Semicollar Skilled skilled 1.12 (501)

25

-2.55 (198)

Unskilled -2.38 (91)

Years lived at this address l-10 11-15 16-29 230

Always

2.87 (659)

-8.71 (76)

0.64 (182)

-4.16 (215)

-7.07 (190)

RAILWAY

NOISE

REACTIONS

IN

GREAT

225

BRITAIN

personal, attitudinal and household characteristics Control for noise by including the characteristic in a regression equation with L,, and Lz,

~

Coding of variable (90% range) (4)

0 = Male 1 = Female (c)*l)

Approx. decibel effect (90% range)

Partial regression coefficient, Bv

(5)

2dB

Squared multiple correlation coefficient

Interaction (I) test statistic,

R2

B*lc+,,

(7)

(8)

-1.61 (0.94)

0.18

cl.65

Age in years (20-75)

16dB

-0.289*** (0.032)

0.25

5.10***

1 = Married 0 = Other (O-l)

3dB

2.89** (1.03)

0.18

2.21*

9dB

2.16*** (0.32)

0.20

3.66***

6dB

5*70** (2.13)

0.19

2.10*

0.50

0.20

No. of people 1 = 1 etc. 5 = 5 or more (l-5)

1 = College

0 = Else (O-1)

1 = Professional/ manager 0 = Other log10 months at address (0.9-2.7)

OdB

cl.65

(1.39)

14 dB

_7.58*** (1.21)

0.22

4,0g***

.I. M. FIELDS AND J. G. WALKER

226

TABLE

Control

for noise through

14 (conr.)

analysis of residuals

Average Contents of row (2)

Characteristic (1) Part B: Relationship Railway

with railway Frequency cl a Never year

usage

dB(EAU) (N) Railway

dB(EAU) (N)

1.26 (436)

4.72 (131)

6.18 (43)

-0.07 (121)

-0.94 (65)

-0.87 (74)

-2.54 (81)

0.31 (1229)

Evaluation

of ticket prices and success in meeting public needs Favourable Unfavourable dB(EAU) 0’)

1.67 (365)

0.82 (199)

-3.61 (326)

1.00 (391)

Annoyance

with railway dirt, smells, loss of privacy Low annoyance

dB(EAU) (N)

-7.89 (173)

-5.90 (563)

2.05 (273)

Felt danger from crossing No danger

Fear (index based on 2 questions) dB(EAU) (N) Preventability (index based on 3 questions)

-2.11 (697)

about railway

Evaluation of British Railway organization

Annoyance with non-noise aspects of railway (5 question index)

2.55 (21)

of respondent’s travel by train l-3a la >2a 2-11 a year month week week

Who in household has worked for railroad Respondent Only spouse Other No one

employment

Part C: Attitudes

residual annoyance score is given for each category (annoyance is measured in Decibel Equivalent Annoyance Units in all columns of the table) (3)

-2.66 (795) Believed Low

dB(EAU) (N)

-0.59 (383) concern

Not at all dB(EAU) (N)

4.43 (465)

lights, property, High annoyance

8.21 (314)

-3.38 (187)

205 1 (130)

tracks or from crashes High danger 0.22 (281)

ability of authorities

-6.62 (344) Perceived

Perceived concern of railway with noise

2.98 (25%

0.06 (172)

to reduce 2.05 (304)

10.84 (118) railway

noise High

10.69 (235)

of British Railways with comfort of residents A little Moderately Very much 2.52 (362)

-3.47 (424)

-7.46 (91)

RAILWAY

NOISE

REACTIONS

IN GREAT

227

BRITAIN

Control for noise by including the characteristic in a regression equation with L,, and Lz, I

Coding of variable (90% range) (4)

1 = aTwice a week 0 = Other (0-l) 0 = No-one works for railway 1 = Other (O-1)

Standard deviation units (-1.5 to 1.5)

Standard deviation units (-1.6 to 1.4) Standard deviation units (-0.7 to 1.3) Standard deviation units (-1.4 to 1.3)

Standard deviation units (-1.2 to 1.0)

Squared multiple correlation coefficient

Approx. decibel effect (90% range) (5)

Partial regression coefficient, Bv (a& 1 (6)

1 dB

0.86 (2.14)

0.18

cl.65

2dB

-1.78 (1.53)

0.18

cl.65

3dB

-1.11 (0.62)

0.18

cl.65

R2

BIl~B,

(7)

(8)

26 dB

8.83*“* (0.64)

0.36

6dB

3*31*** (0.88)

0.21

15 dB

5.38*** (0.64)

0.25

8dB

-3.65*** (0.41)

Interaction (I) test statistic,

0.21

2.25*

cl.65

8.35***

cl.87

228

J.

M. FIELDS

AND J. G. WALKER TABLE 14 (cont.)

Control for noise through analysis of residuals

Characteristic (1)

Average residual annoyance score is given for each category (annoyance is measured in Decibel Equivalent Annoyance Units in all columns of the table) (3)

Contents of row (2)

Belief that a good chance will some day live where less railway noise? Don’t know No Yes, live in quieter place

Expectations

dB(EAU) (N)

-5.01 (532)

8.03 (511)

-3.30 (385)

Part D: Attitudes about noise Health (based on 2 questions

Extent think railway noise and/or other noise can harm health Not harm Sure can harm dB(EAU) (N)

Reported sensitivity to noise generally

-5.03 (264)

-3.27 (420)

2.01 (23 1)

-0.14 (243)

7.69 (295)

Index of importance of noise as problem and own sensitivity Low sensitivity High sensitivity dB(EAU) (N)

Importance

-3.60 (365)

-3.07 (160) Importance Not at all -3.29 (59)

dB(EAU) (N)

0.10 (372)

0.90 (331)

6.54 (225)

of noise in choosing a place to live A little Somewhat Very 1.14 (469)

-2.15 (157)

0.06 (764)

Part E: Other attitudes Satisfaction with life

Life satisfaction

High

Low dB(EAU) (N)

7.04 (154)

2.46 (346)

2.42 (216)

Respondent’s

Moving plans

dB(EAU) (N)

-1.13 (359)

-5.43 (378)

moving plans

Not move

May move

Plan to move

Move because of railway

-1.57 (1092)

3.02 (142)

5.33 (215)

33.09 (4)

RAILWAY

NOISE

REACTIONS

IN GREAT

BRITAIN

229

Control for noise by including the characteristic in a regression equation with L,, and L&

Coding of variable (90% range) (4)

l=Yes O=No, don’t know (O-l)

Standard deviation units (-1.6 to 1.6)

Standard deviation units (-1.6 to 1.5) 1 = Not at all 2 = Little 3 = Somewhat 4 = Very (2-4)

Standard deviation units (-1.5 to 1.2) l=Mayor will move 0 = Not move (O-l) (RW move excluded)

Approx. decibel effect (90% range) (5)

Partial regression coefficient, B,

Squared multiple correlation coefficient

Interaction (I) test statistic,

R2

BJffEl,

(7)

(8)

13 dB

12.83*** (1.30)

0.27

3.20**

14dB

4.37*** (0.64)

0.23

5.32***

9dB

2.95*** (0.59)

0.20

3.29**

2dB

0.78 (0.59)

0.18

cl.65

10 dB

_3.89*** (0.60)

0.214

1.95

6dB

6.07”** (1.30)

0.20

3.08**

230

J. M. FIELDS

AND

J. G. WALKER

at all. Presumably only those who were initially highly annoyed would have taken such steps. Since television viewing is often reported as being disturbed by trains, it was hypothesized that people with televisions in rooms away from the railway would be less annoyed by the railway noise generally. They do report less television disturbance annoyance: the television watching disturbance in a room on a quiet, as opposed to the noisy, side of a house is decreased by just the amount that would be expected from the reduced noise level. (This is true whether noise levels are expressed in L,,or average peak dB(A) noise levels.) For example, the percentage who said their television watching was interfered with by trains with windows closed decreased by 1.5% with each 1 dB at the noisiest facade, and then continued to decrease by 1.5% for each additional decibel of attenuation to the position outside the window of the room containing the television. The effect on television disturbance does not however carry over to general train noise annoyance (Table 13, Part D). Thus it appears that though better noise information for the TV helps to predict the specific, stationary indoor activity disturbance of TV listening, it does little to explain overall annoyance. People who are employed and thus probably less exposed to the railway noise during the day are not significantly less annoyed by railway noise after controlling for age of respondent in Table 15 (many people who are not employed are retired). Respondents whom the interviews judged to have hearing difficulties were less annoyed (5-12 dB(EAU)), but the small numbers of such respondents mean that the effect is not statistically significant. The effect is only slightly reduced by the control for age in Table 15 (-3 dB(EAU)). In short, there is not strong evidence that the five more individualized indicators of exposure used here are related to annoyance. While they are far from precise indicators of the railway noise dose to which people are exposed, the findings suggest that more exact indicators of individual-specific noise dose will not greatly increase the correlation between noise levels and general noise annoyance responses. 7.4. DEMOGRAPHIC CHARACTERISTICS Neither sex nor occupation of the respondents is found to affect annoyance (Table 14, Part A). The apparent effects of marital status, size of household and education in Table 14 all disappear in Table 15 when they are controlled for the respondent’s age. The control for age also eliminates the interactions with noise level. The effect of respondent’s age, however, was not reduced by the introduction of those variables. Age is the only one of these basic demographic variables which directly affects annoyance. Age, length of residence (time lived at present address), and house age (Table 13, Section D) all affect railway noise annoyance. They are inter-related, especially age and the logarithm of length of residence (r = 0.54). Thus it is not surprising to find in Table 15 that each of the variables’ effects is reduced by about one-quarter to one-half when it is included in a single regression equation. Even after being controlled for one another, they have a strong effect on annoyance. From Line 5 of Table 15, it can be calculated that: the 50 year difference in respondent’s ages creates an effect equivalent to about a 11 dB (-0.22 x 50 = - 11) reduction in noise level, an increase from 8 months residence (logi 8 = 0.9) to 42 years residence (log,, (42 x 12) = 2.7) is the equivalent to a 5 dB ((2.7 -0.9) x (-2.95) = -5.3) decrease in noise level, and the change from a recently constructed house (average age 2 years) to a pre-World War I house (estimated average age 74 years) is the equivalent of roughly a 5 dB (72 x -0.07 = -5) reduction in noise level. The possibility that there could be unusual interaction effects which would completely explain some of these variables’ effects has been considered but rejected. However,

