The development of a practical framework for strategic noise mapping

Applied Acoustics 70 (2009) 1116–1127

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The development of a practical framework for strategic noise mapping E.A. King *, H.J. Rice Department of Mechanical and Manufacturing Engineering, Parson’s Building, Trinity College Dublin, Dublin, Ireland

a r t i c l e

i n f o

Article history: Received 15 May 2008 Received in revised form 23 January 2009 Accepted 30 January 2009 Available online 9 March 2009 Keywords: Environmental noise Strategic noise map Noise measurement Noise prediction Action plan

a b s t r a c t There currently exist a number of commercial tools which may be used to develop strategic noise maps in an effort to satisfy the requirements of EU Directive 2002/49/EC. However, these tools may not be readily available to local authorities with limited resources. This paper investigates the possibility of developing a simplified alternative to using detailed commercial software for the creation of strategic noise maps. Inhouse noise prediction software was used to calculate a noise map of Dublin city centre and results were compared to those of commercial standard software. The in-house software tool was then used to assess the impact of various source-dependent action plans in a time-efficient and practical manner. Measurements were also carried out at various locations throughout the test area, which were then used to investigate the accuracy of predictions. Finally, a hybrid approach to developing a strategic noise map by integrating measurements taken on-site with predictions was developed. This approach was applied to the test area and yielded a refined noise map that presented noise levels which were more reflective of the measured levels recorded on-site. This demonstrated that the method could be used to determine noise levels that would be representative of the acoustic environment experienced on-site. Ó 2009 Elsevier Ltd. All rights reserved.

1. Introduction In 2002 the EU issued Directive 2002/49/EC, seeking to develop a common European-wide strategy regarding the management, control and assessment of environmental noise. The Directive calls for the creation of strategic noise maps for designated areas. These maps must be presented in a clear and comprehensible manner and must be accessible to the public, as a significant emphasis is placed on the involvement of the public throughout each stage of the development process. It is important that calculated noise maps are accurate and satisfy public analysis. Furthermore, this will become an issue of some importance during the development and implementation of associated action plans. WG-AEN’s Good Practice Guide recognises the need for accurate maps that will withstand scrutiny when it states ‘‘The END noise maps and subsequent action plans are probably the highest profile activity that the acoustics and noise control community has carried out, in the public’s eye. Based upon previous experience, the generation of these results will probably lead to articles within the media. Articles may compare adjacent towns, states or countries. In order that the industry’s credibility is upheld, good results and robust recommendations for action should be a desirable aim” [1]. However, in order to produce a noise map, a large number of input variables are required, although a complete set of these * Corresponding author. Tel.: +353 1 896 1134; fax: +353 1 679 5554. E-mail address: [email protected] (E.A. King). 0003-682X/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.apacoust.2009.01.005

variables rarely exists. This leads to a certain amount of assumptions and averages being introduced to the modelling process, which will have an impact on final results to some degree. Some assumptions that may apply to a noise mapping study include:  The number of heavy vehicles in the flow may be unknown. In the case described in this paper several short-term counts were conducted in the area to determine this level and applied to all streets in the test area.  The average speed of vehicles may be unknown. One possible suggestion presented in [1] is to use the signposted speed limit to represent the average speed of vehicles.  Topographical data for the test area may be unavailable.  The road surface type for each road may be unknown. Another possible solution outlined in [1] suggests using a default surface type of dense asphalt. These are just some of the many issues that may apply to input data required to create a noise map. In a large scale project the number of unknowns may greatly increase and assumptions introduced will have a significant impact on the resulting noise map. Furthermore, the calculation of a noise map over a large area is a complex task and requires a large amount of processing power and computational time. Given that the model inputs are generally ‘‘best guess” estimates it would seem appropriate to strive for a balance between the complexity of computational procedures and the accuracy of final results.

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Another important feature arises in the assessment of the impact of proposed action plans and presenting this information to the public. If it were necessary to recompute strategic noise maps corresponding to each action plan a substantial amount of computational time and power would be necessary. Thus a more effective methodology is required. 2. Commercial software Commercial strategic mapping software may not be readily attainable for local authorities with limited budgets and resources. As such it was decided that the development of independent inhouse software, as introduced in [2], would prove quite beneficial to these parties, particularly for introducing the basics of noise mapping and the eventual inclusion of refinements to noise maps. This would be particularly attractive to small regional councils as it would encourage more participation in noise planning at a local level. Additionally it is worth noting that although each software product available today may follow certain standards they may not consistently yield the same results. A study of a number of software packages produced a comparison between five different software packages with results obtained by manually calculating noise levels following the CRTN standard [3]. This study revealed the extent of variation between several packages. Most results were within 1 dB(A) of the calculated result, however the results did demonstrate the variations from the predicted methodologies by the various packages. Results obtained from the various packages were also compared over a 1 km2 area of a city. Again a significant variation in results was noted; in one location a difference of 11 dB(A) was observed. It may be concluded that the use of different software with the same input data can have a considerable impact on the resulting noise map. This also highlights the problem associated with the black box approach. As the manner in which standards are implemented in commercial software packages may not be explicitly explored, it is not straightforward to determine why the variation in results exists. This may also be a problem for future studies that may wish to implement the Harmonoise method as it has been identified that the current description of this standard contains some unclear phrases, inconsistencies and loose ends. It is not a robust document for software implementation yet [4]. 3. Description of developed model The developed model follows procedures outlined in the recommended interim method for road traffic noise [5], while the propagation model was developed following a simplified interpretation of the propagation model outlined in XPS 31-133 [6], which accompanies the recommended interim method to be used by Member States and is one of the methods adopted by the Irish Governing Body [7,8]. This method is based on the decomposition of a line source, i.e. a road, into a number of incoherent point sources. The model then calculates the point-to-point propagation of noise from each source to each receiver. In the developed model the source emission model and the propagation model are completely separate, thus it is possible to determine the level of sound attenuation independently from the original source level. This approach of separate source and propagation models is also followed in the Harmonoise model [9]. 3.1. Road traffic noise The level of noise resulting from a flow of road traffic was calculated following the EU recommended noise model for road traffic

