Science of the Total Environment 518–519 (2015) 290–301

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Science of the Total Environment

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A review and comparative analysis of European priority indices for noiseaction plans

Francesco D'Alessandro a,⁎, Samuele Schiavoni b

a Department of Civil and Environmental Engineering, University of Perugia, Via G. Duranti, 06125 Perugia, Italyb Inter-University Research Centre on Pollution and Environment “Mauro Felli” — CIRIAF, University of Perugia, Via G. Duranti, 06125 Perugia, Italy

H I G H L I G H T S

• We did a review of the noise priority indices used in action plans.• Noise indices related to health effects and annoyance were considered.• We applied several noise scores to a real area selected as case study.• We compared the results and the effects of the selection of noise scores.• We highlighted the influence of the selection of noise indices on action plans.

⁎ Corresponding author.E-mail addresses: dalessandro.unipg@ciriaf.it (F. D'Ale

schiavoni.unipg@ciriaf.it (S. Schiavoni).

http://dx.doi.org/10.1016/j.scitotenv.2015.02.1020048-9697/© 2015 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 27 November 2014Received in revised form 27 February 2015Accepted 28 February 2015Available online xxxx

Editor: P. Kassomenos

Keywords:Environmental noiseNoise planningAction planHealth effectsAnnoyancePriority indices

The EuropeanUnion has provided in recent years (and is going to update) several tools to harmonise noisemappingmethodologies through directives and guidelines. Unfortunately the same efforts have not been put in theharmonisation of approaches for Noise Action Plans, the effective instruments tomanage noise impacts. As a conse-quence, each EuropeanMember State at national or even at local level defined its ownmethodology, usually consid-erably different one from the others. Nevertheless, themost common approach to dealwith noise impact at a policy,economic and strategy level is the use of priority indices focused to highlight areas or buildings where mitigationactions are more advisable or urgent. The aim of the present research is to provide a review of the most usedEuropean priority indices and also to test some of them in a study area. The comparative analysis demonstratesthat the method chosen for the prioritisation deeply affects the ranking of the areas where noise measures needto be realized. Somemethods tend to give high priority to noise sensitive locations, others to high populated build-ings, andothers to the areaswhere noise levels are high. The studyproves howmuch commonapproaches areneed-ed also for Noise Action Plans to reach a coherent noise policy within European boundaries.

© 2015 Elsevier B.V. All rights reserved.

1. Introduction

Environmental noise is a global problem and, even if it is not possibleto define precisely how it is evolvingwith time (European EnvironmentalAgency, 2014; Arana, 2010), it is nowadays one of the most impactingpollutants in Europe and worldwide. It can be estimated that the effectsof noisewill increase due to the growing spread of urbanization, especial-ly in developing countries: the United Nations estimates that more thantwo thirds of the inhabitants of the world will live in urban areas by2050 (United Nations, 2014).

Increasing urbanization can be associated with a greater variety ofnoise and some negative health issues. In fact, the World Health

ssandro),

Organization claims that environmental noise annoys one in threeEuropeans during the course of a given day. One in five will have theirsleep disturbed for the same reason (World Health Organization,Regional Office for Europe, 2011). Furthermore, the European Environ-ment Agency estimates that 65% of Europeans citizens of major citiesare exposed to high noise levels (55 dB Lden, 50 dB Lnight), and morethan 20% to night time noise levels at which adverse health effectsoccur frequently (European Union, 2013).

Continued noise exposure has been linked to cardiovascular dis-eases (Babisch, 2014), cognitive impairment in children, sleep dis-turbance and tinnitus (World Health Organization, Regional Officefor Europe, 2011). Several studies (Navrud, 2002; CE Delft et al.,2011) have also assessed the social costs of environmental noisefor the European Union, including health care costs, house deprecia-tion, limitation to land use, loss of working hours due to stress or in-somnia, and learning impairment: it is estimated that road traffic

291F. D'Alessandro, S. Schiavoni / Science of the Total Environment 518–519 (2015) 290–301

noise alone costs 38 billion euros per year (0.4% of the EU gross na-tional product), a terrific amount that is about one third of the socialcosts related to road accidents. So noise cannot be considered only anenvironmental problem, but it has serious consequences on healthand economics.

Moreover, several studies have clearly highlighted that the aware-ness of citizens on noise issues is increasing. For instance, a survey-based research performed in 2014 in 5 different European States provedthat the willingness-to-pay (WTP, i.e. the largest amount of money anindividual is agreeable to pay for a product or service) to avoid healthrisks related to air and noise pollution is similar. The study observedthat the WTP to avoid road traffic noise effects varies from 90 to 320 €

per person per year depending on the awareness on noise related healthrisks of the interviewees; the lowest value was given by a poorlyinformed population while the highest one by those having detailedinformation (Istamto et al., 2014).

In 2002 the European Union issued the fundamental tool to tacklenoise issues with a common approach between all the Member States:the EuropeanDirective 2002/49/CE, also called the END (EnvironmentalNoise Directive) (European Union, 2002). The goal of this legislative in-strument is “to define a common approach intended to avoid, preventor reduce on a prioritized basis the harmful effects, including annoy-ance, due to exposure to environmental noise”.