15

Age of

(years)

respondent

0.27 0.26 0.26 0.28 0.28 0.29

(fog,, months at address)

Length of residence

age

(years)

House

-3.17**

-3.72***

-2.95* -3.49**

indicated

-3.49** (R’=0.26)

(R2=0.21)

-3.69***

Non-noise neighbourhood rating index (Standard deviation units)

-0.07**

-0.08**

-0*07**

variables

_3.23*** _3.2g*** _3.30***

(R* = 0.28)

-3.23***

and noise level (Leqr L&)

-0.08** (R*=0.26)

for age of respondent

_0.11*** (R’=0.20)

_7.58***

(R’=0.22)

only for noise level (L,,, Lfs)

for additional

-0.22*** _0.23*** _0.27*** -0.27*** -0.21*** -0.20***

Part C: Controlled

-

-

Part B: Effect controlled

-0.289*** (R’=0.25)

Part A: Effect controlled

R2

Squared multiple regression coefficient,

Partial

(R* = 0.25)

-1.15

3.04** (R2=0.18)

Employment status 1 = Employed at least half time 0 = Other

Regression

-3.02 (R’=0.25)

-4.05 (R2=0.18)

0 = Normal 1 = Diminished

-0.98 (R2=0.25)

-1.61 (R’=0.18)

O=M l=F

Sex

(not standardized)

Hearing ability

Coefficient

0.42 (R’=0.25)

2.89** (R*=0.18)

l=M 0 = Other

Marital status

5.70**

1 = College 0 = Less

Education

0.14 (R*=0.25)

2.26 (R*=0.25)

0.89 (R*=O.25)

0.50 (R*=O.l8)

1 = Prof. mgr 0 = Other

occupation

,

index expressed

(R2=0.20) (R*=O.19)

2.16**

No. in each household 5=5+

Household size

Personal characteristics’ effects controlled in multiple regression analyses (dependent variable is decibel equivalent annoyance in decibel equivalent annoyance units)

TABLE

3 2

?

z > 1

0

Yi?

2 8

b

:

g

5

$

:

?

232

J. M. FIELDS

AND

J. G. WALKER

a closer examination of the pattern of the effects of these three variables is useful. Both the respondent’s age and length of residence effects interact with noise level. The pattern for age in Figure 13 shows that the effect of age arises not from chronic complainers among the younger groups, but rather from an insensitivity to increasing noise levels among older people. The length of residence variable is similar with long term residents discriminating less clearly between changes in noise levels. After the controls for age and house age, one critical shift in the pattern of the length of residence direct effect is apparent in Table 16: the length of residence effect is primarily caused by the low annoyance responses (-8.9 dB(EAU)) of life-time residents. It thus appears that there is relatively little adaptation to noise over time (at least after the first few days or weeks); it is mainly the people who have always lived with a noise who are much less affected by it.

I/ 20

L-L-

30

24 Figure 13. Interaction +, 60 years or older.

between

respondents’

-A

--i_-.L--2

40

50

60

70

80

h L,(dB(A))

age and noise level. 0, 18-39 years old; 0, 40-59 years old;

While the explanation for the effect of the length of residence variable is self-evident, the explanation for the effect of the respondent’s age and house age are less clear. That they are not explained by a generally critical attitude toward the neighbourhood is evident in Table 15, where the introduction of the non-noise neighbourhood attitude variable only slightly reduces their effects. It seems unlikely that the house-age effect could be traced to changes in transmission loss. Any small changes in construction techniques in the last 80 years would have little effect on interior noise levels since the windows (the weakest acoustical path) have been present in houses for the entire period. The only additional

weak interaction

pattern

is for house age to have less effect on newer residents.

TABLE

16

Efiect of length of residence on annoyance (Summed Annoyance Equivalent Annoyance Units)

Index

in decibel

Annoyance residuals for length of residence (in years) groups Variables controlled for L,, LZq Leq,L&, age of respondent, (Number of respondents)

house age


l-10

11-15

16-29

330

Always

7.00 2.64 (128)

2.87 0.73 (659)

0.64 0.85 (182)

-4.16 1.45 (215)

-7.07 0.01 (190)

-8.71 -8.86 (76)

5 6 7 8 9 10 11 12 13 14 15

0.23 0.29 0.32 0.33 0.32 0.34 0.38 0.46 0.36 0.45 0.23

Part C: Controlled

3 4

Part B: Controlled

2

1

Part A: Controlled

Row

deviation units

-1.29** __2.09*** __1.41** 2.74***

_2.31*** _2.53*** -2.52*** _2.28*** _1.89***

-2.44*** _3.03***

regression

11,25***

9,72*** 7,62*** 10.05*** 7,81***

4.25** 2.12 4.19* 2.00

14.05*** 11.75***

14.89*** (R’ = 0.28)

4.72*** 4.92*** 4.51*** 5.01*** 4.36*** 3.70*** 2.72*** 4.26*** 3,11***

5.15*** (R2=0.30)

5.38*** (R*=0.25)

Believe railway noise is preventable

coefficients

index and life satisfaction

15.47*** (R’ = 0.23)

Tax reduction because of RW noise 1 = Attempt or success 0 = Other

Partial

4.71**

5.60** 4,56*

variables

9.38*** (R’=0.25)

rating

9.43*** (R’ = 0.20)

1 = Complaints 0 = Other

Neighbourhood railway complaints

indicated

_2.71*** __2.79**” -2.62*** _2.40*** _2.44*** -2.29*** _2.63***

17

1,21*

_2.23*** -1.46*** _2.41*** -1.57”**

2.86*** (R2=0.25)

3.31*** (R2=0.21)

Standard

Fear, danger from railway

for

1.19** 1.02 0.88

2.49*** (R’=0.25)

2.95*** (R2=0.20)

units

Sensitivity to noise

Equivalent

deviation

is Decibel

2.59*** 2.42** 2.02** 1.14* 2.15**

_2.73***

(R*=0.26)

-3.13***

(R2=0.21)

-3.65***

Railway concern about residents

(not standardized)

in multiple regression analysis (dependent variable expressed in Decibel Equivlent Annoyance Units)

neighbourhood

for noise level and additional

-

for noise level, non-noise

_3.89***

(R2=0.21)

-3.69***

(R* =0.21)

only for noise level (L,, + 1;&)

Standard

Life satisfaction

effects controlled

Non-noise neighbourhood rating index

characteristics’

Squared multiple regression correlation coefficient, R2

Attitudinal

TABLE

2.39*** 2.19*** 1,62**

3,85*** (R*=0.27)

4.37*** (R2=0.23)

Health

Index

6,61***

6.39***

8.32* (R2=0.39)

8.83*** (R*=0.36)

Bothered by other aspects of railway

Annoyance

I;: w

2 z

z

E

;

2

2 vl

5

E

m

2

z

? F

234

J.

