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Are adverse impacts of neighbourhood noisy areas the flip side of quiet area benefits? R. Klæboe * Institute of Transport Economics, P.O. Box 6110, Etterstad, N-0602 Oslo, Norway Received 26 January 2005; received in revised form 23 May 2005; accepted 25 May 2005 Available online 7 July 2005 Abstract Soundscape researchers have studied how localized areas of noise and quiet within a neigh- bourhood have an effect upon residential noise annoyance. In this paper, noisy and quiet areas are studied simultaneously using data from three surveys and a noise mapping effort for Oslo. Results indicate that noisy neighbourhoods have the potential to increase residential noise annoyance primarily for apartments exposed to low residential noise levels whereas quiet neighbourhood areas have the potential to reduce noise annoyance the most at intermediate and high residential noise levels. Adverse neighbourhood soundscapes are shown to increase residential noise annoyance also after adjusting for possible absence of quiet areas. Whereas Swedish research results document benefits of living in an apartment having access to a quiet facade, no beneficial impacts of quiet neighbourhood areas were found. Results indicate that adjustment factors for apartment having quiet fac ßades and/or adverse soundscapes respec- tively, can be independently applied. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Road traffic noise; Noise mapping; Noise reactions 0003-682X/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.apacoust.2005.05.007 * Tel.: +47 22 573 800; fax: +47 22 570 290. E-mail address: [email protected]. Applied Acoustics 68 (2007) 557–575 www.elsevier.com/locate/apacoust

Are adverse impacts of neighbourhood noisy areas the flip side of quiet area benefits?

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Page 1: Are adverse impacts of neighbourhood noisy areas the flip side of quiet area benefits?

Applied Acoustics 68 (2007) 557–575

www.elsevier.com/locate/apacoust

Are adverse impacts of neighbourhoodnoisy areas the flip side of quiet area benefits?

R. Klæboe *

Institute of Transport Economics, P.O. Box 6110, Etterstad, N-0602 Oslo, Norway

Received 26 January 2005; received in revised form 23 May 2005; accepted 25 May 2005Available online 7 July 2005

Abstract

Soundscape researchers have studied how localized areas of noise and quiet within a neigh-bourhood have an effect upon residential noise annoyance. In this paper, noisy and quiet areasare studied simultaneously using data from three surveys and a noise mapping effort for Oslo.Results indicate that noisy neighbourhoods have the potential to increase residential noiseannoyance primarily for apartments exposed to low residential noise levels whereas quietneighbourhood areas have the potential to reduce noise annoyance the most at intermediateand high residential noise levels. Adverse neighbourhood soundscapes are shown to increaseresidential noise annoyance also after adjusting for possible absence of quiet areas. WhereasSwedish research results document benefits of living in an apartment having access to a quietfacade, no beneficial impacts of quiet neighbourhood areas were found. Results indicate thatadjustment factors for apartment having quiet fac�ades and/or adverse soundscapes respec-tively, can be independently applied.� 2005 Elsevier Ltd. All rights reserved.

Keywords: Road traffic noise; Noise mapping; Noise reactions

0003-682X/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.

doi:10.1016/j.apacoust.2005.05.007

* Tel.: +47 22 573 800; fax: +47 22 570 290.E-mail address: [email protected].

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1. Introduction

1.1. Two parallel lines of research

Acoustical and perceptual soundscape research has recently focused on the acous-tics of quiet areas [1–7]. Focus is on the relationship between the acoustical and thebehavioural and perceptual aspects of quieter urban areas and apartments with ac-cess to quiet fac�ades. One of the research hypotheses in this line of inquiry is thatresidents of apartments having access to quiet areas will suffer less road traffic noiseannoyance. Apartments having access to silent sides (bed-rooms facing a back yard,etc.) will lead to residents experiencing less annoyance and fewer sleep disturbanceswhen indoor [8].

Our research on neighbourhood soundscapes and noise impact maps Klæboe[9,10] has taken a more traditional approach and focused on the adverse impacton residential noise annoyance when the neighbourhood contains areas character-ized by high levels of road traffic noise. The main research hypothesis is that an ad-verse neighbourhood soundscape increases residential noise annoyance, while a lessnoisy than ‘‘normal’’ acoustical neighbourhood soundscape reduces residential noiseannoyance.

A question that quickly comes to mind, is whether the two sets of estimated impacts,at least in part, are mirror images and results of the same causal mechanisms: Is theabsence of noisy areas in the neighbourhood the same as the presence of relatively quietareas, and is a noisy neighbourhood also a neighbourhood lacking quietness?

A reasonable assumption is that the availability of a quiet fac�ade in an apartmentis associated with the availability of quiet areas at the rear end of the apartmentbuilding. If this is the case, an additional question with respect to indoor noiseannoyance can be asked: Is the estimated benefit of not having an adverse sound-scape indirectly due to many apartments possessing a quiet fac�ade?

