Subjective assessment of transportation noise

Journal of Sound and Vibration

SUBJECTIVE

(1975) 43(2), 407-417

ASSESSMENT

OF TRANSPORTATION

NOISE

C. G. RICE Institute of Sound and Vibration Research, University of Southampton, Southampton SO9 5NH, England (Received 5 May 1975) 1. INTRODUCTION

In an age when political and administrative factors influence the choice of evaluative and predictive community noise criteria, it is inevitable that convenience and hence compromise will influence the choice of means of expressing the physical characteristics of the exposure problems produced by transportation noise sources. This situation is not, however, entirely created by the administrator, because from the scientific point of view it must also be realized that in spite of considerable research effort there is still no substantiated unit that will consistently assess subjective reactions to noise. The problem is not new, it is well documented and the cause of considerable consternation. Most rating-scale units (such as dB(A), PNdB, PLdB, EPNdB, etc.) are equally poor in predicting subjective noisiness reactions to noise although slight modifications of these in specific instances do increase the correlation. Because of this established fact, the choice of dB(A) to form the basis of a modifying noise criterion only has merit if consideration is taken of its simplicity and universal incorporation with noise-measuring and analysis equipment. Furthermore, far more use and acquired data has resulted from dB(A) measures than for any other single unit, and this considerable experience has been reasonably well documented. In the U.K. the major sources of transportation noise are road traffic, aircraft and railways. These are currently rated for environmental planning purposes by L,, (18-h), NNI (Noise and Number Index), and dB(A) peak, respectively. Each can be expressed in terms of an “A”-weighted measurement, so that the choice of dB(A) as a basic rating-scale unit upon which to base a unified transportation noise criterion seems reasonable. The form of such a criterion needs further detailed consideration, as does the unifying relationship (e.g., LDN, Lea, LNP, etc.); however, any attempt to predict the annoyance responses of communities exposed to noise requires contributions from both the physical characteristics of the exposure (perceived noisiness) and the attitudinal and environmental activities of the observer (psycho-social variables). A working definition of perceived noisiness (after Kryter [ 11)is “the subjective impression of the unwantedness of a not unexpected, non-pain or fear-producing sound as part of one’s environment.” Description terms such as disturbing, unwantedness, unacceptableness, objectionableness or noisiness fit the total attribute of “perceived noisiness” and are fairly consistently used by subjects in psychological judgment tests. Rating-scale units which may be used to express perceived noisiness are dB(A), PNdB, EPNdB, etc. Annoyance on the other hand (after Borsky [2]) is defined as being a feeling of displeasure associated with any agent or condition realized or believed by an individual or group to be adversely affecting them. While it is often useful or necessary from an analytical point of view to focus attention on a single environmental agent-(such as noise, for example) it should be recognized that the single agent appears in real life as one of a complex of environmental stresses. Annoyance, therefore, includes both perceived noisiness and psycho-social variables, and may be expressed in terms of relationships such as NNI, L,, (18-h), etc. 407

408

C. G. RICE

Whilst there is little doubt that perceived noisiness judgments can be made in the laboratory some doubt has been cast on the validity of similar annoyance studies. More recently, however, it has become apparent that provided the experiment is adequately designed, useful indicators of weakness in community annoyance criteria may be studied in the laboratory. The purpose of this paper is to concentrate on the perceived noisiness components of community noise criteria, and to show that useful contributions towards our understanding of the “noise problem” may be achieved if closer account is taken of the inadequacies shown by existing rating-scale units. It should be noted that the “noise problem” is not limited to the reactions of noise exposed “communities”; the noise “sources” themselves are being increasingly subjected to control and legislative procedures. These restrictions often impose high development, production and operating costs, and in consequence, when required to meet obligatory noise standards, the rating scale unit used should not be seen to favour one “source” rather than another. 2. PROBLEM

DEFINITION

Any comprehensive urban noise model ideally requires a physical expression of the noise in terms of a unit for which equal magnitudes represent equal subjective responses. At present whilst it seems that the choice of an “A’‘-weighted unit might be as convenient as any, it is also a well-known fact that sounds of equal dB(A), L,, or LNP,for example, do not evoke equal perceived noisiness or annoyance responses. A recent in-house perceived noisiness laboratory experiment illustrates this point quite clearly (see Figure 1).