M. FIELDS

AND

.I. G. WALKER

The age of respondent effect would not appear to be due to hearing disabilities, because the change in reactions occurs across all age groups and because the control for obvious hearing disabilities did not reduce the age effect. The two most plausible explanations for the age effect are that older people may have more nostalgic associations with railways as a transportation system and that they experienced a favourable transition to modern diesel or electric trains away from the former dirtier, noisier and more odourous steam engines. 7.5. ATTITUDINAL FACTORS Attitudes toward the railway system and toward noise generally are examined here, but caution should be exercised in interpreting any relationships with railway noise annoyance since the casual ordering of attitudinal variables is often unclear. It is commonly believed that people’s attitudes towards the railway as a transportation system or their use of, or self interest in, the railway transportation system will affect how they feel towards the noise from trains passing by their back garden. In Sections B and C of Table 14, this is not the case; people who use the system regularly are no less annoyed. Households which have members working for the railway are not significantly less annoyed than others. Feelings about ticket prices or the British Railways organization’s ability to meet public needs are unrelated to annoyance. The set of attitudes about a different aspect of the railways, railways as a neighbourhood environmental nuisance, are related to noise annoyance. Railway noise annoyance is related to feelings about the railway’s dirt, smells, intrusive lights, maintenance of railway property, and visual intrusiveness. This pattern is, for the most part, similar to that found by Aubree for annoyance with railways in France [5, Aubree 19731. From the present data it is not possible to determine whether annoyance with the other aspects actually causes the heightened annoyance with railway noise. At least part of the explanation is probably that even after measured noise levels are controlled for, the actual railway nuisances (including noise) will tend to impact the same people. It may even be that it is the noise annoyance which leads to a greater annoyance with the other aspects of the railway. The belief that “people who run the railways” or the “designers and makers of trains” are “in a position to do anything about railway noise”, (Preventability Attitude) is associated with greater noise annoyance. When the statistically significant interaction

40

5024 h L,

-6% (dEl(A

--~

70

80

1)

Figure 14. Interaction between preventability and noise level. +, Noise could be reduced ate preventability attitude: 0, no-one can do anything about the noise.

here; 0, intermedi-

RAILWAY

NOISE

REACTIONS

IN GREAT

BRITAIN

235

pattern is examined (Figure 14) it is found that the reactions of people who believe the noise caltlt~t be prevented are less closely related to noise level. One attitude towards the British Railway management is related to annoyance, but it is a very narrow residential-area-specific attitude: the belief that “the people who run the railways are.. . concerned” about “the feelings and comfort of residents. . .” (Part C, Table 14). As would be expected, the effects of the preventability belief and railway management motivation beliefs are not independent (Line 7, Table 17). People are more annoyed who are more aware of danger to people and children crossing tracks or who “feel there is any danger. . . of a crash. . . when they . . . hear the trains go by. . .” (Part C, Table 14). Thus, as for aircraft, fear and the association of danger for residents with the transportation mode are related to annoyance. Attitudes towards noise generally are explored in Part D of Table 14. The importance which the respondent attaches to “quietness of the area. . . in choosing a place to live” is not related to railway noise annoyance. Both the beliefs about the effect of noise on health and the reported sensitivity to noise generally are closely related to annoyance. The interpretation of these two measures as being separate from noise annoyance itself appears to be especially doubtful. In common terminology, a person whose health is affected by something is by definition affected and bothered by it. Inherent in the process that some people use for deciding if they are “very annoyed” may be their definition of “very” in relation to other people. The health and sensitivity variables are especially vulnerable to arguments that they may be caused by, rather than a cause of, railway noise annoyance. The belief that one’s health is affected by railway noise may come from the experience of being annoyed and feeling bothered by the noise. The belief about one’s relative sensitivity to noise in general may come from discussions with neighbours about railway noise in which a person found that he was more annoyed and more “sensitive” than other people, to railway noise. In Table 14, Part E, and Table 17 an index of self-ratings of “happiness” and “satisfaction” with life is related to railway noise annoyance. While this may show that generally happier people do not let railway noise bother them, it may be that the variable only measures a willingness to express critical feelings in an interview in much the same way that the earlier non-railway neighbourhood critical-uncritical variable may operate. It is for this reason that both variables are included simultaneously as controls in Table 17. The attitudinal variables’ effects are not independent of one another. The attitudinal variables’ effects are generally only slightly reduced when they are controlled for the critical-uncritical dimensions (non-noise neighbourhood rating and life satisfaction) in Part B of Table 17. It can be argued that this critical-uncritical dimension is in some sense more basic than the other variables. However, there do not seem to be strong reasons to assign any particular casual ordering to the other variables. When the various variables are considered simultaneously in Lines 11, 12 and 13 of Table 17, most variables’ partial regression coefficients have been reduced by between one-third and one-half. 7.6. INSIGHT INTO THE NOISE ANNOYANCE REPORTS The inter-relations discovered here provide some insight into the annoyance response itself. Inasmuch as noise annoyance is only an outlet for other feelings, these feelings concern an overall orientation towards the neighbourhood environment rather than feelings towards the noise source. Thus although general attitudes towards British Railways, or the person’s own interests in the railways as a transportation mode, are

236

J. M. FIELDS

AND

J. G. WALKER

unrelated to annoyance, the many neighbourhood environmental attitudes are closely inter-related with the responses to the environmental railway noise. The effect of noise level interacts with five attitudinal variables (preventability, health beliefs, sensitivity, non-noise neighbourhood rating and non-noise aspects of railway) and two demographic variables (age of respondent and length of residence). In each case reactions are similar for all groups at low noise levels, but as noise levels increase, the noise annoyance relationship is steepest and thus closest for the types of people who have the more negative reactions to noise. These sensitive people are thus not “chronic complainers” regardless of noise level, but rather people who are especially sensitive to the difference between high and low level noise environments. Some attitudes that influence the degree of annoyance and also sensitivity can thus be thought of as ones which bring people to be more discriminating in evaluating their environment. One possible interpretation of these patterns is that people who have less extreme reactions to noise and are less likely to differentiate between high and low noise environments are people who cannot allow themselves to form negative impressions of their living environments and thus must suppress any annoyance reactions. This interpretation is supported in Table 14 where the lack of sensitivity to the noise environment is greatest for people who believe that they will never live in a quieter environment (Part C of Table 14) and people who do not think they will move in the near future (last line of Table 14). 8. THE PLACE OF PASSING TRAIN NOISE IN THE TOTAL ENVIRONMENTAL IMPACT OF RAILWAYS IN GREAT BRITAIN

Noise from passing trains is only one of the ways in which neighbourhoods are impacted by the presence of a railway route. Seven other types of railway-related non-noise nuisances were identified in the pretest study and explicitly asked about in the final questionnaire (Tables 18 and 19). Respondents were encouraged to name other problems in the final questionnaire, but none were frequently mentioned. The percentages of the sample bothered by the various railway conditions (Tables 18 and 19) are a function of three separate factors, none of which could be carefully controlled in the analysis: (1) the number of locations at which the railway condition exists; (2) the intensity of that condition; and (3) the amount of annoyance with a particular condition. Due to the study’s probability sample design, Tables 18 and 19 are a good indication of the prevalence of these problems near railways in the country as a whole but do not provide evidence about the relative importance in any particular setting. The proximity to the railway condition is a factor since all problems are reduced rapidly with distance from the railway line. Other analyses in reference [16] found that when dirt, land upkeep or smells were serious enough to be noticed by the acoustician-observers, they were more likely to be rated as problems by respondents. The various non-passing train noises were rated as problems by about half of those who reported hearing them. These contrast with the privacy and train lights conditions which were usually not rated as problems even when they were noticed. The railway environmental impacts are arranged in approximate order of frequency of mention in Tables 18 and 19. The most often mentioned non-noise impact, vibration, is discussed later in section 9. Of the various noise impacts, it is the ones which are most widely spread across the railway network and thus the ones to which the greatest number of people are exposed, which are most often mentioned as problems. The questions about standing trains and shunting refer to operations connected with standard operating conditions since residences within 300 m of the country’s 47 marshalling yards were excluded from the study population.

a Percentages

are the percentage

of all people

(134)

(454)

4% 8%

1%

32% 18%

50% 26%

25-49

line (m)

bothered.

(353)

who are at least “a little”

(205)

3% 3%

0%

0% 1% 0%

0%

1% 1%

15 % 14%

28% 13 %

10% 6%

5%

4% 7% 6%

13 %

10%

so-99

from the railway

100-149

Distance 150-199

in each cell (not in the row or column)

(42)

(20)

(Number

in cells in the column)

0% 0% 0%

0% 0% 0%

of interviews

12% 14%

0% 0%

200-299 5 :/c 7%

300-500 5% 0%

noise

“Men or machines working on the line” “Noise from trains just sitting with their engines on” “Noise from the train’s hooter” “Noise of taking railway wagons off or shunting” “Noise from a level crossing bell” “Any other noises from the railway” “Noise from a railway station”

Type of railway

18

Percentage” at least “a little” bothered by seven types of railway noise

TABLE

(190)

2% 3% 0%

29% 16%

54% 34%

15-24

(52)

2% 6% 12 %

33% 25%

Cl5

(1450)

1% 3% 4%

21% 14%

Total

5

2 ‘i

;

5

8 m

5:

8

6

rated

of

a Percentages

(Number column)

are percentages

interviews

in

(42)

0%

0% (20)

5% 5% 5% 7% 0%

200-299

0% 0% 0% 0% 0%

,300-500

19

Distance

(134)

0%

4% 12% 5% 4% 0%

(205)

0%

3% 9% 4% 1% 0%

100-149

from

line (m)

bothered.

