Road traffic noise – the relationship between noise exposure and noise annoyance in Norway

www.elsevier.com/locate/apacoust

Applied Acoustics 65 (2004) 893–912

Road traffic noise – the relationshipbetween noise exposure and noise annoyance

in Norway

R. Klæboe a,*, A.H. Amundsen a, A. Fyhri a, S. Solberg b

a Institute of Transport Economics, P.O. Box 6110, Etterstad, N-0602 Oslo, Norwayb KILDE-Akustikk, Tvildesvegen 16D, N-5700 Voss, Norway

Available online 20 May 2004

Abstract

Exposure–effect relationships between the level of road traffic noise at the most exposed

side of a dwelling’s fac�ade and the residents’ reactions to road traffic noise have been esti-

mated. The relationships are based on five Norwegian socio-acoustic studies featuring 18

study areas from two cities and a total of near 4000 respondents. The survey questionnaires

distinguish between noise annoyance experienced right outside the apartment and when in-

doors. Exposure–effect relationships for all degrees of annoyance are estimated simultaneously

from ordinal logit models. These predict road traffic noise annoyance when right outside the

apartment and when indoors, respectively, as a function of the road traffic noise level outside

the most exposed fac�ade. Separate analyses indicate that Norwegians react stronger to road

traffic noise than results from a recent compilation of socio-acoustic surveys would lead one to

believe. People having inferior single glazing windows report higher indoor annoyance.

� 2004 Elsevier Ltd. All rights reserved.

Keywords: Noise reactions; Socio-acoustic surveys; Window quality

1. Introduction

While exposures to vehicular air-pollutants have shown a significant reductionover the last decade as a result of the Auto Oil and other EU legislation and pro-

grams, exposure to road traffic noise and road traffic noise annoyance have not been

*Corresponding author. Tel.: +47-22-573-800; fax: +47-22-570-290.

E-mail address: [email protected] (R. Klæboe).

0003-682X/$ - see front matter � 2004 Elsevier Ltd. All rights reserved.

doi:10.1016/j.apacoust.2004.04.001

mail to: [email protected]

894 R. Klæboe et al. / Applied Acoustics 65 (2004) 893–912

significantly reduced in Norway [1]. To break this trend the Norwegian Parliament

has set an ambitious goal of reducing the mean population noise annoyance by 25%

before 2010. To establish a baseline figure for the accumulated annoyance in Norway

in 1999 and monitor the efficacy of the national efforts to reduce noise annoyance, a

bottom up approach was adopted by the authorities [2]:

• A national inventory of the noise exposure at all dwellings was made for all majornoise sources (transport, industrial, military and leisure activities).

• Exposure–effect relationships from an international compilation of survey results

[3] were applied to provide an estimate of the population annoyance.

1.1. Study objectives

Exposure–effect relationships are crucial for defining problem areas, environ-

mental zoning, and calculate the efficacy of and benefits resulting from noiseabatement measures. While expedient, it was clearly unsatisfactory to utilise the

exposure–effect relationships established from a mixed set of heterogeneous inter-

national studies without some form of quality assurance. Establishing a national set

of exposure–effect relationships from Norwegian socio-acoustic surveys was there-

fore deemed necessary for checking on whether the ‘‘EU-relationships’’ from Mie-

dema and Vos [3] adequately predicted Norwegian annoyance responses.

The purpose of the project was thus to establish a national reference that:

• Documents the results from the Norwegian socio-acoustic surveys and the empir-ical exposure–effect relationships for road traffic noise so that they can be included

in future compilations of international survey results.

• Can serve as a check on the assumption that exposure–effect relationships from

the most recent compilations of international surveys are ‘‘close enough’’ to con-

tinue being used for predicting annoyance in Norway.

• Serves as a baseline for subsequent studies of modifying factors utilising the same

data set. Such factors could be other environmental exposures, individual and

site-specific factors.• Provides background information for an ongoing study of the efficacy of a na-

tional noise insulation programme benefiting the 8000 most exposed dwellings 1

in Norway.

2. Study areas and sampling

The studies that were used to analyse the main research questions are three sur-veys performed in the east of Oslo in 1987, 1994 and 1996 [4] and a study in

Drammen consisting of two surveys undertaken in 1998 and 1999, respectively [5].

With the exception of the 1987 Oslo East Survey, the surveys utilised a sampling

scheme that under represents larger households [6]. After quality assurance, there

1 Indoor ðLþ3Aeq ;24 h

Þ > 42 dB with windows closed and ventilators shut.

R. Klæboe et al. / Applied Acoustics 65 (2004) 893–912 895

were 3957 respondents available for analyses of exposure–effect relationships be-

tween road traffic noise and road traffic outdoor annoyance, and 3985 for analyses of

indoor annoyance.

