Main design parameters to build acoustic maps by measurements in Uruguay

Alice Elizabeth González; Pablo Gianoli Kovar; Ignacio Suárez Dores; Héctor Campello Vicente

doi:10.1515/noise-2025-0018

Article Open Access

Main design parameters to build acoustic maps by measurements in Uruguay

Alice Elizabeth González , Pablo Gianoli Kovar , Ignacio Suárez Dores and Héctor Campello Vicente

Published/Copyright: May 9, 2025

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From the journal Noise Mapping Volume 12 Issue 1

Abstract

Uruguay is a small country in Latin America. It has 178.500 km² and approximately 3,400,000 inhabitants. Its environmental legislation is still incomplete; for example, there has been a national act about noise pollution since 2004 but it has never been regulated. Thus, no national regulation on noise but only departmental Ordinances in each of its 19 Departments; in practice, 19 different regulations coexist on such a small surface. Noise maps are not mandatory neither in Uruguay nor in any of its Departments. The Research Group on Environmental Noise at Universidad de la República has developed a research project that seeks the best practical methodology to build noise maps through manual measurements. The fieldwork included the determination of the stabilization time of noise measurements, the comparison between long- and short-time measurements, the comparison between measurements taken at 1.20 m and 3.50 m, and the obtention of a national curve of highly annoyed people (% HA) with a basis in the field measurements and simultaneous survey carried out on site. In this article, we present the results of these works and the proposed methodology for building noise maps throughout the country.

Keywords: noise mapping; noise measuring; environmental noise; traffic noise models; noise measurements duration

1 Introduction

The construction of acoustic maps through measurements is a common practice in many countries, where data is not available for implementing software-based modeling. Particularly, the acoustic features related to facade typologies and the absorption coefficients of the materials used on them have not been systematically studied in the country. This information is not even available for the capital city, nor it is for smaller cities.

In any case, even when acoustic maps are generated using specialized software, conducting measurements to validate the results remains essential, especially when the predictive equations of the model have not been previously validated against local conditions.

Ensuring the representativeness of measurements for constructing an acoustic map (or for validating the results of a model) involves, among other things, ensuring that the measurement duration is adequate, i.e., that stabilization time has been reached; that measurements are taken at a height consistent with the reality to be represented; and that the equation relating classified traffic density to sound pressure levels is valid for the specific site.

The selection of measurement points, aimed at identifying and characterizing homogeneous areas, requires an initial survey of the location to avoid omitting any significant zones or points. Therefore, this is an aspect that should not be overlooked when creating acoustic maps.

This article aims to describe the activities and results of a research project conducted by the team at the Department of Environmental Engineering (DIA-IMFIA) at the Faculty of Engineering, Universidad de la República. The project aimed to define a methodology for the development of strategic acoustic maps in Uruguay.

The work presented here focuses on the process of obtaining acoustic maps through manual measurements. It is based on fieldwork carried out in three cities in the interior of the country and in Montevideo, with the data being processed to derive various relevant results. The following sections provide a summary of the main theoretical background, followed by the results obtained for the key aspects of the methodology. Finally, the central aspects of this methodology are synthesized, along with a brief critical analysis of its main limitations.

2 Theoretical framework

When addressing the issue of acoustic pollution in urban environments, acoustic maps – also known as noise maps – are a highly valuable tool. According to the European Union's definition, a noise map is:

The presentation of data on an existing or predicted acoustic situation based on a noise indicator, which will indicate the exceedance of any relevant limit value, the number of people affected in a specific area, or the number of dwellings exposed to certain noise indicator values in a given area. (Official Journal of the European Communities, 2002).

The application of these maps to urban planning, among many other uses, is unquestionable [1]. They can serve as a basis for defining regulations or zoning, as well as for analyzing changes in infrastructure, traffic flow, or the installation of new urban equipment.

In Latin America, noise maps are mandatory only in Colombia, specifically in cities with more than 100,000 inhabitants [2,3]. Additionally, there is state-level legislation in Brazil that mandates their use in the State of São Paulo [4].