These are not only questions of academic interest, but important considerationswhen applying the respective results in form of adjustment or trade-off factors. Suchfactors tell us how many decibels we should adjust the exposure indicator on themost exposed fac�ade to incorporate the additional impact of a noisy neighbourhood,and how many decibels we should adjust the exposure value to take into account theavailability of quiet areas. However, the amount of overlap then becomes important.Should we simply add the separate adjustment factors or need we compensate foroverlap in order not to count benefits twice?

1.2. Multivariate models allow partial effects to be estimated

One means of exploring the relationship between neighbourhood noisiness and si-lence is by developing indicators that capture both noisiness and silence in the neigh-bourhood of an apartment. The relationship between the two neighbourhoodsoundscape aspects and their relative contributions in modifying residential noiseannoyance reactions can then be explored by means of multivariate statisticalmodels.

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Previous research results show that noisy areas near an apartment result in highernoise annoyance than indicated by merely considering the noise level on the most ex-posed fac�ade. However, these results were obtained without considering nearby quietareas. We therefore ask whether the adverse impact of the neighbourhood sound-scape persists after controlling for the absence of nearby quiet areas? Vice versa,do nearby quiet areas in the neighbourhood lead to somewhat lower annoyance?Does the estimated impact persist when also controlling for the absence of noisyneighbourhood areas? If so, is the effect smaller than without adjustment?

2. Areas studied, questionnaire, noise calculations, and spatial operations

2.1. National noise mapping data for Oslo

Statistics Norway has implemented a national noise annoyance mapping systembased on existing noise exposure calculations for the most exposed dwellings inNorway. For the apartments that are exposed to the higher noise levels, the noiseexposure calculations are provided by the principal municipalities, road, and rail-way authorities, and have a reasonable good quality. In addition, a GIS-basedalgorithm provides a simpler calculation of the noise exposure value for all dwell-ings where such calculations are not available. The noise exposure values havebeen converted to Lden-values for the statistical analyses. The noise mapping datafor the city of Oslo are here utilised to provide information on the availability ofquiet and noisy neighbourhood areas within a city of about half a millioninhabitants.

2.2. City areas and sampling procedures for the three socio-acoustic studies

For the three Oslo studies in 1987, 1994 and 1996 we were able to supplementthe previous obtained indicator of nearby noisy neighbourhood areas [9] with anindicator of the availability of relatively quiet neighbourhood areas within 75 mof the apartment. These studies are here utilised for analyses of the impact of quietareas and noisy neighbourhoods on exposure–effect relationships. After qualityassurance, 2857 respondents were available for analyses of exposure–effect relation-ships between road traffic noise and road traffic outdoor annoyance. In all, 2881respondents were available for analyses of noise annoyance when indoor. Detailedpresentations of the studies, the noise calculation methods, the calculations of theneighbourhood soundscape quality and the questionnaires have previously beenprovided [9,10].

Two additional socio-acoustic studies containing information on residential noiselevel and the adversity of the neighbourhood soundscape were available. However, itwas not possible to obtain an indicator of quiet areas by means of the GIS-basedroutines, and too costly to obtain an indicator by other means. These datasets weretherefore not utilised.

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2.3. Annoyance questions in the three socio-acoustic studies

The annoyance questions distinguish between the situation outside the apart-ment and inside the apartment: People were first asked: ‘‘Can you hear noise fromroad traffic when you are right outside the apartment?’’ People were thereafterasked ‘‘Is the noise highly, somewhat or not annoying for you?’’.1 With respectto indoor annoyance, the questions were: Do you hear road traffic noise (when) in-

side your dwelling? (The answers were ‘‘Yes’’, ‘‘No’’ and ‘‘Not applicable’’, and‘‘Do not know’’). If yes: ‘‘Is this noise highly, somewhat or not annoying foryou.’’ Residential noise annoyance is measured by means of these two questions.To be compatible with the data sets employed by Miedema and Oudshoorn [12],the response categories ‘‘Do not hear’’ and ‘‘Not annoyed’’ were merged beforethe statistical analyses.

2.4. Noise calculations, neighbourhood maximum and minimum noise levels

The 24 h equivalent road traffic noise levels at the apartments most exposed side,LAeq,24h, were calculated using the Nordic calculation method. To make it easier tocompare the results from the noise mapping and socio-acoustic studies with thoseproduced internationally, the values have summarily been converted to A-weightedLden-values by applying a common 24 h traffic volume distribution. We will use theterm residential noise level for short. The residential noise level, Lden,fac�ade, is definedas the calculated equivalent evening and night weighted road traffic noise level on themost exposed fac�ade of an apartment. The term ‘‘on the fac�ade’’ signifies free fieldvalues.

As an indicator of noisy areas within the neighbourhood soundscape, the neigh-bourhood maximum noise level, Lneigh,max, previously been defined as the highestequivalent road traffic noise level within a 75 m radius of the apartment. In addition,we here define the neighbourhood minimum noise level, Lneigh,min, to be the lowestequivalent road traffic noise level found within 75 m of an apartment. The indicatorof quiet areas is thus obtained by exactly the same method that is used to define noisyneighbourhood areas.