2.1. The Oslo east studies

The three Oslo studies were undertaken in the autumns of 1987, 1994 and 1996.

The surveys functioned as before and after studies of two separate tunnel projects,

alleviating a centrally located urban area in Oslo of through-traffic. In 1987 personal

interviewing took place in 8 sub-areas. In 1994 and 1996 telephone interviews were

undertaken in 14 areas, including the original 8. The response rate was approxi-

mately 50% in the three surveys (resulting n ¼ 1028, 1140, 1097). The sub-areas were

selected systematically to reflect areas experiencing traffic increases, decreases and

unaltered traffic situations. They were not selected to obtain a representative sampleof the inhabitants of the area. Within each sub-area probability sampling was used.

2.2. The Drammen studies

In Drammen, the first socio-acoustic survey was undertaken in June 1998 ob-

taining answers from 1215 respondents. The purpose of the survey was to describe

the environmental situation before a major rerouting of the traffic through the city.

In addition to the purposive selection of sub-areas along major roads, a randomsample was selected from the whole city area. To enhance the coverage of the areas

most affected by the road construction package planned for Drammen, 376 addi-

tional interviews were obtained in June 1999. Non-response was higher in the

Drammen study (61%) than in the previous three Oslo studies (50%). This increase in

non-response over the decade has also been observed in other surveys undertaken

during the same period.

3. Questionnaire

3.1. Annoyance questions

There were slight changes in the wording of the noise annoyance questions be-

tween the different surveys. In 1987 people’s annoyance with road traffic noise was

measured by first inquiring: ‘‘Can you hear noise from road traffic when right outside

the house in the yard, on the lawn, on the balcony, etc?’’ (The answers were ‘‘Yes’’,‘‘No’’ and ‘‘Not applicable’’). People were thereafter asked ‘‘Is the noise highly,

somewhat or not annoying?’’ 2 In 1994 and 1996 the first question was shortened to

‘‘Can you hear noise from road traffic when you are right outside the apartment?’’

2 The number of response categories was chosen in the late 1980s for the first of the surveys. For

comparison purposes, the number of categories were kept the same in the following surveys, otherwise a

5-point annoyance scale would more likely have been used.


while the second question was the same as in 1987 except that ‘‘for you’’ was added

at the end of the question.

With respect to annoyance indoors the question in 1987 was: Do you hear road

traffic noise (when) in your dwelling? (The answers were ‘‘Yes’’, ‘‘No’’ and ‘‘Not

applicable’’, and ‘‘Do not know’’). If yes: ‘‘Is this noise highly, somewhat or not

annoying?’’.In the rest of the surveys ‘‘in’’ your dwelling was replaced with ‘‘inside’’ and ‘‘for

you’’ was added to the annoyance part to emphasize that it was the respondents

opinion that was of interest, not what other persons might think. The resulting

question was: Do you hear road traffic noise (when) inside your dwelling? (The

answers were ‘‘Yes’’, ‘‘No’’ and ‘‘Not applicable’’, and ‘‘Do not know’’). If yes: ‘‘Is

this noise highly, somewhat or not annoying for you?’’ The questions in the

Drammen study were the same for both indoor and outdoor noise annoyance as in

the Oslo studies of 1994 and 1996.

3.2. Filter question, definition of degrees of annoyance

There has been a discussion on the use of filter questions (whether one can ‘‘hear

noise’’ from road traffic). The question(s) on whether one can hear the sound from

road traffic and whether this sound is considered to be a ‘‘noise’’ can be perceived as

double-barrelled. The recommendation in the new ISO technical specification [7] is

therefore to not pose filter questions. However, filter questions have been routinelyemployed in Norwegian socio-acoustic and social surveys and the analyses indicate

that the response characteristics of the ‘‘do not hear noise’’ alternative are the same

as for the other degrees of reaction. We have therefore kept this response alternative

when estimating the model.

The different degrees of annoyance are here understood as people’s answers to

verbal categories (Annoying is a translation of the Norwegian ‘‘plagsom’’). The

different degrees of annoyance can also be defined in terms of the percentiles of an

annoyance distribution from 0% to 100%. When defined as parts of an annoyancescale the term ‘‘highly annoyed’’ is defined as the upper 28% of an annoyance scale,

‘‘annoyed’’ as the upper 50% etc. – see [8].

The exposure–effect relationships, described in this paper, are defined by the label

attached to each response category. A comparison of Norwegian exposure–effect

relationships relative to those produced by Miedema and Oudshoorn [8] has been

undertaken and the results presented here. A more detailed version of this com-

parison will be presented in a separate paper.