Over the years, numerous authors and research groups have worked on the characterization of noise within noise prediction models, particularly in relation to specific scenarios. In response to this challenge, and in order to make the results from different countries and authors comparable, some of the European Union projects that have addressed this issue include CNOSSOS [5,6], IMAGINE [7], HARMONOISE [8,9], and GIpSynoise [10], among others. The “Good Practice Guide for Strategic Noise Mapping and the Production of Associated Data on Noise Exposure” [11] sought to address some of the issues that had arisen, although its success was only partial.

Based on international experience with strategic noise mapping, it is possible to understand how these studies are currently conducted to ensure the representativeness and comparability of the methods at all stages [12].

Among the key studies conducted in Uruguay, two noise maps of Montevideo should be highlighted, completed in 1998 [13] and 1999 [14], respectively. Both studies demonstrated the need to develop a methodology for measuring and modeling environmental sound levels due to the frequent occurrence of certain acoustic events, which were termed “anomalous events.” These events were not addressed in the literature at the time: honking, sudden braking, motorcycles with open exhausts, sirens, alarms, barking, and others. The prevalence of these events was so significant that they became the focus of further research [15]. They were also clearly identified in studies of sound levels in specific areas of other cities in the country: in the acoustic mapping of the city of Salto, conducted in 1997 [16], in the acoustic mapping of the city of Rivera [17], and in surveys conducted by the same team at various other locations. These experiences were compared and summarized by González et al. [18]. The main results were the obtention of a sound pressure levels model for the city of Montevideo and of the best duration for manual measurements in the city, taking into account the difficulties posed by the anomalous events [15]. The model was an explicit equation that was based on more than 1,300 manual measurements, with the following structure:

L Aeq, 1 h = K + 10 log ( A + b · B + c · C + m · M ) + q · Q p + 10 log d

where K, a, b, c, m, q, and p are coefficients experimentally adjusted. A is the number of passenger cars/hour, B the number of buses/hour, C the number of trucks/hour, M the number of motos/hour, Q = A + B + C + M, and d is the distance from the axis of the street to the sound-level meter. The term q·Q ^p is the term that considers the anomalous events’ occurrence.

The measuring time proposed in 2000, with a basis in the same set of experimental results, was intended to be 30 min to get the stabilization time in at least 90% of the cases [15].

3 Fieldwork

In the project, we have been working on 2022–2023, the fieldwork was carried out using two Class 1 sound-level meters owned by DIA-IMFIA: a Bruel & Kjær 2250 and a Casella CEL-63X, both equipped with windshields and tripods [19]. Both instruments were set to measure levels with A-weighting and real-time third-octave band filters. In addition, a telescopic pole was used to perform height measurements, enabling simultaneous recordings at two different heights during long-duration measurements (12 h).

For the fieldwork, three locations with distinct typologies were selected in Montevideo and also three other places in other cities in the interior of the country. The latter were chosen from the departmental capitals, with preference given to those with varying population sizes and socio-economic profiles. Maldonado (the capital of the eponymous department) is the second most populous city in the interior and has the highest population growth rate nationwide. It forms an urban area with the Punta del Este resort and has a significant tourism sector, which is actively being diversified to reduce its seasonal nature. Minas, the capital of Lavalleja Department, is a small town in a hilly area mainly dedicated to forestry, with some industrial activity. Rocha (the capital of Rocha Department) is a small city in the east of the country, with limited local productive activity and a steady decline in its population. It has little productive activity of its own. Its economy is heavily dependent on seasonal tourism along the picturesque coastline, although this is constrained by the climatic restrictions of the region.

The main characteristics of these cities are presented in Table 1, and their location is shown in Figure 1.

Table 1

Characteristics of the selected cities

City (Department)	Montevideo (Montevideo)	Minas (Lavalleja)	Maldonado (Maldonado)	Rocha (Rocha)
Population (Census 2011)	1,318,800	38,400	87,000	25,400
Approximate area (km²)	417	8.2	25	8
Average hourly traffic (veh/hour)	—	196	350	367

Note: A daily average traffic value for Montevideo is not defined due to the city's high heterogeneity. Source: Own data.

