Approaching Quietness as an Urban Sustainability Opportunity

Quietness in an urban environment is vital for the well-being of city residents. Nevertheless, the ambiguity in the conceptualization of the terms noise and quietness as urban acoustic planning and design objectives, has resulted in two different approaches: the soundscape approach and the noise control approach. The main purpose of this research is to supplement the existing approaches by proposing a new ecological acoustics approach in order to identify quiet areas in the city of Mytilene (Lesbos Island, North Aegean, Greece). The use of the soundscape approach involved the participation of Mytilene’s residents and the collection of subjective and objective eligibility criteria. By means of Multi-Criteria Decision Making two urban green areas were highlighted as potential quiet areas. For the noise control approach, road noise maps have been created through a commercial noise mapping software, validated by trough measurements. As a result, two areas located in the outskirts of the city were highlighted. Finally, the novel ecological acoustics approach involved acoustic recordings and the extraction of the Composite Urban Quietness Index (CUQI). The outcome of this approach converged with the soundscape approach results. Quietness, as an urban acoustic planning and design goal, could be viewed as an opportunity for ecologically sustainable urban environments.


Introduction
The immediacy of sound could serve as an indicator of urban sustainability which is the main focus of ecological urban planning and design [1]. Changes in the urban environment produce an acoustic impact highlighting sound as an indicator of environmental alteration associated even with climate change [2]. Therefore, an increasing number of urban planners and designers have turned their attention towards soundscaping [3]. Nevertheless, the lack of ecological knowledge in order to deal with the material and immaterial qualities of the urban environment has created the need for transdisciplinary research collaborations [4] between urban planners and acoustic ecologists.
Efforts aiming towards noise pollution reduction are determined by the way in which the concepts of noise and quietness are interpreted as objectives of urban acoustic planning and design. The polysemy of the concept of noise and the variety of characterizations attributed to this term [5] has determined the interpretation of the concept of quietness in an analogous manner as a counterpoint. The version of noise as an unwanted sound renders quietness as a desirable acoustic condition and thus a positive or pleasant soundscape [6,7]. Concurrently, if noise is interpreted as a sound of high intensity [8] characterized by a high decibel value [9], then quietness is the opposite. A vital urban acoustic planning and design objective is the creation of quiet areas, along with the noise reduction efforts in a noise polluted area. The approaches dealing with the two differentiating objectives are the soundscape approach [10] and noise control approach [11]. These two different approaches and the general ambiguity in the conceptualization of the relevant terms has caused the The noise control approach aims at reducing noise levels from various sources that can be measured, predicted and addressed [45][46][47]. According to the END provisions, strategic noise mapping [48,49] must be implemented for all heavily dense urbanized areas in order to manage the abatement of environmental noise and for action plans to be shaped [50,51]. Through the noise control approach, quiet areas are perceived as acoustic environments with low noise dB(A) levels. Therefore, a range of 50-55 dB(A) regarding the L den indicator is suggested, coming into an alignment with the World Health Organization prompt of road traffic noise limitation at 53 dB(A) of the same indicator [52,53]. Implementations similar to noise barriers could support the noise control approach. According to simulations and actual implementations, the use of a noise barrier can affect sound attenuation due to diffraction that is highly dependent on the barrier's height [54,55].
Ecological principles [56] can be applied in urban planning and design through ecosystem services [57,58] provisioning in order to achieve both the sustainable and desirable in regard to quality of life [59]. In an urban environment different sounds are transmitted by a variety of biological, geophysical and man-made sources [60][61][62][63] reflecting the landscape. Noise in a city, apart from the annoyance and direct health implications in humans [53] also disrupt communication between species inhabiting the urban environment [64]. Man-made noise occupies a layer of the of the city's acoustic palimpsest, causing auditory masking and forcing city birds to sing in a higher pitch [65,66], leading to numerous implications [67] that eventually harm the ecosystem's integrity. High levels of acoustic complexity in an acoustic environment are a result of biotic sounds such as bird songs [68]. It is well understood that man-made noise is the reason for complexity deterioration [69], leading to diversity and ecosystem resilience decline [70].
Conceptual limitations of the terms "noise" and "quiet" and their interpretation as a contradiction have initiated design tactics with reduced ecological co-benefits, promoting short-term benefits of pleasant soundscapes. The main idea in the ecological acoustics approach is to break the association between these concepts and assign quietness a value in order for it to become an autonomous quantity. The association of quietness with biodiversity [30] and the fact that nature sounds are enjoyed by humans [71] present an opportunity for long-term ecological urban planning and design. In this manner quietness can become the means towards a truly sustainable city with high levels of both biological and cultural complexity [72].