(353)

1%

12% 21% 8% 4% 0%

SO-99

railway

who are at least “a little”

150-199

in each cell (not in the row or column)

in the

of all people

cells

Vibration The way the railway keeps up its property Dust or dirt Fumes or smells from trains Passengers being able to see into your house or garden Lights from train

Condition

TABLE

(454)

3%

30% 3 1% 26% 14% 10%

25-49

Percentage” rating each of six non-noise railway characteristics as a “problem”

(191)

2%

38% 26% 28% 15 % 15 %

15-24

(52)

2%

31% 42% 36% 23% 15 %

<15

(1451)

0%

20% 22% 17% 9% 6%

Total for all of sample

$ k :

0

% z

g

i 3 F

239

RAILWAY NOISE REACTIONS IN GREAT BRITAIN TABLE 20

Comparing annoyance with maintenance noise and “train noise” Train noise level in 24 h L,, dB(A) c

<40

40-49

50-59

60-69

370 ’

7% 3% 90%

14% 9% 77%

23% 18% 59%

38% 21% 4 1%

44% 30% 26%

25% 16% 59%

100% (147)

100% (372)

100% (356)

100% (373)

100% (157)

100% (1405)

Maintenance is more annoying Trains more annoying Neither annoying Total

Total --

Maintenance noise is the most important non-passing train noise. In Table 20 it can be seen that maintenance noise is the one type of noise which annoys more people than passing trains. People who are closer to the tracks are more likely to hear maintenance noise. When the people closer to the lines do hear it, they also hear it more often. Maintenance is not a once-a-year, inconsequential phenomenon. In some types of areas over one-quarter of the respondents near lines report they hear maintenance noise at least once a month. Maintenance is a day-time as well as a night-time problem. It becomes more of a night-time problem with increasing distance. At the points furthest from tracks over 60% of those noticing maintenance noise only notice it at night. The combined impact of all these non-noise and non-passing train noise sources is more important than the chief subject of this report, the noise from passing trains. When respondents were directly asked whether particular noise sources were “more or less annoying than the noise of trains going by” it is found in Table 21 that more than three times as many people at every noise level find at least one of the many other sources of railway noise is more annoying than the noise from passing trains. In Table 22, non-noise aspects are again more important than through-train noise. These tables probably do under-estimate the effect of the through-train noise because the questions used for comparing the sources did not emphasize the frequency of the annoyance and because the questionnaire item for classifying people as “ever bothered” by through-train noise differed from the item used for the classification of “ever bothered” by other sources. Nonetheless, it is clear that annoyance with the noise from moving trains occurs in a context in which people find one or another of the other railway impacts is more important.

TABLE 21

Type of railway noise which is most annoying by noise level Noise level in 24 h L,, dB(A) r--m

40-49

50-59

60-69

1% 16%

4% 29%

8% 41%

7% 57%

19% 58%

83%

67%

5 1%

36%

23%

100% (145)

100% (368)

100% (355)

100% (365)

100% (152)

<40 Passing train noise is most annoying At least one other train noise is more annoying No railway noise is annoying Total

370

annoyance

judgment

Passing train noise is mrst annoying At least one non-noise aspect is more annoying Neither aspect is annoying

Comparative

Total

TABLE 22

100.0% (19)

100~0%

0% 0%

300-500

100~0% (40)

75.0%

7 .5 % 17 ’5 %

200-299

100~0% (133)

73.7%

3 .8 % 22.5%

150-199

Distance

58.2% 100~0% (340)

100.OO/” (199)

7.1% 34.7%

50-99

100~0% (439)

100.0% (186)

30.1%

17 .2 % 52~7%

17 ’8 % 5 0 .3 % 31.9%

15-24 25-49

line (m)

78.9%

5.0% 16.1%

100-149

from the railway

100~0% (52)

25.0%

13 .5 % 61.6%

<15

100~0% (1408)

50.5%

11.3% 38.2%

Total

Rating of relative annoyance rr,ithpassing-train rloise and non-noise aspects of the railway’s presence by distance from the railway

!

z K

$ tJ + 0

Fi F1

I2

L g

RAILWAY

NOISE

REACTIONS

IN GREAT

241

BRITAIN

This does not necessarily mean that the almost exclusive focus on rail-wheel noise is misplaced. Of the various railway impact problems rated by respondents, only one other problem, maintenance noise, was rated as being as serious as through-train noise and even this problem is so diverse that no single source can be identified. It is very clear that the solution of no other single problem would bring greater relief to the residents of railway impacted areas than would the reduction of rail-wheel noise.

9.

REACTIONS

TO

VIBRATION

The most often mentioned non-noise disturbance from railways-vibration-cannot be fruitfully analyzed in as much detail as noise, because vibration levels were not measured. In this section, it is possible to describe the vibration effects, describe the impact of operating conditions on vibration effects, identify factors which mediate vibration reactions and compare the extensiveness of railway and other sources of vibration in residential environments. 9.1. EXPERIENCE WITH VIBRATION FROM RAILWAYS Four types of reactions to vibration are graphed in Figure 15. The experience that trains ever make “your house or things in it vibrate or shake or rattle” is almost universal near a railway line. The vibration is at least a “little” annoying (second line in Figure 15) for most people who notice it. The vibration is not lightly dismissed by the much smaller number of respondents who go on to label it as a “problem” (third line in Figure 15), or the few who are “very” annoyed. When asked do . . . “you think anything may be damaged by the vibration, or shaking or not?“, about as many thought there might be damage as had earlier reported that vibration was a problem. Such perceptions are evidence of the seriousness with which some respondents view vibration, but should not be accepted as evidence as to the veracity of any hypothesized relationship between vibration and damage. Though it was not possible to determine whether the vibration was ground-borne or induced in the structures by noise, it is clear that the vibration is more than the occasional loose window pane. Over 80% of those experiencing vibration

T

---7

$

a&

0

50

Number of lntervlews(52)(454)(353) (191)

100

150

Dlstonce (205)

200

250

300

350

from facade to rmlwoy he

(134)

(42)

400

J

450

500

Cm) (20)

“Do the trains ever make your house or things Figure 15. Four reactions to vibration by distance. --, in it vibrate or shake or rattle” (Q32); -. -, (if notice vibration) At least “a little annoyed” when the (if notice vibration) “Would you say that the trains . . . “make the house vibrate or shake”. (Q18iv); -, vibration caused by the trains is a problem or not?” (Q33d); - - - -, (if notice vibration) “Very annoyed” when the trains “make the house vibrate or shake” (QlSiv).

of

0 = Not heard 1 = Other (O-1) 0 = None, slight 1 = Marked (O-1)

Rhythmic noise from wheels crossing joints

% of trains at night (O-25)

1 = Clearly visible 0 = Else (O-1)

railway noises

Ancillary operation

Night usage

Part B: Railway operating

Visibility railway

1%

4%

6%

7%

9%

1 = Touches 1 = Not touch (O-1)

14%

Resident’s property touches railway

km/h (30-140) 21%

levels

Range of effect (90% range) (3)

log,, number per day (1.0-2.6)

conditions

of vibration

(2)

Coding of variable (90% range)

-1.24 (4.42)

-3.91 (3.30)

0.27 (0.23)

6.89** (2.49)

9*15*** (2.75)

13.00** (5.00)

0.13** (0.05)

Partial regression coefficient,a B, (Cl?“) (4)

Vibration disturbance measured by percent saying “problem”

Traffic density

Speed

Part A: Likely indicators

Characteristic (1)

23

0.07 (0.17)

0.04 (0.13)

0.0072h (0.0081)

0.20** (0.08)

0*43*** (0.11)

0.46** (0.16)

0.0042** (0.0013)

a on

0.25

0.26

0.26

0.26

0.28

0.28

0.28

Squared multiple regression coefficient, R * (6)

disturbance measured vibration index

Partial regression coefficient,’ Bv (Utr”) (5)

Vibration

Effect of factors associated with vibration disturbance controlled for distance to railway

TABLE

$

9

%

F VI

3

il 9 ”

E

type

Tenure

Years (2-74)

l=Own 0 = Other (O-l)

1 = Flats 0 = Else (O-l)

24%

1 = Tried or success 0 = Other (O-l)

Believes neighbours got rates reduced because of noise

24.19*** (4.98)

-3*94** (1.41)

(0.05)

_0.25***

-4.59 (1.64)

-0.10* (0,04)

2.42 (2.46)

-5.89 (5.60)

0.74** (0.12)

(0.03)

-0.16***

O-0085*** (0.0017)

-0.059h (0.062)

-0.0021 (0.02)

0,015 (0.091)

-0.30 (0.29)

0.16 (0.11)

0.0002 (0.003)

-0.056 (0.157)

a Only respondents within 200 m are included in this table (N = 1401). All partial regression coefficients come from equations which include b The interaction term is related to the vibration index at p < 0.01 level even though the simple partial regression coefficient is not.