Figure 1

Location of the selected cities.

In all four cities, both 12-h and 1-h measurements were conducted. Simultaneously, classified traffic counts were performed across four categories (light vehicles or passenger cars, trucks, buses, and motorcycles), as well as opinion surveys using a pre-designed questionnaire. For this article, also newer environmental sound pressure-level meters have been included, both to better obtain the stabilization time of the measurements and the number of points regarding the surface and population of the city. The key data from the fieldwork are summarized in Table 2.

Table 2

Summary of the fieldwork conducted

City	Montevideo	Maldonado	Minas	Rocha
12-h measurements	3	1	1	1
1-h measurements	143	28	20	26
Opinion surveys	240	80	78	82

Note: Source: Own data.

3.1 Selection of sampling points

The selection of sampling points followed different criteria in Montevideo and the cities in the interior of the country. What all points have in common is that they have been chosen far from the two road intersections that define a block [20].

In Montevideo, points were chosen based on varying street typologies, building types, density, and traffic composition [21]. The 12-h measurements were taken on Ellauri, Uruguay, and Rivera streets. The Ellauri Point is located in a residential area with a medium-high socioeconomic status, close to both a primary and secondary school. The traffic flow is relatively low, and the passage of trucks and buses is minimal. The point on Avenida Uruguay is situated on a wide street, with old single-story buildings on both sides; it has a high flow of buses and trucks. It serves as a major entry point for passenger transport services coming from various zones of the Montevideo Metropolitan Area. The measurement point on Avenida Rivera is located in a middle-class neighborhood with a high traffic volume, ranging from light vehicles to buses operating urban passenger transport lines. Another 143 points were selected all across the city, to represent the sound pressure levels of the different neighborhoods of Montevideo. They were selected over a chart of neighborhoods, to maximize the representativity.

In the cities of the interior, the points selected for the 12-h measurements were located on one-way streets near the commercial centers, with access to electricity to ensure continuous measurement recording. Additional points were chosen based on the proximity to health centers, schools, high schools, and other notable features, ensuring relatively homogeneous areas between measurement locations. The selected points were always positioned away from intersections, specifically in the middle of the block, to avoid problems associated with street crossings, both in terms of source allocation and acoustic propagation phenomena.

The number of selected points in each city of the interior enables the relationships shown in Table 3.

Table 3

Summary of the characteristics of the sampling points in the cities of the interior

City (Department)	Montevideo (Montevideo)	Minas (Lavalleja)	Maldonado (Maldonado)	Rocha (Rocha)
Population according to the 2011 census	1,380,800	38,400	87,000	25,400
Approximate area	417 km²	8.2 km²	25 km²	8 km²
1-h measurement points	143	20	28	26
Average point density (points/km²)	0.3	2.4	1.1	3.3
Average point density (points/1,000 inhabitants)	0.10	0.52	0.32	1.02

Note: Data source: Own data.

3.2 Measurement height

Unless specified otherwise in certain locations where manual measurements must be conducted at a height of 4 m, as required by regulations (e.g., as stipulated in Resolution 0627, 2006, in the Republic of Colombia [2]), the most common practice is to perform manual measurements at a height of 1.20 ± 0.20 m above ground level. In contrast, measurements for simulation model inputs are generally taken at 4 m, which is the standard height used by most specialized computational programs.

However, measuring at different heights represents different realities, even when the numerical values obtained for L _AF,eq are very similar. This was also verified in the context of this study, in order to assess the possibility of using measurements taken at different heights interchangeably.