Materials and Methods
The city of Mytilene (39.1067 • N, 26.5573 • E) was chosen as a case study area for this research. Mytilene is the capital city of the island of Lesbos, located in the North Aegean Region in Greece. Islands are notable for their biological endemism and encapsulate within their borders various biological and anthropological processes, such as species migration and human demographic concentration. Amongst the most valuable resources associated with islands are their acoustic environments, which are part of their cultural heritage and reflect important ecosystem services [73].

Soundscape Approach Methodology
The soundscape approach involved the active participation of Mytilene's residents through a small-scale citizen science program [74,75]. As can be seen in Figure 1, four major steps were implemented for this approach.
Citizen input regarding the assessment of soundscapes and acoustic environments is a promising field and new citizen science tools such as applications on smartphones are emerging [25]. For this research a total of 55 inhabitants participated in acoustic ecology themed seminars, workshops, discussions and educational soundwalks. The participants' age class was 18-26 years (45.25% male, 54.75% female). All of them were members of the academic community of the city's local university and permanent residents of Mytilene. The participants were asked to observe their daily routine, including weekdays and weekends, mainly by focusing on their acoustic environment. The next step was a follow-up interview, Environments 2022, 9, 12 4 of 15 the purpose of which was to identify the acoustic environments chosen by the participants as the most acoustically interesting. Furthermore, several related issues were discussed regarding sounds liked and disliked and also the feeling of safety that the participants had in these areas as users. The resulted areas were categorized as (a) urban green areas, (b) public spaces, (c) archaeological sites and (d) areas of designated use and were handled as case study areas. These areas were incorporated in the data collection procedure in order to set the list of quiet area selection criteria.
Due to the fact that noise levels were one of the criteria chosen, a sound level meter was used in order to conduct measurements and collect the L den values for each area. The device was calibrated prior of this research using a calibrator as required for all Class 1 measuring instruments and in accordance with the specifications of EN61326-1:(1997 + A1):1998.
The complete list of criteria, apart from the noise levels, included the area's health restoration and recreation opportunities, its size and distance from the city's center and also the presence of green infrastructure. These criteria were incorporated in a multi-criteria decision making (MCDM) tool in order to prioritize the case study areas. The MCDM method chosen was the Analytical Hierarchy Process (AHP) [76].
follow-up interview, the purpose of which was to identify the acoustic environments chosen by the participants as the most acoustically interesting. Furthermore, several related issues were discussed regarding sounds liked and disliked and also the feeling of safety that the participants had in these areas as users. The resulted areas were categorized as (a) urban green areas, (b) public spaces, (c) archaeological sites and (d) areas of designated use and were handled as case study areas. These areas were incorporated in the data collection procedure in order to set the list of quiet area selection criteria.
Due to the fact that noise levels were one of the criteria chosen, a sound level meter was used in order to conduct measurements and collect the Lden values for each area. The device was calibrated prior of this research using a calibrator as required for all Class 1 measuring instruments and in accordance with the specifications of EN61326-1:(1997 + A1):1998.
The complete list of criteria, apart from the noise levels, included the area's health restoration and recreation opportunities, its size and distance from the city's center and also the presence of green infrastructure. These criteria were incorporated in a multi-criteria decision making (MCDM) tool in order to prioritize the case study areas. The MCDM method chosen was the Analytical Hierarchy Process (AHP) [76].

Noise Control Methodology
A noise map in order to assess the effects of road traffic noise was created using the CadnaA (Computer Aided Noise Abatement) software [77]. The Leq (dBA) levels deriving from 13 roads crossing the case study areas were collected using the same noise level meter described above. As can be seen in Figure 2, for each road three check spots were chosen in which the noise measurements were conducted.