11%

14%

8%

7%

2%

6%

deviation units (-2.0 to q*s,

Standard

Years (20-75)

log,, months (0.9-2.7)

characteristics

Overall satisfaction with neighbourhood

tried or

and individual

of residence

Age of respondent

Months

House age

type

Part C: Housing

House

5.00 (3.20)

10%

1 = O-3% freight 2 = 4-39% freight 3 = 40-100% freight (l-3)

Service type (3 categories)

0.00 (0.11)

0%

% freight (O-SO)

Service type (% freight)

-0.60 (4.83)

1%

0 = Overhead electric 1 = Other (O-l)

Traction (electrification)

log,,

distance.

0.29

0.27

0.27

0.26

0.26

0.26

0.26

0.26

0.25

0.25

244

J.

M. FIELDS

AND

J. G. WALKER

went on to report they actually felt something move, such as the “floor, whole house, bed or chair”. The attempt to obtain reports of vibration may have been relatively successful because of the use of the common words “shake” or “rattle” as well as the more technical term “vibrate”. Attempts to limit reports to actually feeling vibrating objects were probably successful, though the colloquial use of “feel vibrations” in respect to feeling a low frequency sound, may have inflated the number of responses. The specific effects of vibration which caused disturbances were not identified. Thus, it is not known whether annoyance with vibration arises because of disturbance with specific activities such as sleep, because of anxiety about supposed damage or because vibration is simply a disagreeable sensation in residential environments. The choice of a particular vibration reaction for analysis in the remainder of this section is largely arbitrary because all four vibration reactions (perception, being bothered, identification of problem, and perception of damage) are highly inter-related and similarly affected by explanatory variables. Given the interchangeability of the scales most results are presented for a single question, percentage rating vibration as a “probIndex which is the average of each individual’s standard lem”, or for the Vibration deviation scores on the four vibration reaction questions. Because of the roughly equal inter-correlations of this small number of items factor analytic techniques would not have substantially improved the index. 9.2.

RELATIONSHIP

BETWEEN

VIBRATION

EXPERIENCE

AND

OTHER

VARIABLES

In the absence of actual physical measurements of vibration levels, the most powerful variable is distance from the railway line. In Figure 15, reports of vibration rapidly decrease between 25 and 150 m and then decrease more slowly until none of the small number of respondents (20) at an average distance of 500 m report vibration. The response to vibration within 200 m (where sufficient interviews are available) is better fitted by a logarithmic transformation of distance than by linear, quadratic or cubic equations. The relationships between vibration experiences and other variables, controlled for distance from the railway (log,,, distance) are presented in Table 23. The most obviously meaningful indicator of vibration experience in this table is the estimate of the percentage of the population which believes vibration is a “problem”. Partial regression coefficients and 90% range effects are presented in Columns 3 and 4 for the mention of vibration as a “problem”. The more reliable, but less easily interpreted Vibration Index’s partial regression coefficients, are presented in Column 5 together with their variances and the significance of the partial regression coefficients. The percentage of the variance in the vibration index which is explained (R2) by the included variables is given in Column 6. Since the percentage who list vibration as a problem is virtually zero at 200 m, it is obvious that the simple additive model without interaction terms which is presented here is not a realistic model over the entire range of distance. As an example, Figure 16 shows that the night-time effect is an interactive one. Without information about actual vibration levels, there would be little value in presenting a more complex model. The presence of interaction between distance and all effects means that all these effects can only be interpreted as the average of the effects of a third variable over the entire range. Thus while there is, for example, an average 14% increase in the percentage of a vibration for the age effect range (55 years in Column 2) this would be higher very close to tracks and would disappear at 200 m where virtually no-one perceives a problem. The variables with large effects (Columns 3, 4 and 5) and statistically significant effects (Column 5), would seem to affect vibration perception for several diverse reasons. Four

RAILWAY

NOISE

REACTIONS

IN GREAT

245

BRITAIN

Dstonce from railway kne (177) Figure 16. Effect of night-time traffic on reports night: 0, O-5%; X, 6-21%; A, 22% or more.

of vibration as a problem. Percentage of total traffic at

of the variables are probably predictors of actual unmeasured vibration levels: train speed, number of trains, nearness to railway property, and visibility of railway. Several other variables seem to indicate that some of the basic attitudes which are related to noise annoyance may also affect vibration annoyance: age of respondent, length of residence, attitude towardsthe neighbourhood, and knowledge of local tax rate reductions. Although the respondents’ comments about particularly bothersome vibration showed that the vibration effect is not an exclusively night-time phenomenon, there is evidence in Table 23 and Figure 16 that, unlike noise annoyance, vibration annoyance is increased by night-time traffic. Just as for noise annoyance it is again found that home ownership and house type have no effect on vibration reactions. Several other variables which affected noise annoyance do not affect vibration reactions: traction type, audibility of wheels crossing joints, and presence of other than passing train noise. This suggests that these variables may have had an acoustical, rather than attitudinal basis for their effects on noise annoyance.

9.3.

COMPARING

THE

EXTENSIVENESS

OF

EXPERIENCED

RAILWAY

AND

OTHER

VIBRATION

In a road traffic survey based on a probability sample of England, some 38% said they “got some vibration from road traffic” (28% said they were bothered), [30, MortonWilliams et al. 19781. From the same survey it appears that less than 2% of the population would have reported they experienced railway vibration (2% reported railway noise and it was found in the railway survey that more people report experiencing noise than vibration). The internal analyses of the railway survey in Table 24 show a similar pattern. While railway vibration is on the average relatively more often reported near the routes at higher noise levels, at lower noise levels below 40~5,~ (railway noise) other sources and traffic noise in particular are more often mentioned. These results are averaged over all the range of road traffic conditions present near railways in Great Britain. Individual areas with greater or lesser amounts of road traffic would differ. While these data clearly show that road traffic vibration is much more frequently experienced, the data do not give any evidence as to the relative intensity of vibration or annoyance with it in particular areas. No evidence is available in the survey as to

whether people find the same magnitude of vibration less or more annoying from different modes of transport.

246

J. M. FIELDS AND J. G. WALKER TABLE

24

Percentage reporting vibrations from trains, road traffic and other sourcesa Train

noise level in 24 h L,, dB(A)

I <40

40-49

SO-59

60-69

270

Trains

14% (148)

27% (376)

51% (373)

67% (388)

82% 11691

Road traffic’

18% (146)

26% (371)

16% (366)

15% (381)

10% (167)

Other sources

12% (146)

Sources

of vibrationi’

(&:I

(l?!,

a Numbers in the parentheses are the numbers of interviews on which the percentages are based. b Respondents could mention both trains and one other source. Thus the sum of the road traffic and other mentions is the total percentage mentioning any source other than trains. ‘Some respondents who did not specify the source but may have been thinking of road traffic appear in the next line of the table. Thus the effect of road traffic may be slightly underestimated.

10. SUMMARY 10.1.

RAILWAY

AND

CONCLUSIONS

NOISE IMPACT

Railway noise is a problem for people near railway lines. Two percent of the population of England is bothered by railway noise. About 170 000 people live where railway noise levels are above 65 dB(A) L,,. They find that railway noise is the worst aspect of the railway’s presence, though vibration is almost as important. Of the various railway noises, maintenance noise is at least as annoying as the noise from passing trains. The impact of railway noise increases steadily with noise levels so that above at least 45L,, dB(A) there is no particular “acceptable” noise level where annoyance begins. At high noise levels (beginning above 50-65 dB(A)) railway noise is less annoying than aircraft or road traffic noise of an equivalent level. In England, railway noise bothers considerably fewer people than does either road traffic (about one-tenth as many) or aircraft noise (about half as many). 10.2. A NOISE INDEX FOR RAILWAY NOISE Reactions to railway noise are more closely related to 24 h L,, dB(A) than to any other accepted environmental noise index which gives a different weighting to number of events or a greater weighting to numbers of night-time events. However, estimates from the survey are not precise enough to confidently reject other number or time-of-day weightings. Similarly, the A-weighting for L,, cannot be rejected even though residents’ responses are somewhat more closely related to Linear-, D- and B-weightings. The possibility that increased ambient levels reduce railway noise annoyance by an important amount can be rejected. 10.3. RAILWAY OPERATING CONDITIONS Overhead electrified routes are estimated to be less annoying than diesel or third-rail (electrified) routes by the equivalent of about 10 dB above 55L,, dB(A). The differences in reaction persist when many possible confounding variables’ effects are examined. Though a Linear-weighting for L,, greatly reduced the traction-type annoyance gap, the basis for the difference in reactions has not been fully explained.

