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Assessment of acoustical environment condition at urban landscape
Applied Acoustics 160 (2020) 107126
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Assessment of acoustical environment condition at urban landscape Hsiao Mun Lee a,⇑, Yi Liu c, Heow Pueh Lee b,c a Center for Research on Leading Technology of Special Equipment, School of Mechanical and Electric Engineering, Guangzhou University, 230 Wai Huan Xi Road, Guangzhou 510006, PR China b Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117575, Singapore c National University of Singapore (Suzhou) Research Institute, No. 377 Linquan Street, Suzhou Industrial Park, Suzhou, Jiangsu, China
a r t i c l e
i n f o
Article history: Received 7 August 2019 Received in revised form 9 October 2019 Accepted 30 October 2019
Keywords: Acoustical environment Urban landscape Smartphone
a b s t r a c t Acoustical environment conditions of two famous landscapes at Suzhou, China were investigated. The studies were conducted through sound level measurements and questionnaire surveys at different zones at Guanqian area and Pingjiang Ancient Town. Measurement data showed that the sound levels at these two areas were considered safe for human because the maximum sound level measured from these areas was 80 dBA which was still under the permissible exposure limit (90 dBA) that recommended by Occupational Safety and Health Administration (OSHA). Negative linear relationship was found to be existed between the perceptions of quietness/comfort level and sound level at Pingjiang Ancient Town. The major sound sources at Guanqian area and Pingjiang Ancient Town were daily living and natural sounds, respectively. It was found that gender did not had significant effect on the perceptions of quietness and comfort level. It was also found that natural sound could let human felt more pleasant while machinery sound let human felt uncomfortable. Ó 2019 Elsevier Ltd. All rights reserved.
1. Introduction For a long time, the research on noise pollution is focused on the concept of ”noise” and researchers tried to improve the acoustical environment by reducing the sound pressure level (SPL) through noise control. However, some studies pointed out that the reduction of SPL cannot improve perception of people toward noise effectively and many factors such as psychological condition can affect this perception. Thus, the scope of the conventional noise control method has been widen so that human’s perception toward noise is accredited as the focus center in the method. In 1960s, the idea of soundscape was first introduced in order to improve the life quality and health of human [1]. In 2014, the International Organization for Standardization (ISO) defined soundscape as the sound environment experienced and perceived by individual or group of people in a particular context [2]. Great attention only has been paid in the field of community noise and environmental acoustics by researchers about two decades ago although the concept of soundscape was introduced about 50 years ago [3,4]. Lebiedowska [5] analyzed the interaction between transport noise and background noise in urban space. They proposed five types of urban soundscape which ranging from very quiet area to ⇑ Corresponding author. E-mail address: [email protected] (H.M. Lee). https://doi.org/10.1016/j.apacoust.2019.107126 0003-682X/Ó 2019 Elsevier Ltd. All rights reserved.