50

60

70

80

Peak dB(Al

Figure 1. Subjective reaction to different transportation noises. 1, Diesel goods train; 2, electric passenger train; 3, simulated STOL T/O; 4, continuous traffic noise.

A unifying criterion inevitably therefore will involve the use of corrections between the different noise sources in order to account for the inability of the chosen rating-scale unit to effectively align the physical characteristics of the noises when judged to be subjectively equal. These corrections are ideally suited to being investigated under laboratory conditions as they exclude the emotive overtones which precipitate annoyance reactions and concentrate more on relative comparisons of the different noise characteristics. Straightforward perceived noisiness comparisons of the physical characteristics of noise therefore result, and these are of particular value to the “source” problem where greater accuracy is required (e.g., noise certification of aircraft, vehicle noise regulation, etc., to within + O-5 dB) than the + 10 dB acceptable in normal “community” studies. The concept of the “subjective correction” to rating-scale units is one that carries with it great attraction, because it allows a unit to be chosen on political rather than scientific merit.

409

SUBJECTIVE ASSESSMENT OF NOISE

Laboratory experiments lend themselves very well to this task of correcting the chosen units, because they enable “perceived noisiness” judgments to be made with great precision, the results of which may then be incorporated into annoyance criteria. When considerable efforts are currently being made to unify subjective reactions to all types of community noise by such schemes as L,, and LNP, it seems obvious that such “subjective corrections” could improve the claims of these units by reducing some of their inherent error. That psycho-social variables appear to dominate noise exposure terms in the formulation of noise criteria is no excuse for neglecting to attempt their obvious need for correction. In fact in the legislative control of “source” noise the manufacturers should have a moral, if not legal right to a jury concept laboratory test of their product, if they felt it was being unfairly penalized by inadequacies in the measurement unit,

3.SENSITIVITY

OF PHYSICAL

MEASURES

In trying to find an ideal noise unit two factors are important : firstly, the ability of the unit to be sensitive to changes in the physical characteristics of the noises under consideration; and, secondly, the ability of the unit to produce equal numerical values for judged conditions of equal noisiness or annoyance.

-10

0

(12 1

+10

Time

(13)

(s)

Figure 2. Time history of test signals of traffic noise study.

Illustration of the first is taken from a recent traffic-noise study [3] in which a complex set of varying traffic-situation noises were aligned at equal background noise levels (see Figure 2). The measured physical values of this set of noises produced the following approximate ranges (and standard deviations, a,) : L,,-12(4.0)

dB(A),

Peak-20(7*0)

L,,-17(6*0)

dB(A),

L,,--25( 10.0) dB(A),

NNI--2q6.5)

dB(A),

TNI-55(24-O)

dB(A), dB(A).

On this basis it could be argued that LNp is a far more sensitive index to changes in the physical parameters of noise than is Lea,and therefore should be preferred. To counter this

410

C. G. RICE

argument, however, when the same set of noises was judged subjectively the standard deviations, a,, of their numerical values at the equality levels were as follows : L,,--1.8 L,,-2.0 Peak-2.3

dB(A), dB(A),

L,,-3.5

dB(A),

NNI-5.7

dB(A),

TNI-18.3

dB(A), dB(A).

On this basis it could be argued that L,, is a far more efficient unit than LNp in rating the noisiness of the set of sounds. It is obvious, therefore, that some balance has to be set between the sensitivity of a unit and its subjective worth. A proposal is made that the best unit would be the one which allows maximum flexibility and sensitivity of physical measurement (i.e., large a,) with minimum subjective scatter (i.e., small a,) at the judged equality levels. This factor is defined as the Goodness Factor (GF) and is the ratio of the standard deviations of the unit values of the noise set: therefore, GF = ~,/cr~. The lower the GF the better the unit. Application of this technique to the traffic noise situation gives the following approximate values: L~()-O.30, Peak-0.30,

L,,-O*50, TNI-0.76,

L,,-O*35,

NNI-088.