RAILWAY

NOISE

REACTIONS

IN GREAT

247

BRITAIN

There is no evidence that train speed or rise-time increases annoyance with railway noise. Respondents’ reports and some correlational evidence suggest that some types of passing train noise (banging, wheels crossing joints), may increase annoyance beyond what would be expected from the noise level itself. The presence of other railway related noise and non-noise characteristics may increase annoyance with the passing trains’ noise. Evidence for an additional annoyance for freight traffic is mixed. After the possible effects of errors in noise measurements have been taken into account, it appears to be unlikely that the distance from the railway route or the visibility of the railway would increase annoyance above what would be expected from the noise level itself. AND PERSONAL CONTEXT 10.4. THE NEIGHBOURHOOD Most of the objective characteristics of neighbourhoods and demographic characteristics of respondents are unrelated to railway noise annoyance (social class, quality of neighbourhood environment, ambient noise level, type of dwelling, type of tenure, size of household, education). No evidence was found that a closer specification of individualized noise exposure than that at the house facade would increase the closeness of the noise/annoyance relationship. There is evidence that annoyance decreases for older houses, older people and people who have always lived in their present house. Some evidence suggests that annoyance is increased by the legitimacy that is given to railway noise problems by knowing that neighbours have complained or that local tax rates have been reduced because of the noise. Railway noise annoyance is not related to general feelings about railways as transportation modes, but is closely related to a more specific, localized set of attitudes about the neighbourhood (attitudes towards other aspects of the neighbourhood), the railway as an environmental intrusion in the neighbourhood (attitudes towards the dirt, smells, vibration or danger from the railway) and the possibility of reducing railway noise levels in the neighbourhood. The observed interactions between many of these variables’ effects and noise level effects suggest that these localized attitudes have less effect on noise annoyance at low noise levels. In such cases it is the reactions of the most annoyed types of people which are most closely related to noise level.

ACKNOWLEDGMENTS This research has been supported by the Science Research Council Grant B/RG/3777.3 and British Railways. The project has been conducted in accordance with Science Research Council guidelines which provide for open publication of all results without interference by any sponsor. We are indebted to many staff members of ISVR and University of Southampton. Special acknowledgements are due to Professor J. B. Large, Mr C. Walton, Mr P. Winter, Mr C. Krizek, Mr T. J. Tomberlin and Mr A. Burns. Assistance was also provided by the staff of Social and Community Planning Research and employees of British Railways.

RELATION

OF THIS ARTICLE

TO PREVIOUS

PUBLICATIONS

ON THE

STUDY

More than 25 publications, papers and reports have been produced on this survey during the last six years. Most of these were either preliminary or offered only a broad overview of the findings. This article incorporates some revisions in earlier conclusions about relatively minor issues. It contains less detail than ISVR Technical Report No. 102 about the traction type effect, study m&hods and a few other topics [16, Fields and Walker 19801. The most detailed information about the railway versus other source

248 annoyance reactions and Walker 19821.

J.M. FIELDS AND J.G. WALKER is in the recent

Journal

of Sound

and

Vibration

article

[27, Fields

REFERENCES 1. Command 2056 1963 Noise: final report of the Committee on the problem of noise. London: Her Majesty’s Stationery Office. 2. T. NIMURA,T. SONE, M. EBATA and H. MATSUMOTO 1975 Noise ControlEngineering 5, 4-l 1. Noise problems with high-speed railways in Japan. 3. M. KUMAGAI, S. KONO, T. SONE and T. NIMURA 1975 Proceedings of Internoise 75, 429-432. A consideration on the rating of train noise from ordinary railways. 4. A. TAMURA and S.GOTOH 1977Proceedings of the 9th International Congress on Acoustics, Madrid, 31. Community response to outdoor noise at the sites exposed to road or railway noise. 5. D. AUBREE 1973 Technical Information Report No. 88, Bolt, Beranek and Newman Inc. Acoustical and sociological survey to define a scale of annoyance felt by people in their homes due to noise from railroad trains. (An English translation of “Enquete acoustique et sociologique permettant de definir une Cchelle de la gene eprouvee par l’homme dans sons logement du fait des bruits de train”. Paris: Centre Scientifique et Technique du Bbtiment.) 6. D. AUBREE 1975 Centre Scientifique et Technique du BLitiment, Nantes, Report EN-SH-75.2. La gene due au bruit de trains. (Annoyance due to train noise.) 7. D. WALTERS 1969 Proceedings of the Conference on Architectural Psychology, University of Strathclyde, March 1969. Annoyance due to railway noise in residential areas. 8. J. R. HEMINGWAY 1975 Presented at the Canadian Acoustical Association Symposium on Applied Acoustics. The assessment of annoyance due to train noise. 9. R. DE JONG 1983 (to appear) Journal of Sound and Vibration 87. Some developments in community response research since the Second International Workshop on Railway and Tracked Transit System Noise in 1978. 10. V. KNALL and R. SCH~JMBER 1983 (toappear)Journal of Sound and Vibration 87. The differing annoyance levels of rail and road traffic noise. 11. G. HEIMERL and E. HOLZMANN 1978 Verkehrswissenschaftliches Institut an der Universitat Stuttgart. Ermittlung der Belastingung durch Verkehrslarm in Abhangigkeit von Verkehrsmittel und Verkehrsdichte in einem Ballungsgebiet (Strassen- und Eisenbahnvdrkehr). (Summary of this work is translated as NASA TM-75414, Determination of traffic noise nuisance as a function of traffic type and density in a heavily populated area.) 12. T. V. ANDERSEN, K. KOHL and E. RELSTER 1983 (to appear) Journalof Sound and Vibration 87. Reactions to railway noise in Denmark. 13. S. SORENSEN and N. HAMMAR 1983 (toappear)Journal of Sound and Vibration 87. Annoyance reactions due to railway noise. 14. S. KONO, T. SONE and T. NIMURA 1975 Journal of the Acoustical Society of Japan 29, 225-234. A study on noisiness of a train noise. 15. C. G. RICE 1975 Journal of Sound and Vibration 43, 407-417. Subjective assessment of transportation noise. 16. J. M. FIELDS and J. G. WALKER 1980 Institute of Sound and Vibration Research Technical Report No. 102. Reactions to railway noise: a survey near railway lines in Great Britain. 17. J. G. WALKER 1977 Journal of Sound and Vibration 51, 393-398. Factors affecting railway noise levels in residential areas. 18. L. KISH 1965 Survey Sampling. New York: Wiley. 19. R. E. WINDLE 1977 M.Sc. Dissertation, University of Southampton. Investigation of nonresponse in an interview survey. 20. J.M. FIELDS andJ.G. WALKER 1977Proceedings of Noise-Con 77, NASA Langley Research Center, Hampton, Virginia, 137-154. A national study of railway noise in Great Britain: the first assessment of its design. 21. J.M. FIELDS and T. J.TOMBERLIN 1978 Proceedings of Internoise 78, 597-600. Noise survey design and the precision of statistical results: further evaluation of the design of a national railway noise survey. 22. J.GARNSWORTHY 1977M.Sc.Dissertation, University of Southampton. A study of question order and wording experiments. 23. Arbeitsgemeinschaft fiir Sozio-psychologische Flugarmuntersuchungen 1973 Sozio-psychologische Flugarmuntersuchung im Gebeit der drei Schweizer Flughafen: Zurich, Genf, Basel. (Translation available as 1980 NASA TM-75787. Sociopsychological investigation of airport noise in the vicinities of three Swiss AiTpOTtS: Zurich, Geneva, Basle.)

RAILWAY

NOISE REACTIONS

IN GREAT

BRITAIN

249

HAWKINS 1979 Proceedings of the Institute of Acoustics Spring Meeting, Southampton. Subjective evaluation of noise in areas with low ambient levels. I. D. GRIFFITHS, F. J. LANGDON and M. A. SWAN 1980 Journal of Sound and Vibration 71, 227-240. Subjective effects of traffic noise exposure: reliability and seasonal effects. F. L. HALL 1980 Proceedings of Internoise 80,799-802. A comparison of community responses to rail yard, road traffic and aircraft noise. J. M. FIELDS and J. G. WALKER 1982 Journal of Sound and Vibration 81,51-80. Comparing the relationships between noise level and annoyance in different surveys: a railway noise us. aircraft and road traffic comparison. J. M. FIELDS 1977 Journal of Sound and Vibration 51,343-351. Railway noise annoyance in residential areas: current findings and suggestions for future research. P. GILBERT 1973 Presented at the Institute of Acoustics Meeting, Southampton. The effect of train noise on the environment. J. MORTON-WILLIAMS, J. B. HEDGES and E. FERNANDO 1978 Road Traffic and the Environment. London: Social and Community Planning Research. R. RYLANDER, S. SZ~RENSEN and A. KA.ILAND 1974 Journal of Sound and Vibration 24, 419-444. Annoyance reactions from aircraft noise exposure. BRITISH STANDARDS INSTITUTION 1975 BS 4142: 1967 Amended 1975. Method of rating industrial noise affecting mixed residential and industrial areas.

24.M. M. 25. 26. 27.

28. 29. 30. 31. 32.

