noise exposure in eu cities

Noise Exposure in EU cities: a challenging comparison

G. Licitra and E. Ascari

AIA-DAGA 2013Conference on Acoustics

EAA Euroregio - 18-21 March 2013

AIA-DAGA 2013 conference on Acoustics

Introdution

First round of END implementation has been completed, first action plans has been drawn up;

Despite an homogeneous reporting system, it’s still difficult to compare and analyse results;

In particular, difficulties in comparing maps results and exposition reflect into different possible actions;

Indicators and techniques to identify critical and quiet areas have been attempted but national laws and requirements are various.


Hot spots identification Actions has to be identified for hot spots and critical areas.

Different scores are defined according local laws and guidelines; a review of different methods has been proposed by Probst.

e.g. Qcity project has proposed a methodology different from the general linear scoring.

Hot spot identification is now provided by many softwares, as it is a relevant issue.

By the way hot spots identification is still a long post-process detailed activity that often leads to loose contact with concrete actions.

Noise Mapping in the EU: Models and Procedures, CRC Press, 2012 edited by G.LICITRAFrom noise maps to critical hot spots: Priorities in action Plans; W. Probst


Group indicator: areal solutions

The need of an indicator of global noise quality improvement has been highlighted.

Lot of studies are now trying to analyse perspectives and to evaluate effects of mitigation actions along time as an average over a defined population.

A group noise indicator called Gden has been proposed in a lots of previous article to analyse environmental noise decrement along time and to compare different locations of a city.

M. Weber; J. Jabben, An indicator for area specific noise impact: GdenInternoise 2010, Lisbon


Gden for European cities comparison Gden could be used also at European level to compare

pollution of different cities because it is simply based upon population and Lden values, which are available for all mapped cities.

Gden values rise with population ni:

Using it as it is commonly defined would lead to identify larger cities but not to understand worst polluted cities.


Gden adaptation to European data [1]

Gden should be scaled on total population N.

where i indicates exposure classes and ni is population in that class.

With this renormalization Gden would be equivalent to average noise exposure of city population.


Gden adaptation to European data [2]

To apply Gden calculation to EIONET database of European exposure, average values of Lden should be assigned also to external classes of exposure;

This approximation obviously introduces errors which would be larger for those cities that has an huge number of people in extreme classes.

Class i Not reported (<55 dBA)

55-60 dBA

60-65 dBA

65-70 dBA

70-75 dBA

>75 dBA

Ldeni [dBA] 50 57.5 62.5 67.5 72.5 80


Gden use and relation with annoyance

As already shown in cited study Gden is well related to highly annoyed (HA)

Normalized Gden vs total percentage of HA:

Notice that different mapping methodologies affect results We want to try to improve this relation finding groups of data within european exposure dataset.

y = 0,0003e0,0921x

R2 = 0,7475

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Groups within European dataset

There are large difference reported in shapes of exposure curves.

In other papers group of mapping data has been already highlighted;

In particular: Germany curves are created based on national method of

people distribution; England maps are produced all by the same institute (DEFRA)

so are all similar.

Here some type of curves will be identified according shape and ratio values between classes.

M. van den Berg, G. Licitra EU-noise maps: Analysis of submitted data and comments Euronoise 2009, Edinburgh


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72 monotonic decreasing

20 curves have less than 50% of population under 55 dB and more than 15% over 65 dB

46 curves have more than 50% of population under 55 dB and less than 15% over 65 dB (in this group there are 26 German cities)

Exposure shapes [1]

Decreasing >50% Decreasing <50%

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Exposure shapes [2]

45 with a single peak at 60-65 class

19 curves are England cities and they have more than 45% of population in peak class

Peak shaped >45% Peak shaped <45%

All other 26 curves are smoother and are so distributed within countries:


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decreasing >50%

decreasing <50%

peak shaped >50%

peak shaped <50%

Relation with annoyance within groups Gden vs %HA within identified groups

Two groups don’t follow the trend line


Relation with annoyance for countries England and Germany are highlighted

This is a better agreement that one considering whole sample (R2=0.74)

Gden(dBA)

%H

A


Results & further analysis

Data shows that an exponential law relates Gden and %HA;

Therefore Gden can be used to evaluate health risks in a specific area/city.

Following map reports Gden values for European city: National cluster can be observed.

Worst values are highlighted and city names reported.

Average values for each country


Gden values for European cities


Countries average values


National hot spots Since national mapping methods influences Gden results, Gden

could be used at least within region/country to evaluate worst situation and to assign funds to improve noise average quality.

Gden(dBA) Gden(dBA)


Mapping time evolution

Gden has been used also to evaluate improvements and mitigation actions along time;

It is a good indicator to evaluate also hypothetical actions and to understand global solution effectiveness;

It let policy makers understand average situation:

It is an indicator not only of noise quality but also of policies quality.

It could be useful also at local level to evaluate lower scale solutions and hot spots.J.Jabben, E.Verheijen, E. Schreurs Group Noise Exposure level Gden/Gnight; applications to airport noiseReport RIVM 2010 (in Dutch)


Local hot spots identification techniques

As already said, it is a long detailed activity and often it is hard to identify immediately worst situation without completing the whole project;

A lot of techniques are available and a study to compare them has been already carried out by authors;

Here a comparison between Gden and Qcity method is reported

Notice that in this comparison number of inhabitants has been corrected for schools and hospital to reflect Italian laws

E.Ascari, C.Chiari,P.Gallo, G.Licitra, D.PalazzuoliComparison of methods to identify hot spots in Pisa MunicipalityAIA National Conference 2010 (in Italian)


Comparison with Qcity method in Pisa

Probst proposed a method considering weighted levels (Ldenw) to reflect annoyance from different sources;

Noise Score(NS) is assigned based on inhabitants, using maximum over buildings;

Then a spatial average of values is carried out to reflect NS of that area (100 m radius).

)(65L10.max den_w50)-*(L0.15 den_w AdBifinhabNS

building

)(65L10.max den_w57.5)-*(L0.30 den_w AdBifinhabitNS

building


Hot spots according Qcity method


Gden levels haven’t been weighted in this study because we used directly total levels (road traffic is the main source).

Gden resolution depends on extension of aggregation areas available for each agglomeration, so here Italian census areas are used.

Gden calculation in Pisa

↑ Rijnmond Area (NL) ↑ Pisa (IT)


Hot spots according Gden method


Comparison

G.Licitra, P.Gallo, E.Rossi, G.Brambilla A novel method to determine multiexposure priority indices tested for Pisa action plan Applied Acoustics 72(8):6 (2011)

Property Qcity Gden

Resolution High Low

Elaboration time Slow Fast

Simplicity for public and policy makers Low High

Response to developments and local changes Slow Fast

Multiexposure correction introduced Yes To be done


Conclusions

Gden method is very simple to be implemented and also to be reported and explained to citizens;

It is useful to compare different cities and different countries and to establish common policies within Europe;

It is a method that it is robust along time and that allows comparisons based upon census units which are stable along time;

Improvements to Gden indicator to reflects annoyance due to multi-source exposure could be carried out in further studies.

noise exposure in eu cities

Business

gden dba

acoustics gden adaptation

acoustics gden use

gden values

ascari aiadaga

gden calculation

gden internoise

renormalization gden