and incorporates the guidelines on revised interim methods published by the Commission in 2003 [10]. In this method the basic sound power level, LA,w,i of a point source i, for each octave band, j, is calculated from:

LA;w;i ¼ LA;w=m þ 10 log10 ðli Þ þ Rj þ C;

ð1Þ

where LA,w/m is the sound power level per meter along the road for each octave band, li is the length of the line section of the source, Rj is the spectral value for each octave band and C is the correction for the type of road surface. LA,w/m is calculated from:

LA;w=m ¼ 10 log10 ð10ðElv þ10

logðQlv ÞÞ=10

þ 10ðEhv þ10

logðQhv Þ=10Þ

Þ þ 20; ð2Þ

where Elv and Ehv are the sound emission levels for light and heavy vehicles respectively, determined from nomograms supplied with Guide du Bruit 1980 [11], and Qlv and Qhv are the respective volumes of light and heavy traffic flow during the reference interval. The sound emission levels, Elv and Ehv are caused by the movement of a vehicle at a speed v, in the case of one of four flow types (fluid continuous flow, pulsed continuous flow, pulsed accelerated flow or pulsed decelerated flow) and one of three gradient types (up, down or flat). The nomograms supplied in [11] are essentially charts representing a numerical relationship between the noise level and the conditions under which the vehicle is travelling. An alternative to these charts has been developed with a view to making them more practical to implement in software [12]. The length of the line section of the source, li, depends on the segmentation of the road and is described in more detail in Section 3.2, while Rj is the spectral value for each octave band the value of which is presented in Table 1. Finally, different road surfaces are accounted for by a correction for different types. These values are presented in Table 2 [10]. It should be noted that a comparison between the emission data for roads in Guide du Bruit and the German RLS 90 and the Austrian RVS 3.02 models has been conducted [13]. This study found that the data in Guide du Bruit was as good as these models, both of which are still in use today. 3.2. Segmentation of source of noise As described in XPS 31-133, a line source may be divided into several point sources by a number of methods: equiangular decomposition, decomposition by a uniform step or variable decomposition (a combination of the first two). However the length of step between two consecutive point sources should not exceed half the orthogonal distance between the point source and the nearest receiver. To account for this decomposition the level of sound power for a point source, per octave band, is then corrected, as presented in Eq. (1), with the term 10 log10(li). 3.3. Geometrical divergence As a sound wave travels from a point source, it’s energy is conserved but the energy of the wave must be spread out over a

Table 1 Value of Rj for each octave band. J

Octave band (Hz)

Rj [dB(A)]

1 2 3 4 5 6

125 250 500 1000 2000 4000

14.5 10.2 7.2 3.9 6.4 11.4

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Table 2 Road surface corrections.

Table 4 Values for G for various ground surface types.

Road surface

Noise level correction

Porous surface

0–60 km/h 1 dB

Smooth asphalt Cement concrete and corrugated asphalt Smooth texture paving stones Rough texture paving stones

61–80 km/h 2 dB 0 dB +2 dB

81–130 km/h 3 dB

+3 dB +6 dB

2

Adiv ¼ 10 logð4pd Þ;

ð3Þ

where d is the distance between the source and receiver, in metres. This signifies a sound level which decreases by 6 dB per doubling of distance, or a 20 dB reduction for each tenfold increase of distance and is similar to the equivalent equation approved in ISO 9613-2 [14]:

Adiv ¼ 20 logðd=d0 Þ þ 11:

ð4Þ

3.4. Atmospheric absorption The attenuation for air absorption may be calculated from the method outlined in ISO 9613-2;

Aatm ¼ ad=1000;

ð5Þ

where a is the coefficient of atmospheric attenuation and d is the distance through which the sound is propagating. a may be determined from tables supplied with ISO 9613-1 [15]. Table 3 shows the value to be used for a for a temperature of 15 °C and a humidity of 70%. 3.5. Diffraction If a barrier is situated between a source and receiver a correction must be applied to account for any subsequent attenuation. Generally sound will reach the receiver point by diffraction over the top of the barrier or by direct transmission through the barrier. When calculating the attenuation due to diffraction over a barrier, Abar, it is convenient to initially investigate if there is adequate diffraction to impede the noise propagation. This is achieved by calculating the difference in sound path length, d, i.e. the difference in path length that sound would travel from source to receiver with and without the presence of the barrier. For pure diffraction, with the absence of ground effect, the attenuation may be given as [6]:

Abar ¼ 10 log10 ð3 þ ð40=kÞC 00 dÞ

ð6Þ

provided (40/k)C’’d P 2; if (40/k)C00 d < 2 then Abar is 0 dB. k is the wavelength of sound of the nominal central frequency for each considered octave band and d is the difference in pathlength between the diffracted path and direct path. C00 is the coefficient accounting for multiple diffraction:

C 00 ¼ ð1 þ ð5keÞ2 Þ=ð1=3 þ ð5keÞ2 Þ;

ð7Þ

where e is the total distance between the two extreme diffraction edges and the direct path. The calculated values for Abar must lie be-

Table 3 Sample values for a. 125 0.38

250 1.13

500 2.36

1000 4.08

Example of surface

Value

Hard Soft Mixed

Concrete, water, etc. Grass, vegetation, etc. Both hard and soft ground

G=0 G=1 0
tween 0 dB and 25 dB. This means that if Abar exceeds 25 dB, it then assumes the value of 25 dB, and similarly if Abar is negative, it is equal to 0 dB.

greater area. In XPS 31-133, geometrical divergence, Adiv is accounted for by the formula:

Nominal center frequency (Hz) a (dB/km)

Surface

2000 8.5

4000 26.4

3.6. Ground effect Ground attenuation is primarily due to sound propagating directly from source to receiver being interfered with by sound reflecting from the ground surface. The extent of this attenuation depends on the type of ground cover between the source and receiver. The level of ground attenuation is also dependent on the presence of barriers in the area, thus Agr and Abar must be considered together. XPS 31-133 specifies a method to determine the level of ground attenuation that involves breaking the propagation path into three separate regions; the source region, the middle region and the receiver region, with the attenuation due to each region calculated individually. The acoustical properties of different ground surfaces are expressed through the use of a ground factor G, which is defined for three surface types, hard, soft and mixed, Table 4. The corresponding formulae to calculate Agr are presented in Appendix A. 3.7. Combining the models The total attenuation term for each octave band is then calculated as a sum of all different attenuation mechanisms. For homogeneous conditions this may be expressed as:

Atotal;j;H ¼ Adiv þ Aatm þ Agr;H þ Abar;H

ð8Þ

while the noise level at a particular point of interest LA,i,H may be calculated from

LA;i;H ¼ LA;w;i  Atotal;i;H

ð9Þ

where LA,w,i is the original sound power level produced by a point source for each octave band in homogeneous conditions. LA,i,F representing the sound level at the same point in conditions favourable to propagation is calculated in a similar manner and the total long-term sound level can then be determined from:

LA;i;LT ¼ 10 log10 ðp10LA;i;F =10 þ ð1  pÞ10LA;i;H =10 Þ

ð10Þ

where p is the level of occurrence of favourable conditions, which takes a value of between 0 and 1.

4. Initial results Figs. 1 and 2 present two strategic noise maps around the Trinity College campus in central Dublin, created with a grid spacing of 10 m. Fig. 1 was created using standard commercial software and Fig. 2 was created using the developed software. Results from both models were exported to ArcGIS and the GIS mapping tool was used to interpolate and display the maps presented below. It is noted from Figs. 1 and 2 that the attenuation calculated by the developed software appears to be more severe in places. A summary of some of the general statistics associated with each noise map is presented in Table 5.

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Fig. 1. Noise map obtained from commercial software.

Fig. 2. Noise map obtained from the developed software.

Fig. 3 displays the difference, in dB(A), between the two maps. This difference was determined by subtracting the noise level at each receiver point, as calculated by the developed software, from the noise level at the same point as calculated by the commercial

Table 5 Comparison of predicted results. Statistic

Commercial software

In-house software

Min level Max level Mean level Standard deviation Computation time

36 [dB(A)] 75 [dB(A)] 55 [dB(A)] 10 [dB(A)] 5 h 40 min

38 [dB(A)] 76 [dB(A)] 55 [dB(A)] 10 [dB(A)] 26 min

software and plotting the results as a map. It is clear that both maps yield similar results although slight variations are noted. Fig. 4 presents a histogram of the differences between the commercial software and the independent model. The mean difference of 0.34 dB is also displayed while a standard deviation of 1.48 dB was observed in results. From Table 3 and Fig. 4 it is evident that, while some variations in results exist, the noise maps generally show good agreement with each other. It is therefore evident that the developed software is capable of producing results that concur with the standard commercial software. It is worth noting that the independent model completed calculations in 26 min while the commercial software took over 5 h. It also has the added benefit of being a more flexible tool, as it may be adapted further to accommodate numerous

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Fig. 3. A map plotting the difference between the two maps.

changes to the model. As such, it strikes a balance between the complexity of the problem and computing results in a time-efficient manner. 5. Assessment of action plans Once noise maps have been produced and released to the public it will become clear what action needs to be taken in order to improve the overall acoustic environment. Inevitably this will lead to the introduction of several noise mitigation measures to an area. Some examples of mitigation measures include the erection of noise barriers, the introduction of low noise road surfaces or reducing noise through the use of traffic management schemes. Several mitigation measures may seek to reduce the noise level at the