To this extent several actions are needed by each Member State:

• evaluation of the population exposed to high levels of noise (notconsidering military activities, neighbourhood or occupationalnoise) by means of noise mapping activities;

• a proper information and communication campaign to increase theawareness of citizens and all the involved stakeholders about noiserelated effects;

• definition of common strategies to solve or mitigate noise problemsand protect quiet areas.

The END specifically requests to agglomerations, i.e. urban areas withmore than 100,000 inhabitants, roads withmore than threemillion vehi-cle passages per year, railways with more than 30,000 train passages peryear and airports withmore than 50,000movements per year to realize anoise map of their emissions, evaluating the exposure of the population,and to plan actions to tackle these issues (Action plans). Other impactingsources, such as large industrial plants (Alayrac et al., 2010), wind farms(Nissenbaum et al., 2012) or ports (Murphy and King, 2014; Schenoneet al., 2014), are not specifically considered in the END (they are analysedonly if they are included inside an agglomeration), even if their noiseemissions can be detrimental for citizens' health.

Concerning noise mapping, the European Commission has decid-ed to harmonise the methodologies that the Member States need toadopt by introducing CNOSSOS‐EU (Common Noise aSSessmentMethOdS) (Kephalopoulos et al., 2012, 2014). This common methodshould be fully operational for the next round of EU strategic noisemapping in 2017. Of course having a common method does not nec-essarily guarantee good noise mapping, because of the need of pro-viding the models with high quality input data to obtain significantoutputs, according to the concept of “garbage in garbage out”(WG-AEN, 2007). However this is the first important step to obtaincomparable data from all the Member States: this is of particular im-portance since one of the greatest failures of the first rounds of stra-tegic noise mapping was the impossibility of comparing noise dataand maps coming from the different EU countries (Arana et al.,2014).

On the contrary there are no common methodologies for the realiza-tion of action plans and for the time being no attempt to define or tobuild them has been made; in particular no procedure has beenestablished for the identification of the most critical areas, i.e. areas thatmost urgently need noise mitigation actions. Commonly noise action

plans rank the different parts of the examined area, i.e. agglomerationor area affected by road, railway or aircraft sources, in terms of howthey are impacted by noise using scoring systems.

In the years a lot of scores have been proposed by researchers orpublic administrations, each characterized by a different algorithm.Some of them consider only the noise level in their formula, othersalso the number of people affected by noise, still others the presenceof schools and hospitals and so on.

The scope of the paper is to provide a review of these scoringsystems and to apply some of them to an area selected as a case study,in order to show the peculiarities of each of them and the differencesderiving by their applications in a possible action plan.

Recently some authors have proposed other procedures, mainlybased on the so called soundscape approach, that integrate physicalparameters (acoustic measurements or calculations) with peoples' per-ception and expectations in noise action plan definition (Schomer et al.,2013; Vogiatzis and Remy, 2014). These procedures, though reallyinteresting, requires a lot of qualitative data that cannot be found innoisemaps and so they have not been considered suitable for a compar-ison with the other indices analysed in the present paper.

2. Review of noise priority indices

This section reports a review of the indices proposed by researchers,private bodies, public administrations or states to define a ranking of theareas where noise can be considered most impacting. These rankingsare commonly used to give priorities to the mitigation measuresproposed in noise action plans of transportation infrastructures oragglomerations, as the ones required by the END.

As the following text will show, some indices mainly focus on thesound pressure level, others on the land use, for instance highest valuesare reached if schools or hospitals are included in the area, others on thenumber of annoyed people and so on. A brief description of each index isreported in each subsection; further information can be found in thesuggested references.

2.1. Indices based on effects of noise on people's health

The European Environment Agency released in 2010 a technical re-port aimed at summarizing some proved relationships between noise ex-posure and health effects such as annoyance, sleep disturbance andischemic heart disease (European Environmental Agency, 2010), inparticular the dose response relationships defined by Miedema andOudshoorn (2001). Annoyance is defined as an “emotional state connect-ed to feeling of discomfort, anger, depression and helplessness” thatshould be evaluated by means of ISO 15666 questionnaires (ISO 15666,2013). Concerning this topic, the evaluations recommended by the reportconsider the kind of noise source and its acoustic impact in terms of Lden;the outcomes are the percentages of people annoyed (%A) and highlyannoyed (%HA):

%Aroad ¼ 1:795 � 10−4 Lden−37ð Þ3 þ 2:110 � 10−2 Lden−37ð Þ2þ 0:5353 Lden−37ð Þ ð1Þ

%HAroad ¼ 9:868 � 10−4 Lden−42ð Þ3−1:436 � 10−2 Lden−42ð Þ2þ 0:5118 Lden−42ð Þ ð2Þ

%Arail ¼ 4:538 � 10−4 Lden−37ð Þ3 þ 9:482 � 10−2 Lden−37ð Þ2þ 0:2129 Lden−37ð Þ ð3Þ