3.3. Modifying factors

The respondents age was reported. Noise sensitivity was measured by a single

question using a 3-point scale: ‘‘Would you say you are highly, somewhat or not

sensitive to noise?’’ The survey questions on noise sensitivity were posed in all the

studies except the 1998 study in Drammen. The 1998 Drammen data are there-

fore not utilized in analyses featuring noise sensitivity as an independent variable.


Sensitivity and age were the most important modifying variables. Variables, such

as gender, having small children, marital status, education level, were not found

to contribute substantially to the model and these variables were therefore ex-

cluded from the models. This is in accordance with the findings of Miedema [9]

and Fields [10].

4. Input to the noise calculations and method

4.1. Quality assurance of the input

In the Oslo East area about 300 road segments were defined for the 2 km2 study

area. In addition to the information drawn from the public road administrations

traffic database for the streets in Oslo, custom traffic counts were undertaken atseveral important road segments and crossroads in the study area. Their purpose was

to improve the vehicular air pollution emission database and the road traffic noise

emission data.

For each respondent, the outdoor noise was calculated at the most exposed room.

This location was determined from the questionnaire questions on which streets the

different rooms faced. The choice between the possible resulting locations was de-

termined after several tests of consistency.

1. The address of the respondent’s dwelling obtained from the national telephone di-rectory was double-checked against the address provided by the respondent.

2. The respondents information on which streets they overlooked from their bed and

living room windows was checked for consistency with the address data.

3. Independent inspection by a noise expert at the address of the respondent.

For dwellings where it was not possible to decide between locations and where the

resulting noise exposure diverged 6 dB or more, the noise exposure information was

deleted and the observation not used for the exposure–effect estimations.

Noise calculations in Drammen were obtained from the County Road Authority.As their database focused on dwellings exposed to higher noise levels, a special effort

was made to supplement their database with dwellings exposed to intermediate and

lower noise levels. The data were quality assured by a noise calculation expert and

adjusted to allow the data to be pooled together with the Oslo East studies. As a

result of the quality assurance process noise calculations for 507 of the respondents

were excluded.

4.2. Nordic calculation method utilised in all surveys

The 24 h equivalent noise levels at the apartments most exposed side, LAeq;24 h, were

calculated using the Nordic calculation method. This method adds 3 dB due to re-

flection from the fac�ade [11]. In most cases the noise was calculated from one or two

dominating streets. For dwellings in a high rise area affected by noise emissions from

a larger number of streets, a terrain model was deemed necessary and subsequently

applied to obtain exposure values with the required precision. The calculated noise


values is for each of the surveys deemed to be within �4 dB of the true level, with the

exception of a small number of observations in the Drammen study having up to �7

dB. When the calculated noise exposure levels, LAeq;24 h, were less than 50 dB, they

were set to 50 dB. This was done to be on the conservative side. Because there might

be possible contributions from numerous distant noise sources not taken into ac-

count by the calculation model, calculated results below 50 dB would tend to un-derestimate the real noise exposure level. The cut off of 50 dB guards against

erroneously assuming that the noise levels are much lower than 50 dB, while in fact

they in some cases may be higher – confer with results obtained by Kropp and co-

workers [12].

4.3. Corrections for model changes and conversion to Lden

As the Nordic calculation method was revised during the time period, all calcu-lations were converted to the 1987 version, in order for the data sets to be pooled. To

make it easier to compare the results with those produced internationally, the values

have summarily been converted to A-weighted Lden values by detracting 1.4 dB from

the 1987 version LAeq;24 h values. (The Lden-values are lower than the LAeq;24 h-values in

spite of the evening and nighttime weighting because of the deduction of 3 dB in

order to arrive at free field values).

5. Statistical models and procedures

5.1. Ordinal logit models for exposure–effect relationships

As noise reactions are influenced by a variety of individual and situational factors

other than noise, it is not to be expected that any statistical model should be perfectly

adapted. However, for relationships between an ordinal variable and a continuous

independent variable such as the road traffic exposure indicator, an ordinal logitmodel [13,14] is an obvious choice.

The main purpose of the analyses presented in this paper is to provide relation-

ships between road traffic noise exposure and road traffic noise annoyance for

planning purposes. While demographic and other information is of interest for

predicting individual responses, this is not the main goal of our analyses. Simple

models featuring the noise exposure indicator as predictor for noise annoyance when

in- and outdoors were therefore formulated and estimated. The models utilize the

whole data set.