Fig. 4. Histogram showing the range of difference between the commercial software results and in-house software results. Note: the number of occurrences is calculated from the interpolated difference map and represents how many times that difference was observed.

source as opposed to interfere with the propagation of noise. Furthermore, it was reported in [16] that the most cost-effective methods of reducing road traffic noise exposure levels involve measures taken at the vehicle level. These measures would correspond to a change at the source of the noise. Consequently, this means that action plans involving a reduction of noise at the source can be evaluated by solely calculating the change in noise levels at the source. The in-house software has been developed to accommodate these calculations, as a clear distinction exists between the source model and propagation model. Both models are completely separate and are only amalgamated at the final stages. This makes it possible to easily determine the impact of changes at the source without the need for recalculating the propagation model. As such, if a proposed action plan involves altering a factor influencing the source and does not directly impact the propagation model, e.g. restricting the flow of heavy vehicles, changing a speed limit, pedestrianising a road, etc., the entire model does not need to be recalculated. The new source model can be re-compiled and the impact can be determined almost instantaneously. Fig. 5 shows the effect of removing all traffic from Pearse St., Tara St. and a portion of Nassau St., thus representing the possibility of designating these roads as pedestrian streets, assuming the neighbouring road’s traffic flow remain constant, while Fig. 6 shows the effect of a blanket ban on all heavy vehicles around Trinity College coupled with a partial closure of Nassau St. These maps were calculated by altering the input variables of the source model and the propagation model remained unchanged. It is noted from Fig. 6 that a blanket ban on all heavy vehicles throughout central Dublin would result in a decrease in noise levels from road traffic noise. However, when evaluating an action such as this, using the recommended model as described in [10], it is important to highlight a potential problem associated with this approach. The calculation method applies a standard correction, Rj, to convert overall traffic noise levels (dB(A) values) to octave band levels independent of traffic composition. Removing heavy vehicles from the traffic stream will tend to shift the spectral shape towards the higher frequency bands which will not be accounted for in this method of calculation.

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Fig. 5. Noise map with selected streets closed to traffic.

6. Validation of noise maps with measurements The Good Practice Guide for strategic noise mapping suggests that in order for the industry’s credibility to be upheld, accurate results should be presented in maps, along with robust recommendations for action. It is reasonable to assume that if a noise map is found to be wholly inaccurate then any associated action plan will be brought into question. As such it is important to investigate how a noise map compares with measurements taken on-site. In an effort to validate the noise map produced for the test area a measurement campaign was undertaken to establish environmental noise levels in Dublin city centre. 6.1. Measurement procedure A number of short-term measurements were made at various times throughout the day period (between 07:00 and 19:00) over

a 1-month period at the locations indicated in Fig. 7. In each case the measurement height was 4 m, the measurement period was 15 min and measurements were conducted away from the façade of buildings in an effort to minimise the impact of reflections from near facades. In addition to these measurements, continuous noise levels were recorded at a fixed location in Dublin city centre for a period of one week. These week-long measurements were used to determine the variation of noise throughout the day period which would enable an accurate estimation of Lday using short-term measurement results. This would then allow for comparisons to be made between measurements taken on-site and the noise map. It was found that a 15 min value was generally within 3 dB of the 12-hour Lday level. Further details of the measurement campaign are presented in Appendix B. It is evident that the most accurate manner to determine Lden levels, and Lday levels, would be to undertake a series of long-term measurements, but for initial comparative purposes the short-term method described here would appear sufficient.

Fig. 6. Noise map with complete ban of heavy vehicles in the test area and a portion of Nassau St. closed.

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Fig. 7. The locations of short-term measurement positions.

A similar measurement approach is described in the CRTN shortened measurement procedure, which uses only three measurements which are representative of an hourly value to estimate an 18-hour value [17]. This method is also adapted for use by the Irish National Roads Authority which uses three 15 min measurements to estimate the 18-hour value [18]. While these methods are used to determine a value for L10(18h) which is a statistical descriptor of noise as opposed to the Leq index, it would appear that the method adopted in the current case is acceptable.

Table 6 A comparison of predicted noise levels with measured noise levels. Note the average and standard deviation values presented were calculated with the extreme outlying values omitted. Site number

Location

Calculated Lday [dB(A)]

Measured Lday [dB(A)]

Measured– calculated [dB(A)]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Westland Row 1 Westland Row 2 Westland Row 3a Pearse St. 3 Pearse St. 2 Pearse St. 1 College Green Westmorland St. D’Olier St. Dame St. Grafton St.b Dawson St. Kildare St. Nassau St. 1 Nassau St. 2 Nassau St. 3 Lincoln Place Chemistry Buildingc Average Standard Deviation

68.9 69.6 68.3 71.7 71.8 71.4 70.4 67.5 70.1 68.1 49.1 69.2 66.8 68.3 68.7 66.4 66.1 47.8 69.0 1.9

73.5 73.9 81.1 75.5 74.2 74.9 73.4 70.1 71.3 73.6 66.8 70.4 67.8 71.1 70.8 70.3 73.4 65.5 72.3 2.2

4.6 4.3 12.8 3.8 2.4 3.5 3.1 2.6 1.2 5.5 17.8 1.2 1.0 2.8 2.1 2.9 7.3 17.7 3.2 1.7

a b c

This location on Westland Row was underneath a railway bridge. Grafton St. is a pedestrianised street in Dublin city centre. The Chemistry Building is in the middle of Trinity College.