very loud area. Coensel and Botteldooren [6] proposed an indicator to study the temporal structure of the urban soundscape by drawing on the analogy with music and self-organization. They found that the indicator followed more closely the original ideas behind urban soundscape research by using the analogy with music. Jeaon et al. [7] conducted laboratory experiments to investigate which water sound was appropriate for masking urban noise. Their experimental results revealed that preference scores for the urban soundscape were affected by the visual images of water features and acoustical characteristics of water sounds. Oldoni et al. [8] developed a numerical model to classify the sounds that were presented in the soundscape and simulated how a typical listener would switch attention over time between different sounds. Listening evaluations were conducted by Andringa et al. [9] to analyze the role of suboptimal soundscapes and sound annoyance on the lives of individuals. They concluded that a good soundscape or more generally a good sensescape, was at the same time conductive as well as pleasant for the adoption of healthy habits. Payne [10] designed a Perceived Restorativeness Soundscape Scale (PRSS) to access perception of a soundscape’s potential to provide psychological restoration. They claimed that the PRSS was able to differentiate between soundscapes from different urban parks. Listening evaluations were conducted by Mackrill et al. [11] with 24 participants who rated their cognitive (Interest and Understanding) and emotional (Relaxation) responses to a variety
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of hospital ward soundscape clips across three interventions (steady state, natural and written sound sources). They claimed that a repeated measured ANOVA revealed that the ’Relaxation’ response was significantly influenced by the intervention with natural sound producing a 10.1% more positive response. Soundscape data on specifically defined temporal and spatial scales were evaluated and observed by Liu et al. [12] in a multi-functional urban area in Rostock, Germany. Their results showed that urban soundscapes were characterised by artificial sounds (mechanical, human and traffic sounds) overwhelming the natural sounds (geophysical and biological sounds). Chew and Wu [13] conducted spatial-temporal analysis by the integration of sound amplitude, frequency and time to show how various types of traffic noise dominated urban landscape soundscape during different time periods. They found that taxis and cars were the dominant sources of noise in commercial and residential areas in the afternoon and evening. Martin et al. [14] conducted a seismic survey campaign involving four vessels in Baffin Bay, West Greenland. Their results showed that the soundscape of Baffin Bay was typical for open ocean environments and Melville Bay’s soundscape was dominated by glacial ice noise. Li et al. [15] analyzed the sound comfort level relationships with each class of sound sources, land use, subjective evaluation, sound harmoniousness, sound level, age and gender using shared data for over a year. They claimed that women were higher-quality data providers where they exhibited better performance than man and adults (19–40 years old) with respect to data integrity. Zhang et al. [16] studied the effects of relaxation, spatiality, communication and dynamics on acoustic comfort in urban open public spaces. They found that the perceived dominance of sound sources had a significant effect on relaxation, spatiality, communication and dynamics. Xu and Kang [17] explored the performance of monaural and binaoral recordings in soundscape evaluation. Monaural and binaural recordings were simultaneously made at twelves sites with different acoustic scenarios. They found that the two recording methods presented good agreement on most soundscape evaluation indicators included acoustic comfort, overall impression, pleasantness, loudness and eventfulness. Hong et al. [18] developed a objective and subjective transformation model of soundscape in urban park (Shiba Park and Kamogawa Park in Japan) based on radial basis function neural network. They found that the model had higher accuracy for subjective evaluation value where it was up to 91.23% for average prediction accuracy rate. Lin et al. [19] analyzed the sound environment at Feng Chia night market in Taiwan where this market had large number of visitors and was close to high density residential area. Their research outcomes could provide a reference for urban planning project as quieter environment is required by most of the community nowadays. From reported studies, it can be seen that in addition to noise level, many subjective factors also have strong effect on the quality of urban acoustical environment. With the expansion of the city and development of economy, urban environmental pollution has become more serious especially