The neighbourhood maximum noise level and neighbourhood minimum noiselevel are correlated with the residential noise level, Lden,fac�ade. To separate the ef-fects of the neighbourhood indicator from that of the residential noise level, it ispreferable to look at the differences. We are thus interested in how much noisieror how much quieter the neighbourhood can be within a 75 m radius from theapartments exposed to a given residential noise level. Road traffic noise levelsare calculated from an emission level 10 m from the midline of the road. Thislocation will often represent the neighbourhood maximum for apartments locatedclose to the road.

1 The questions in the 1987 were slightly different – See [11]. for a detailed description.

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2.5. Neighbourhood maximum and minimum differences

The neighbourhood maximum difference, Ldiff,max, is defined as follows:

Ldiff ;max ¼ Lneigh;max � Lden;fac�ade

The neighbourhood maximum difference, Ldiff,max, is simply the number of deci-bels that the noise level in the immediate neighbourhood of an apartment exceedsthe noise level at the most exposed fac�ade of the residence. It describes the adversityof the immediate neighbourhood relative to the noise level encountered at the apart-ment itself (Lden,fac�ade).

The neighbourhood minimum difference Ldiff,min defined as

Ldiff ;min ¼ Lden;fac�ade

� Lneigh;min

The neighbourhood minimum difference, Ldiff,min, is the reduction in the number ofdecibels between the noise exposure level at the apartment, Lden,fac�ade, and the qui-etest spot within the immediate neighbourhood of an apartment. Both indicatorsare thus non-negative.

2.6. Illustration of noisy neighbourhood areas

Noisy areas within the neighbourhood soundscape are often pavement and recre-ational areas along and bordering onto major roads that traverse the city landscape.Let us commence by exploring the exposure situation for three different apartmentsthat are located near a main road – see Fig. 1. We distinguish between the front rowapartments A and D and the second row apartments B and C. ‘‘Front’’ and ‘‘secondrow’’ is here used to signify the location relative to the main street.

Fig. 1. Maximum neighbourhood differences (Ldiff,max) for front row and second row apartments. Ldiff,max

of apartment D is 3 dB, signifying that the neighbourhood soundscape noise levels are not much worsethan the noise levels at the apartment itself, while the relative neighbourhood soundscape noisiness(Ldiff,max) of apartments B and C is 15 dB.

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Apartments B and C have a much lower noise level at the main fac�adeðL

den;fac�ade¼ 60 dBÞ than apartment A ðL

den;fac�ade¼ 72 dBÞ. This is due to intervening

buildings that shield against the noise emissions from the main street and the reduc-tion in noise emissions due to the distance from the main road.

The relatively low residential noise levels that apartments B and C are exposed to,is the rationale for regarding a second row location as advantageous. However, acloser analysis reveals that for a fixed value of the residential noise exposure indica-tor (Lden,fac�ade) these locations are inferior with respect to the their neighbourhoodsoundscape.

To keep the residential noise level, Lden,fac�ade, fixed, the neighbourhood maximumnoise levels for apartments B and C are compared against the neighbourhood max-imum noise level of an apartment facing a road with much less traffic. Due to a re-duced volume of traffic, the residential noise level, Lden,fac�ade, of apartment D is also60 dB. We can now limit our attention to apartments B, C and D that all are exposedto the same residential noise level.

The road traffic noise levels that the residents of apartments B and C encounterwhen they walk along the main road exceeds the residential noise levels with as muchas 15 dB. Their neighbourhood maximum noise level, Lneigh,max, is 75 dB and theneighbourhood maximum difference Ldiff,max is 15 dB. The value of 60 dB thus de-scribes the residential noise level but fails to address the higher noise levels thatare part of their apartments� immediate neighbourhood.

For apartment D, the residential noise level, Lden,fac�ade, and the maximum neigh-bourhood noise levels are similar in size, and the residential noise level of 60 dB pro-vides an adequate description also of the neighbourhood maximum noise level, andLdiff,max, is only 3 dB. With respect to the maximum neighbourhood noise level, loca-tions B and C are preferable to location A, while location D is to be preferred overlocations B and C.

2.7. Illustration of quiet neighbourhood areas

Researchers focusing on the availability of an apartment fac�ade that is quietwould point out that the rear side of some of the buildings are shielded from themain street and much less noisy than the residential noise level. Residents of apart-ment A will thus benefits from the availability of quiet areas in the neighbourhood.For through going apartments with rooms located towards the rear, the residentswill benefit from the apartment having a quiet side. The neighbourhood minimumnoise level, Lneigh,min, for apartment A is at least below 60 dB, and the neighbour-hood difference, Ldiff,min, is 12 dB (or more if we include the rear side the apartmentB building).

The noise level on the most exposed fac�ade (Lden,fac�ade) supplemented with theindicators of the neighbourhood maximum difference (Ldiff,max) and neighbourhoodminimum difference (Ldiff,min) are summarized for all apartments locations A–F, seeTable 1.

Table cells for apartment locations depicted in Figs. 1 and 2 that have noisyneighbourhoods and/or lack quiet areas are in a darker colour.

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Fig. 2. Minimum neighbourhood noise levels and minimum differences for front row and second rowapartments. Apartments A, B, and D are better off than apartment C, E and F with respect to theavailability of quiet areas in the neighbourhood.