Most measurements were taken by the street side although the site at the Chemistry Building is a green area within Trinity College, while Grafton Street is a pedestrian street with no traffic allowed. 6.2. Measurement results A comparison of measured Lday results with predicted Lday results is displayed in Table 6. (Note: in this table the calculated results correspond to those results obtained with the developed software). It is worth noting that the quiet area beside the Chemistry building is not accurately predicted compared to measurements. However, the measured noise in this location may not be regarded as environmental noise as defined by the Directive as it was influenced by ambient noise in the area, such as people talking, walking and activity in the park and surrounding buildings. This is also noticeable on Grafton Street where measurements were influenced by people and nearby shops. A third point of interest is recorded at Westland Row 3. This measurement location was underneath a railway bridge and was influenced by multiple reflections in the area and as such represents a scenario outside the scope of the prediction model. From Table 6 it is clear that measurements are predominantly higher than predicted levels throughout the map, and if the propagation model is assumed to be correct, it is evident that the noise sources are not accurately represented. Also, when predicted results fall below the ambient noise level, as is the case near the Chemistry building and Grafton Street, the comparison between predicted levels and measurements is not appropriate, as these sites are not representative of a site where environmental noise is dominant. Fig. 8 shows a scatterplot of predicted vs. measured values. From this graph the outlying points may be clearly identified. A simple regression line with an R2 value of 0.433 is shown to fit the data. It should be noted that if outliers were removed from the analysis this relationship would improve significantly. Following a direct comparison of predicted noise levels with measured noise levels it is evident that maps predicted by both the commercial and the independent software do not agree completely with measurements taken on-site. As outlined in the introduction a

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Fig. 8. Scatterplot of predicted vs. measured Lday levels.

number of averages and assumptions were introduced to the development process in order to calculate the map. These assumptions were primarily related to describing the source, e.g. traffic volumes, traffic speed, traffic composition, etc. It is evident that these assumptions, along with possible factors outside the scope of the models, introduced some degree of error to the process, resulting in an inaccurate representation of the source. Noise maps would present a more realistic acoustic scenario if sources were more accurately represented. However, given that the source is influenced by a number of variables, many of which are unknown and not represented in the noise model, it not feasible to calculate the source more accurately. This means a more accurate source should be determined by a method other than prediction. 7. Integration of measurements with map By integrating measurements with a noise map the source of the noise can be refined to yield a more realistic representation of the source. Integrating measurements in this manner ensures the integrity of the propagation model is upheld as only the noise levels at the source are altered. 7.1. Creating maps with measurements A measurement program has been initiated in Madrid to comply with the Directive, known as the SADMAM system. The main goal of SADMAM is to produce fast and cheap measured noise maps that combine both long-term and short-term noise levels along with a realistic propagation model. Measurements are generally taken by mobile noise monitoring terminals over short time periods at strategic locations in the city. These measurements are used to determine source strengths that are then fed into a prediction model that creates the map. The source strengths are determined by measuring noise at receiver positions and using a reverse engineering approach to determine the noise levels at the source [19]. This approach was also used to map the main campus of Pusan National University, in the Republic of Korea [20]. Again the maps produced were based on source strengths determined from measured data while it was noted that the quality of the map was dependent on the number and accuracy of the measured data. 7.2. Validating maps with measurements Maps created by predicted methodologies may also incorporate measurements to some degree. As previously outlined, maps created for the test area were compared directly to on-site measure-

ments and it was found that results did not concur. A more refined approach may be adopted to include measurements within predicted results. The difference between predicted and measured values can be identified and integrated with the map. Manvell [21] outlines two possible techniques for calibrating noise maps with measurements; a global correction of noise levels or a local correction of noise levels. A global correction would imply that the author believes the error to be constant for every source in the test area. This is unlikely to be the case but offers a simple solution to what could be considered a complex problem. A local correction would provide a more refined approach as it assumes the error at each measurement point is independent and arises from separate sources. Following an evaluation of the uncertainties in the source model, the most appropriate factor to be adjusted in order to best improve the overall uncertainty may then be determined. 7.3. In-house software integration methodology In the case of the developed model, a local correction methodology is adopted. This feature can be developed to allow for the effective integration of measurements with predicted results yielding a noise map which has been corrected to match the acoustic scenario on-site. Computationally this is achieved in the same manner as the impact of proposed action plans may be evaluated, however in this case, instead of the user defining a difference in the source, i.e. changes in traffic speed, traffic composition, etc, the difference is calculated by comparing measurements taken on-site with predicted values and adjusting the source terms accordingly. If multiple measurements yield different levels of correction for the same road source, then the average correction is determined. It was expected that corrections should be similar for all sources so any outliers showing an extreme difference were flagged for further investigation and a more in-depth examination. For the current case this resulted in measurements conducted at Locations 3, 11 and 18 being omitted from the integration process. This calibration yields the new noise map displayed Fig. 9. Corrections are particularly evident around Westland Row and Pearse St., as measurements have yielded a higher source in these locations. In general it may be observed that the overall map shows higher noise levels throughout. It is worth noting that reflections have been omitted from calculations and as such will influence results. If a uniform correction of 3 dB is taken for corrections along each street and locations 3, 11 and 18 are ignored, predictions displayed in Table 6 would appear to yield much more accurate results. This correction term would