noise pollution. Long term noise exposure can lead to non-auditory and auditory effects on human health such as cognitive impairment in children, annoyance, cardiovascular disease, sleep disturbance and tinnitus [20]. Therefore, in order to obtain deeper insight into acoustical environment in urban area, this study will investigate the soundscapes at Guanqian area and Pingjiang Ancient Town. These two locations are located at Suzhou, China and they are famous landscapes and commercial streets in Suzhou. At first, the real-time noise levels at these locations were recorded using smartphone. After that, questionnaire survey was conducted to investigate the subjective perception of the respondents. It is expected that the outcome of the current studies can provide some noise control inputs to the urban planning project. Consequently, comfort level of residents or visi-
tors in the urban area with proper noise control plan could potentially be improved. 2. Methods 2.1. Sound sources and zone distributions at Guanqian area and Pingjiang Ancient Town The maps and pictures of Guanqian area and Pingjiang Ancient Town are shown in Figs. 1 and 2, respectively. These two areas are well-known commercial zones and historical sites in Suzhou with rich landscape compositions. The areas of Guanqian area and Pingjiang Ancient Town are large and thus, the soundscapes at these two places vary greatly among different regions. Through observation of the sound environment conditions and landscape characteristics at these two areas, these two areas were divided into different zones for the purpose of data collection in order to have more accurate and in-depth grasp towards acoustical environments of these two areas. In addition, from the on-site observation, the sound sources at these two areas were summarized and were classified into three categories where they were machinery, natural and living sounds. Machinery sound sources included sounds from car, bus, van, bicycle or electric bicycle, airplane, road cleaning machine, lawn mowing, entertainment facilities and so on. Natural sound sources included sounds from bird, god, insect, wind, rain, leaf rubbing, and so on. Living sound sources included sounds from footsteps, hawking, knocking silver and so on. Guanqian area was divided into six zones as shown in Fig. 3. Zone 1 was close to traffic road and it was quite crowded (see Fig. 4(a)). Its sound source mainly consisted of machinery and daily living sounds included traffic sound and voice of pedestrians. Zones 2 and 3 were commercial districts (see Fig. 4(b) and (c)), they basically consisted of daily living sound. Zones 4 and 5 were located in Xuanmiao Temple (see Fig. 4(d) and (e)). There were many tourists in these two zones and these two zones basically consisted of daily living and natural sounds. Zone 6 was located at the commercial center of Guanqian Street, so this zone was very crowded. Distinctive sound of Guanqian Street also existed in this zone - sound of knocking silver (see Fig. 4(f)). Pingjiang Ancient Town was divided into five zones as shown in Fig. 5. Zone 1 was close to traffic road (see Fig. 6)) and its sound source mainly consisted of machinery and daily living sounds. Zones 2, 3, 4 and 5 were located at residential or tourist attractions areas (see Fig. 6(b)(b) to (e)), they basically consisted of daily living and natural sounds. 2.2. Sound measurements One Samsung A9 smartphone and One ZTE AXON M smartphone were used in the present studies for sound measurements. Noise Explorer software was installed in these smartphones and was used for data acquisition. A specific averaging method was used to calibrate both smartphones [21]. After the calibration, by comparing sound level data measured by these two smartphones with the data measured by PCB Piezotronics class 1 type microphone (model 377B02), both smartphones were proved to be able to achieve accuracy up to ±0.7 dB. In the present studies, each zone had five data collection points. Equivalent sound pressure level (LAeq ) was recorded at each point and it is defined as:
LAeq ¼ 10 log
! n X SPLi ti 10ð 10 Þ ;
ð1Þ
i¼1
where t i is the fraction of the time period that the noise has a sound level of SPLi . The sampling time at each point was about 1 min. One sound sample was collected at each point during morning (9am and
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Fig. 1. (a) Map of Guanqian area (b) real view of Guanqian area.
Fig. 2. (a) Map of Pingjiang Ancient town (b) real view of Pingjiang Ancient Town.
2.3. Questionnaire survey
Fig. 3. Map of the six data collection zones at Guanqian area.
10am), afternoon (2 pm and 3 pm) and evening (7 pm and 8 pm). The data were collected twice a month (one weekday and one weekend) during October and November in 2018 and March and April in 2019. Therefore, the total sound recording time at Guanqian area and Pingjiang Ancient Town were about 24 and 20 h, respectively.
