Community noise levels — a statistical phenomenon

Jotmtal of So,rod and Vibration (1973) 26 (4), 489-502

COMMUNITY

NOISE

LEVELS--A

STATISTICAL

PHENOMENON

H. B. SAFEER

Office of Noise Abatement, Department of Transportation, Washington, D.C. 20590, U.S.A. (Received 16 October 1972) The increasing interest in community noise levels has generated numerous community noise measurement programs. This paper is concerned with the statistical variability in community noise levels and the potential errors associated with the data collection and analysis procedures. The need for proper study design is emphasized and order of magnitude estimates of the degree of error which can be introduced by improper design are developed. I. INTRODUCTION Noise in the community is a matter of increasing concern among the public today. Sound levels are claimed to be increasing in both intensity and area coverage, as technology and engineering generate bigger, faster, and more powerful machines for use in everyday life. Although the escalation in noisiness has been arrested and reversed at the source for some types Of equipment--particularly new commercial jet aircraft--and there is a proliferation of state and local regulations specifying maximum noise levels for other types of equipment and activities, the overall noise levels in many communities seem to continue their steady rise as the number of noise sources increases and their use becomes more widespread. It is becoming increasingly unclear as to whether noise levels are increasing, whether the public is becoming more conscious of noise levels which have existed all along, or whether what appear to be measured increases in noise levels are nothing more than a statistical artifact resulting from the way in which the data were collected and analyzed. This paper addresses the third aspect o f the problem: what are the problems associated with obtaining statistically reliable and representative community noise level data and how might some of these problems be solved? The answers to many of the questions which will be raised are not yet available, and for this reason the Department of Transportation has joined with the Environmental Protection Agency to undertake an extensive program .for the measurement of community noise levels and the associated human response. 2. COMMUNITY NOISE LEVELS--STATISTICAL VARIATION Community noise levels should be treated as a statistical phenomenon varying as a function of a large number of variables. The noise level at any given point in a community is the result of the complex interaction of a large number of independent noise sources under varying atmospheric conditions and physical attributes of the area surrounding the measurement site which may serve to reinforce or reduce the sound levels between the sources and the receiver. The sources themselves may be at a fixed location, moving in a periodic fixed pattern or moving in a random pattern both in time and space. Because of the variability in noise level, location and appearance of the sources, the noise level at any given point will also 4

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vary. Such variation can occur within any given hour, hourly over the day, daily over a week, monthly over a year, or yearly over a long period of time. Thus, a single noise level value or number for a given moment in time at some fixed point in the community is not a measure o f the noise level in that community. In many cases it is not even a measure of the noise level at that particular point. The single noise level number is a statistic, subject to variation, which may or may not, depending upon the degree o f variation, be a good representation of the noise level at the measurement site. Similarly, depending upon the variation among sites, the single number for a single site may or may not be representative of the noise levels for a much larger area. Finally, even if the single number at a single point represents a representative noise level for some given point in time, it may or may not be representative of some longer time period. In order to obtain a noise level number (or set o f numbers) which is a statistically reliable descriptor of the noise environment which is representative of a given area, one must consider the following factors: number of measurement sites in an area, location of the measurement sites, frequency of measurement at each site, method o f measurement. Each of these factors will be discussed below. 3. NUMBER OF MEASUREMENT SITES IN AN AREA The number of measurement sites required to develop an accurate picture of the noise climate is a direct function o f the homogeneity o f the area with respect to noise sources. Consider, for example, the extremes o f the Mohave Desert and a large city. On the Mohave Desert one measurement site may adequately represent the noise environment o f several hundred square miles. In a large city one measurement location may be representative o f an area of less than one-twenty-fifth (1/25) of a square mile. Thus, the first determination which must be made for any community noise survey is how homogeneous is the community with respect to potential noise exposure. Homogeneity can be defined by a number of different parameters: land use, population density, and location of noise sources. L a n d use. One would expect, a priori, that a residential area would have a noise exposure different from that of a park, industrial or commercial area. This difference has been shown in a number o f different community noise surveys [1-5]. Table 1 summarizes some of the results of these surveys in terms of median (Lso) and decile (Lao and Lgo) sound levels. Population density. Measured differences in noise levels have been observed between areas of high population density and areas of low population density. Population density, however, can generally be related to land use: i.e., single family residential versus apartment houses, suburban residential versus urban commercial, and numbers and types of noise sources, particularly motor vehicles. Location o f noise sources. The number and location of fixed noise sources such as generators and large air conditioners and fixed noise source paths such as highways, train right-of-way and aircraft flight tracks, relative to the area being measured will affect the