Noise Control Methodology
A noise map in order to assess the effects of road traffic noise was created using the CadnaA (Computer Aided Noise Abatement) software [77]. The L eq (dBA) levels deriving from 13 roads crossing the case study areas were collected using the same noise level meter described above. As can be seen in Figure 2, for each road three check spots were chosen in which the noise measurements were conducted. The noise level measurement results were imported into the noise mapping software (CadnaA MR1) and the case study areas were assessed as receivers. Each potential quiet area was assessed as a receiver of road traffic noise propagating from the nearby road(s). The simulated noise levels of each area were used in order to rank the areas from the quietest to the noisiest.
On each of the 13 roads, three noise measurements were conducted at the beginning, middle and last point of each selected part of the road network. The calibrated Class 1 sound level meter was mounted on a tripod at 1.5 m above ground and pointed towards the source (0° reference direction). All measurements were conducted at morning hours (8.00 am-11.00 am) and lasted 5 min each. The A-weighted equivalent continuous sound level (Leq) was extracted for all 39 points checked.
Of the 13 roads checked, three of them were rough textured local roads and ten smooth asphalt ordinary roads. The width of each road was measured and imported as a feature in order to obtain realistic results. Furthermore, all traffic lights that were active during the measurement hours were incorporated in the modeling procedure. A dry road surface and a constant vehicle speed at 50 km/h were used for all types of vehicles. Most of the data required for successful traffic noise prediction have three-dimensional spatial characteristics. The management and visualization of these three-dimensional spatial data is important for urban planners and engineers as it offers them the ability to interactively modify their plans for ideal results [78].
Structural morphology data were collected and imported to the noise mapping software along with the noise measurement data. More specifically, a detailed cartographic representation of the area under consideration that included the building and foliage height and exact location [79] were incorporated. The noise level measurement results were imported into the noise mapping software (CadnaA MR1) and the case study areas were assessed as receivers. Each potential quiet area was assessed as a receiver of road traffic noise propagating from the nearby road(s). The simulated noise levels of each area were used in order to rank the areas from the quietest to the noisiest.
On each of the 13 roads, three noise measurements were conducted at the beginning, middle and last point of each selected part of the road network. The calibrated Class 1 sound level meter was mounted on a tripod at 1.5 m above ground and pointed towards the source (0 • reference direction). All measurements were conducted at morning hours (8.00 am-11.00 am) and lasted 5 min each. The A-weighted equivalent continuous sound level (L eq ) was extracted for all 39 points checked.
Of the 13 roads checked, three of them were rough textured local roads and ten smooth asphalt ordinary roads. The width of each road was measured and imported as a feature in order to obtain realistic results. Furthermore, all traffic lights that were active during the measurement hours were incorporated in the modeling procedure. A dry road surface and a constant vehicle speed at 50 km/h were used for all types of vehicles. Most of the data required for successful traffic noise prediction have three-dimensional spatial characteristics. The management and visualization of these three-dimensional spatial data is important for urban planners and engineers as it offers them the ability to interactively modify their plans for ideal results [78].
Structural morphology data were collected and imported to the noise mapping software along with the noise measurement data. More specifically, a detailed cartographic representation of the area under consideration that included the building and foliage height and exact location [79] were incorporated. At this point it is important to mention that the noise map created for this research does not represent the holistic noise climate of the city of Mytilene from multiple sources. Nevertheless, the scope of this procedure was to assess the effects of the dominant road traffic noise on the potential quiet areas of the city.

Ecological Acoustics Approach Methodology
The analysis of digital sound recordings and the extraction of the Acoustic Indices (AI) [80] have been used for Rapid Biodiversity Assessment (RBA) [81] in an increasing rate for a variety of environments [82][83][84]. Furthermore, the scientific field of ecoacoustics [85,86] has offered a new approach regarding the investigation of the ecological role of sound [87][88][89][90]. The use of several AI for biodiversity monitoring in urban environments face challenges due to the auditory masking effect caused by anthropogenic noise [91]. The proposed ecological acoustics approach embrace's these challenges and utilizes two of the available AI's, placing them out of their original context regarding RBA.
The R Statistics software (v. 3.6.1) [92] was used in order to extract AIs. More specifically, the R computational packages seewave [93], tuneR package [94], soundecology [95] and ineq [96] were used. For this research, the Acoustic Complexity Index (ACI) [69] that highlights the degree of complexity by processing the intensities recorded in an audio-file and the Normalized Difference Soundscape Index (NDSI) [97] were extracted.
As can be seen in Figure 3, sound recordings were conducted in eight check points on the perimeter of a case study area (edges) and one on the area's center (core). The AI's ACI and NDSI were extracted and used as sub-indicators in a novel composite index entitled Composite Urban Quietness Index (CUQI) [14]. The CUQI index was calculated for all case study areas and the results were ranked in order to highlight the potential urban quiet areas of Mytilene.
The CUQI (1) index is calculated according to the following formula: where: AD = anthropogenic disturbance calculated as a ratio of the resulted NDSI values; RG ACI = range of the acoustic complexity values; CB = ratio of the acoustic complexity values.
At this point it is important to mention that the noise map created for this rese does not represent the holistic noise climate of the city of Mytilene from multiple sou Nevertheless, the scope of this procedure was to assess the effects of the dominant traffic noise on the potential quiet areas of the city.