Table 1Road traffic noise exposure information for apartment locations in typical noisy and quietneighbourhoods

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2.8. Spatial operations for extracting neighbourhood soundscape indicators

All apartments that were included in the noise mapping of Oslo and the socio-acoustic surveys were geographically located with x- and y-coordinates by meansof digital maps. This made it possible to perform spatial analyses utilising geograph-ical information systems (GIS). Custom built scripts were developed to obtain thenecessary neighbourhood soundscape information. These were implemented by Sta-tistics Norway in Arc Info for use with noise mapping data, and by the Institute ofTransport Economics in ArcView 3.2 for use with the socio-acoustic survey data.

The neighbourhood maximum and minimum noise level Lneigh,max and Lneigh,min

were calculated as the highest and lowest equivalent road traffic noise level encountered

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Fig. 3. Apartments exposed to different residential noise levels Lden,fac�ade (colour coded) and theneighbourhood maximum values Lneigh,maximum (colour coded).

564 R. Klæboe / Applied Acoustics 68 (2007) 557–575

within a 75 m radius of an apartment. The choice of 75 m was a tradeoff between thewish to capture all nearby significant areas, but to not include areas that were so faraway that they would not be used. Tests using different radii indicate that for theOslo city areas 75 m may be a reasonable choice [13].

The methodology is illustrated in Fig. 3. The light shaded circle with radius 75 maround one target apartment encompasses one dark dot (P65 dB). The neighbour-hood maximum noise level for this target apartment is therefore set to 65 dB.2 Theneighbourhood minimum value for the same apartment (not shown) is 655 dB inter-val because the apartment itself has such a low noise level, as does the apartment thatlies a bit upwards and to the left of the target apartment. The neighbourhood max-imum for all apartments in the left panel of Fig. 3 have been calculated using thesame procedure and the results displayed in the right panel.

The calculations of the neighbourhood minimum and neighbourhood maximumin the socio-acoustic studies were undertaken using only the information on theapartments of residents that took part in the surveys. As the sampling proportionswere quite high in the sub-areas that were sampled, the values should be reasonablyaccurate. However, if the person living at the apartment with the lowest or highestnoise level within 75 m of the target apartment had failed to respond to the question-naire, the values returned by the spatial routines could be affected. Apartments be-yond the sub-area borders were excluded from the spatial search. However, theborders were drawn along the midline of major streets, so the neighbourhood max-imum noise levels would almost always have been captured. Along sub-area bordersaway from the main streets, the neighbourhood minimum may be estimated a littletoo high.

2 As the method fails to take into account that pavement areas are exposed to higher noise levels thanapartments on the fac�ade, 2 dB were added to the estimates before the statistical analyses.

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The noise mapping data for Oslo is complete. The spatial routines in ArcView 3.2used for the noise mapping data also capture noise exposure values for nearby pave-ment areas when allocating the neighbourhood maximum and minimum values.Here the indicator values should be quite accurate.

3. Statistical procedures

3.1. Box plots of noisy and quiet neighbourhood indicators

The relative neighbourhood soundscape quality (as indicated by Ldiff,max andLdiff,min-values) vary a lot for the for the apartments depicted in Figs. 1 and 2 ex-posed to the same residential noise exposure (Lden,fac�ade). However, are such largedifferences also found in practice?

To find out, the noise levels of quiet areas and of noisy areas were calculated fromthe national noise mapping data for Oslo (2001-figures) and described as functions ofthe residential road traffic noise exposure level, Lden,fac�ade, by means of box plots.These show the distribution of Ldiff,max- and Ldiff,min-values for each 5-decibel inter-val of Lden,fac�ade. The shaded boxes show the interquartile range (25th to 75th per-centile) and thus cover the values typical for 50% of the respondents� apartments.The whiskers extend 11

2box-length from the edge of each box, provided there are suf-

ficiently high and low values. Outliers and extreme values are not shown.In addition to the box plots, the partial correlation between Ldiff,max and Ldiff,min

while controlling for Lden,fac�ade was calculated. The partial correlation providesinformation as to whether the two values are correlated for apartments with a givenresidential noise level.

3.2. Estimation of average neighbourhood maximum and minimum differences

Simple box plots were also used to visualize the distribution of the neighbourhoodmaximum and minimum noise levels, Ldiff,max and Ldiff,min, for 5-dB residential noiseintervals. The average Ldiff,max-values decreases while the average Ldiff,min-values in-creases as a function of the residential noise level, Lden,fac�ade. As the Nordic calcula-tion model is not adapted to quiet areas [6,7], a cut off value of 49 dB was employed.That is, if the calculated noise exposure value was lower than 49 dB it was set to49 dB.

Whereas the noise mapping data and partial correlation coefficients give an indi-cation to what extent quiet and noisy neighbourhood areas are systematically relatedto each other, the linkages between the residents� reactions and these exposure indi-cators also need to be established. To facilitate these analyses, the statistical indica-tors of quiet and noisy neighbourhoods are developed a bit further. The first step inthis elaboration is to obtain the average maximum and minimum difference indica-tors for a given residential noise level. Knowledge of these averages will help deter-mine whether the neighbourhood of an apartment is more or less quiet or noisy than‘‘usual’’.