%HArail ¼ 7:239 � 10−4 Lden−42ð Þ3−7:851 � 10−3 Lden−42ð Þ2þ 0:1695 Lden−42ð Þ ð4Þ

%Aair ¼ 8:588 � 10−6 Lden−37ð Þ3 þ 1:777 � 10−2 Lden−37ð Þ2þ 1:221 Lden−37ð Þ ð5Þ

292 F. D'Alessandro, S. Schiavoni / Science of the Total Environment 518–519 (2015) 290–301

%HAair ¼ −9:199 � 10−5 Lden−42ð Þ3 þ 3:932 � 10−2 Lden−42ð Þ2þ 0:2939 Lden−42ð Þ: ð6Þ

In each of the above equations Lden is the daily-evening-night equiva-lent sound level generated separately by each noise source, i.e. road forEqs. (1) and (2), railway for Eqs. (3) and (4) and aircraft for Eqs.(5) and (6).

The negative effects of noise on sleep are defined by European Envi-ronmental Agency (2010) in terms of self-reported sleep disturbance,polysomnographic sleep (EEG-reactions), bodymovements and reportedawakening. Usually self-reported sleep disturbance is the parameter usedto define a dose–effect relationship between the night-time noise levelLnight and the percentages of people disturbed (%SD) and highly disturbed(%HSD). The relationships are as follows:

%SDroad ¼ 13:8−0:85 � Lnight þ 0:01670 � L2night ð7Þ

%HSDroad ¼ 20:8−1:05 � Lnight þ 0:01486 � L2night ð8Þ

%SDrail ¼ 12:5−0:66 � Lnight þ 0:01121 � L2night ð9Þ

%HSDrail ¼ 11:3−0:55 � Lnight þ 0:00759 � L2night ð10Þ

%SDair ¼ 13:714−0:807 � Lnight þ 0:01555 � L2night ð11Þ

%HSDair ¼ 18:147−0:956 � Lnight þ 0:01482 � L2night ð12Þ

Also in this case Lnight refers only to the generating source (road, railor aircraft).

If these percentages are multiplied by the number of people, ni, livingin the i-th of a set of N buildings, 12 different noise scores can be calculat-ed: for instance the noise score related to annoyance caused by road traf-fic noise (NS%A,road) is given in Eq. (13):

NS%A;road ¼XNi¼1

ni �%Aroad

100ð13Þ

All the abovementioned indices consider separately the effect of noisesources. Within the activity of the 6th FP EU project Qcity, Miedema andBorst (2007) developed a method to evaluate the annoyance due to thecontemporary exposure to multiple sources. This procedure requires toevaluate separately the noise impacts of roads, railways and aircrafts interms of Lden and the corresponding percentages of highly annoyed peo-ple using respectively Eqs. (2), (4) and (6). Then these data are used tocalculate the equally annoying road traffic levels for aircraft and for rail-ways (re(Lden,i), where i is either railways or aircraft):

re Lden;i� �

¼ 46:85þ 168:9 � F %HAið Þ− 0:8843F %HAið Þ for Lden;i N42 dB Að Þ

Lden;i for Lden;i ≤ 42 dB Að Þ

8<:

ð14Þ

where:

F xð Þ ¼ −2:374 � 10−4 þ 1:05x � 10−4 þffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi2 � 10−7−5x � 10−8 þ 1:11x2 � 10−8

p� �1=3:

ð15Þ

Then the equivalent road noise level Lden,T is calculated through:

Lden;T ¼ 10 � log 100:1re Lden;airð Þ þ 100:1re Lden;railð Þ þ 10 0:1Lden;roadð Þ� �: ð16Þ

The percentage of annoyed and highly annoyed people due to theexposure to multiple sources is calculated inserting Lden,T respectivelyinto Eqs. (1) and (2). A noise score formultiple sources based on annoy-ance can be finally calculated in the same way described for Eq. (13).

2.2. House depreciation index

The EEAGuidelines (European Environmental Agency, 2010) give anestimation of the house value reduction due to road noise exposureanalysing the real European estate markets, indicating that in averagehouses prices lose 0.5% of their value for each dB(A) above 50–55 Lden.The value of house depreciation in terms of lost €/dB(A) can be usedas a noise score to rank the buildings that are most economically affect-ed by noise.

2.3. Building Prioritisation Score (BPS)

This methodwas developed by the Scottish Government to evaluatethe noise exposure of residential buildings (Scottish Government,2009). For each building and for each kind of source (road, railwayand aircrafts) BPS is calculated as follows:

BPS ¼ L þ 10 � log NAð Þ ð17Þ

where:

L noise level (Lden or Lnight) at the considered building generatedby the considered source;

NA ¼ N � PA � A100

ð18Þ

N number of address points within the building;PA population per address;A percentage of people annoyed, given by Eqs. (1), (3) or (5)

depending on the source.