491

COMMUNITY NOISE LEVELS

number of measurement locations required to describe the noise environment of a given area. Consider, for example, Table .2, which summarizes the median sound level as a function of type o f road nearest to the measurement locations. TABLE 1

Measured median and decile sound level as a function of domhzant land use--24 hour contbluotts movement measurement Location

A-weighted sound level (dBA) Lgo Lso Llo

3rd floor apartment, next to freeway 3rd floor high rise, downtown Los Angeles 2nd floor tenement, New York City Urban shopping center Beach on Pacific ocean Urban residential near major airport Urban residential near ocean Suburban residential near R/R tracks Urban residential Urban residential near small airport Old residential near city center Small town residential cul-de-sac Small town residential main street Suburban residential in hill canyon Farm in valley Grand Canyon, north rim Industrial area, Medford, Mass. Commerical area, Medford, Mass, Residential area, Medford, Mass. Open parkland, Medford, Mass. 270 feet from Interstate highway Medford, Mass.

72 62 62 52 52 48 45 39 44 38 43 36 36 37 29 17 48 55 43 41 58

79 69 69 62 58 56 53 52 51 47 49 42 53 49 37 23 51 58 46 44 62

84 80 74 68 63 73 61 58 60 55 58 49 47 59 44 36 59 62 54 51 66

Sources: references [3] and [51.

TABLE 2

Median sound level (Lso) as a function of type of nearest roadway

Type of road Limited access highway Major throughfare Local traffic

Median (Ls0) A-weighted sound level London noise survey 7 a.m. - 10 a.m. Medford noise survey 4 p . m . - 7 p.m. 7.30 a . m . - 8.30 a.m. 67.5 63.5 62.0

67.0 61-7 55"0

Sources: references [1] and [3]. The data in Table 2 have b6en averaged over a variety of land uses; thus the differences can be attributed to the type of roadway which was dominant relative to the measurement location.

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n.B. SAFEER

Esthnathzg the number of measurement locations The number of measurement sites within any given area should be determined independent of and prior to the selection of the specific measurement locations. Two determinations are required: first, how large an area should be surveyed as a "homogeneous sampling unit," and second, how many locations are required to arrive at a statistically reliable measure o f the noise levels which is representative of the sampling unit. As indicated in the previous section, the size and boundaries of the sampling unit can generally be determined through an analysis of the land use and any specific, identifiable noise sources. The number o f measurement locations is a function of the expected variation in a particular statistic (Lso, Ll0, Lgo, Leq) within the sampling unit. In a recent pilot study [6] for a survey of the City o f New York, it was suggested that for large cities one square mile is a reasonable choice for the homogeneous sampling unit, and that the desired number o f measurement locations to achieve a given level of precision would be 25. These estimates were based upon an assumed spatial distribution of values for the lowest decile (Lgo). The number 25 was arrived at by assuming that the Lgo level was normally distributed between locations, that the standard error was 5 dBA and the desired accuracy was a 95 percent confidence that the average Lg0 noise level would be accurate within plus or minus 2 dBA. Before this heuristic approach to determining the appropriate number o f measurement locations is to be used, better information is required as to the statistical distribution o f sound levels in different types of environments. Other studies of urban noise levels have shown a wide range o f variances about the statistical descriptors of community noise now in use (Lso, Llo, Zgo, Leg). An alternative approach is to empirically determine the size and boundaries of the homogeneous sampling unit and the number of measurement locations. This can be done through a series of measurements and a determination after each measurement cycle as to whether the sampling unit had been properly defined and whether the variance is sufficiently small.