It can be seen that the Llo measure gives the best result in the traffic-noise situation and this reflects the wisdom of its choice in planning procedures. This measure does not always reflect the best choice for other transportation systems, in particular aircraft and railways where its use has been actively discouraged because of the relatively fewer events and their non-normal distribution of noise levels. In some circles dB(A) peak is being actively canvassed as an alternative aircraft-noise measure and it is already in use for the railway-noise situation. Hence the choice of units available for a unifying index seem to centre on “A’‘-weighted peak, L,, or LNP measures. Some caution is recommended with the use of approximated formulations for L,, and

Relative

Figure 3. “A”-weighted Figure 2 for key.)

statistical distribution

level (dB(A))

of four traffic noises aligned for subjective equality.

411

SUBJECTIVE ASSESSMENT OF NOISE

LNp when the instantaneous noise levels are not normally distributed. By way of example, if the results previously discussed are examined in more detail we see that the GF changes if approximations are used. Reference to Figure 3 shows that many of the noises in the traffic noise set were not normally distributed and calculation of the Goodness Factors obtained by using analogue to digital conversion and real-time analysis facilities (RTA), the B & K Dosemeter and the B & K Statistical Distribution Analyser reveal the differences shown in Table 1. TABLE

1

Goodness factors for some measures applied to traJic noise

Unit (traffic study) L eQ1= Energy Mean (RTA) Lee2 = Dosemeter Lq3 =

Ll + (Lo

- Jw2/57

LNpl= LcqJ + 2.56 ~7 LN,q = Le,,Z+ 2.56 Q LNpJ = Leq, +

2.56 u

LNP4 = LeqJ + &J

-

‘%I?)

LNP5 = LsqZ + (LlO

-

L90)

%I%

0s

=1,

1.92

4.51

0.42

2.11 4.54

4.39 2.78

0.48 1.63

8.87 10.36 10.62 9.16 9.98

0.40 0.42 044 0.45 0.45

3.51 4.45 4.63 4.12 4.54

In view of the relative complexity and inconvenience in calculating the true energy mean (L,,J and the apparent drop in sensitivity of its approximated equivalent (L,,,), LNPseems a rather more stable compromise as it seems less sensitive to changes in these approximations, the standard deviation term appearing to dominate the relationships. 4. EXPERIMENTAL DATA In a recent laboratory study by Powell and Rice [4] to determine the subjective responses to aircraft noise in different road-traffic background-noise levels, various rating-scale units and criterion concepts were examined. Subjects were asked to rate the same aircraft sounds presented to them on separate occasions in differing but continuous traffic backgrounds using a numerical category scaling method. The results were analysed using regression and analysis of variance techniques. There was no major or consistent difference between the predictive ability of the various rating-scale units used in the assessment of the subjective reactions to the aircraft noises. The mean correlation coefficients obtained by separately relating the subjective scale values to physical values for each background noise condition being as follows: L, = 0.983,

PNdB

z- 0.983,

L,, = O-985,

PNLT

=: 0.981,

L,, = 0.980,

EPNdB = 0.973, PLNB = 0.987.

L,, = O-969,

As only slight differences occur between the correlation coefficient values, it is felt that sufficient justification can be made for the choice of dB(A) as the preferred unit. This supports the conclusion drawn earlier that the convenience of the “A’‘-weighted unit outweighs the claims of its more complicated rivals. Figure 4 shows that in general the mean subjective score values for a given aircraft noise deereased with increasing background level. The slopes of these regression lines are not

412

C. G. RICE

01 40

50

60

70

Lp, @3(A))