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Fig. 9. Recalculated noise map, changed to better represent the scenario as described by measurements.

also serve to account for the variability and uncertainty of the measurement process. 7.4. Accuracy implications of this hybrid approach Reflection effects were omitted from calculations in the independent model in an effort to increase the computational speed of the software. This omission will have had an impact on the accuracy of results. However, if it is considered that, in general, reflections will contribute approximately 3dB to the noise level in certain locations, which is within the variation of short-term measurement levels compared to long-term levels, the trade-off seems acceptable. It is envisaged that the primary use of this hybrid approach would enable local authorities to produce a noise map which is comparable to reality, and would be particular useful in determining ‘‘hot-spots”. The method described in this paper will not achieve total accuracy but will deliver a representation of noise levels perceived in the area, which is a stated objective of the Directive. Results of this kind may serve to boost public confidence in results as they provide noise levels which are reflective of the actual scenario on-site. Furthermore, an interesting clause is presented in the CRTN shortened measurement procedure [17], which states that when future values of L10(18-hour) are predicted to be between 66 dB(A) and 69 dB(A), as calculated with the shortened measurement procedure, it is necessary to re-measure over the entire 18-hour period. This is with reference to the limit of 68 dB(A) which applies to the Noise Insulation Regulations in the UK. A similar approach could be adopted for use with the independent model. The proposed onset levels for assessment of noise mitigation measures in Ireland are 70 dB(A) Lden and 57 dB(A) Lnight [22]. Adopting 3 dB(A) as a buffer value, if levels are found to lie within 67 dB(A) and 73 dB(A) Lden or 54 dB(A) and 60 dB(A) Lnight, at a sensitive location, then these areas should be subjected to further examination. Thus the model may be used as an indicative tool for noise mapping and assessment as opposed to a precision software tool. 7.5. Meeting the requirements of the Directive Over the course of this work a number of methods have been described which may be used to either create or adapt a noise

map. A strategic noise map as defined by the Directive means a ‘‘map designed for the global assessment of noise exposure in a given area due to different noise sources” (Figs. 1 and 2). It is, in essence, a map to be used for strategic purposes. However, if the map is found to be erroneous any associated action plans may be called into question by the general public. In an effort to satisfy public analysis a further noise map was developed for this work, the refined noise map presented in Fig. 9. This map is based on measurements and as such may be influenced by factors outside the scope of the prediction model, and possibly by factors outside the scope of the Directive. It will however yield a noise map which is more reflective of the actual scenario experienced by the public and should therefore improve overall public confidence in results.

8. Future work The goal of this work was to investigate the possibility of developing methodologies that circumvent the restrictions caused by today’s commercial noise prediction software. A number of further improvements to the developed model may be introduced to enhance the process:  A more detailed measurement campaign would increase confidence and help determine the long-term variation of noise over an entire day. This may involve the long-term use of permanent monitoring units.  Noise maps should concentrate on environmental noise as defined in the Directive and this type of noise should be reflected in measurements. As such some method of filtering measurements to present the level of environmental noise would be quiet beneficial.  A more complex propagation model could be developed where required, incorporating, for example, a simple reflection model.  While it remains to be seen how the Harmonise method will be received it is reasonable to assume that all Member States will one day have to attempt to implement it. Accordingly, it is envisaged that this software will be adapted to meet this forthcoming European standard.  It would be beneficial to assess any economic advantages the method outlined in this paper may hold over any alternative

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methods for producing noise maps. A study of this sort would be of particular importance for local authorities with limited resources.

9. Conclusions The work described in this paper presents details of an environmental noise study of Dublin city centre. Throughout the course of the study an independent noise mapping tool was developed which enabled an investigation into the manner in which measurements could be integrated with noise maps. A number of conclusions may be drawn from this study. The accuracy of a noise map is limited by the accuracy of the input data. If averages and assumptions have to be introduced during the development of a noise map, there cannot be complete confidence in predicted results. It would therefore seem appropriate to strive for a balance between the complexity of the problem and accuracy in final results. For the current case it would seem that the developed model represents a step towards this goal. It has been demonstrated that it is capable of predicting noise levels to a reasonable level of accuracy, using standard commercial software as a benchmark. An integral theme of the model was to keep a clear distinction between the source model and the propagation model. This structure makes the simple evaluation of several source-dependent action plans possible. The model is also capable of integrating measurements taken on-site with maps. This is achieved using a simple reverse engineering approach to refine the source and means the propagation model does not need to be recalculated. However, it is evident that this approach is subject to certain limitations. When calibrating a noise map with measurements, care must be taken to ensure that measurements have not been influenced by extraneous noise. This is almost impossible within an urban scenario and as such it is important to present possible reasons for differences between maps and measurements. Additionally, it should be noted that noise levels vary throughout different times of the day and if short term-levels are used to determine long-term levels a certain amount of error must be expected, particular when comparing measurements to a noise map that represents annual levels. Although with careful consideration of measurements, it may be possible to draw certain conclusions as to the accuracy of the noise map, especially if a good knowledge of the measurement campaign is present. Reflections may also influence on-site measurements and must be considered in detail when using measurements to calibrate a predicted noise map. Measurement positions should be selected where reflections due to the nearside façade are either eliminated, e.g. open sites, or at facades where the façade effect is known. One possible solution to this issue would be the use of the backing board method which involves positioning the microphone on a total reflecting panel which simulates a theoretical +6 dB reflection [23]. Thus the façade effect will be known and can be corrected for when integrating results with the predicted noise map. Additionally, it should be noted that, while the model presented here has been shown to yield comparable results with commercial software, several improvements could be made to the calculation process to improve accuracy. However it may be concluded that the model and approach described here could be used to determine indicative noise levels, which, given the accuracy of the input data, would be acceptable. One goal of Directive 2002/49/EC was to establish a uniform approach to the assessment and management of environmental noise. However, to truly achieve complete standardisation in studies it would be required for all competent authorities to not only