5.2. Indoor annoyance, noise exposure outside

The exposure–effect relationship for indoor annoyance should ideally have been

estimated on the basis of noise measurements or calculations for the indoor noise

exposure. We have only information about the noise exposure outside the most

exposed fac�ade. However, we do have questionnaire data on window quality. To


estimate the effect of window quality on road traffic noise annoyance when indoors,

an indicator of window quality was constructed as a combined indicator of the

quality of the bedroom and living room window. The indicator signifies whether at

least one of the windows has inferior quality (single glass). The indicator was

introduced into the exposure–effect ordinal logit model in addition to the noise

exposure (Lden).

5.3. Statistical control for modifying factors

If factors such as noise sensitivity, age group, etc. co-vary with the noise exposure

indicator or the sample is different from the population on which the results are to be

applied, neglecting modifying factors may mean that an exposure–effect relationship

only featuring the noise exposure level may be misleading. Ordinal logit models with

known modifying factors were therefore also estimated and tested see Appendix A.The purpose of these analyses was merely to check that the estimated parameter for

the impact of road traffic noise did not change too much. The Norwegian socio-

acoustic surveys are more or less alike with respect to questionnaire, noise calcula-

tions and overall methodology. It can still be argued that between survey differences

should be taken explicitly into account. A set of dummy variables distinguishing the

surveys were therefore also constructed and made part of the expanded ordinal logit

model described in Appendix A to capture survey differences.

Exposure–effect models should also take information about other environmentalexposures into account when available. The purpose of this paper is limited to

providing a baseline before undertaking such analyses and Lden is thus the only

exposure indicator utilised for the analyses.

5.4. Statistical error bands for the relationships

The estimated exposure–effect curves from the ordinal logit models are dependent

on the set of cut point estimates and the estimated parameters in front of the in-dependent variables. These parameter estimates and cut points are obtained by

maximum likelihood estimation (MLE), they are thus consistent and asymptotically

multinormal. The exposure–effect relationships are monotonic functions of linear

combinations of the cut points and parameter estimates. The standard errors for the

estimated relationships can therefore be obtained by matrix calculations given the

covariance matrix of these estimates. The estimated covariance matrix is obtainable

from SPSS and thus allows us to produce 95% confidence intervals for the estimated

exposure–effect relationship.

6. Results

All five socio-acoustic surveys were designed to over-represent sub-areas with high

traffic volumes. This is reflected in the road traffic noise level distribution – see Fig. 1.

The 1998 Drammen study contained an additional sub-sample drawn from the

L(d

B)

den

Dramm

en 1999

Dramm

en1998

Oslo East 1996

OsloEast1994

OsloEast 1987

80

75

70

65

60

55

50

45

Fig. 1. Box plot showing the distribution of road traffic noise levels Lden. Five Norwegian socio-acoustic

surveys. N ¼ 3957.


municipality as a whole. As a result we find a higher proportion of respondents with

lower road traffic noise exposure levels in this study.

The box plot in Fig. 1, show the median value (horizontal line), the interquartile

range (grey area or ‘‘box’’) and the largest and smallest observation (whiskers) not

being an outlier. Outliers are defined as lying 1.5–3 box lengths from the edge of the

box. However, there were no outliers in this plot.

6.1. ‘‘Empirical’’ exposure–effect relationships

The proportion of the residents that experience different degrees of annoyance

when right outside the apartment and when indoors have been tabulated as a

function of the noise exposure – see Appendix B.

With nearly 4000 respondents and purposive sampling, a large number of re-

sponses were obtained for all noise level intervals – see Fig. 2. The relationshipsbetween the road traffic noise exposure level and each cumulative degree of an-

noyance when right outside the apartment at each noise exposure interval should

therefore be reasonably precise. These relationships show the characteristic sigmoid

curves that indicate that an ordinal logit model might be appropriate for the sta-

tistical analysis of the relationships.

People spend most of the time indoors. For other environmental exposures such

as dust and grime from vehicular traffic, people are also more annoyed when indoors

7065605550

Cum

ulat

ive

num

ber 900

800700600500400300200100

Lden dB7065605550

Cum

ulat

ive

prop

ortio

n % 100

9080706050403020100

Does not hearNot annoyingA little annoyingHighly annoying

Lden dB

Fig. 2. People experiencing different degrees of annoyance right outside the dwelling when exposed to

different levels of road traffic noise, Lden, outside the most exposed fac�ade. Cumulative number – left panel,

and proportion – right panel. Five Norwegian socio-acoustic surveys. N ¼ 3957.


than when outdoors. However, as shown in Fig. 3 the situation is the opposite for

road traffic noise annoyance. People are less annoyed indoors than when right

outside their apartment.

6.2. Road traffic annoyance when right outdoors: model results

The results (see Table 1) from the iterative MLE of the ordinal logit model show

that Lden is a significant and substantial explanatory factor for road traffic noise

annoyance right outside the apartment. (The parameter estimates are consistent and

asymptotically multinormal.)