During the 12-h measurements, simultaneous recordings were taken at two different heights: 1.20 and 3.50 m, with the aim of verifying whether the results obtained at different heights are “interchangeable”. The L _Aeq values (1-min intervals) were considered, and statistical comparisons were made between the records at both heights using the Mann & Whitney test [22]. This is a non-parametric statistical test (it is worth noting that urban noise samples are generally non-normal, or as Don and Rees [23] put it, “anything but Gaussian”) that helps determine whether two samples come from the same population, with a confidence level assumed to be 95%. The comparisons corroborated the findings of Jaramillo et al. [24] in the city of Medellín, Colombia: although the equivalent continuous sound levels yield very similar values, the series of sound levels obtained at the same location but at different heights describe distinct realities. A summary of the results is presented in Table 4.

Table 4

Number of comparable and non-comparable simultaneous measurements at two different heights at the same location, during a total of 12 h of measurement in each case

	Comparable/total hours
Montevideo – Ellauri Street	11/12
Montevideo – Av. Uruguay	12/12
Montevideo – Av. Rivera	0/12
Maldonado	1/12
Minas	7/12
Rocha	5/12

Note: Data source: Own data.

As can be seen, the results are totally unpredictable: at the points in Montevideo, 12/12 non-comparable results and 12/12 comparable results were obtained in different points of the city. Similar unpredictability can be found in the interior of the country, where non-comparable results fluctuated from 5/12 to 11/12.

3.3 Determination of the stabilization time of measurements

The stabilization time of environmental sound pressure–level measurements is a concept introduced by González [15]. It refers to the time t*, which is the minimum time after which the L _A,eq,t* and L _A,eq,T of the studied period T (in this case, T = 1 h) differ by less than a predetermined tolerance ε, which can be set depending on the application intended to be carried out:

t* is the minimum value of t for which | L Aeq , T − L Aeq , t * | ≤ ε

In other words, measuring t* minutes leads to the same result (±ε dB) as measuring T minutes. T is the possibility of reducing the measuring time from T to t* minutes is then translated to the schedule and budget of a noise map, due to the reduction in the total measuring time in the city.

To determine a representative measurement time for the 1-h sound pressure level, six 12-h measurements were conducted at different locations: three in Montevideo, at sites selected based on varying typologies and traffic densities, and the remaining three in the previously mentioned cities in the interior of the country. Also, 143 1-h measurements across the city of Montevideo have been also considered to arrive at the stabilization time. The results are summarized in Figure 2, represented as a permanence curve. To draw the curve, all values have been sorted from maximum to minimum and a percentage of exceedance has been assigned. The x-axis shows the percentage of noise samples that have been stabilized, and the y-axis represents the amount of minutes that have been needed to stabilize each of them.

Figure 2

Average stabilization times for Montevideo and the interior, for 1-h measurements with 1-dB tolerance. Note: Data source: Own data.

In general, cities with lower populations showed longer stabilization times. However, this does not imply that the stabilization times in Montevideo are significantly shorter, as these are strongly influenced by traffic flow and its typology. It can generally be observed that measurement periods shorter than 45 min are not advisable if a tolerance of 1 dB is required and 95% of the measurements need to stabilize. To achieve the same tolerance while stabilizing 90% of the samples, the measurement time can be reduced to 40 min.

Additionally, it is important to note that when measurements last at least 40 min, the probability of adequately representing the sound levels for the period from 8:00 AM to 8:00 PM at the selected location is 95%.

The relationship between stabilization time and total hourly traffic (based on all the data generated in the project) is presented in Figure 3. In this case, the curves have been constructed with the stabilization time of 10, 50, 75 and 90% of the samples within a traffic range. That is, the curve of 75% considers the points defined by the stabilization time of 75% of the samples in a given range of traffic flow (more than 1,400 veh/h; between 750 and 1,400 veh/h, between 400 and 750 veh/h, less than 400 veh/h). It can be observed that, if stabilizing 50% of the samples is deemed sufficient, a sampling duration of 10 min may be adequate. However, for more stringent requirements, this duration would only be applicable in areas with a traffic flow of at least 1,000 vehicles per hour. To stabilize 75% of the samples, a minimum of 20 min of measurement would be recommended in areas with up to 400 vehicles per hour, and approximately 35 min would be necessary in areas with fewer than 200 vehicles per hour. Finally, if the total hour traffic flow is known or can be estimated, the measurement time can be better selected from Figure 3. If this data are not known, the stabilization time to use in Uruguay to suit every range of traffic flow should not be less than 45 min to stabilize 95% of the samples or 40 min to stabilize 90% of them.