4. LOCATION OF MEASUREMENT SITES Specific measurement sites within an area can be selected either randomly or deterministically. One form of random sampling is to overlay on a map o f an area a grid which can be used in one o f two ways. One can measure at the intersection of all grid lines or specific grid points can be randomly selected. The random location approach tends to treat an area as if it were homogeneous, and the results o f such an analysis can be treated statistically as independent samples. The major shortcoming o f such an approach is that major, fixed, noise sources may not enter into the sample. Deterministic selection relies on detailed knowledge o f the area being surveyed so that selection o f measurement sites can be made on the basis of known characteristics. Thus the location o f highways, airports and fixed noise sources can be directly determined and their influence on the noise environment can be assured o f inclusion in the survey. However, the results are not as amenable to statistical analysis since they are no longer random or necessarily independent samples, and may not be representative of the entire sampling area. There is a tradeoff between the two approaches, and depending upon the objective o f the survey one or the other may be more appropriate. F r o m a purely statistical standpoint it would not be technically correct to combine the two procedures to arrive at an estimated noise environment for an area. It may be easier to redefine the sampling area into a set o f subsampling areas and use some form o f stratified sampling to maintain statistical accuracy.

C O M M U N I T Y NOISE LEVELS

493

5. F R E Q U E N C Y O F M E A S U R E M E N T A T E A C H SITE

The number of measurement samples at each site is a function of the temporal distribution of sound levels. Other community surveys have shown that there are significant differences in the temporal distribution of sound levels. The following tables and figures show these differences. Figures 1, 2 and 3 show the 24 hour time history of the median (Lso) sound level from a number of different surveys in residential, commercial and industrial areas. While there is a significant spread between the different cities, a clear pattern emerges: low noise levels in the early morning rising to a high day-time level which falls off slowly in the evening to a low night-time level. Thus, as an initial break one may want to consider day, evening and night. In areas affected by substantial commuter traffic it may be desirable to divide the day into rush-hour and non-rush-hour time periods, and even further into morning rush-hour and evening rush-hour. If there are other discernible patterns of noise source operations it may be desirable to further break out time periods when these sources are present: i.e., construction noise may be present from 7 a.m. to 3.30 p.m., dominating all other sources. 70

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Figure I. Median sound levels in residential areas. E]---[3, Boston, Mass.; , Medford, Mass.; - - Tokyo; × - - x , Los Angeles, Calif.; I-o--1, London, England. 70

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Figure 2. Median sound levels in commercial areas. , Medford, M a s s . ; - - - , Tokyo; x , Inglewood, Calif.; F-o--I, London, England.

494

H.B. SAFEER 70

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I 23456789101112123456789101112 o.m.

p.m. Time of day

Figure 3. Median sound levels in industrial areas. Calif.;I--o--I, London, England.

, Medford, M a s s . ; - - - , Tokyo; x, Inglewood,

Similarly, there m a y be daily differences, particularly as between week days and the weekend. Such differences were observed in one study of Inglewood, California [4], as shown in Table 3. TABLE 3

Average weekday and weekend median sotmd level --Ingleli'ood, California Median (Lso) sound level (dBA) Area

Weekday

Saturday

Sunday

Residential Commerical Industrial

49 56 58

41 43 53

43 53 46

Source: reference [4]. M o n t h to month variability in the median and decile sound levels is shown in the data collected by the Department of Transportation in Medford, Massachusetts and summarized in Table 4.