Ecological Acoustics Approach Methodology
The analysis of digital sound recordings and the extraction of the Acoustic In (AI) [80] have been used for Rapid Biodiversity Assessment (RBA) [81] in an increa rate for a variety of environments [82][83][84]. Furthermore, the scientific field of ecoacou [85,86] has offered a new approach regarding the investigation of the ecological ro sound [87][88][89][90]. The use of several AI for biodiversity monitoring in urban environm face challenges due to the auditory masking effect caused by anthropogenic noise The proposed ecological acoustics approach embrace's these challenges and utilizes of the available AI's, placing them out of their original context regarding RBA.
The R Statistics software (v. 3.6.1) [92] was used in order to extract AIs. More cifically, the R computational packages seewave [93], tuneR package [94], soundeco [95] and ineq [96] were used. For this research, the Acoustic Complexity Index (ACI that highlights the degree of complexity by processing the intensities recorded in a dio-file and the Normalized Difference Soundscape Index (NDSI) [97] were extracted As can be seen in Figure 3, sound recordings were conducted in eight check p on the perimeter of a case study area (edges) and one on the area's center (core). The ACI and NDSI were extracted and used as sub-indicators in a novel composite inde titled Composite Urban Quietness Index (CUQI) [14]. The CUQI index was calculate all case study areas and the results were ranked in order to highlight the potential u quiet areas of Mytilene.
The CUQI (1) index is calculated according to the following formula: where: AD = anthropogenic disturbance calculated as a ratio of the resulted NDSI valu RGACI = range of the acoustic complexity values; CB = ratio of the acoustic complexity values.

Results
The soundscape approach, the noise control approach and the ecological acou approach were tested in the city of Mytilene. The previous studies conducted, regar the soundscape approach [74,75] and the ecological acoustics approach [14,72],

Results
The soundscape approach, the noise control approach and the ecological acoustics approach were tested in the city of Mytilene. The previous studies conducted, regarding the soundscape approach [74,75] and the ecological acoustics approach [14,72], were supplemented by the noise mapping in order to holistically investigate the potential quiet areas of Mytilene.

Soundscape Approach Results
The soundscape approach practically involved city residents in order to define the case study areas and highlight soundscapes perceived as interesting. As can be seen in Figure 4, in total 18 areas were derived. Amongst the areas, 6 were urban green areas, 3 were public spaces, 3 were archaeological sites and 6 were areas of designated use. supplemented by the noise mapping in order to holistically investigate the potential quie areas of Mytilene.

Soundscape Approach Results
The soundscape approach practically involved city residents in order to define th case study areas and highlight soundscapes perceived as interesting. As can be seen i Figure 4, in total 18 areas were derived. Amongst the areas, 6 were urban green areas, were public spaces, 3 were archaeological sites and 6 were areas of designated use. In Figure 5, the ranking resulted from the AHP is presented. Two urban green area located in the city's center gave the highest scores in the paired evaluation conducted (th Agias Eirinis park and the Karapanagiotis park, the two areas colored green in Figure 2 For the AHP, higher weights were attributed to the restoration and recreation criteria and lower to the noise level thresholds of the areas. Finally, in the follow up interviews tha were conducted, most of the participants conveyed the fact that they do not feel safe in th areas that they selected, especially during the night period. Furthermore, they highlighted the positive sounds present. Most of these sounds were natural, including biological (bird singing) and geophysical (sea waves) sounds, followed by several anthopogenic recrea tional sounds, similar to music and the vocal expression of enjoyment of children playing. In Figure 5, the ranking resulted from the AHP is presented. Two urban green areas located in the city's center gave the highest scores in the paired evaluation conducted (the Agias Eirinis park and the Karapanagiotis park, the two areas colored green in Figure 2). For the AHP, higher weights were attributed to the restoration and recreation criteria and lower to the noise level thresholds of the areas. Finally, in the follow up interviews that were conducted, most of the participants conveyed the fact that they do not feel safe in the areas that they selected, especially during the night period. Furthermore, they highlighted the positive sounds present. Most of these sounds were natural, including biological (bird

Noise Control Results
The measured noise levels (Leq dBA) for each checkpoint on each road are presented in Table 1. As expected, the local roads measured where quieter due to the lesser amount of road traffic. In Table 2, the simulated noise levels, along with the measured, are presented. Due to the fact that several areas were affected by more than one road, the total measured mean was calculated in order for a comparison between the noise measured and the noise simulated to take place.