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The average ‘‘normal’’ neighbourhood maximum and minimum difference levelsat a given Lden,fac�ade-value are designated3 as follows:

ð dLdiff ;max jLden;fac�adeÞ and ð dLdiff ;min jLden;fac�ade

Þ.

These averages could simply have been estimated by simply averaging the valuesfor each given Lden,fac�ade-value. However, the number of observations within each dBinterval would not be sufficient for these estimates to be reliable. To capitalize on thefact that the differences should be more or less alike for neighbouring values of theresidential noise level, an empirical curve fitting approach was adopted.

Average Ldiff,max-values were already available from a regression model estab-lished in a previous research effort [9], and the previously estimated values useddirectly.

To obtain the average neighbourhood minimum difference values,ð dLdiff ;min jLden;fac�ade

Þ, a linear regression model was estimated with Ldiff,min as depen-dent variable, and Lden,fac�ade as independent. Due to non-linearity, a quadratic termwas added to the regression model.

3.3. Calculation of neighbourhood maximum and minimum deviations

Traditional exposure–effect relationships ignoring neighbourhood soundscapeinformation are constructed by summarizing the degrees of annoyance reported byall respondents exposed to a given residential noise exposure level Lden,fac�ade. Theaverage degree of annoyance is thus determined by averaging the responses frompeople living both in noisy and quiet neighbourhoods, both having and lacking ac-cess to quiet sides. The responses are thus obtained from respondents living in a mix-ture of neighbourhood soundscapes.

Typical neighbourhood maximum differences (Ldiff,max) are positive for lowLden,fac�ade-values and the typical neighbourhood minimum differences (Ldiff,min)are positive for high Lden,fac�ade-values. The degree of annoyance that is registeredat a given Lden,fac�ade-value ‘‘ignoring’’ soundscape information will automaticallyand inadvertently also be influenced by the associated neighbourhood quality.The residential noise exposure indicator thus serves as a proxy for the combinedeffect of the residential noise level itself along with the average soundscape impactson residential noise annoyance. It is reasonable that these average neighbourhoodsoundscape impacts are functions of the average neighbourhood maximum andminimum values.

As the average impacts of the neighbourhood soundscape quality is already ‘‘ta-ken care’’ of, it is possible to proceed further and focus on departures from the ‘‘nor-mal’’ states of affairs. What impact does a neighbourhood have that is noisier thanthat which a given residential noise level Lden,fac�ade usually signifies? What impact

3 The vertical bar is read as given or conditional on (the Lden,fac�ade-value).

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does an area have that is quieter than that what is usually associated with the resi-dential noise level Lden,fac�ade?

To provide information on the number of decibels that the values of Ldiff,max andLdiff,min deviate from their averages, we introduce the neighbourhood maximumdeviation, and neighbourhood minimum deviation, Ldev,max and Ldev,min. These indi-cators tell us how much the neighbourhood maximum and minimum differences ex-ceed or have values lower than their estimated average values for the givenresidential noise level Lden,fac�ade. The neighbourhood maximum deviation:

Ldev;max ¼ Ldiff;max � dLdiff ;max jLden;fac�ade

� �

provides information on whether the neighbourhood soundscape is noisier than‘‘normal’’ for a given residential noise level, Lden,fac�ade. The neighbourhood mini-mum deviation:

Ldev;min ¼ Ldiff ;min � ð dLdiff ;min jLden;fac�adeÞ

provides information on whether the neighbourhood soundscape is quieter than‘‘normal’’ for a given residential noise level, Lden,fac�ade. Both indicators were calcu-lated for the apartments of all residents participating in the surveys and the informa-tion added to the data file.

3.4. Ordinal logit regression models

Ordinal logit models [14–16] for road traffic noise annoyance when right outsidethe apartment and when indoor were thereafter estimated. These models featurethe residential noise level, Lden,fac�ade, together with both the Ldev,max and Ldev,min

indicators as independent variables. The estimated parameters from these modelsare compared with those of the simpler models where each of the neighbourhoodindicators are introduced separately into a model along with the residential noiselevel. The purpose of the comparison is to see whether the inclusion of the secondsoundscape indicator leads to changes in the estimated effect sizes. Such changes inestimated effect sizes may indicate that there is an overlap and that one of theneighbourhood soundscape quality indicators serves in part as a proxy for theother.

4. Results

4.1. Neighbourhood maximum and minimum difference values for Oslo

Box plots that show the variation in the maximum and minimum difference indi-cators, Ldiff,max and Ldiff,min, for Oslo apartments exposed to the same residentialnoise level Lden,fac�ade (5-dB intervals) are provided in Fig. 4. The vertical axis (y-axis)for the Ldiff,min-values has been inverted to show both distributions in the same plot.

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Fig. 4. Neighbourhood maximum difference (Ldiff,max), and neighbourhood minimum difference (Ldiff,min)values as a function of 5-dB intervals of the residential noise level Lden,fac�ade. Box plots calculated fromnoise mapping data for Oslo in 2001. N = 506 542.