TABLE 4

Median and decile sound levels--3Iedford, J~lass., March attd November 1971 A-weighted sound level (dBA) 7.30-8.30 a.m. 11.30 a . m . - 12.30 p.m. Area

Date LlO

Lso

Lgo

Llo

Lso

Lgo

Residential

31 March 1971 8 November 1971

59.0 57"9

50.1 50"1

47.1 46"3

58"0 57"9

48"0 51"1

45"0 46.6

Highway

29 March 1971 16 November 1971

68"7 68-2

66"0 65"3

63"8 62"9

66"5 67-3

62"1 63"5

58"4 60"0

10 March 1971 10 November 1971

67-7 63"6

56"3 52"8

52"5 49"7

56.8 58"0

51"0 49"9

48"9 47"4

Industrial Source: DOT files.

495

COMMUNITY NOISE LEVELS

If there have been no significant changes in the distribution of and noise level from the sources over time, one would not expect to find anything more than random differences in the noise level. In areas where there are significant changes in transportation patterns or land use, however, one would expect significant changes in the noise level over time. Thus, insofar as temporal variability is concerned, the major variables appear to be time of day and weekday v e r s u s weekend, with seasonal factors exerting an indirect effect on the use and distribution of noise sources. 6. METHOD OF MEASUREMENT After the measurement locations and the times at which measurements should be made have been selected, the next problem is how long a time period is required to obtain an estimate of the noise level distribution which is representative of the true distribution over that time period. For example, if the sound level is constant over a time period, then a single measurement of one second would be adequate for that time period. If the sound levels were cyclical and the cycle repeated itself every minute, then a one-minute sample would be adequate. At the extreme, if the sound levels were completely random, then complete accuracy could be obtained only by continuous monitoring of the sound level. Where large numbers of measurement sites are being surveyed over a number of different days and time periods, it is often too expensive to perform continuous monitoring and some type of sampling must be performed. The various sampling schemes usually involve one x minute sample where x is less than 60 minutes. These schemes are based on the assumption that the statistical distribution of sound levels obtained from an x minute sample is fairly representative of the distribution which would be obtained from a continuous sampling of the full 60 minutes. Two recent I

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level

(dBA)

Figure 4. Distribution of(a)/.1o, (b)/-50, and (e)/--9o sound level estimates froom 5 minute samples from a 60 minute tape of sound levels in a residential area with large single and multi-family dwellkngs.

496

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studies [7, 8] have shown that only under a very limited set of conditions can such an assumption of representativeness be made, unless errors in excess of 4 - 2 d B are acceptable. Figures 4 and 5 show the range of estimates of the median and decile sound levels which can be obtained from a continuous 5 minute sample of sound levels during a given hour and the true value obtained from a continuous 60 minute analysis. {o)

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Figure 5. Distribution of (a) Llo, (b) Lso and (c)Lgosound level estimates from 5 minute samples from a 60 minute tape of sound levelsin an undevelopedwooded area. The variability in sample results can be seen in Tables 5-8. Table 5 contains the range of estimates of the median (Lso), decile (Lto and Lgo) and centile (Lot and L99 ) sound levels obtained from 5, 10 and 20 minute samples and the true values from a continuous 60 minute analysis. The disparity between the sample estimates and the true value varies as a function of the sampling time, the statistic which is computed and the shape of the hourly distribution of sound levels (rectangular and skewed). Tables 6-8 contain the probability that the error (difference between sample and true value) will exceed + 1, __+2 and _.+ 3 dB, respectively. An alternative scheme has been proposed whereby "time compression sampling" would be employed. Time compression sampling is achieved by constructing an x minute sample from a series of sub-samples of briefer duration. For example, a five minute sample (300 seconds) can be constructed by using 300 one second sub-samples, or 150 two second sub-samples, or 60 five second sub:samples, or 30 ten second sub-samples.