2.4. Multi Annoyance Building Prioritisation Score (MABPS)

In 2011 Licitra et al. (2011) proposed to improve the BPS in order toevaluate the contemporary exposure to multiple sources. The proposedMABPS can be calculated as follows:

MABPS ¼ Ltot þ 10 � log NAð Þ ð19Þ

where Ltot is the estimated value of the noise level in the most exposedfaçade due to all the impacting sources in terms of Lden. In this relationNA is expressed similarly to Eq. (18) but the annoyance is calculatedfor multiple noise sources using the annoyance equivalents model pro-posed byMiedema (2004). This method aims at evaluating the percent-age of annoyed people due to multiple noise sources using Eq. (1)where the Lden,r value is responsible of the same annoyance due to thenoise exposure to multiple sources:

Lden;r ¼ 10 � logXNn¼1

10 � expLr;n=10

!: ð20Þ

Lr,n are the noise levels, in terms of Lden, of the different sourcesconsidering their different effects on people's annoyance:

• Lr,m = Lden,road;• Lr,r = (2.1 ∗ Lden,rail − 3.1) / 2.22;• Lr,a = (2.17 ∗ Lden,aircraft + 15.6) / 2.22 or (2.05 ∗ Lden,aircraft + 61) / 2.22;

Table 2Kilkenny Noise Action Plan prioritisation matrix.

Decision selection criteria Score rangeday

Score rangenight

Noise band dB(A) Lden/Lnight b45 5 645–49 4 550–54 3 455–59 2 260–64 1 365–69 2 470–74 3 575–79 4 6≥80 5 7

Type of location Urban centre 1 1Commercial 1 2Residential 2 3Noise sensitive location 3 3Quiet area 3 1Recreational open space 2 2

Type of noise Road 3 4Rail 2 3Industry 2 3Airport 3 4

Table 1Dublin Noise Action Plan prioritisation matrix.

Decision selection criteria Score rangeday

Score rangenight

Noise band dB(A) Lday/Lnight b55 3 455–59 2 260–64 1 365–69 2 470–74 3 5≥75 4 6

Type of location City centre 1 1Commercial 1 2Residential 2 3Noise sensitive location 3 3Quiet area 3 3Recreational open space 2 2

Type of noise Road 2 3Rail 1 2Airport 3 4

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• Lr,i = Lden,industry + 3;• Lr,wt = (1.65 ∗ Lden,windturbine + 41) / 2.22.

2.5. Gden

Jabben et al. (2010) defined the Gden indicator to have an estima-tion of the noise exposure of a city, combining the overall noise levelin terms of Lden with the population exposed to noise. Licitra (LicitraandAscari, 2014) revised this indicator introducing theweighting factor1/Ntot to obtain the normalized parameter Gden,norm:

Gden;norm ¼ 10 log1

Ntot∑in

Lden;i�

10i

� �ð21Þ

where Ntot is the population of the studied area, ni is the number ofdwellers exposed to the i-th class of exposure and Lden,i is the represen-tative noise level of the i-th class; for instance 57.5 dB(A) is the repre-sentative noise level of the class of exposure 55–60 dB(A). While Gdengives higher scores to areas that are intensively populated but not nec-essarily noisier than the surrounding ones, the weighting factor includ-ed in Gden,norm allows to givemore importance to noise pollution: thisis important when the goal is to compare all the different areas of a cityor agglomeration. On the contrary, the unweightedGden can be usefullyemployedwhen the goal is restricted to the identification of hot spots orto the assignment of a score to every building, as in the present paper.The Lden value should be calculated in compliance with the Miedema'sannoyance equivalents model reported in Eqs. (14)–(16).

2.6. Qcity noise scoring proposal

Within the activities of the already mentioned Qcity project, Petzet al. (2007) proposed an exponential relationship to calculate a noisescore taking into account the noise level at the relevant façade Lden,i,the number of people exposed to this level ni, the sound insulationproperties of the façade and the kind of noise source. As reported byLicitra (2012), the indicator QC can be simplified without consideringthe effect of façade insulation, a parameter that commonly cannot beevaluated:

QC ¼ ∑ini100:15� Lden;i−50ð Þ for Lden;i≤65 dB Að Þ

∑ini100:30� Lden;i−57:5ð Þ for Lden;iN65 dB Að Þ

8<: : ð22Þ

The Lden,i could be referred to the noise of the single sources,in order to have separate scores for each kind of source, i.e. road, railand aircraft, or calculated in compliance with the annoyance equiva-lents model reported in Eqs. (14)–(16) in order to have a scoreaccounting for the contemporary influence of all the sources onpeople's annoyance.