33. INTERNATIONAL

ORGANISATION FOR STANDARDISATION 1971 IS0 R1996. Acoustics. Assessment of noise with respect to community response. 34. J. JOHNSTON 1972 Econometric Methods. London: McGraw-Hill. 35. F. J. LANGDON 1976 Jounal of Sound and Vibration 47, 243-263. Noise nuisance caused

by road traffic in residential areas: Part I. 36. F. J. LANGDON 1976 Journal of Sound and Vibration 47, 265-282. Noise nuisance caused by road traffic in residential areas: Part II. 37. F. J. LANGDON 1976 Journal of Sound and Vibration 49, 241-256. Noise nuisance caused by road traffic in residential areas: Part III. 38. N. D. WEINSTEIN 1980 Journal of Sound and Vibration 68, 241-248. Individual ditferences in critical tendencies and noise annoyance. 39. L. KISH and M. FRANKEL 1974 Journal of the Royal Statistical Society 36, l-22. Inference from complex samples. 40. B. R. PHILLIPS 1978 M.Sc. Dissertation, University of Southampton. The analysis of Social Science data: the ordinal-interval controversy.

APPENDIX

A: METHODOLOGICAL SOCIAL SURVEY

PROBLEMS ANALYSIS

FACED

IN THE

The survey design and analysis were planned and have been executed so as to provide information in the most useful form possible while at least addressing most of the issues

frequently raised concerning the validity of using social survey data to assess noise effects. 1. METHOD

OF ASSESSING EFFECTS OF NOISE ON PEOPLE

The percentages

of people

who report

various

section

3. Thus a large part of the direct-effect interpretation of indices’ scores. 2.

INACCURACY There

is no doubt

that respondents’ in them

one reason why many people mean

are random

if people’s

by noise levels in

with

reports

are biased

other

sampling

in the technical

A number

to estimate

variables;

on the relationships

for by the calculated

the errors is not zero.

answers to single noise annoyance

and thus are in that sense unreliable.

must be interviewed

(uncorrelated

of zero) then their effects

fully accounted

are presented

upon the

OF SELF-REPORTS

a large error component errors

effects

assessment is not dependent

statistical

The more

responses.

variance

being estimated

errors.

of experiments

average

normal

questions

have

This is of course If these

and expected

in this analysis

serious

problem

sense that the expected

within the questionnaire

could

are

arises

value of find no

250

J. M. FIELDS

AND

J. G. WALKER

evidence for such bias: respondents gave no more annoyed responses before knowing the subject of the study was railway noise than they did after 30 min of questions about railway noise; annoyance responses did not increase for people who were told that the survey was partially sponsored by British Rail; people who had heard about the survey before the interview gave no more annoyed reports; virtually no one reported serious noise effects at low noise levels (section 3); and feelings (possibly “biased” feelings) towards the railways as a transportation mode do not carry over to affect the evaluation of railway noise (section 7). That differences in question wording can affect responses indicates that these are reports about unprecisely defined basically subjective phenomena. However, we cannot find evidence that the major relationships of interest in this analysis are being “biased” by such self reports. 3.

METHOD

OF MEASURING

AND

MEANINGFULLY

SCORING

ANNOYANCE

Annoyance is measured with an index made up of answers to five separate annoyance questions (Summed Annoyance Index), but it will be seen that it was then scored in terms of a universally meaningful unit for noise studies which is labelled the Decibel Equivalent Annoyance Unit in this paper. A principal component factor analysis with iterations was performed on 18 measures of annoyance with railway noise. The first factor accounted for most of the variance (46.9% for the first factor, 7’5% for the second, 5.7% for the third). The final annoyance index was made up of five items which loaded heavily on the first factor (0.71-0.90) and were each on face validity grounds obvious measures of evaluations of railway noise effects, rather than purely descriptive statements about noise levels. Eight different methods of weighting the items to form a single index were examined (including the use of factor scores) but in the end each item was simply scored equally (the two extreme responses on each item were scored 1 and 11 with equal intervals between intermediate points) and the items’ scores were averaged (see Appendix B). The resulting index is referred to as the Summed Annoyance Index. The Summed Annoyance Index was more highly correlated with noise level than was an index of the same five items using factor weights. To give the Summed Annoyance Index scores a readily interpreted meaning scores on the Summed Annoyance Index were divided by the estimated regression coefficient (BL = 0.14) from the regression of the Summed Annoyance Index on 24 h L,,dB(A).t The resulting index scores are labelled Decibel Equivalent Annoyance Scores. The Decibel Equivalent Annoyance Unit, dB(EAU), in which they are expressed is the amount of annoyance which is caused by a single decibel change in noise level (24 h L,,). This method of measuring annoyance has the advantage of reducing some of the unreliability in the annoyance scores (by using an index) while at the same time expressing the annoyance in directly meaningful decibel units. 4.

CORRECTING

FOR THE

EFFECTS

OF

NOISE

MEASUREMENT

ERROR

The errors in noise measurements described in section 2.3.2 have two main consequences for the analysis of the social survey data: they increase the variance of the estimates of any statistic based on noise levels and they downwardly bias the estimate of the regression coefficient for the regression of annoyance on noise level. The effect of the t The partial regression coefficient was first corrected for errors in noise measurements as is described in the next section. Because of the curvilinear trend in the noise/annoyance relationship, the regression was only based on the part of the sample above 45 L,,. Thus it somewhat understates the equivalent decibel values for the 20% of the sample at these low noise levels.

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NOISE

REACTIONS

IN GREAT

BRITAIN

251

increase in the variance is routinely incorporated in this analysis because, as will be seen in the next section, the variance estimation techniques take into account correlated errors within Primary Sampling Units. The more serious effect of errors on noise measurements is to reduce the steepness of the slope of the relationship between annoyance and noise level. Both the earlier noise measurement error estimates and the results of a two-stage least squares instrumental variable analysis suggest that the true slope relating noise to annoyance should be about 30% greater than the observed slope. This has been taken into account in the Decibel Equivalent Annoyance Index by using the instrumental variable analysis estimate of B = 0.14 rather than the observed value of 0.11 in calculating Decibel Equivalent Annoyance Units. The possible effects of noise measurement errors are considered whenever explanatory variables are analysed which could be related to the true noise level (for example, visibility of the railway). The instrumental variable analyses are used for this purpose in Table 10. In other analyses, controls are introduced for both the measured noise level and a noise level predicted from topographical and train performance data (Table 14). -The analysis of the repeated noise data suggested that errors may be greater at lower noise levels. This is consistent with the observation that the noise annoyance relationship is not as steep at lower noise levels. No evidence could be found that the values of the regression coefficients were being more severely downwardly biased in some types of areas where greater difficulties in making noise measurements could have been experienced (small numbers of measured trains, poor weather, necessity to interpolate noise data, high ambient levels, judgment of the acousticians as to the difficulty of the site). While the effects of errors in noise measurements have not been completely removed, the analysis has taken steps to reduce their effects. 5.

GAUGING

THE

IMPORTANCE

OF ADDITIONAL

VARIABLES

The effects of non-noise variables (time of day, ambient levels, neighbourhood characteristics and attitudes) are all expressed in terms of the Decibel Equivalent Annoyance Units. As a result, variables are identified as being important if they can create a change in annoyance which is the equivalent of an important change in noise level. This is fundamentally different from those previous surveys which have used correlations as descriptive statistics. Such correlations are affected not only by the amount a variable can effect annoyance, but also by the extent to which the variable’s extreme values are present in the sample and by the basis used for any grouping of respondents in the analysis. In general then, the focus of the article is on the statistics of regression rather than correlation. 6.

REMOVING

THE

EFFECTS

OF NOISE

LEVEL

Additional variables’ effects on annoyance are examined only after the effects of noise level have been removed. Multiple regression is used to remove the effect of noise level in either of two ways. When the third variable (or its transformation) can be assumed to be linearly related to annoyance, the third variable is simply included in a regression equation with L,, and L&. If no assumptions are being made about the form of the third variable’s effects, the second method is used: the annoyance residuals (from the regression of the Summed Annoyance Index on L,, and L$) are examined for each category of the third variable. The chief advantages of the analysis of residuals over a similar dummy variable regression approach are that it is computationally simpler for examining large numbers of variables

J.

252

M. FIELDS

AND

J. G. WALKER

and in most analyses here it again leans in the direction of assigning all possible effects to the imperfectly measured primary noise variable. Since the residual analyses here are based on the residuals from the simple regression of annoyance on noise level, the effect of noise level on annoyance is assumed to be unchanged by the addition of third variables. This makes it simpler to express the effects in terms of Decibel Equivalent Annoyance Units. Unfortunately, if noise level and the additional variable are correlated, the effect of noise level will be changed by the introduction of the third variable. This is one of the reasons why additional techniques are needed for the more detailed examination of the traction-type effect. Where there is the possibility of an interaction between noise level and the additional variables’ effects, statistical tests for interaction effects are performed and the annoyance noise level relationships are examined within categories of the third variable. 7.