COMMUNITY NOISE LEVELS

497

TABLE 5

Range of esthnates of distributive statistics front 5, 10, and 20 minute samples and correct vahte from 60 minute tape (in dBA) Distributive statistics

Sample duration (minutes) 5 10 20

Correct value

Tape 1--Rectangular

L99 /"90 Lso L,o Lox Tape 2---Skewed L99 Lgo Lso Llo Lot

49-66 55-67 62-70 73-76 76-83

49-61 55-66 63-70 73-75 77-82

51-56 56-60 63-69 74-75 78-80

53 58 66 74 79

40-46 42--48 dd 51 46-58 48-68

40-45 42-48 44-51 46-56 48-66

40-42 42-43 44--47 49-53 54-64

41 43 46 52 59

TABLE 6

Probability that distributive statistics esthnated from samples will have an error greater than +_ 1 dB Distributive statistics Tape 1--Rectangular L99 Lgo Lso

Sample duration (minutes) 5 I0 20

0.82 0.79 0"67

0-76 0.74 0"64

0.53 0-52 0"62

Correct value

53 58 66

LIO

0"33

0"25

0"15

74

Lol Tape 2--Skewed

0"55

0"47

0"13

79

L99 Lgo Lso Lto Lol

0"65 0"65 0"73 0"76 0-86

0"52 0"55 0"64 0"72 0-85

-0"20 0"40 0"58 0"80

41 43 46 52 59

An estimate of the reduction in errors due to time-compression sampling may be derived f r o m Table 9. This tabulation displays t]ae standard error of the sample estimates from r a n d o m continuous five minute samples, and from time-compressed five minute samples constructed from 1, 2, 5, and 10 second sub-samples. The rather limited number of cases examined tends to indicate that the degree of sampling error can often exceed any differences which may be observed over time at a given measure-

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TABLE 7

Probability that distributive ~tatistics estimated from samples )viii have an error greater than 4- 2 dB Distributative statistics

Sample duration (minutes) 5 10 20

Correct value

Tape 1--Rectangular

/-'99 Lgo LsO LIo Lot Tape 2--Skewed

L99 Lgo Lso

Llo Lot

0"65 0"57 0"39 0"05 0"23

0-55 0"50 0"35 0"02 0"I 6

0-21 0"19 0"32 -0"01

53 58 66 74 79

0.36 0"38 0"48 0"55 0"73

0"23 0"23 0"36 0"48 0"70

-0"01 0"09 0"28 0"62

41 43 46 52 59

TABLE 8

Probability that distributive statistics estimated from samples )viii have an error greater than + 3 dB Distributive statistics

Sample duration (minutes) 5 10 20

Correct value

Tape I--Rectangular

L99 Lgo Lso LI o Lol Tape 2--Skewed

L99 Lgo Lso LIo Lot

0"50 0'40 0"21 -0"07

0"36 0"32 0"16 -0"03

0"06 0"05 0"13 ---

53 58 66 74 79

0.17 0"18 0"29 0"38 0"62

0"07 0"07 0"16 0"28 0"58

--0"01 0"09 0"45

41 43 46 52 59

ment location or between measurement locations for a given time period. To some extent the degree of error can be reduced by time-compressed sampling; however, even then there can still be significant errors. It is important, therefore, that the researcher have some a priori knowledge o f the time dependent noise history in an area before designing an extensive measurement program. At locations where the noise sources are fairly homogeneous and static a small number o f

COMMUNITY NOISE LEVELS

499

TABLE 9

Comparison of standard errors for conthntous 5 mhlute samples and timecompressed 5 mhntte samples for 1, 2, and 10 second sttb-samples (continued) Distributive Continuous statistic 5 minute sample