2.7. Dutch Population Annoyance Index (PAI), Norwegian Støyplageindeks(SPI) and German Lärmfaktor (LF)

These methods take into account only exposure to road traffic noise.The Population Annoyance Index, PAI, was developed by de Ruiter(2009) considering the alreadymentioned dose–response relationshipsdefined byMiedema and Oudshoorn for people highly annoyed by roadtraffic noise (Eq. (2)). The method requires to assign each building ordwelling to a noise exposure class (45–50 dB(A), 50–55 dB(A), etc.)considering its estimated noise level; then the central value of thenoise class (Lcentralvalue,den) is assigned to each dwelling or building.The PAI index of the i-th building or dwelling, having a number ni of

residents, is calculated as follows:

PAI ¼ ni � 0:0323 Lcentralvalue;den−42� �2

: ð23Þ

Similar indicators are the Norwegian SPI (Støyplageindeks, in En-glish “noise annoyance index”, Eq. (24)) (Gjestland et al., 2003) andthe German LF (Lärmfaktor, in English “noise factor”, Eq. (25))(Arnold et al., 1977):

SPI ¼ ni � 1:58 � Lden−62:5ð Þ ð24Þ

LF ¼ ni � 2Lden10 −5:75�

: ð25Þ

2.8. Prioritisation matrixes of the noise action plans of Dublin and Kilkenny

In theNoise Action Plan of the agglomeration of Dublin (Dublin LocalAuthorities, 2013), the prioritisation of the areas to be acousticallymitigated is performed using a decision matrix that considers thenoise exposure, the land use and the impacting sources (Table 1). Forinstance, a building in the city centre affected only by road noise withLday of 57 dB(A) and Lnight of 50 dB(A) has an overall score of(2 + 4) + (1 + 1) + (2 + 3) = 13.

Table 4Noise prioritisation methods considered in the comparative analysis.

Index Reference Shortname

Dublin prioritisation matrix Dublin Local Authorities (2013) DubMatKilkenny prioritisation matrix Kilkenny City Council (2013) KilMatMulti-annoyance BuildingPrioritisation Score

Licitra et al. (2011) MABPS

Number of people highly annoyed European Environmental Agency(2010)

NHA

Number of people annoyed European Environmental Agency(2010)

NA

Qcity noise scoring proposal Petz et al. (2007) QCNSGden indicator Jabben et al. (2010) GdenItalian Priority Index Italian Government (2000) IP

Table 3Noise limits under Italian law.

Acousticclasses

Characteristics of the area Noise limits dB(A)

Llim,diurno Llim,notturno

Class I Noise sensitive locations (schools, hospitals,important green areas etc.)

50 40

Class II Areas mainly dedicated to a residential use 55 45Class III Mixed areas (average traffic and density of

population, presence of commercial activities,offices, low density of handcraft activities andabsence of industries)

60 50

Class IV Intensive human activities areas (busy roadtraffic, high density of population, high presenceof commercial activities and offices, presence ofhandcraft activities).

65 55

Class V Mainly industrial areas 70 60Class VI Exclusively industrial areas 70 70

294 F. D'Alessandro, S. Schiavoni / Science of the Total Environment 518–519 (2015) 290–301

A similar procedure was used by the Councils of the County and Cityof Kilkenny for its Noise Action Plan (Kilkenny City Council, 2013); nev-ertheless they decided to use Lden indicator instead of Lday and the clas-ses are slightly different (Table 2). For instance, a building in the CityCentre affected only by road noise having a Lden of 57 dB(A) and Lnightof 50 dB(A) has an overall score of (2 + 4) + (1+ 1) + (3 + 4) = 15.

It is worth noting that the highest scores are assigned to the areaswhere noise levels are below 55 dB(A) for Dublin and 45 dB(A) forKilkenny and above 75 dB(A) for Dublin and 80 dB(A) for Kilkenny(see Tables 1 and 2): in this way the attention is focused both onquietest areas (in order to protect them) and on the worst pollutedones (in order to mitigate them).

2.9. Italian Priority Index

The Italian national Priority Index IP was issued by the Ministry ofthe Environment in 2000 (Italian Government, 2000). For the i-th

Fig. 1. Aerial image of the urban area of Ponte San Giovanni (source Google Maps). The studylegend, the reader is referred to the web version of this article.)

building it takes into account the number of people ni affected bynoise, the noise level and the characteristics of the area in which thenoise limits are overtaken:

IPi ¼ ki � ni �MAX Ldiurno−L lim;diurno; Lnotturno− L lim;notturno

� �ð26Þ

where:

• ki is a correction coefficient, equal to 4 for hospitals and retirementhomes, 3 for schools and kindergartens and 1 for other residentialbuildings;

• ni is the number of people affected by noise;• Llim,diurno and Llim,notturno are the Italian noise limits for the i-th build-ing in the Italian diurno (06-22) and notturno (22-06) time period.Noise limits depend on the characteristics of the area and are reportedin Table 3;

• Ldiurno and Lnotturno are the average values of the A-weighted noiselevel estimated at the i-th building façade in the Italian diurno(06-22) and notturno (22-06) time period.

area is highlighted in yellow. (For interpretation of the references to colour in this figure

Fig. 2. Position of the calculation points (in green) on the façade. Each j-th calculationpoint is representative of the part of façade (of the i-th building) having a length equalto li,j. (For interpretation of the references to colour in this figure legend, the reader is re-ferred to the web version of this article.)

295F. D'Alessandro, S. Schiavoni / Science of the Total Environment 518–519 (2015) 290–301

3. Methods

3.1. Case study

The comparative analysis was performed in the urban area of PonteSan Giovanni (Fig. 1), a district in the suburbs of Perugia, central Italy.The study area has a surface of 5.63 km2 and houses 1,200 residentialbuildings and 14,000 inhabitants (ISTAT, 2011). The area is mainly flatand quite intensively populated for the Italian standards, withmany of-fices and commercial activities and some industrial areas. Nine schoolsare included in the study area; the number of students in each buildingwas estimated from the floor area of the school. Schools are the onlynoise sensitive buildings/areas, since no hospitals or particularly valu-able urban parks are included in the study area.