Figure 3

Stabilization time measured for different percentages of samples and a tolerance of ±1 dB, as a function of total hourly traffic. Note: Data source: Own data.

3.4 Levels of annoyance experienced by the population

To assess the public’s perception of environmental noise and construct an annoyance curve related to sound pressure levels, a questionnaire consisting of ten (10) questions was designed and administered, along with five additional questions to gather demographic data about the respondents (age, gender, occupation, education level, and weekly working hours). The focus was on making the questionnaire quick to answer, although this may have resulted in the omission of other aspects.

The questionnaire was administered simultaneously with the sound pressure–level measurements, allowing the assignment of an environmental noise level to each respondent's answers [25]. In Montevideo, the questionnaires were collected during the 12-h measurements. In the other cities, they were collected during all measurement periods (not only the 12-h ones). The questions were designed to progressively guide respondents to reflect on environmental noise, beginning with an inquiry about the most urgent environmental issues in their neighborhood.

Firstly, it is important to note that noise pollution did not emerge as a significant environmental issue in most responses: fewer than 10% of respondents regarded it as an urgent problem to be addressed. Regarding the main sources of noise pollution, traffic in Montevideo was identified as the primary source of disturbance in nearly 50% of cases. However, in none of the three cities in the interior included in the study did it exceed 20%. Among the components of traffic noise, motorcycles and open exhaust systems were found to be the most bothersome across all six sampling locations.

Furthermore, following the methodology proposed by Ramírez González [25], the measured sound pressure levels were correlated with the instantaneous annoyance levels reported by the respondents (“How would you rate the noise you are experiencing at this moment, here and now?”). This correlation allowed for the creation of annoyance level maps on a scale from 1 to 5, where 5 represents extremely annoying and 1 represents not annoying at all. As an example, the annoyance-level map for the city of Minas is presented in Figure 4.

Figure 4

Instantaneous annoyance-level map for the city of Minas. Note: Data source: Own data.

Although the number of surveys is relatively small, it was sufficient to plot an L _Aeq,12h curve, and the percentage of highly annoyed population (% HA), as shown in Figure 5. While the comparison parameter used is not the one conventionally employed (L _DN) for such curves, it can be considered a preliminary approximation in cases where data of sufficient duration to calculate the L _DN value are unavailable. The data points on the graph correspond to each of the 12-h measurements taken. One possible interpretation of the results is that populations exposed to higher levels of environmental noise tend to develop greater tolerance, as evidenced by the points representing Av. Uruguay and Av. Rivera. Additionally, in inland cities, the highest tolerance to noise is observed in Rocha, where there is a notably greater concern with issues related to employment and the local economy.

Figure 5

Percentage of highly annoyed population as a function of the measured L _Aeq,12h. Note: Data source: Own data.

When respondents were asked for their suggestions on how to improve the city's acoustic quality, the majority of responses emphasized the need for stricter control and enforcement of loud exhaust systems on motorcycles.

3.5 Prediction model for traffic noise sound pressure levels

The current coefficients for the prediction model for Montevideo are shown in the equation below. They have been readjusted during 2023, considering the new 1-h measurements for Montevideo city and the long-term ones.

L Aeq , 1 h = 43.5 + 10 log ( A + 24.76 B + 10.44 C + 2.5 M ) + 22.6 . Q − 0.3811 + 10 log d

where K, a, b, c, m, q, and p are coefficients experimentally adjusted. A is the number of passenger cars/hour, B is the number of buses/hour, C is the number of trucks/hour, M is the number of motors/hour, Q = A + B + C + M, and d is the distance from the axis of the street to the sound-level meter. The term 22.6 Q ^−0.3811 is the term that considers the anomalous events’ occurrence.