The questionnaire used in the present studies is shown in Table 6 in appendix. According to the needs of the research, the questionnaire included the interview time, venue of the interview, zone of the venue, gender and age of the interviewee, perceptions of comfort level and quietness of the interviewee towards the environmental sound and sound sources in the particular zone. The score for perceptions of quietness and comfort level is shown in Table 1. At each data collection point, one interviewee was asked to fill in the questionnaire on around 9.30 am, 2.30 pm and 7.30 pm. This is the timing where the first sound recording on that particular session was completed (9 am, 2 pm and 7 pm) and before the second sound recording was started (10 am, 3 pm and 8 pm). The questionnaires were distributed on the same day when sound recording was conducted which means twice a month (one weekday and one weekend) during October and November in 2018 and March and April in 2019. Therefore, about 720 and 600 interviewees were asked to fill in the questionnaires at Guanqian area and Pingjiang Ancient Town, respectively. There are 302 male and 418 female interviewees at Guanqian area and 318 male and 282 female interviewees at Pingjiang Ancient Town. The gender ratio of interviewees at these two areas is shown in Fig. 14 in the appendix. The age distribution of interviewees at these two areas is shown in Fig. 7. The order of the age from highest to lowest proportion for both areas are the same where they are youth!middle age!old age!under age (the proportions for under age and old
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Fig. 4. Real view of the six data collection zones at Guanqian area. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5 (f) zone 6.
3. Results and discussion 3.1. Sound data
Fig. 5. Map of the five data collection zones at Pingjiang Ancient Town.
age are the same at Guanqian area). These results are reasonable as youth people normally is the major group of people who working, visiting or living in commercial district and tourist attraction area.
Fig. 8 shows the average LAeq measured at the six data collection zones at Guanqian area from 9am to 8 pm over weekday and weekend. Average LAeq is obtained by averaging all LAeq measured at the particular zone and timing among four months time. Generally, the average LAeq at Guanqian area during weekend is higher than that of weekday for all zones. The trends of the average LAeq at zone 1 are similar for both weekday and weekend (see Fig. 8(a)). Zone 1 is located near a main traffic road, so no matter weekday and weekend, there are always a lot of vehicles and pedestrians passing by the main traffic road. Therefore, the average LAeq at zone 1 for both weekday and weekend are generally higher than all other zones except zone 6. In the morning (9 am and 10 am), most of the shops at zone 1 are not open yet, consequently, the crowd is relatively rare on these timings. In addition, the volume of traffic is also low in the main road on these two timings as the heavy traffic flow normally happens from 8 am to 9 am. Therefore, the average LAeq on 9 am and 10 am are the lowest compared to other timings. After the shops are opened, the number of people increases gradually and thus, the average LAeq also increases during afternoon and reaches its peak value on 7 pm where this is the timing when heavy traffic flow happens in the main road. On 8 pm, peoples are leaving this zone and thus, the average LAeq decreases gradually. Zones 2 and 3 are located at commercial districts, so their average LAeq during weekend increase gradually with time
Fig. 6. Real view of the five data collection zones at Pingjiang Ancient Town. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5.
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H.M. Lee et al. / Applied Acoustics 160 (2020) 107126 Table 1 Score for perceptions of quietness and comfort level. Score
1
2
3
4
5
Quietness Comfort level
Very noisy Very comfortable
Not quiet Comfortable
Medium Medium
Relatively quiet Uncomfortable
Very quiet Very uncomfortable
Fig. 7. Age distribution of interviewees at (a) Guanqian area and (b) Pingjiang Ancient Town.
Fig. 8. Average LAeq measured at the six data collection zones at Guanqian area from 9 am to 8 pm over weekday and weekend. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5 (f) zone 6.
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Fig. 9. Average LAeq measured at the five data collection zones at Pingjiang Ancient Town from 9 am to 8 pm over weekday and weekend. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5.
