THE RESPONSE TO RAILWAY NOISE IN RESIDENTIAL AREAS IN GREAT BRITAIN

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1 Journal of Sound and Vibration (1982) G(2), THE RESPONSE TO RAILWAY NOISE IN RESIDENTIAL AREAS IN GREAT BRITAIN J. M. FIELDS? AND 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 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 and Canada [8, Hemingway The British railway study in 1975 f Now at NASA Langley Research Center, Hampton, Virginia 23665, U.S.A X/82/ Academic Press. Inc. (London) Limited

2 178.I. M. FIELDS AND 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 In addition to these field studies, two laboratory studies have been completed [14, Kono et al. 1973; 15, Rice 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 ) The National Railway Proximity Cartographic Survey conducted in the planning stage for this study divided the entire miles of railway routes into 3098 sections,

3 RAILWAY NOISE REACTIONS IN GREAT BRITAIN 179 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 selection techniques. They are not distinguished from other areas in the analysis in this article.) Each study area was visited and divided into noise strata on the basis of a railway noise prediction technique [17, Walker 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 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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5 RAILWAY NOISE REACTIONS IN GREAT BRITAIN 181 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 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] DATA COLLECTION 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 Seventy-four percent of the interviews were completed between 15 October and 18 December 1975 with 99% being completed by 31 January All interviews were completed in a study area before noise measurements were begun there 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 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

6 182 J. M. FIELDS AND J. G. WALKER 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 A- weighted 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 Hz; reference site: *2 db from 50 Hz to 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 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

7 RAILWAY NOISE REACTIONS IN GREAT BRITAIN 183 neighbourhood environment which is uncontaminated by the respondent s own subjective feelings about the neighbourhood environment (section 7.1) 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 NOISE DATA EVALUATION The analogue tape recordings were analyzed and evaluated in the ISVR laboratory 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,, ( ), 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

8 184 J. M. FIELDS AND J. G. WALKER 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 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;= = 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 = , the reliability coefficient for the noise level is (151* /151*99) = The method for correcting for noise measurement errors in the social survey analysis is described in Appendix A 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 EVALUATION OF THE SURVEY METHODOLOGY 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.

9 RAILWAY NOISE REACTIONS IN GREAT BRITAIN COMPLETE 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 activity interference from train noise. -, Q21 *... Stop talking or pause or speak louder. in the back garden ; ---, Q19f, g, h.. made it hard to hear... TV. when the windows are open ; ---, Q20e, f, g... make you stop talking, pause or speak louder... when the windows are open ; , Q18a (iii)... interfere with listening to radio or TV ; --, Q18a (v)... interfere with conversation ;......, Q18a (ii, vii).. wake up... or.. interfere with sleep ; -.. -, Q18a (i). startle you. 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

10 186 J. M. FIELDS AND J. G. WALKER 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 to railway noise. -, Q27a.. make you keep doors or windows shut ; --, Q30b.. double glazed at least partly because of the railway noise ; - -, Q46a. complained about railway noise. hi... 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.

11 RAILWAY NOISE REACTIONS IN GREAT BRITAIN h L,(dB(A)) J 8( 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 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.

12 188 J. M. FIELDS AND J. G. WALKER 3 I/y : ; x x I I * I x I x xr2x.x I x*x I i x XI 2x x3. x:x: I x 1x1 x f x *I x XXI I 2 *xxxx IX. I x x x x xxx x II : 12 xx :. x I I x :2 xx3 2 1 I x : xx 22 x x i I x2 xi I x I I 2 IX xx x xx2 3, xx- x 2 2: 3 ;:; x xx 2 I x2 2 2r x x 2 x 1341 II I I xx 3xxx I22 I 4x 4x x x 1. ;. : 3 XIXXXI :. XX 2x :. 2 x I xx x2 IX I xx2 2 2 x2 2 xxx I I x I xx XX" a xx x x x r2r ; II x '; 2 xx 4x XI xx 34 2 xx : x I x2 223 XI 3x 3 r3 22 2, 3 x2 I I : xxx 2 x I 2x 2x 2X2" I x:2 2x IX 2r 2x i 32x s 2: xx 23 Y 22 x4 x x i&t 222 2x r 2 x 2 2 x xx x2 I 2 2 x I 2x 32x 3 X3& 25 2 x*3 xx xx x x r2 x I x II x.x 2x2 6 xx 2 II 2 I i; x 22 x 532 x4 4 x x 32 rr2 2rx x2 x3, 38.x I I 4rr x 1 x 3 2 ;h 5, 5 6 4xr 4x x I I 1 24x 2x x2 11" 2 22 I II 41 2 x23 2 4x 2 4 3x "I 46 x r r 2, rr5 7x *2.a 2 x ;, 22 L3 2x 42 p " x s 32x IX xx h L,@ (db(a)) Figure 6. Individuals annoyance by noise level. (The number of individuals at each point is indicated. One respondent is indicated with x ; nine or more is 9.) 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 h L,(dB(A)) Figure 7. Annoyance by noise level (in 5 db groups).

13 RAILWAY NOISE REACTIONS IN GREAT BRITAIN 189 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 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

14 190 J. M. FIELDS AND J. G. WALKER 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 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 *00139 x L,, x LZJ, but in fact the regression coefficient for the Lzq term is not statistically significant in an equation which already includes L,,. If the sample is split at 45L,, and separate 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,

15 RAILWAY NOISE REACTIONS IN GREAT BRITAIN 191 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 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 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 and Germany [lo, Knall1983; 11, Heimerl and Holzmann 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 Japanese data reviewed [28, Fields 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 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 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.

16 192 J. M. FIELDS AND J. G. WALKER TABLE I Number of dwelling units and residents at three levels of railway noise in Great Britain 60 and above 65 and above 70 and above Noise level (24 h L,, db (A)) Dwelling units Residents r \, \ Standard Standard No. of deviation 9.5% deviation 95% dwelling of confidence No. of of confidence units estimate interval residents estimate interval oooto to to to to to 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 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 estimate is about * 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 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 Hearing (95% confidence interval), Road traffic Aircraft Children Animals People Trains Factories Construction (*l.l) (*2.1) (*3.0) Being bothered, (ko.4) (+1.8) (*0.4) disturbed or annoyed Being the most bothersome t Percentages are cumulative; e.g., the 88.6% hearing road traffic noise includes the 22.9% who are bothered. This table is based on data from a study of road traffic noise in England. 95% confidence intervals are given in parentheses for the three sources for which they were specially calculated using the successive differences technique. All other estimates come from figure 7 of the road traffic survey report [30, Morton-Williams er al

17 RAILWAY NOISE REACTIONS IN GREAT BRITAIN 193 [30, Morton-Williams et al (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 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. I I I00 Average peak nme level (db(a)) Figure 8. Reactions in number categories. Number of passbys per day: 0, O-99; 0, ; +, ; x, ; & 500 and over.