The area is affected by the noise emissions of dual carriageways(the annual average daily traffic of the most important one is about

Fig. 3. Example of the creation of the 10m spaced grid (points in green) in the study area. (Forweb version of this article.)

77,000 vehicles/day), urban roads, railways and slightly by a commer-cial area. The noise limits are defined in the Acoustic Zoning Plan ofthe Municipality of Perugia.

The acoustic zoning plan is a plan that each Italian municipality isobliged to issue in order to manage environmental noise. The plan clas-sifies the territory of the municipality in six areas, related to differentcity planning characterizations, activities and conditions for the use ofthe territory: the six areas are characterized by different noise limitvalues, as shown in Table 3. Ponte San Giovanni district is mainly classi-fied as Classes III and IV, while schools are classified as Class I.

3.2. Calculation of the noise priority indices

The comparative studywas performed only for the indices consider-ing multi-source exposure listed in Section 2; they are listed in Table 4togetherwith the corresponding short names thatwill be used through-out the paper.

The Lden and Lnight noise indicators were estimated in calculationpoints placed on each building façade, as requested by the END proce-dure, whereas the Italian noise legislative framework requires to esti-mate Ldiurno and Lnotturno in calculation points located at 1 m from eachbuilding façade. The Italian noise indicators were estimated in order tocalculate the Italian Priority Index IP, while all the other noise priorityindices were calculated using EU noise indicators Lden and Lnight, exceptfor DubMat that requires Lday.

The noise simulations were performed using SoundPLAN® 7.1(SoundPLAN) and the following methods: NMPB-Routes for roads(AFNOR XPS 31–133, 2001), RFI (Italian Rail Network method) forrails (RFI, 2006) and ISO 9613-2:1996 for Industrial plants (ISO 9613-2, 1996). The input data used for the characterization of the sourceswere the same used by the Authors for the Strategic Noise Map of theagglomeration of Perugia (Italy). Demographicswere updated consider-ing the outcomes of the Italian population census of 2011 (ISTAT, 2011)and applying the procedure defined by the European Good PracticeGuide on strategic noise mapping (WG-AEN, 2007) and successfullyused by the authors during the noise mapping activities of theEuropean co-funded LIFE 2009 ENV/IT/000102 NADIA project

interpretation of the references to colour in this figure legend, the reader is referred to the

Fig. 4. Realization of the buffers. A buffer area is highlighted in yellow. The green dots are the grid points, the red dots are the calculation points. (For interpretation of the references tocolour in this figure legend, the reader is referred to the web version of this article.)

296 F. D'Alessandro, S. Schiavoni / Science of the Total Environment 518–519 (2015) 290–301

(Asdrubali et al., 2012, 2013). This procedure allowed to estimate thenumber of residents in each residential building, while the number ofstudents in each building was estimated from the floor area of theschool since data about schools population was not available.

Usually a value of a priority index is assigned to a portion of anagglomeration or to one or a group of buildings by summing, averagingor maximizing the single values of the priority index evaluated in eachcalculation point. In this way a ranking between areas/buildings canbemade andmost neededmitigation actions can be selected. However,since the scope of the present research is to compare the effect of theapplication of the different procedures to a limited area selected ascase study, all the priority indices were calculated singularly for eachcalculation point (not for buildings or areas) so a score was assignedto each point.

The calculation of several indices requires to evaluate the number ofpeople affected by a certain noise level. The procedure for assigning the

Fig. 5. Cumulative frequencies of the tested noise priority scores in th

number of people to each calculation point is reported as follows. Eachj-th calculation point is placed at the centre of the j-th part of façadeof the i-th building at a height of 4 m above the ground. Each façadewas divided in sub-façades having a maximum length of 5 m; thenthe calculation point was placed in front of the sub-façade in order toobtainmore detailed data. The advantages of this procedure for calcula-tion point localisation have been already evidenced by the authors in(D'Alessandro et al., 2014).

The number of people ni,j assigned to the j-th calculation point of i-thbuilding is:

ni; j ¼ li; j � Di ð27Þ

where li,j is the length of the portion of the façade assigned to the j-thcalculation point (Fig. 2) and Di is the population density of the i-thbuilding, defined as the number of residents (or students) divided by

e case study area (values are normalized in the range of 0–100).

Fig. 6. Boxplots of the distribution of noise priority scores (values are normalized in the range of 0−100).

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the perimeter. This procedure, developed in D'Alessandro et al. (2014),allowed to have amore detailed calculation of the noise priority indices,since a high number of specifically located calculation points were usedin comparison with the END procedure, which requires a single pointlocated on the centre of the most exposed façade.