The estimated cut points divided by the parameter for the noise exposure indi-

cator (Lden) tells us that an estimated 50% of the respondents find road traffic noise

highly annoying at 70 dB, 50% at least somewhat annoying at 58 dB and that 50% of

the respondents report that they can hear noise at 46 dB (extrapolated). The esti-mated odds for reporting a higher degree of annoyance increases with 13%

(e0:131 ¼ 1:13) as the result of a 1 dB increase in the noise exposure indicator Lden.

7065605550

Cum

ulat

ive

num

ber 900

800700600500400300200100

07065605550

1009080706050403020100

L den dB

Cum

ulat

ive

prop

ortio

n %

Does not hearNot annoyingA little annoyingHighly annoying

L den dB

Fig. 3. People experiencing different degrees of annoyance indoors when exposed to different levels of road

traffic noise, Lden, outside the most exposed fac�ade. Cumulative number – left panel, and proportion –

right panel. Five Norwegian socio-acoustic surveys. N ¼ 3985.

0 %

10 %

20 %

30 %

40 %

50 %

60 %

70 %

80 %

90 %

100 %

50 55 60 65 70 75Lden dB

Cu

mu

lati

ve p

rop

ort

ion

Highly annoying

A little annoying

Hears, not annoying

Does not hear

Fig. 4. Cumulative proportion of people experiencing different degrees of annoyance for different road

traffic noise exposure values (Lden). Annoyance when right outside apartment. Five Norwegian socio-

acoustic surveys. N ¼ 3957.

Table 1

Parameter estimates from an ordinal logit model for road traffic noise annoyance when right outside the

apartment

Parameter estimates Estimate SE df Sig. (%) 95% confidence interval

Lower

bound

Upper

bound

Threshold

Hears noise 6.026 0.2619 1 0.0 5.513 6.539

A little annoying 7.608 0.2713 1 0.0 7.076 8.139

Highly annoying 9.141 0.2835 1 0.0 8.585 9.697

Location

Lden 0.131 0.0046 1 0.0 0.122 0.140

Five socio-acoustic studies. N ¼ 3957.


Fig. 4 show the estimated proportion of respondents that report different degrees

of annoyance as a function of the noise exposure level.

6.3. Road traffic noise annoyance when indoors: model results

The results from the estimation of the ordinal logit model for indoor annoyance

also show that Lden is a significant and substantial explanatory factor – see Table 2.

The noise level at which the estimated curve for highly annoyed cross the

50% – see Fig. 5, is 76 dB (extrapolated) for indoor annoyance. The estimated ex-

posure–effect curves for ‘‘hears noise’’ and ‘‘a little annoying’’ cross at 55 and 62 dB,

respectively. An increase in the noise exposure indicator Lden of 1 dB, increases the

0 %

10 %

20 %

30 %

40 %

50 %

60 %

70 %

80 %

90 %

100 %

50 55 60 65 70 75Lden d B

Cu

mu

lati

ve p

rop

ort

ion

Highly annoying

A littleannoying

Hears, not annoyingDoes not hear

Fig. 5. Cumulative proportions of people experiencing different degrees of annoyance for different road

traffic noise exposure values (Lden). Indoor annoyance. Five Norwegian socio-acoustic surveys. N ¼ 3985.

Table 2

Parameter estimates from an ordinal logit model for road traffic noise annoyance when indoors


Lower

bound

Upper

bound

Threshold

Hears noise 6.074 0.2636 1 0.0 5.557 6.591


Highly annoying 8.477 0.2798 1 0.0 7.929 9.026

Location

Lden 0.111 0.0045 1 0.0 0.103 0.120



odds of a respondent reporting a higher degree of annoyance with 12%

(e0:111 ¼ 1:117).

6.4. Comparison with results from international surveys

When comparing with the proportion of people ‘‘highly annoyed’’ one has to bear

in mind that the verbal categories are defined differently in different surveys. A

comparison of Norwegian results with those produced by Miedema and Oudshoorn

[8] that superseded the work by Miedema and Vos [3] was undertaken after the

categories ‘‘Does not hear’’ and ‘‘Not annoying’’ were merged into one combined

category. The work undertaken to compare the results from Miedema and Oud-

shoorn and the Norwegian results is presently only described in the form of a report[15] and working documents, but is in preparation for publishing as a follow-up

paper. The comparison of the Norwegian relationships with those from Miedema

0 %10 %20 %30 %40 %50 %60 %70 %80 %90 %

100 %

50 55 60 65 70 75 80Lden dB

Highly anno ying Miedema

Highlyannoying

No rway

A littleand highly annoying Miedema

A little and highly annoying NorwayNot annoying

Cu

mu

lati

ve p

rop

ort

ion

Fig. 6. Cumulative proportions of people experiencing different degrees of annoyance for different noise

exposure values. Annoyance when right outside the apartment and ‘‘at home’’. Five Norwegian socio-

acoustic surveys. N ¼ 3957. Twenty-six socio-acoustic studies [8]. N¼ 19172.