(see Fig. 8(b) and (c)) as the number of people also increases gradually with time. However, during weekday, peoples are leaving after 7 pm, so the average LAeq at these two zones also decrease after 7 pm. Zone 4 is located inside a temple, visitors normally will lower down their voices when visiting the temple, so average LAeq at this zone during both weekday and weekend are the lowest compared to all other zones except zone 5 (see Fig. 8(d)). During weekend, number of visitor increases during afternoon, so peak average LAeq is observed on 2 pm. After that, visitors are leaving gradually and the average LAeq also decreases gradually. Zone 5 also located inside a temple, but it is located at the rear side of the temple, so its average LAeq during weekday and weekend are similar as shown in Fig. 8(e) as the number of visitor did not
increase during weekend. Zone 6 is located at the commercial center of Guanqian Street, it is very crowed and thus, this zone has the highest average LAeq for both weekday and weekend compared to all other zones. Fig. 9 shows the average LAeq measured at the five data collection zones at Pingjiang Ancient Town from 9 am to 8 pm over weekday and weekend. Similar to the results at Guanqian area, the average LAeq at Pingjiang Ancient Town during weekend is generally higher than that of weekday for all zones. Zone 1 is located at the highway near the entrance of the town. It can be observed from Fig. 9(a) that its average LAeq increases with the increasing of time for both weekday and weekend. This is because at this zone, the number of visitor of the town and the number of vehicle in the
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Fig. 10. Average LAeq measured at the six and five data collection zones at (a) Guanqian area and (b) Pingjiang Ancient Town, respectively, from 9 am to 8 pm over weekend.
Fig. 11. Proportions of the sound sources at (a) Guanqian area and (b) Pingjiang Ancient Town.
highway increase with the increasing of time even after 7 pm. Zones 2 and 3 are located at historical scenic spots. These two zones have lesser human activities in the morning and evening. Visitors normally appear in these two zones during afternoon and thus, the average LAeq at these zones reach their peak values during afternoon as shown in Fig. 9(b) and (c). Zone 4 is located at residential area, most of the residents go out from their homes for daily activities on 7 pm, so peak average LAeq also appears on 7 pm no matter weekday or weekend (see Fig. 9(d)). Zone 5 is located at a business district, many peoples come this zone for shopping from 10am to 7 pm. Some of the shops close after 7 pm, so numbers of people decrease after 7 pm and consequently, the average LAeq also decrease after 7 pm for both weekday and weekend as shown in Fig. 9(e). In order to have an overview about the changes of average LAeq among different zones within a same area, Fig. 10 is plotted to compare the average LAeq measured at all data collection zones at Guanqian area and Pingjiang Ancient Town. Only data over weekend are compared because the sound levels at these two area over weekend are higher than weekday and the trend differences between weekday and weekday are not very significant. At Guanqian area (see Fig. 10(a)), among these six zones, zone 6 is the most noisy place as it is located at the commercial center of Guanqian Street. The second noisy place is zone 1 as it is located near to a main traffic road. For all other zones, the differences of sound levels among them are very small in the morning. These differences keep increasing with time and become largest during evening time especially in between zones 2/3 and zones 4/5. This is because not much people would like to visit temple (zones 4 and 5) during evening time but commercial districts (zones 2 and 3)
normally still full of peoples during evening time. At Pingjiang Ancient Town (see Fig. 10(b)), zone 1 is the most noisy place followed by zone 5 as these two zones are located at the highway and business district, respectively. Among all other three zones, sound level at zone 4 (residential area) during 7 pm is highest where this is the timing when most of the residents go out from their homes to conduct daily activities. 3.2. Survey data 3.2.1. Proportions of the sound sources From the survey data, proportions of the sound sources at Guanqian area and Pingjiang Ancient Town are computed and are shown in Fig. 11. For more detailed analysis of sound sources at these two areas, further computations of sound source proportions for all zones are conducted and the results are shown in Figs. 12 and 13. It can be seen that sounds at Guanqian area (see Fig. 11 (a)) are mostly composed by daily living sound (53%) followed by natural sound (32%) and then by machinery sound (15%). Daily living sound has the highest proportion at Guanqian area because zones 2, 3 and 6 are mostly composed by daily living sound where their proportions are as high as 79%, 51% and 72%, respectively (see Fig. 12. Among six zones at Guangqian area, natural sound has the highest proportion at zones 4 and 5 which are about 53% and 57%, respectively, as shown in Fig. 12(d) and (e). Machinery sound has the lowest proportion at Guanqian area because among its six data collection zones, only sound in zone 1 is mostly composed by machinery sound (56%) (see Fig. 12(a)). While at all other zones, the highest proportion of this type of sound is only as low as 11% at zone 2 (see Fig. 12(b)). Different with the case of Guanqian area,
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Fig. 12. Proportions of the sound sources for the six data collection zones at Guanqian area. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5 (f) zone 6.