Noise Control Results
The measured noise levels (L eq dBA) for each checkpoint on each road are presented in Table 1. As expected, the local roads measured where quieter due to the lesser amount of road traffic. In Table 2, the simulated noise levels, along with the measured, are presented. Due to the fact that several areas were affected by more than one road, the total measured mean was calculated in order for a comparison between the noise measured and the noise simulated to take place. As can be seen in Figure 6, two archeological sites located on the outskirts of the city and near local roads were the quietest and therefore can be described as Mytilene's quiet areas. As can be seen in Figure 6, two archeological sites located on the outskirts of the city and near local roads were the quietest and therefore can be described as Mytilene's quie areas. Finally, the noise map that was created using the cadnaA software is presented in Figure 7. Finally, the noise map that was created using the cadnaA software is presented in Figure 7.

Ecological Acoustics Approach Results
The results provided by the CUQI calculations ( Figure 8) appear to give similar outcomes to the soundscape protocol used to identify urban quiet areas (Agias Eirinis park and Karapanagioti park, Mytilene, Lesbos Island, North Aegean, Greece). The CUQI appears to comply with research requirements that balance the multi-factor perspectives of environmental complexity as an easy-to-use decision-making tool.

Ecological Acoustics Approach Results
The results provided by the CUQI calculations ( Figure 8) appear to give similar outcomes to the soundscape protocol used to identify urban quiet areas (Agias Eirinis park and Karapanagioti park, Mytilene, Lesbos Island, North Aegean, Greece). The CUQI appears to comply with research requirements that balance the multi-factor perspectives of environmental complexity as an easy-to-use decision-making tool.

Ecological Acoustics Approach Results
The results provided by the CUQI calculations ( Figure 8) appear to give similar outcomes to the soundscape protocol used to identify urban quiet areas (Agias Eirinis park and Karapanagioti park, Mytilene, Lesbos Island, North Aegean, Greece). The CUQI appears to comply with research requirements that balance the multi-factor perspectives of environmental complexity as an easy-to-use decision-making tool.

Conclusions
Quietness can be interpreted subjectively in terms of pleasantness and tranquility, or objectively in terms of low intensity levels. Depending on how the term is understood, a different approach can be used in order to identify quiet areas in an urban environment. Though interrelated, the two major approaches are the soundscape approach and the noise control approach. The authors of this research argue that the issue of urban quiet areas presents an opportunity for urban sustainable development. Therefore, a third supporting approach is proposed in an effort to introduce ecological acoustic concerns in future urban acoustic planning and design.
For this research the soundscape approach conducted in order to identify the quiet areas of Mytilene utilized quantitative data from measurements and qualitative data from a citizen science scheme. The results highlighted two urban green areas located in the city's center. For the noise control approach a road traffic noise map was created by conducting noise level measurements. The assessment of the results highlighted areas with lower sound pressure levels, which were two areas located in the outskirts of the city. Finally, for the ecological acoustics approach, the Composite Urban Quiet Index (CUQI) was applied, resulting in the same areas as the ones with the soundscape approach. This similarity is due to the fact that the qualitative criteria used in a similar way to the restorative and recreational value were the ones responsible for the increased levels of biological and cultural complexity.
The views and preferences of local residents, as well as the needs of a community, are valuable tools for sustainable urban planning. However, a risk of bias emerges, which concerns the lack of, or the coincidental presence of, ecological co-benefits, particularly in soundscape design efforts that include the preferable natural sounds.
Future research involves the theoretical and practical advancement of the ecological acoustics approach. Planners and designers in collaboration with ecologists need to plan ahead in small scale, "safe to fail" projects in order to "learn by doing" [98]. Quietness and the creation of quiet areas present an opportunity for a truly sustainable urban planning and design, following three main principles: planning for resilience, planning for biodiversity and planning for connectivity [1,99] that can be summarized as "planning for quietness". The green infrastructure, including ecological networks, patches, corridors, green roofs and walls can be the means to both abate excessive amounts of noise levels and increase biodiversity [100], thus creating urban quiet areas that are able to recover from disturbances and adapt to change while maintaining their fundamental structure and function.