Time-compressed 5 minute sample Sub-sample duration (sec) 1 2 5 10

Residentialarea("Rectangular"distribution--Tapel) 1.6 0.8 0.9 1.4 1-3 0.9 0.5 0.5 0.5 0.7 2.3 0.5 0.5 0.9 0.8 Lgo 3"6 0"5 0"5 0"7 0"8 L99 4"3 0"4 0"7 1"5 1"7 Undevelopedwoodedarea("Skewed"distributionmTape~ ~l 5"4 0"7 1"2 3"0 3"7 LIo 3"3 0"0 0"5 0"4 0"8 Lso 2"5 0"0 0"2 0"4 0"5 Lgo 1.9 0-0 0.0 0.0 0.0 L99 1.5 0.5 0.5 0.5 0.5 Nearm~orhighway("Normal"distribution--Tape3) ~t 1-2 0-5 0"6 0-6 1-2 Llo 0"6 0"0 0"0 0"2 0"6 L5o 0.4 0"0 0"0 0.0 0"3 Zgo 0"5 0"0 0"0 0"0 0"0 L99 0"7 0"0 0"2 0"5 0.7 Underflightpath("Bimodal"distribution--Tape~ Lol 11"6 1.2 3"2 5"3 6.5 Llo 5.6 0"4 1"3 1-7 3"0 Lso 1-5 0"5 0.5 0-5 0-7 Lgo 0"9 0.0 0"0 0"0 0"5 L99 0"8 0"4 0"4 0"4 0"5 Lol Llo Lso

short, continuous samples may be adequate to determine the shape o f the noise climate distribution. Where the sound levels are from a variety of different sources which randomly appear then either more extensive sampling or some form of time-compressed sampling may be necessary.

7. DATA ANALYSIS Further statistical errors are introduced as a function of the way in which the data are analyzed. A number of different schemes have been employed in past studies o f community noise levels and while intuitively one would expect some degree o f variability as a direct result of the technique employed, this problem is very seldom discussed in the research reports. The general methodology involves conversion of analog signals to digital data which are then analyzed to produce the statistical distribution of noise level versus frequency of occurrence. Various distributive statistics, Lso, Llo, Zgo, are then computed from the frequency distribution. In studies performed to date different size windows have been used for aggregating the digital data, ranging from a I dB window (where the values between 50.5 and 51-5 dBA are collected at 51.0) to a 5 dB window (where the values for 48, 49, 50, 51 and 52 dBA are

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collected at 50 dBA). As an order o f magnitude estimate of the degree of difference introduced by aggregating consider the results presented in Table 10. The same analog tapes as were used in the previous exercise (sampling design) were converted to digital data and collected in 1, 3, and 5 dB windows. There are differences of from I to 3 dBA between the calculated distributive statistics depending upon the methodology employed to aggregate the data. The tradeoff, once again, is between accuracy and cost.

TABLE 10

Comparison of median and decile sound levels when I, 3 and 5 dB windows are used for data aggregation

Distributive statistics

A-weighted sound levels (dBA) 1 dB 3 dB 5 dB window window window

Tape 1--Rectangular

L9o Lso Llo

58 66 74

59 67 76

59 68 77

43 46 52

43 47 53

44 48 55

Tape 2--Skewed

L9o Lso Llo

The computed values of the median and decile sound levels appear to be relatively insensitive to the starting point for the aggregation. For example, with a 3 dB window, one can start at either 49, 50 or 51 dBA and aggregate every 3 dB from the starting point. Table 11 summarizes the results of such an experiment for a 3 dB window when the different starting points O0, 0z + 1), and 0) + 2) are used.

TABLE 11

Comparison of decile and median sound level estimates as a fimction of location of start of aggregation for a 3 dB window