Since all the indices have different scales and measurement units,normalization was required in order to compare their values properly.A min–max normalization was applied to all the indices (x) in order

Fig. 7.Map reporting normalized QCNS values in the case study

to obtain normalized indices (xN) whose values are included in therange of A–B as follows:

xN ¼ x−xmin

xmax−xmin

� �B−Að Þ þ A ð28Þ

where A=0 and B=100 in order to have values in the range of 0–100.

area; the squares highlight the area with the highest value.

298 F. D'Alessandro, S. Schiavoni / Science of the Total Environment 518–519 (2015) 290–301

The decision of applying a normalization relies on the fact that,except for DubMat and KilMat, the other indices have not a definedrange of variation since they are calculated using, among the other pa-rameters, the population and the noise level. Since these latter parame-ters have not well defined ranges of variation, the corresponding rangeof the indices cannot be defined a priori.

Moreover, the following assumptions were made:

• A value of 0 was assigned to MABPS and to NA if Lden is lower than37 dB(A). This approach is justified because Eq. (1) considers thatthe percentage of annoyed people, used in NA andMABPS evaluation,is positive only above this threshold;

• For the same reason, a value of 0 was assigned to NHA if Lden is lowerthan 42 dB(A) (see Eq. (2));

• A value of 0was assigned to the indices DubMat and KilMat if Lday, Ldenor Lnight is lower than 35 dB(A). This operation was necessary sincehigh scores are assigned to points where the noise levels are low(see Tables 1 and 2) but under 35 dB(A) the impact of noise sourcescan be considered negligible;

• Still concerning DubMat and KilMat, the score due to the type of loca-tion was evaluated taking into account the noise limits given by theItalian legislation: Class I was considered as “Noise sensitive location”,Class II as “Residential”, Classes III and IV as “Urban centre” and ClassesV and VI as “Commercial”.

3.3. Maps realization

The comparison between the selected noise priority indices wasperformed also thanks to maps realized using QGIS version 2.6 (QGISDevelopment Team) and the following procedure:

Fig. 8.Map reporting normalized IP values in the case study

1. A grid of points with a 10meter spacingwas created inside the studyarea (Fig. 3): 56,280 grid points were defined;

2. A circle area centred on the grid point with a radius of 10 m wasrealized for each point;

3. The values of the priority indices of the calculation points included ineach circle area created in step 2 were averaged and the averagevalue was assigned to the centre of the circle area: so a value of pri-ority index was assigned to each grid point. As an example, in Fig. 4the circle area is in yellow colour, four red calculation points areincluded in the area and the average value of the priority index calcu-lated in these points is assigned to the green point at the centre of thearea;

4. The distribution of the indices was then analysed colouring the gridpoints with respect to the values estimated in the step 3 fromgreen (0), to yellow (50) and to red (100). Figs. 7–10 are examplesof the outcomes of this procedure; data were mapped without inter-polation processes.

4. Comparative analysis

All the following considerations refer to the normalized values of thenoise priority scores (in the range of 0–100), obtained by means ofEq. (28).

The outcomes of the comparative analysis show that the analysednoise priority scores have two different behaviours; these behavioursare highlighted by the analysis of the cumulative frequency of the valuesassumed by the different scores in each one of the 9,075 calculationpoints (Fig. 5):

• Highly selective indices: The indices belonging to this category assignvery high values to few points, highlighting only the most criticalsituations. QCNS, IP, NHA and NA fall into this category;

area; the squares highlight the areas with high values.

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• General indices: Gden, MABPS, DubMat and KilMat show a lessselective behaviour, and they can be used to have a more generalidea of the noise climate of the area.

This effect is clearly visible in Fig. 6 that reports the boxplots of thedistribution of the normalized scores. The bottom and the top of thebox indicate respectively the 25th and the 75th percentile while thered line represents the median value. The whiskers extend to 1.5times the height of the box or to the minimum or maximum values.The cases that do not fall inside the whiskers are indicated as circleswhile extreme outliers (asterisks) have values more than three timesthe height of the boxes.

QCNS is the most selective indicator, giving the highest priority topoints with high noise levels. In the studied area, except for the calcula-tion point characterized by the 100 value, there is only one point wherethe normalized noise priority score is over 10. In the other points thescore is always under 7.5.

IP assigns the highest priority to noise sensitive buildings because ofthe application of the correction coefficient in Eq. (23), of the low noiselimits (usually Class I, 50 dB(A) from 06 to 22 and 40 dB(A) from 22 to06) and of the high number of population in these buildings; in schoolsand hospitals respectively, the number of students and of beds are con-sidered. In the studied area, the residential building characterized by thehighest IP value has a normalized score of 14.5. The index is less selec-tive than QCNS, but also in this case about 99% of the 9,075 calculationpoints have a normalized score lower than 10.

Also the methods related to the number of annoyed and highlyannoyed people (Miedema and Borst, 2007) are highly selective: thepercentage of calculation points in which the normalized score isunder 10 is 88.6% for NA and 91.6% for NHA. Whereas QCNS and IP

Fig. 9. Map reporting normalized MAB

assign high scores respectively to high exposed façades and to noisesensitive buildings, NA and NHA give greater values to the most popu-lated buildings.