568 R. Klæboe / Applied Acoustics 68 (2007) 557–575

Each of the box plots in Fig. 4 illustrate that apartments belonging to the same 5-dBinterval have very different neighbourhoods. At lower residential noise levels, max-imum differences are often higher than 10 dB. At high residential noise levels mini-mum differences (Ldiff,min) are easily larger than 10 dB.

(As the data are not used for further analyses, a 50 dB cut-off value has not beenimplemented. It should be kept in mind that the minimum difference may be overes-timated because ambient city noise, distant road traffic noise sources and other noisesources are not properly taken into account by the calculation model – See [7]).

4.2. Small partial correlation between the maximum and minimum difference indicators

The simple correlation between the neighbourhood maximum and the neighbour-hood minimum difference value is relatively small r = 0.30. This is a reflection of the

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relationship of each indicator with the residential noise level Lden,fac�ade. However, thecorrelation between the two indicators for apartments exposed to the same residen-tial noise level is more interesting. When statistically controlling for the residentialnoise level, this partial correlation coefficient becomes negligible (�0.05). For anapartment exposed to a given residential noise level, the presence or absence of rel-atively noisy and relatively quiet areas are not systematically related.

4.3. Average neighbourhood maximum difference values

The box plot of the neighbourhood maximum difference as a function of residen-tial noise levels indicates a linear relationship between Ldiff,max and Lden,fac�ade – seeFig. 5, left panel. The parameter estimates obtained from previous research efforts[9] for the average Ldiff,max-value given the residential noise level are reproduced inTable 2.

That is dLdiff ;max jLden;fac�ade¼ 34� 0.472� L

den;fac�ade.

The estimated average neighbourhood maximum difference values become nega-tive for Lden,fac�ade-values over 71 dB and are set to zero.

The following results are based on the pooled data set from the three socio-acous-tic surveys.

Fig. 5. Box plots of the neighbourhood maximum differences, Ldiff,max, and neighbourhood maximumdeviances, Ldev,max, as a function of Lden,fac�ade (5-dB intervals). Dashed line shows the regression line thatserves as a base-line for calculating the Ldev,max-values.

Table 2Parameter estimates from a linear regression model where Ldiff,max-values are regressed on Lden,fac�ade

Unstandardizedcoefficients

Standardized coefficients 95% Confidence interval for B

B Std. error Beta t Sig. Lower bound Upper bound

Constant 34.007 0.663 51.259 0.000 32.706 35.308Lden,fac�ade �0.472 0.011 �0.557 �42.173 0.000 �0.494 �0.450

Five socio-acoustic surveys N = 3950.

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Fig. 6. Box plots of the neighbourhood minimum differences, Ldiff,min, and neighbourhood minimumdeviances, Ldev,min, as a function of Lden,fac�ade (5-dB intervals). Dashed line shows the regression curve thatserves as a base-line for calculating the Ldev,min-values.

Table 3Estimated parameters from a linear regression model linking Ldiff,min to Lden,fac�ade

B2 (Lden,fac�ade)2 B1 (Lden,fac�ade) B0 (constant)

0.0289 �2.7912 67.6143

Three socio-acoustic surveys. N = 2884.

570 R. Klæboe / Applied Acoustics 68 (2007) 557–575

4.4. Average neighbourhood minimum difference values

The plot of neighbourhood minimum differences as a function of residential noiselevels indicated a quadratic rather than simple linear relationship with Lden,fac�ade –see Fig. 6 left panel. This was confirmed by a curve-fitting test. A quadratic regres-sion model was therefore employed (see Table 3) to obtain average Ldiff,max-values asa function of Lden,fac�ade.

That is dLdiff ;min jLden;fac�ade¼ 67.6143þ 2.7912� L

den;fac�ade� 0.0289� L2

den;fac�ade.

The neighbourhood maximum deviation values (Ldev,max) and neighbourhoodminimum deviation values (Ldev,min) for all respondents were thereafter obtainedfrom the relationships:

Ldev;max ¼ Ldiff ;max � ð dLdiff ;max jLden;fac�adeÞ and

Ldev;min ¼ Ldiff ;min � dLdiff ;min jLden;fac�ade

� �.

4.5. Maximum neighbourhood difference and deviation values

The neighbourhood maximum differences vary a lot for apartments exposed tothe same low residential noise levels see Fig. 5, left panel. The box plots for the cor-responding neighbourhood maximum deviation Ldev,max-values as a function of the

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residential noise level is illustrated in the right panel of Fig. 5. These box plots showhow many decibels a neighbourhood noisy area deviates from the average value for agiven residential noise level Lden,fac�ade.

4.6. Minimum neighbourhood difference and deviation values

Apartment A – see Fig. 2, has a ‘‘quiet’’ side with Ldiff,min = ca. 12 dB. With thecut off value of 50 dB, Apartment D has a Ldiff,min = 10 dB while C, E, F are exposedto road traffic noise from both apartment sides and a minimum difference Ldiff,min =ca. 0 dB. The box plots for the neighbourhood minimum difference – see Fig. 6, leftpanel, indicate that such large variations in the quality of the neighbourhood sound-scape with respect to quiet areas is typical. The largest variation is seen at interme-diate and high residential noise levels.