apply the same calculation procedures but also use the same software format. The framework for the software developed in this project may accommodate this type of distribution. At a European level this could be achieved with the establishment of a repository making simple software available to competent authorities that may wish to avail of it. This would then make noise mapping and action-planning more accessible to local authorities with limited resources. Acknowledgements The authors would like to acknowledge funding received from the Irish Environmental Protection Agency (EPA), Dublin City Council and the National Roads Authority (NRA) through the E.T.I. Capability Development Project. Additionally some work discussed above was performed under the Project HPC-EUROPA (RII3-CT-2003-506079), with the support of the European Community – Research Infrastructure Action under the FP6 ‘‘Structuring the European Research Area” Programme. Appendix A. Calculating ground attenuation The overall attenuation due to ground effect, in favourable conditions may be calculated from

Agr ¼ As;F þ Am;F þ Ar;F ;

ðA:1Þ

where As,F , Am,F and Ar,F represent the attenuation due to ground effect in the source, middle and receiver zones, and may be calculated from (see Table A.1) where 2

2

6 2 dp

 ¼ 1:5 þ 3e0:12ðz5Þ ð1  edp =50 Þ þ 5:7e0:09z ð1  e2:8:10 aðzÞ 2

Þ; ðA:2Þ

 ¼ 1:5 þ 8:6e0:09z ð1  edp =50 Þ; bðzÞ  ¼ 1:5 þ 14e0:46z2 ð1  edp =50 Þ; cðzÞ

ðA:3Þ

 ¼ 1:5 þ 5e0:9z2 ð1  edp =50 Þ; dðzÞ

ðA:5Þ

ðA:4Þ

where dp is the distance between source and receiver, perpendicular to the average ground profile in metres and q may be determined from: (see Table A.2). zs and zr are the source and receiver heights respectively. Note: the calculation of the attenuation due to ground effect in this manner does not consider the effects due to diffraction over discontinuous ground.

Table A.1 Formulae to calculate ground attenuation. Frequency (Hz)

As,F or Ar,F (dB)

Am,F (dB)

125 250 500 1000 2000 4000

1.5 + G.a‘(z) 1.5 + G.b‘(z) 1.5 + G.c‘(z) 1.5 + G.d‘(z) 1.5(1  G) 1.5(1  G)

3q(1  G) 3q(1  G) 3q(1  G) 3q(1  G) 3q(1  G) 3q(1  G)

Table A.2 Formulae to the variable q. if

q

dp < 30(zs + zr) dp > 30(zs + zr)

q=0 q=1

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conducted at random times throughout the day period at each location.

Appendix B. Measurement results Results of the week-long measurement campaign are presented in this appendix. Fig. B1 presents the overall variation of noise while Fig. B2 presents the variation of 15-minute levels with the value for Lday for each weekday during the measurement period. In this case only weekday measurements are considered and weekend results were omitted from the analysis as all short-term measurements were conducted on weekdays. It may be seen that, in general, a 15 min measurement lies within 3 dB of the equivalent value for Lday in each case. Table B.1 presents a more complete summary of the short-term measurement campaign described in Section 6. Each measurement lasted 15 min in duration and several measurements were

B.1. Summary of the NRA adaptation of the CRTN shortened measurement procedure The CRTN shortened measurement procedure states that measurements of L10 should be taken over three consecutive hours between 10:00 and 17:00. L10(18h) values may be derived by subtracting 1 dB(A) from the arithmetic mean of the L10 values measured during the three sample periods. The NRA guidelines in Ireland state that measurements should be 15 min in duration while presenting the observation that the use of 15 min sample periods should permit measurements to be made at a total of three

Fig. B1. Variation of noise over one complete week.

Fig. B2. Variation of 15-minute levels compared to the measured value for Lday for each weekday, Monday to Friday.