ESTIMATES LATED

OF SAMPLE

ERRORS

VARIANCES

WHICH

ACCOUNT

FOR AREA

EFFECTS

AND

CORRE-

IN MEASUREMENT

Given the enormous variability in people’s annoyance responses under similar conditions, the analysis must determine whether observed patterns are statistically significant. Inasmuch as there are study area effects on annoyance, or noise measurement errors which are shared by dwellings at a single noise measurement site (primary sampling unit) then any estimate of the variability of the sample’s estimates must also take into account these correlated errors in measurements within the Primary Sampling Units. Two commonly used methods in noise/annoyance surveys would not have been satisfactory. Standard simple random sample statistics with degrees of freedom based on the number of interviews incorrectly overestimate the precision of the sample’s findings. Another technique, aggregating the data to a homogeneous noise-group level, would not have been satisfactory in this case, because there were several homogeneous noise groups within each sampling unit. In any case, the group aggregation strategy cannot help in evaluating the significance of additional individual level variables’ effects, and gives inaccurate estimates when the groups are of unequal size. A psuedo-replication technique, balanced repeated replication, has been used here to estimate the variance of all sample statistics [39, Kish and Frankel 19741. That some such technique is essential for social surveys of noise annoyance is obvious from Table Al, in which the simple random sampling statistics underestimate the true standard deviations of partial regression coefficients by as much as factors of 2.83 (for noise level). For the percentage freight variable, the effective sample size is (1/2.23)2, one-fifth of that assumed by the simple random sample calculations. 8.

USE

OF SAMPLE

WEIGHTS

With the sample’s probability design it was possible to calculate the weights (the inverse of the probabilities of selection) which would then give a weight to each respondent proportional to the fraction of the population which the respondent represents. This procedure was followed in estimating the distribution of the population across noise levels in section 3.4 and between different traction types in section 6.1. The data have not been weighted for the other (mainly regression) analyses. The decision not to weight the sample was based on two major considerations and two more minor ones. (1) It appears that the noise measurement errors very severely bias the weighted estimates of the noise annoyance relationship. Weighting gave much lower estimates of annoyance at all noise levels, but the differences between weighted and unweighted

RAILWAY

NOISE REACTIONS IN GREAT BRITAIN

253

TABLE Al Comparison

of observed

and incorrectly calculated

standard

deviations of regression

coefficients

Summed annoyance index (Decibel Equivalent Units) is regressed ona 24 h L,, (above 45 L,,)

Partial regression coefficient, B 0.095

Observed standard deviation, ~BBO

Incorrect estimate based on simple random sample (SRS) estimates,

0.021

Ratio of (observed)/ (SRS) estimates, ~B<,/(+BSRE

UBSRS

0.007

2.83

(Note: The remaining equations all include L,, and Lzq as well as the listed variable) Percentage of traffic which is diesel powered

0.065

0,021

0.011

1.88

Percentage of traffic which is freight log,,, distance to railway line

0.059

0.045

0.020

2.23

2.84

1.72

1.66

-11.79

(m) Ambient noise level

0.12

0.10

0.07

‘1.34

Number of night-time passbys

0.02

0.05

0.02

2.68

Marital status 0 = Other)

2.89

1.03

1.02

1.01

(1 = Married;

Age (years)

-0.29

0.03

0.02

1.30

Evaluation of neighbourhood (four point scale)

-4.55

0.51

0.46

1.10

a These variables are described in more detail in Tables 6, 13 and 14. b The observed standard deviation is calculated using the balanced repeated and Frankel 19741. The sample is not weighted.

replication

technique

[39, Kish

disappeared when instrumental variable estimates were used. The weights are very unequal (varying from 1 to 490). Weights are for the most part a function of estimated noise levels, with low noise level sites having very high weights. As a result, when very heavily weighted selections which were rightly presumed to be from low noise environments (but wrongly measured as having come from a high noise environment) are combined in measured noise level groups, the estimates in that group will be totally dominated by the unannoyed respondents from the presumed low noise level environments. (2) The second major consideration is that the interest in noise policy is not concentrated at the heavily weighted low noise levels, but rather either evenly across all noise levels or perhaps especially at high noise levels. Thus, inasmuch as weighting should serve to weight the individuals in proportion to their importance for public policy, the unweighted sample is more representative than the weighted one. (3) Weighted estimates have very large variances. (4) The combination of the hypothesized bias (point 1, above) from one aspect of the sample weights (and thus questions about whether there might be other undiscovered difficulties) and the fact that no other noise survey had used weighted estimates made it likely that the use of unweighted estimates could enhance comparability in measurement and analysis procedures with previous surveys. results virtually

254 9.

J. USE

OF ANALYSIS

M. FIELDS

PROCEDURES

AND

BASED

J. G. WALKER ON

INTERVAL

LEVEL

ASSUMPTIONS

The dependent variable in all the complex analyses (Summed Annoyance Index) is based on annoyance measures which can be strictly claimed to be no more than ordinal level representations of underlying interval annoyance scales. The selection of interval level procedures has been based on an intensive analysis of this survey’s data [40, Phillips 19781 as well as considerable thought about the implications of the choice of analysis methods. It was concluded that any methodological gains from ordinal analysis methods in terms of not overstating the properties of the annoyance variable would be vastly out-weighed by the losses of other methodologies which could deal with the much more serious problems found in noise surveys. Four points support the use of interval level scales. (1) Any seemingly reasonable departure from equal interval scaling (as well as a large number of seemingly unreasonable departures) have been found to not affect a wide range of this study’s conclusions; the regression analyses which used correlation coefficients are found to be quite robust with respect to scale scoring alterations [40, Phillips 19781. (2) Only interval level techniques made it possible to provide the descriptive information outlined above which would be useful for noise policy (e.g., the decibel equivalent of third variable’s effects). (3) The interval level assumptions are felt to also provide a better balance between Type I and II errors of inference. (4) Only interval level techniques provide the well understood approaches which can provide a considerable degree of control over the other major noise/annoyance survey analysis difficulties: adjusting for errors in noise measurements; simultaneously controlling for large numbers of variables; increasing reliability of annoyance measure; controlling for the continuous noise level variable.

APPENDIX

B: ANNOYANCE

SCALES

The two most often used annoyance scales in this article are the categorical rating scale and the Summed Annoyance Index. The categorical rating scale is the first item (Q17a) in the Summed Annoyance Index. 1.

QUESTIONNAIRE

ITEMS

INCLUDED

IN THE

SUMMED

ANNOYANCE

INDEX

The numerical value for each answer was used in the averaging procedure below.

described

Q17. a REFER TO QlOa: Can I just check, you said you did/did not hear train noise (Not hear = 1) here? b Does the noise of the trains bother or annoy you (4) Very much, (3) Moderately, (2) A little, (1) Not at all. (For measures of high annoyance, “very annoyed” in this article, “very” annoyed is scored “1” and all other valid data are scored as “O”.) QlO. a Coming back now to your house/flat. When you are indoors, do you ever (No = 0) hear. . . trains? , bother or disturb or annoy you at all? b Does noise from. . . trains. . (No = 0, Yes = 1) Definitely Qll. b In particular, how do you feel about Satisfactory 1 the amount of noise here from passenger, to goods, and other trains? (SHOW CARD D) Definitely Unsatisfactory 7

RAILWAY

NOISE

REACTIONS

IN GREAT

BRITAIN

2.55

Q43. a If you had the choice, would you rather live in a place where there was no railway noise at all, or in a place where you could sometimes hear some noise from the railway? b Here is a scale showing the different amounts of railway noise that there might be in an area. (SHOW CARD Gl IF CODE 1 ABOVE, CARD G2 IF CQDE 2 ABOVE.) What number would you pick to rate the place where you live now? (Gl: No railway noise at all) (G2: The amount of railway noise that would be perfect for you) 1 2 3 4 5 6 7 8 9 The worst imaginable amount of 10 railway noise. Q61. Now, just to be sure that I have it all straight. How do you feel about the amount of noise here from passenger, goods and other trains? (SHOW CARD J) 1 Definitely satisfactory 2 3 4 5 6 7 Definitely unsatisfactory 2.

SUMMED

ANNOYANCE

SCALE

The reasoning behind the Summed Annoyance Index is explained in Appendix A. (The slightly different earlier version of this scale, “5 item general annoyance index”, is used in section 6 at several points. It differed from the Summed Annoyance Index only in that people who reported that they could not “hear” railway noise were given lower annoyance scores on each of the component items.) The five items listed and coded as above were averaged after being re-coded according to the following formula (question numbers are used to identify items): ((QlO)xlO)+l; QlOa and b, (((Qllb - 1)/6) x 10) + 1; Qllb (((Q17b - 1)/3) x 10) + 1; Q17a and b, (((Q43 - 1)/9) x 10) + 1; Q43, (((Q61- 1)/6) x 10) + 1. Q61,