the sounds at Pingjiang Ancient Town are mostly composed by natural sound (45%) followed by daily living sound (33%) and then by machinery sound (22%) as shown in Fig. 11(b). Zones 3 and 4 at this area are mostly composed by natural sound which are about 72% and 55%, respectively, as shown in Fig. 13(c) and (d). For daily living sound, it has its highest proportion at zones 2 and 5 which are about 45% and 47%, respectively (see Fig. 13(b) and (e)). Similar with the case of Guanqian area, among five zones at Pingjiang Ancient Town, only zone 1 is mostly composed by machinery sound which is about 49% as shown in Fig. 13(a). 3.2.2. Score of perceptions for quietness and comfort level Table 2 shows the score of perceptions for quietness and comfort level at Guanqian area. It is found that zone 4 has the highest score of quietness which is about 4.1. This result is consistent with the objective data shown in Fig. 10(a) where zone 4 also has the minimum average LAeq among all six zones. Zone 5 obtains second highest score of quietness which is about 3.8 and this zone also obtains second lowest average LAeq among all six zones (see Fig. 10(a)). Similar phenomenons are observed for zones 3 and 2 where their subjective data are also consistent with objective data. However, this phenomenon does not hold true for zones 6 and 1
where zone 6 has the highest average LAeq while it does not has the lowest score of quietness. The order of comfort level from highest to lowest score for the six zones at Guanqian area is zones 4 ? 2 ? 3 ? 5 ? 6 ? 1. This order is almost the same with the order of quietness (zones 4 ? 5 ? 3 ? 2 ? 6 ? 1). The only difference is the switch of ranking for zones 5 and 2 compared with that of quietness. Consequently, for score of comfort level, only result at zones 4 is consistent with objective data shown in Fig. 10(a). It should be take note that the major sound source at zones 4 and 1 are natural and machinery sounds, respectively. Table 3 shows the score of perceptions for quietness and comfort level at Pingjiang ancient town. The order of quietness from highest to lowest score for the five zones at Pingjiang ancient town is zones 3 ? 2 ? 4 ? 5 ? 1. This order is consistent with the objective data shown in Fig. 10(b) where the order of the average LAeq from highest to lowest value is zones 1 ? 5 ? 4 ? 2 ? 3. For comfort level at Pingjiang ancient town, its order from highest to the lowest score is exactly same with that of quietness which is also zones 3 ? 2 ? 4 ? 5 ? 1. Same with the case at Guanqian area, major sound sources at zones 3 and 1 are natural and machinery sounds, respectively. Thus, it can be concluded here that natural sound make human feels more pleasant while machinery sound
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Fig. 13. Proportions of the sound sources for the five data collection zones at Pingjiang Ancient Town. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5.
Table 2 Score of perceptions (quietness and comfort level) at Guanqian area. Zone
1
2
3
4
5
6
Quietness Comfort level
1.3 2.8
2.5 3.0
3.6 3.2
4.1 3.6
3.8 3.3
2.3 3.1
Table 3 Score of perceptions (quietness and comfort level) at Pingjiang ancient town. Zone
1
2
3
4
5
Quietness Comfort level
1.8 2.7
3.6 4.1
3.8 4.2
3.4 3.8
2.6 3.6
Table 4 How gender ranks quietness and comfort level at Guanqian area.
Table 5 How gender ranks quietness and comfort level at Pingjiang Ancient Town.