and Oudshoorn, indicate that Norwegians react stronger to road traffic noise – see

Fig. 6.To avoid confusion concerning the labels for the degrees of annoyance, it bears

repeating that the estimated grouped regression model of Miedema and Oud-

shoorn [8] has been utilised to produce exposure–effect curves for the three degrees

of annoyance used in the Norwegian surveys. According to the method for har-

monising the results from surveys employing different annoyance scales this means

that the Norwegian annoyance categories are presumed to cover from 0% to 33%,

33–66% and from 66% to 100% of a continuous annoyance scale from 0% to

100%.In part the difference between the results from Miedema and Oudshoorn, and

those found from the analyses of the Norwegian socio-acoustic surveys could be

explained by a difference in the location. In the Norwegian surveys annoyance are

reported separately for the indoor and outdoor situation that may differ somewhat

from annoyance ‘‘at home’’. However, also the exposure–effect relationships for

indoor annoyance lie somewhat above those presented by Miedema and Oudshoorn

[8] – see Fig. 7.

6.5. Impact of inferior type windows

There is a systematic relationship between the window quality and outdoor noise

level – see Fig. 8. This relationship can be seen as the result of behavioural adap-

tation to higher noise levels, and of the subsidies for building improvement offered

by the public road authorities to residents being exposed to equivalent noise lev-

els (Lden) of more than 64 dB from county or national roads. The window quality

varies systematically with road traffic noise exposure. This ‘‘disturbs’’ the simplerelationship between noise exposure values in front of the fac�ade and indoor

annoyance.

Lden dB7065605550

Cu

mu

lati

ve p

rop

ort

ion

100 %

90 %

80 %

70 %

60 %

50 %

40 %

30 %

20 %

10 %

0 %

Window

Normal

Inferior

Fig. 8. Proportion of respondents who have single glazings in either the bed or living room, for different

levels of road traffic noise outside the most exposed fac�ade. 5 dB noise level Lden intervals. Five Norwegian

socio-acoustic surveys. N ¼ 3947.

0 %10 %20 %30 %40 %50 %60 %70 %80 %90 %

100 %

50

Cu

mu

lati

ve p

rop

ort

ion

55 60 65 70 75 80

Lden dB

Highly annoying Miedema

Highly annoying Norway

A little and highly annoying Miedema

A little and highly annoying NorwayNot annoying

Fig. 7. Cumulative proportions of people experiencing different degrees of annoyance for different noise

exposure values. Annoyance when in doors and ‘‘at home’’. Five Norwegian socio-acoustic surveys.

N ¼ 3985. Twenty-six socio-acoustic studies [8]. N¼ 19172.


An ordinal logit model statistically controlling for the quality of the window

insulation properties, indicate that apartments having single glazing in one or

both of the rooms (N ¼ 435), have an annoyance level comparable to residents

exposed to 2.5–3 dB higher noise levels and normal double-layer glazing

(N ¼ 2330) (see Table 3).

Table 3

Parameter estimates from an ordinal logit model for road traffic noise annoyance when indoors, as a

function of outdoor noise exposure and window quality


Lower

bound

Upper

bound

Threshold

Hears noise 6.163 6.3362 1 0.0 5.504 6.822


Highly annoying 8.486 0.3537 1 0.0 7.792 9.179

Location

Lden 0.113 0.0057 1 0.0 0.102 0.124

Inferior 0.295 0.0961 1 0.2 0.107 0.484

Normal window quality Window insulation reference group



(The result of 2.5–3 dB follows from dividing the parameter for the impact of

having an inferior window quality with the parameter for the impact of the road

traffic noise exposure indicator).

It was not possible to detect any additional benefit of having special noise insu-

lating windows in these analyses.

7. Confidence intervals for the relationships

Confidence intervals for the exposure–effect relationships have been estimated on

the basis of the pooled data set. Systematic differences in the relationship associated

Fig. 9. 95% Confidence bands for the cumulative proportions of people experiencing different degrees of

annoyance when right outside the apartment. Five Norwegian socio-acoustic surveys. N ¼ 3957. Addi-

tional between survey variability is about �3 dB.


with the data coming from different surveys, have not been taken into account. With

only five surveys, there is not enough information on the second (survey) level to

estimate a two-level ordinal logit model. The estimated statistical error bands (see

Fig. 9) are therefore narrower than they ‘‘should’’ be, given the modest between

survey variability of �3 dB. However, the average exposure–effect relationships are

reasonably precise even when allowing for this additional source of error.