The box plots for the neighbourhood minimum deviation Ldev,min-values as afunction of the residential noise level, Lden,fac�ade, is illustrated in the right panel ofFig. 6. The box plot show how many decibels a neighbourhood quiet area exceedsor lies below the average Ldiff,min value for a given residential noise level Lden,fac�ade.

The partial correlation between the two indicators Ldiff,max and Ldiff,min when con-trolling for the residential noise level Lden,fac�ade is about 0.10 which is very low andindicates no systematic relationship between the presence or absence of noisy andquiet areas for a given apartment. The number of observations used to estimatethe partial correlation was 2434.

4.7. Road traffic noise annoyance when right outside the apartment

For this analysis the neighbourhood minimum deviation is introduced in additionto the neighbourhood maximum deviation as potential modifier of exposure–annoy-ance relationships by entering them as independent variables in addition to the res-idential noise level, Lden,fac�ade (see Table 4).

From the estimated results for annoyance from road traffic noise right outside theapartment, we observe that the parameter for the impact of the noise level on the

Table 4Estimation results of an ordinal logit model for road traffic noise annoyance right outside the apartment asa function of the noise level on the most exposed fac�ade (Lden,fac�ade), neighbourhood maximum deviation(Ldev,max), and neighbourhood minimum deviation (Ldev,min)

Estimate Std. error Sig. 95% Confidence interval

Lower Bound Upper Bound

Threshold A little annoyed 8.440 0.373 0.00% 7.709 9.171Highly annoyed 10.013 0.387 0.00% 9.253 10.772

Location Lden,fac�ade 0.145 0.006 0.00% 0.133 0.158Ldev,max 0.082 0.008 0.00% 0.066 0.098Ldev,min 0.008 0.009 38.10% �0.010 0.026

Three socio-acoustic surveys. N = 2857.Link function: Logit.

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most exposed fac�ade plays the most important role. An increase in the residentialnoise level of 1 dB increases the relative odds of a person reporting a higher degreeof annoyance with 16% (e0.145 = 1.16). The estimated effect size for the neighbour-hood maximum deviation, Ldev,max, is 0.082 which means the relative odds for a per-son reporting a higher degree increases with 8.5% when this indicator increases with1 dB (other factors held constant). An important point with respect to the possibleoverlap is whether the inclusion of an indicator of available quiet neighbourhoodareas Ldev,min has the indirect effect of leading to a reduction in the estimated effectsize of adverse neighbourhood areas indicated by Ldev,max. The parameter value re-ported by [9] is 0.074, which means that the effect size is about the same. The changein effect size, if any, is towards a stronger and not a weaker impact. The parameterestimate for the neighbourhood maximum deviation Ldiff,max is about 57% of 0.145,which means that about a 2 dB increase in the neighbourhood maximum deviationhas about the same impact on road traffic noise annoyance right outside the apart-ment as a 1 dB increase in the residential noise level indicator, Lden,fac�ade.

The estimated ordinal logit regression model results in a non-significant effect forthe presence of quiet areas as indicated by the neighbourhood minimum deviation,Ldev,min.

4.8. Road traffic noise annoyance when indoor

From the estimated results for road traffic noise annoyance when indoor see Table5, we observe that the parameter for the impact of the noise level on the most ex-posed fac�ade again plays the most important role.

An increase in the residential noise level of 1 dB increases the relative odds of aperson reporting a higher degree of noise annoyance when indoor with 14%(e0.129 = 1.14). The parameter estimate for the neighbourhood maximum deviation0.62 is about the same as in the model without statistical control for quiet areas(0.57). The effect size is about 48% of 0.129, which means again that a 2 dB increasein the neighbourhood maximum deviation has about the same impact on road traffic

Table 5Estimation results of an ordinal logit model for road traffic noise annoyance when indoor as a function ofthe noise level on the most exposed fac�ade Lden,fac�ade, neighbourhood maximum deviation (Ldev,max), andneighbourhood minimum deviation (Ldev,min)

Estimate Std. error Sig. 95% Confidence interval

Lower Bound Upper Bound

Threshold A little annoyed 7.888 0.377 0.00% 7.149 8.627Highly annoyed 9.450 0.390 0.00% 8.685 10.215

Location Lden,fac�ade 0.129 0.006 0.00% 0.117 0.141Ldev,max 0.062 0.008 0.00% 0.045 0.079Ldev,min 0.033 0.009 0.03% 0.015 0.051

Three socio-acoustic surveys. N = 2881.Link function: Logit.

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noise annoyance as 1 dB increase in the residential noise level indicator by Lden,fac�ade.This is about the same trade-off value that was reported previously [9].

The analysis also shows that the parameter for the indicator of the availability ofquiet areas, the neighbourhood minimum deviation is significant. However, the signis opposite of what we would expect, and the analysis thus fails to show any bene-ficial impact of quiet areas on road traffic noise annoyance when indoor. (Analyseswithout an indicator of the adverseness of the neighbourhood soundscape show thesame result.)