Figure 4. Regressions of mean subjective scores for aircraft on dB(A) for different background traffic noise 32.3; C--, 37.1; ?? ------, 46.4. conditions. Mean background noise level, dB(A): o -,

significantly different, and assuming common slope for the different background levels reveals that the trend is significant at the 0.01 level. This means that judgments of aircraft noise can be directly related to background-noise level, and in this particular case an increase in background-noise level of 14 dl3 is equivalent to an apparent reduction in aircraft-noise level of 5 dB, a finding which supports earlier work by Pearsons [5]. The responses to individual aircraft noises were then examined using the LNPconcept for a triangular-shaped noise event, attributable to Robinson [6]. Figure 5 shows the regression of

L,,(dB(AN

Figure 5. Regression of mean subjective scores for aircraft on noise pollution level. Mean background noise level, dB(A): o, 32.3; Cl, 37.1; 0.46.4.

mean subjective scores on noise-pollution level (with 95 % confidence intervals) which has an associated correlation coefficient of 0.983. This has the same value as the correlation coefficients obtained for SSV vs. dB(A) for each background condition separately; when this same data is pooled the correlation coefficient drops to O-953. These results indicate the increased efficiency of the LNp concepts in this particular case, and shows encouragement for the way in which account is taken of the background-noise changes.

SUBJECTIVE

ASSESSMENT OF

413

NOISE

TABLE 2 Data from tests on effect of background level Traffic background level zY-zZz$

Aircraft study Mean subjective response Standard deviation

4.350 0.147

3.961 0.159

3.415 0.163

Lo (mean background level) L 90 L 50 L 10 u

32.3 32.0 37.3 56.4 10.2

37.1 38.0 42.4 56.8 7.6

46.8 46.8 51.2 57.5 4.4

L,, (dosemeter) LNp= L,, + 2.56~

52.2 78.3

52.3 71.7

53.2 64.5

Of more importance than the effect of background level on subjective response scores of ratings for individual flyovers is the effect of background level on long-term exposure. In order to investigate this effect the mean subjective scores obtained within each backgroundnoise session were correlated with L,, and LNp values determined for those sessions (L,, was determined by the energy dosemeter method and L,, from this L,, value plus 2.560, where CJ was the standard deviation in level over the session obtained using real time analysis facilities). The test session and subjective acoustic data are shown in Table 2.

3

j 60

1

I 70

;3”0

L,ddENN)

Figure 6. Regressionof mean session score on noise-pollution level. Figure 6 shows the results of the regression of the mean response on LNp with 95 % confidence limits. Of particular interest are the small differences between L,, and L10 values for the different test sessions, and this result confirms the earlier opinion about the relative physical insensitivity of the L,, concept, Although laboratory verification under much wider conditions is necessary to give conclusive evidence of the validity of LNP,it is still interesting to note that similar support for LNp was found in a social study survey by Bottom [7]. In comparison with the earlier Goodness Factors for varying forms of L,, and LNp the correlation coefficients with SSV in this latest study are as shown in Table 3. Because the instantaneous noise levels in this study were normally distributed, the use of approximated relationships is permitted. For significance the correlation coefficients need values of O-997 and 1-Oat the 5 % and 1% levels, respectively. The results again confirm the superior ability of the L,, concept over that of L,,, and in

414

C. G. RICE TABLE 3 Correlation coeficients for the aircraft noise study Unit (aircraft study) L eq~= Energy Mean Lcsz = Dosemeter Leq3= LX?+ (LlO-L&/57 LNP~= Leqf + 2.560 LNPZ= Leqz + 2.56a LNP~= Leql + 2.56~ ‘5NP4

= L,,,

+

@I,

-

L9o)

LP5

=

+

&o

-

L90)

L es2 L -

Lpb0

J&Z

&P 0.42 0.48 1.63 040 0.42 044 0.45 0.45 -

L90

-

L90

-

L90

-

r 0.944 0.959 0.974 0.998 0.983 1.0 1.0 0.988 1.0 1*o

particular stress the importance of the standard deviation term. Of equal merit, however, is L,, - Lw, which is a background-corrected equivalent energy level. If this concept is used to interpret the results of the earlier traffic study (Figure 2) it is seen that the approach appears to be promising (see Table 4).