8. Discussion

The exposure–effect relationships for both Drammen and Oslo are based on data

collected by purposive sampling. The main goal has been to have respondents ex-

posed to a wide variety of road traffic noise exposure values, and where the traffic

would be increased or decreased as the result of the new highway system. In additiona couple of control areas were selected. This is typical for data used for modelling

exposure–effect relationships the world over.

For purpose of comparing results in Norway with those established in other

countries on similar types of samples, either from single surveys or on the basis of

merged data sets, the Norwegian exposure–effect relationships are ‘‘representative’’

for Norway, in the meaning that they are the best that exist. They have also been

established on a larger and more varied sample of sub-areas and more recent surveys

than most comparable data sets.For the comparison with the results from Miedema and Oudshoorn [8] differences

in the road traffic noise calculation methods, survey differences and differences in the

formulation of the annoyance questions, number of categories, etc. mean that we can

only conclude that the results indicate that Norwegians may react stronger to road

traffic noise. With respect to the Norwegian authorities using the results from

Miedema and Oudshoorn [8], it is possible to conclude somewhat stronger – that

applying the exposure–effect results of Miedema and Oudshoorn [8] to Norwegian

exposure data implies that the level of noise annoyance in the population is beingunderestimated.

As we have only data from two cities, it is not possible to guarantee that results

from other city-areas cannot deviate from those presented here for Norway. How-

ever, we would be surprised if the average relationships are very different. The dif-

ferences between those for Oslo, the capital with half a million inhabitants, and

Drammen a relatively small city with 50,000 inhabitants are within �3 dB. Parts of

these differences are also due to differences in annoyance reactions over time, dif-

ferences in methodology, random variation in population characteristics and contextrelated factors, and not model errors. Annoyance reactions in Drammen 1999 are

stronger than in Oslo 1987 relative to the noise exposure. We are therefore not in a

situation where the size of the city plays a dominant role. However, topography may

play a role. Both the studied cities are of a basin type, where air pollution can ac-

cumulate during temperature inversions, and annoyance reactions can therefore be

somewhat stronger due to the combined effects of noise and air pollution than in city

areas where air pollution is less of a problem.


With respect to the results showing the effect of having inferior window insula-

tion, one should bear in mind that these dwellings may also in other ways be inferior

or be occupied by people with lesser resources than others.

9. Conclusions

Exposure–effect relationships for road traffic noise and noise annoyance have

been estimated on the basis of five Norwegian socio-acoustic surveys. The rela-

tionships serve as a national reference. Separate analyses indicate that these rela-

tionships imply that Norwegians tend to react stronger to road traffic noise than

predicted from the most recent international compilation of international socio-

acoustic surveys.

Acknowledgements

We thank the Public Road Authorities and The Research Council of Norway, for

their support of this research.

Appendix A

The parameter estimates for road traffic noise annoyance when right outside the

apartment as a function of the noise exposure and modifying factors are presented

(see Table 4). The modifying factors are which survey the data come from, the agegroup of the respondent and their noise sensitivity. As information on noise sensi-

tivity was lacking in the Drammen survey, the four remaining socio-acoustic surveys

was used.

A.1. Estimated covariance matrix for parameter estimates from the ordinal logit model

for outdoor noise annoyance

We wish to estimate the confidence intervals for the estimated road traffic noise

annoyance right outside the apartment as a function of the noise exposure indicator

Lden. It is then necessary to know the covariance matrix between the threshold pa-

rameters and the parameter in front of the noise exposure indicator Lden (see Table 5).

The estimated covariance matrix can be obtained by checking an output option in the

PLUM module of SPSS used for estimating the relationships.

Appendix B

Researchers wishing to compare the Norwegian results (see Table 6) with those

produced internationally might want to: (a) merge the does not hear and not annoying

Table 4

Parameter estimates for road traffic noise annoyance when right outside the apartment as a function of

noise exposure outside most exposed fac�ade, survey number, age group and noise sensitivity


Lower

bound

Upper

bound

Threshold

Hears noise 5.149 0.3654 1 0.0 4.432 5.865


Highly annoying 8.468 0.3835 1 0.0 7.716 9.219

Location

Lden 0.129 0.0053 1 0.0 0.119 0.140

Oslo East 87 0.250 0.1297 1 5.4 )0.004 0.504

Oslo East 94 )0.481 0.1293 1 0.0 )0.734 )0.228Oslo East 96 )0.379 0.1289 1 0.3 )0.632 )0.126Drammen 99 Reference

group

Age group

16+ 0.300 0.1147 1 0.9 0.075 0.525

20–29 0.686 0.1216 1 0.0 0.448 0.925

30–39 0.470 0.1379 1 0.1 0.199 0.740

40–49 0.248 0.1515 1 10.2 )0.049 0.554

50–59 0.252 0.1540 1 10.2 )0.050 0.554

60+ Reference

group

Noise sensitivity

Not sensitive )1.257 0.1186 1 0.0 )1.489 )1.024A little sensitive )0.531 0.1176 1 0.0 )0.762 )0.301Highly noise sensitive Reference

group

Four socio-acoustic surveys. N ¼ 3215.