The prioritisationmatrixmethods assign integer values so the trendsof the cumulative frequencies are stair-shaped. DubMat is the less selec-tive method between the ones tested: about 50% of the calculationpoints have the same normalized value 77.8, corresponding to a notnormalized value of 14. The peculiarity of this model is that it assignshigh priority scores also to noise sensitive location affected by lownoise levels; so the method is able to identify areas exposed to highnoise levels to be mitigated, but also quieter areas to be protected. Sim-ilar results were obtained using the index KilMat.

The cumulative frequencies of Gden and KilMat are similar, but inthefirst one theweight of noise exposure is considerably higher. Finally,the results for MABPS are quite similar to the ones of Gden.

The maps allow to graphically highlight the aforementioned differ-ences between the indices. In the maps realized for the highly selectivepriority scores (QNCS, IP, NA and NHA) only few critical areas canbe recognized. Figs. 7 and 8 report two examples of this kind of mapsshowing respectively the values of QCNS and IP. The red coloured areain Fig. 7 (QNCS) identifies the areawhere Lden has the highest values, in-dependently from the type of building. On the contrary the highestvalues of IP are assigned to noise sensitive buildings, as shown in Fig. 8.

Figs. 9 and 10 report an example of maps realized using respectivelyMABPS and DubMat. In the first one the highest values characterize theareas with the highest noise levels due to the proximity to noisiestsources, such as the major roads close to the studied area. In Fig. 10the areas having an average value of DubMat between 90 and 100 aredifferent and they comprise noise sensitive locations, zones affectedby very low and very high noise levels.

PS values in the case study area.

Fig. 10. Map reporting normalized DubMat values in the case study area.

300 F. D'Alessandro, S. Schiavoni / Science of the Total Environment 518–519 (2015) 290–301

5. Discussion and conclusions

TheEuropeanCommissiondefineda commonmethod (Kephalopouloset al., 2012) to perform noise mapping activity specifying the noise prop-agationmodel tobeused andalso releasing apractical guideline (WG-AEN,2007). The END states that the outcomes of noisemaps should be used forthe realization ofActionPlans, i.e. specificplans focused on thedefinition ofnoise mitigation measures through priority-based methods. A commonmethod for noise action plans has not been proposed yet and as a conse-quence different procedures have been defined in each EuropeanMemberState, at national or even at local level.

The comparative analysis performed in the present research demon-strates howmuch the selection of the noise priority score influences theresults in terms of identifying the most critical areas. Different noisescores applied in the same study area will lead to different rankings.

The indices IP, QCNS, NHA and NA assign high values to very fewareas; so they should be chosen if the aim of the action plan is to localizeand identify very clearly few zones where noise mitigation is more

Table 5Summary of the factors influencing the noise priority scores.

Noisescore

Scores influenced by (● highly influenced, ♦ influenced,○ not influenced):

High noiselevels

Density ofpopulation

Noise sensitivebuildings

Quiet areas to bepreserved

Landuse

MABPS ● ♦ ○ ○ ○Gden ● ♦ ○ ○ ○DubMat ♦ ○ ♦ ♦ ♦KilMat ♦ ○ ♦ ♦ ♦QCNS ● ♦ ○ ○ ○IP ♦ ♦ ● ○ ●NA ♦ ● ○ ○ ○NHA ♦ ● ○ ○ ○

urgent. Otherwise the other indicators (Gden, MABPS, DubMat andKilMat) should be preferred because they assign the noise priorityscore in a more gradual way.

IP, DubMat and KilMat tend to give high scores to noise sensitivelocations, such as schools and hospitals. For Gden,MABPS and especiallyQCNS indices the noise exposure has the greatest weight while for NAand NHA the most influencing parameter is the population density.

Moreover, DubMat and KilMat assign high values also to areaswhere the noise levels are low; this approach is useful for noise actionplains focused not only to the rehabilitation of the noisy areas, butalso to the preservation of the quieter ones.

The comparison of the maps developed within this research usingthe investigated noise priority scores confirmed the results of theanalysis.

A summary of the factors influencing the different noise priorityscores is reported in Table 5.

The comparative analysis carried out in this research demonstrateshow the prioritisation method can deeply affect the priority rankingand therefore the whole Action Plan. These differences are due notonly to the parameters taken into account, but also to how these param-eters are considered. Somemethods give a highweight to thenumber ofcitizens affected by noise, other to the noise levels and others to theurban characteristics. Several methods, named highly selective in thepresent paper, assign high priority score only to few areas and lowvalues to the other ones; other noise prioritisation procedures, namedgeneral indices in the paper, assign values more gradually.

For these reasons, the definition of a common European procedurefor the prioritisation of noise mitigation actions or for the localizationof the most critical areas should be considered as an objective by theEuropean policy makers for the further improvements of the EuropeanDirective; the use of a common method should allow to better definecommon strategies in Europe to tackle noise impacts. Obviously these

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results could be more easily achieved if all the Member States wouldadopt entirely the contents of the Noise Directive, above all substitutingor integrating their national regulations for noise pollutionmanagement.

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