Inclusion of an indicator with the wrong sign is likely to mess up other estimates.As we have dispelled the possibility of the results showing impacts of adverse neigh-bourhood soundscapes being influenced by the absence of quiet areas or quiet apart-ment sides, there is nothing to keep us from keeping the previously estimatedestimators as these were based on the extended data set. We thus fall back on to theseestimates and where the exact parameter values are provided in [9]. However, for allpractical purposes, the main results can be summarized in the trade-off value, whichis approximately 2. Each two-decibel increase in the relative adverseness of theneighbourhood soundscape, Ldev,max, increases the degree of residential noise annoy-ance, whether right outside the apartment or indoor, with the same amount that anincrease of one decibel in the residential noise level, Lden,fac�ade, does. As the neigh-bourhood maximum deviation is derived from the neighbourhood maximum differ-ence Ldiff,max the same trade off factor applies to Ldiff,max.

5. Discussion

5.1. Significant and substantial impacts of adverse neighbourhoods

Previously found impact estimates from ordinal logit models for residential noiseannoyance when right outside the apartment and when indoor of having an adverseneighbourhood soundscape are not diminished when also controlling for the avail-ability of quiet areas. A neighbourhood soundscape that is 2 dB noisier, increasesthe degree of residential noise annoyance with the same amount as an increase inthe residential noise level, Lden,fac�ade, by 1 dB. For road traffic noise annoyancethe same trade-off factor was found both when right outdoor, and when indoor. Thismeans that noise mapping efforts utilising this trade-off factor need not be modified.

5.2. No beneficial impacts of quiet neighbourhood areas shown

While we expected that the adverseness of the neighbourhood would prove to bethe dominating modifier of exposure–effect relationship, we were surprised that theanalyses fail to indicate that the availability of quiet areas (as captured by the GIS-routines) reduces road traffic noise annoyance when right outside the apartment.There are large differences in neighbourhood soundscape quality between apart-ments with and without quiet sides as witnessed by our box plots of the neighbour-hood minimum deviance, Ldev,min – see Fig. 6. The wide value range for the

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neighbourhood minimum difference indicator-values suggests that even a small effectshould be detectable. The failure to show an impact of quiet areas for noise annoy-ance right outside the apartment is therefore likely to be more than the failure ofautomated spatial routines to detect useful quiet neighbourhood areas. In the typeof city areas studied here, the noise levels may remain too high for quieter outdoorareas to provide much of a respite.

The availability of quiet areas where the noise levels are such that they offer realrecreational value may thus be more important for apartments exposed to lowernoise levels. However, our study areas are city-areas exposed to relatively high noiselevels, and the cut-off value of 49 dB that is utilised precludes such analyses of thesepossible impacts at lower residential noise levels.

It is less surprising that we fail to find an effect of quiet areas on road traffic noiseannoyance when indoors. The indicator is primarily designed to capture the avail-ability of quiet outdoor areas, and the relationship between quiet rear building areaswith the availability of quiet apartment sides hypothesized by us is not documented.As Ohrstrom et al. [8] have delivered compelling evidence that apartments having ac-cess to a quiet fac�ade have a strong and beneficial effect on noise annoyance, we canonly conclude that the GIS-based routines fail to show this impact and that moredetailed and higher quality analyses targeting lower residential noise exposure levelsare necessary.

5.3. Results indicate that apartment having access to quiet fac�ades and adverse

neighbourhood soundscapes are not mirror images

The various results indicate that there is no likely overlap between the impacts ofadverse neighbourhoods and quiet sides. The high neighbourhood maximum differ-ence values found at low residential noise levels, indicate that a noisy neighbourhoodhave the greatest potential for affecting residential noise annoyance at these levels.The large neighbourhood minimum difference values found at high residential noiselevels signify where the potential benefit of having access to quiet areas is the highest.This is found both from the analyses of the noise mapping data and of the data fromthe socio-acoustic surveys.

The partial correlation coefficients between the neighbourhood maximum andminimum differences, Ldiff,max and Ldiff,min, is �0.05 for the Oslo noise mapping dataand 0.10 for the data from the socio-acoustic surveys after controlling for the resi-dential noise level, Lden,fac�ade. These low partial correlation coefficients also suggestthat the respective estimated neighbourhood soundscape impacts will be determinedindependently of each other by multivariate statistical regression models.

This should mean that the results obtained on the importance of adverse neigh-bourhood soundscapes are not a mirror image of silent area benefits and also notin competition with the results by Ohrstrom et al. [8] on the importance of quietapartment sides. Possible correction factors for quiet apartment sides and adverseneighbourhood soundscapes can be applied independently. In particular the methoddescribed by Klæboe et al. [9] can be employed to take into account the adverse im-pacts of an adverse neighbourhood soundscape on road traffic noise annoyance.

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Acknowledgements

We thank The Research Council of Norway and the Public Roads Administrationthat have funded this research. We thank Statistics Norway for implementing thespatial routines to extract neighbourhood soundscape information from noise map-ping data, and the resulting noise maps.

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