Table 5

Estimated covariance matrix for the threshold estimates and the parameter estimate for the impact of the

road traffic noise level (Lden) (Model for annoyance right outside the apartment)

Threshold Location

LdenHears noise A little annoying Highly annoying

Asymptotic covariance matrix

Threshold

Hears noise 0.068570 0.070204 0.072876 0.001189

A little annoying 0.070204 0.073620 0.076156 0.001238

Highly annoying 0.072876 0.076156 0.080398 0.001290

Location

Lden 0.001189 0.001238 0.001290 0.000021

Five socio-acoustic surveys. N ¼ 3957.


Table 6

Degrees of road traffic noise annoyance and modifying factors for each 5 dB interval Lden. Percentages.

For Ldiff and NO2: average values in dB and lg/m3, respectively

50 55 60 65 70 Mean

Road traffic noise annoyance outdoor

Does not hear 39.6 24.7 13.8 8.7 4.9 19.8

Not annoying 38.3 35.4 29.2 23.7 11.8 29.3

A little annoying 16.1 27.7 35.7 34.8 31.5 28.8

Highly annoying 6.0 12.2 21.3 32.8 51.8 22.1

100 100 100 100 100 100.0

Road traffic noise annoyance indoor

Does not hear 64.9 45.1 36.1 26.0 20.3 40.3

Not annoying 19.8 22.8 18.4 17.2 11.2 18.5

A little annoying 12.5 23.8 31.8 32.7 33.7 26.1

Highly annoying 2.9 8.2 13.7 24.1 34.7 15.0

100 100 100 100 100 100.0

Gender

Male 45.5 47.0 48.9 48.5 42.5 46.9

Female 54.5 53.0 51.1 51.5 57.5 53.1

100 100 100 100 100 100.0

Child under 10

None 82.4 84.7 85.7 86.4 84.8 84.8

At least one 17.6 15.3 14.3 13.6 15.2 15.2

100 100 100 100 100 100.0

Member of workforce

In workforce 66.8 68.7 62.1 61.1 63.8 64.6

Not in workforce 33.2 31.3 37.9 38.9 36.2 35.4

100 100 100 100 100 100.0

Sensitivity to noise

Not sensitive 50.0 47.9 43.3 41.3 42.0 44.9

Somewhat sensitive 40.0 43.8 45.8 48.5 46.1 45.0

Sensitive 10.0 8.3 11.0 10.2 12.0 10.1

100 100 100 100 100 100.0

Window quality

Single glazing 20.2 18.3 16.6 13.8 6.8 15.9

Other 79.8 81.7 83.4 86.2 93.2 84.1

100 100 100 100 100 100.0

Marital status

Married/Cohabiting 57.8 63.7 67.1 64.2 58.6 62.8

Other 42.2 36.3 32.9 35.8 41.4 37.2

100 100 100 100 100 100.0


Table 6 (continued)

Education level

Mandatory 25.8 18.6 18.1 20.2 25.5 21.0

Intermediate 36.9 34.5 38.0 36.5 36.5 36.4

Advanced 17.9 17.2 19.7 19.4 19.8 18.7

Highest 19.5 29.7 24.2 23.9 18.2 23.9

100 100 100 100 100 100.0

Age group

16–29 24.8 33.8 34.5 34.3 35.4 32.3

30–39 22.2 24.6 23.5 26.1 20.9 23.8

40–49 16.4 12.6 12.1 11.3 12.4 13.0

50–59 12.1 9.8 9.9 9.4 8.4 10.1

60–69 9.6 8.8 7.3 7.1 8.9 8.3

70+ 14.8 10.4 12.6 11.8 13.9 12.6

100 100 100 100 100 100.0

Ldiff (dB)

Noise interval means 32.9 39.0 39.6 43.2 54.7 40.6

NO2 (lg/m3)

Noise interval means 10.9 8.1 6.1 2.6 1.7 6.2



categories and (b) look up how Miedema and Oudshoorn [8] merge results from

different surveys by converting annoyance categories to annoyance scores.

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