L,, - L,for

TABLE 4 the tra$ic noise study

Unit (traffic study) L es1

-

L90

L eq2 L w3 -

L90

Lq2

a

+

L90

Leqa+ Ku

as

a,

4.58 4.39 3.70 4.45 3.51

10.86 10.66 9.28 10.36 8.87

0.42 0.41 0.40 0.42 040

In many environmental noise situations the instantaneous noise levels tend to be normally distributed, so that LIO - LvOx L,, - L,, x KG. These results are still compatible with previous conclusions that LNp is superior to L,, on its own; the question is “Does L,, - Lm provide an equally efficient solution ?” If it does, then it would appear that L,, and LgOvalues of community noise measures would suffice, and this would obviate the need to measure exactly the (r term in LNp. For the present, however, it is felt that further research is required, on a wider selection of noises, in order to resolve these issues. The relative merits of the dosemeter and statistical distribution analyser also need further investigation, although the use of a dosemeter in conjunction with a background-noise reading (perhaps from a sound-level meter) should hold attraction for the administrators and planners. What is clear, however, is the limitation of the use of L,, on its own. 5. DURATION STUDY Following the studies previously discussed it was felt that it would be of importance to know how people would rate different transportation noises having a wide variety of durations. In a study carried out by Howard [8] subjects were asked to judge fifteen transportation

415

SUBJECTIVE ASSESSMENT OF NOISE

noise pass-bys (aircraft, trains, trucks and cars) of 10 dB down durations varying between 1.5 and 33 s. Instructions were to base judgments on the combined effect of level and duration of each sound, and to listen to the whole of the sound before making a judgment. Parry and Parry [9] have concluded that duration is not an inherent factor in noisiness judgments in the laboratory, unless it is introduced as an additional factor in the judgment (as it was here); and that the result is explainable on the basis of the subject measuring duration by equivalent changes in sound level. The results of Howard’s [8] study certainly confirms that a duration correction of the form lOlog7”lO (where Tis the 10 dB down duration) added to peak dB(A) measures improves the correlation of SSV on dB(A) when a duration cue is used. Figure 7(a) indicates the ranges of the regressions of each of the fifteen sounds, the

60

65

70

75

60

65

70

75

L,(dB(A))

L, (dB(A))

40

50

60

70

L,,(dB(A)l

Figure 7. Effects of duration on noisiness of transportation sounds, Howard [8]. (a) Range. of separate regressions of SSV on dB(A) and duration converted dB(A), ------, dB(A) + lOlog(T/lO); -> dWA) ; (b) pooled regressions of SW on (LB(A); 1, aircraft, 6-32 s; 2, trains, 2-16 s; 3, motor vehicles, l-2 s. (c)regressions of SSV on LNPaccording to duration; 1, < 4 s; 2,4-8 s; 3,8-16 s; 4, 1632 s.

pooled correlation coefficients being reduced from 0.95 to 0.84 in the absence of duration corrections. In view of the success when using LNp for individual aircraft sounds in the Powell and Rice [4] study, similar approaches were made by Howard in the analysis of his data. The intention was to see ifL,, offered advantages without recourse to a duration correction or to the classseparation yielded by the regressions of Figure 7(b). Regression analysis of subjective score values on LNp yielded a correlation coefficient of only O-76,considerably inferior to both dB(A) and duration-corrected dB(A). Part of the reason for this may be explained in Figure 7(c), where it can be seen that the data groups into transportation noises of similar durations. Thus the concept of LNpas applied to individual vehicles does not work when results are pooled across a wide selection of transportation-noise durations, indicating the inability of LNp to correct for the duration element. The good correlation in the Powell and Rice [4] study was due to the relatively similar durations of the aircraft used. It appears, therefore, that people have the uncanny knack of grouping sounds into clearly defined groups according to the experience in which they find themselves. This infers that,

416

C. G. RICE

depending upon the particular environment in which they live, and according to the relative amounts of exposure they receive from different transportation-noise sources, so their frame of reference for subjective assessment will vary. Because there is an infinity of such situations in real life the task for providing a unifying criterion is all the more difficult. Future laboratory experiments should therefore concentrate on creating noise sets which cover a wide range of physical values, care being taken that when different transportation noise sources are used each set also covers the same physical range. Subjects expand to fill the range of subjective scale values available to them so that careful experimental designs will be necessary in order to reduce subjects’ facility for grouping.