Distributive statistics

A-weighted sound level (dBA) Start at Start at Start at n n+ 1 n+ 2

Tape l--Rectangular

Lgo Lso Llo

58.6 67"3 75.6

58.6 67"3 75-5

58"4 67.2 75"6

43"5 47"3 53.1

43.2 47"4 53"3

43"6 47"5 53"5

Tape 2--Skewed

Lgo Lso Llo

COMMUNITY NOISE LEVELS

501

Another area where transformation of the analog signals to digital data may introduce an error involves the time over which the analog signal is integrated to arrive at the digital value, and the number of times the digitized data are sampled. The various analyzers which are available permit the operator to select the duration of integration and the number of samples per second. Thus, a one-eighth (1/8) second duration of integration yields eight digital records per second. All eight can be retained, or some number less than eight can be collected on a sample basis. Similarly, a one-fourth (1/4) second integration will yield four digital records per seond, a one-half (1/2) second integration yields two records per second and a one second integration yields one record per second. With the same two analog tapes as in the previous exercise being used, an analysis was performed to evaluate the sensitivity of the distributive statistics to differences in the duration of integration and the number of samples per second. The results are summarized in Table 12. Within the range of 1/8 to 1 second duration of integration and 1 to 8 samples per seond, the distributive statistics do not appear to vary significantly. The effect, however, of longer integration periods should be investigated.

TABLE 12

Median and decile sound levels as a ftmction of duration of hltegration and the number of samples per second Distributive statistic

Duration of integration (second)

A-weighted sound levels Number of samples per second 8 4 2 1

Tape 1--Rectangular 1/8 1/4 I/2

Lgo

57.7 x x

57.9 57.8 x

57.7 57.7 58.0

x

x

x

I

I/8 I/4 /12 I 1/8 1/4 I/2 I

66"4 × × x 74.4 × × x

66"5 66"4 × x 74.5 74"4 × x

66-3 66"4 66'6 x 74.3 74-3 74"5 x

I

I/8 1/4 112 1 1/8 1/4 I/2 I 1/8 1/4 I/2

42"8 ×

42"7 43.1

I

Lso

Llo

57.6 57.8 58.0 58"I 66"3 66"4 66"5 66"8 74.4 74"3 74.6 74.5

Tape 2--Skewed

Lgo

Lso

Llo

f

f

I

x

x

x 46-3 x

x 46"2 46"5

x

x

x 52"1 x

x 51"9 52"2 x

42"7 42.8 43.0 x 46"2 46"2 46"4 x 42"0 52"0 52-2

×

x

x

x

42"7 42.8 42.9 42"9 46"2 46"2 46.3 46"3 52"0 52"0 52.2 52.1

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H.B. s h r r r g 8. SUMMARY

The intent of this paper is to point out to the collector and the user of community noise data some of the problems associated with the data. It is becoming increasingly evident that the mere presentation o f a number or set o f numbers as being representative o f a community noise environment is quite often misleading, and in m a n y cases erroneous. The combined effects of all o f the potential sources o f statistical error can generate statistics which differ by as much as 10 dB, whereas the true noise levels m a y be, in reality, equal. The more probable statistical error range is o f the order of 3-5 dB, which, in m a n y cases, exceeds the observed difference between two places or two different time periods which are being compared. The level o f adequacy o f measurement program design must be brought up to the level of precision of the measurement and analysis equipment if studies of community noise levels are to have any meaning for policy and planning purposes. REFERENCES 1. P. H. PAR~:IN 1968 London Noise Survey. London: Her Majesty's Stationery Office. 2. T. MOCHIZUK1and N. IMAIZU~n 1967 Journal of the Acoustical Society of Japan 23, 146--167. City noises in Tokyo. 3. TRANSPORTATIONSYSTEMSCEtcI~l~ 1971 (August) Report DOT-TSC-OST-72-1. A community noise survey of Medford, Massachusetts. 4. P. S. VENEr,~LASENand AssocIATES, Santa Monica, California 1968 (November). Noise exposure and control in the City of Inglewood, California. 5. U.S. ENVIRONMENTALPROTEC'qIONAGENCY 1971 (December) Community Noise, NTID 300.3. 6. A. SENKO and P. V. KrgSHNAN 1971 (November) L. S. Goodfriend and Associates Report No. 4--1262. Urban noise survey methodology. 7. T. J. SCHULTZ 1972 Sound and Vibration 6, 18-27. Some sources of error in community noise measurement. 8. H. B. SArrER, J. E. WrSLER and E. J. RICKLEY1972 Journal of Soundand Vibration 24, 365-376. Errors due to sampling of community noise level distributions.