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E.A. King, H.J. Rice / Applied Acoustics 70 (2009) 1116–1127 Table B.1 Results of short-term measurement campaign. Location

Measurement result Leq,15min [dB(A)]

Westland Row 1 Westland Row 2 Westland Row 3 Pearse St. 3 Pearse St. 2 Pearse St. 1 College Green Westmorland St. D’Olier St. Dame St. Grafton St. Dawson St. Kildare St. Nassau St. 1 Nassau St. 2 Nassau St. 3 Lincoln Place Chemistry Building

72.8 75.8 84.9 72.1 75.6 72.8 71.8 67.8 73.2 70.9 68.2 71.9 68.8 72.2 72.6 69.5 73.0 68.1

76.6 72.3 79.4 77.2 72.2 74.7 75.2 69.7 71.3 74.8 66.5 71.8 70.2 72.6 71.4 72.4 75.3 62.7

72.6 73.6 77.8 76.3 75.0 75.8 71.2 72.6 69.3 71.2 64.5 68.1 66.1 71.4 70.5 69.3 74.1 64.2

locations in any given 3-hour period provided they are sufficiently close together. Finally, the NRA guidelines state that it is important to note that the L10(18h) values obtained at locations with low traffic volumes using this approach only represents a snapshot of the daytime existing background noise levels and they are not to be used to represent a long-term assessment of noise levels at such locations. For further details the reader is referred to the National Road Authorities ‘‘Guidelines for the Treatment of Noise and Vibration in National Road Schemes”. References [1] European Commission Working Group. Assessment of exposure to noise. Good practice guide for strategic noise mapping and the production of associated data on noise exposure, Version 2; January 2006. [2] King EA, Rice HJ. The development of an independent noise prediction model. In: Proceedings of the 19th International Congress on Acoustics, Madrid; 2007. [3] Hepworth P. Accuracy implication of computerized noise predictions for environmental noise mapping. In: Proceedings of Internoise 2006, Hawaii, USA; 2006. [4] Hartog zan Banda E, Stapelfeldt H. Software implementation of the harmonoise/imagine method, the various sources of uncertainty. In: Proceedings of Internoise 2007, Istanbul, Turkey; 2007. [5] NMPB-Routes-96, (SETRA-CERTU-LCPC-CSTB). [6] AFNOR. Acoustique: Bruit des infrastructures de transports terrestres; April 2001. XP S 31-133. [7] Directive 2002/49/EC of the European Parliament and the Council of June 2002. Official Journal of the European Communities; 2002. [8] Statutory Instrument No. 140 of 2006. Environmental Noise Regulation, 2006. Department of the Environment, Heritage and Local Government, Ireland; 2006.

Average [dB(A)] 71.6 75.4 82.4 76.1 73.5 74.8 75.2 70.3 71.0 75.0 67.8 69.2 67.4 69.1 71.3 70.3 71.4 66.8

74.5 73.4

72.4 72.9

73.9 75.2 75.8 73.0 68.1 72.3 74.6

77.6 73.9 75.7 74.2 72.2 70.4 74.9

70.2 66.8 70.0 69.2 71.6 72.4

71.2 67.4 71.1 69.6 68.6 74.3

73.8 73.8

73.5 73.9 81.1 75.5 74.2 74.9 73.4 70.1 71.3 73.6 66.8 70.4 67.8 71.1 70.8 70.3 73.4 65.5

[9] Harmonoise Work Package 3. Engineering method for road and rail noise after validation and fine tuning, HAR32TR040922-DGMR20; January 2005. [10] Commission Recommendation of 6 August 2003 concerning the guidelines on the revised interim computation methods for industrial noise, aircraft noise, road traffic noise and railway noise, and related emission data. [11] Guide du Bruit 1980 des Transports Terrestres. Prévision des niveaux sonores, CETUR; 1980. [12] AR-INTERIM-CM. Adaptation and revision of the interim noise computation methods for the purpose of strategic noise mapping. WP 3.1.2 Road traffic noise – Noise emission: databases. Wolfel et al. [13] AR-INTERIM-CM. Adaptation and revision of the interim noise computation methods for the purpose of strategic noise mapping. WP 3.1.1 Road traffic noise – description of the calculation method. Wolfel et al. [14] ISO 9613-2. Acoustics – attenuation of sound during propagation outdoors – Part 2: General method of calculation; 1996. [15] ISO 9613-1. Acoustics – Attenuation of sound during propagation outdoors – Part 1: calculation of the absorption of sound by the atmosphere; 1993. [16] den Boer LC, Schroten A. Traffic noise reduction in Europe. CE Delft; 2007. March. [17] Calculation of Road Traffic Noise. Department of Transport and Welsh Office, HMSO; 1988. [18] Guidelines for the Treatment of Noise and Vibration in National Road Schemes. National Roads Authority; 25th October 2004. [19] Manvell D et al. SADMAM – combining measurements and calculations to map noise in Madrid. In: Proceedings of Internoise 2004, Prague, Czech Republic; 2004. [20] Dae Seung Cho et al. Noise mapping using measured noise and gps data. Appl Acoust 2006;68:105–1061. [21] Manvell D. The use of measurements and GPS for noise mapping. Joint BalticNordic acoustics meeting, Mariehamn, Aland; 2004. [22] Environmental Protection Agency (EPA). Draft guidance note for noise action planning; May 2008. [23] Bérengier Michel. Noise classification methods for urban road surfaces: ‘Backing Board’ method: LCPC contribution. Silence Report No. F.R1, Work Package F.4: Noise classification methods for urban road surfaces.