3.6 Catalogue of management measures to improve environmental sound pressure levels

The last step of the methodology refers to the selection of the best management measures to improve the environmental sound pressure levels. Thus, a catalogue has been built, to find the most accurate measurements for each situation. The measures comprised by the catalogue were as follows:

4 Proposed methodology

The proposed methodology for constructing acoustic maps through measurements in Uruguay includes the following aspects [19]:

4.1 Selection of measurement points

Ideally, the measurement points should cover the city's diverse environments, including specific locations such as those near healthcare centers, educational institutions, large commercial areas, industrial sites, etc. Based on the results obtained and the fieldwork guidelines presented in Table 3, it is recommended to use the higher value between four points per km² or one point for every 1,000 inhabitants. Measurements should be taken at locations away from intersections with cross streets, ensuring that the chosen point is representative of the area (e.g., if sidewalks are generally narrow, avoid measuring in a location where they are occasionally wide; or if there are typically front gardens and setbacks, avoid choosing a location where this is not the case). A sketch of the location should always be made, indicating the door number where the sound level meter is placed, and describing the main features of the site. Simultaneously with the recording of sound levels, a classified traffic count should be conducted, along with hourly recordings and the identification of any anomalous events (horns, barking, alarms, etc.).

4.2 Measurement height

Unless a different objective is intended, sound levels and annoyance should be measured at a height of 1.20 m to reflect pedestrian exposure. If the goal differs, the measurement height should be adjusted according to the relevant guidelines or to more accurately capture the specific context being studied.

4.3 Measurement duration

In Uruguayan cities, unless more specific local data are available, sound-level measurements on public streets should last at least 45 min to adequately represent the sound pressure levels over the course of one (1) hour. If hourly traffic data are available, the duration may be adjusted accordingly, with the minimum duration corresponding to the time required for 90% of the samples to stabilize, as shown in Figure 3. It is recommended to select a duration that is a multiple of 5 min (for instance, instead of 13 min, use 15; instead of 37 min, use 40; etc.).

4.4 Predictive model

It is desirable that the predictive equation used to complement the measured data has been at least validated in the location where the acoustic map is being created. It is quite common to use equations developed to describe contexts different from the one being studied, which leads to an increase in the margin of error.

4.5 Assessment of the highly annoyed population

To estimate the percentage of individuals who are highly annoyed, an initial approach suggests using the curve from Figure 5 along with the local daytime sound pressure levels. If the objective is to assess the percentage of the resident population that is highly annoyed, it is recommended to consider population density data from the most recent official Population and Housing Census and adjust the measured sidewalk sound pressure levels by reducing them by 5 dB [26].

5 Main limitations of this study

Clearly, having more field data would have enabled better estimations of the measurement stabilization times and the number of measurement points relative to the city's size. However, it is considered that this methodological approach will allow for the development of reasonably accurate noise maps through direct measurements, at a cost-effective rate.

6 Conclusions

The creation of acoustic maps through manual measurements remains common in many regions. The guidelines presented in this article regarding the design of fieldwork – particularly in terms of sample point selection, measurement height, and duration – may be of interest to other researchers or urban noise pollution managers. More importantly, it is essential to present our methodology for obtaining this information, which ultimately influences not only the duration and cost of fieldwork, but also, and more importantly, the reliability and representativeness of the results.

Acknowledgments

The authors are grateful to Valentina La Manna and Joaquín Sharoian, who carried out most of the 1-h measurements in Montevideo.

Funding information: This research was funded by the CSIC I+D funds (Research and Development funds of the Central Commission on Scientific Research) of Universidad de la República, Uruguay.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and consented to its submission to the journal, reviewed all the results, and approved the final version of the manuscript. AEG designed the experiments, and PGK, ISD, and HCV carried them out and processed the data. AEG prepared the manuscript with contributions from all co-authors.
Conflict of interest: Authors state no conflict of interest.

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Received: 2025-01-28

Revised: 2025-03-19

Accepted: 2025-03-25

Published Online: 2025-05-09

This work is licensed under the Creative Commons Attribution 4.0 International License.