6. CONCLUSIONS At present, community noise sources in the U.K. are separately classified and rated, the major groupings together with their associated rating-scale units being aircraft noise (NNI), traffic noise (LlO%dB(A)) and railway noise (peak dB(A)). Reasonably well-documented procedures are available within these classifications to allow standardized instrumentation, measurement and analysis techniques to be used in order to formulate central tendency conclusions regarding subjective reactions. Moreover, theoretical methods are available which allow noise-exposure predictions to be made when changes or extensions of existing operations are required. However, these units must be judged as compromises, and as such have error and limitation, associated with them; so that it is not unlikely that a sufficiently versatile single index could be found to replace them which is at least as valid as those in use at present. Any such new noise index which is introduced must, however, be at least as accurate as each of the existing separate units, and must additionally be as easy to use and apply within existing and proposed legislation. Precedents for the choice of a single index for assessing community noise already exist, most noteworthy of which is the L,,.In the first instance therefore it might be advisable to accept the L,,(dB(A)) concept and transcribe existing separate criteria in use in the U.K. in terms of this index (an exercise incidentally that will not be without difficulty). The use of empirical corrections (such as day/night, frequency of operations, etc.) may or may not be required depending on the subjective reactions to any given noise situation. For example, a busy aircraft-traffic noise mix, whilst being variable for different modes and time periods during the day, may be constant enough between days and unique enough in itself, to allow a single 24-h L,, measure to be used. One possibly major disadvantage of Leq,however, is its inability to account for the background-noise situations. Recent studies have shown that judgments of aircraft noise are influenced by varying traffic noise backgrounds, and that whereas L,,does not account for and LNp do. The objections to LNp on grounds of its this subjective reaction, both L,,- L9,, complexity may well not be justified, providing a reasonable approximation to a normal distribution of instantaneous-noise samples is obtained. Certainly the objection cannot be on account of the difficulty in obtaining the noise-distribution histogram, nor on the arithmetic involved thereafter in calculating LNP.An additional advantage of LNp is its superior ability to account for the physical characteristics in noise, L,,being a relatively insensitive measure in this respect. In conclusion it would seem that in the first instance it is probably better to choose an index such as L,,(with simple background and other corrections as necessary), accept that it has limitations, and encourage research into the development of a more sophisticated index such as LNp as a matter of some urgency.

SUBJECTIVE ASSESSMENTOF NOISE

417

REFERENCES 1. K. D. KRYTER 1970 The E&cts of Noise on Man. New York: Academic Press. 2. P. N. B~RSKY 1972 Journal of Soundand Vibration 20,527-530. Some boom exposure effects II. 4: Annoyance reactions. 3. C. 0. RICE, BRENDA M. SULLIVAN, J. G. CHARLES, C. G. GORDON and J. A. JOHN. 1974 Journalof Sound and Vibration 37, 87-96. A laboratory study of nuisance due to traffic noise in a speech environment. 4. C. A. POWELL and C. 0. RICE 1975 Journal of Soundand Vibration 38,39-50. Judgments of aircraft noise in a traffic noise background. 5. K. S. PEARSONS 1966 Federal Aviation Administration Technical Report ADS-78. The effects of duration and background noise level on perceived noisiness. 6. D. W. ROBUWN 1971 NPL Aero Report Ae 49. A new basis for aircraft noise rating. 7. C. G. BOTTOM 1971 Journal of Sound and Vibration 19,473476. A social survey into annoyance caused by the interaction of aircraft noise and traffic noise. 8. D. A. HOWARD 1974 M.Sc. Dissertation, University of Southampton. The effect of duration on the subjective assessment of transportation noise. 9. H. J. PARRYand J. K. PARRY 1972 Journalof Soundand Vibration 20,51-57. The interpretationand meaning of laboratory determinations of the effect of duration on the judged acceptability of noise.