Gender
Quietness
Comfort level
Gender
Quietness
Comfort level
Male Female
2.9 3.2
3.2 4.3
Male Female
3.8 3.8
4.0 3.8
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make human feels more uncomfortable. Lastly, how gender ranks quietness and comfort level at Guanqian area and Pingjiang Ancient Town are shown in Tables 4 and 5, respectively. At both areas, the scores given by female and male for quietness and comfort level are similar. Only slightly big difference exists between male and female for the score of comfort level at Guanqian area. It is found that the score of comfort level given by male is lower than that of female. This might be due to the reason where the major sound source at Guanqian area is daily living sound as male normally has lower tolerance towards daily living sound compared to female.
Appendix A Table 6, Fig. 14.
Table 6 Questionnaire for the survey at Guanqian area and Pingjiang Ancient Town. 1) Time:
4. Conclusions Soundscape studies were conducted at Guanqian area and Pingjiang Ancient Town (Suzhou, China). They are famous landscapes and commercial streets in Suzhou. The studies were conducted through sound level measurements and questionnaire surveys at the six and five zones at Guanqian area and Pingjiang Ancient Town, respectively. The sound levels that measured during weekend were generally higher than that during weekday at both areas and at all zones. The sound levels at these two areas were considered safe for visitors and residents because the maximum sound level measured from these areas was 80 dBA which was still under the permissible exposure limit (90 dBA) that recommended by OSHA. The order of sound levels from highest to lowest value at Guanqian area and Pingjiang Ancient Town were zones 6 ? 1 ? 3 ? 2 ? 5 ? 4 and 1 ? 5 ? 4 ? 2 ? 3, respectively. Negative linear relationship existed between the perceptions of quietness/ comfort level and sound level at Pingjiang Ancient Town. Although this exact negative linear relationship did not existed at Quanqian area, but zone 4 with lowest environment sound level still was selected by the interviewees as the most quiet and most comfortable zone. The major sound sources at Guanqian area and Pingjiang Ancient Town were daily living and natural sounds, respectively. It was found that gender did not had significant effect on the perceptions of quietness and comfort level. It was also found that natural sound could let human felt more pleasant while machinery sound let human felt uncomfortable. From the results of the present studies, it is suggests that natural sounds such as sounds from bird and insect can be used to mask out daily living and machinery sounds in an environment where peoples are always disturbed by unpleasant outdoor environment sound. Sounds from bird and insect can be introduced into a landscape by building some new parks surrounded the particular landscape. In addition, sound from water fountain is also an another good option for masking out unpleasant sound in a particular area. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgement This research was funded by National Natural Science Foundation of China [51908142] and Natural Science Foundation of Guangdong Province [2019A1515012223, 2018A030313878]. We would like to thank the Jilin University for providing administrative supports to this study.
2) Location:
3) Zone:
4) Gender:
Weekday morning Weekday afternoon Weeknight Weekend morning Weekend afternoon Weekend night Guanqian area Pingjiang Ancient Town 1 2 3 4 5 6 Male Female
5) Age:
Under age (10–17 years old) Youth (18–30 years old) Middle age (31–50 years old) Old age (Above 50 years old)
6) How do you feel about the environmental sound in this zone?
Very comfortable Comfortable Medium Uncomfortable Very uncomfortable
7) Please rate the quietness of the environmental sound in this zone:
Very quiet Relatively quiet Not noisy and not quiet Not quiet Very noisy
8) Please choose the sound that you can hear in this zone (multiselect):
People Talking Footsteps Hawking Knocking silver Other daily living sound Car, bus or van Bicycle or electric bicycle Airplane Road cleaning machine Lawn mowing Entertainment facilities Other machinery sound Bird Dog Insect Wind Rain Leaf rubbing Other natural sound
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Fig. 14. Gender ratio of interviewees at (a) Guanqian area and (b) Pingjiang Ancient Town.
References [1] Southworth M. The sonic environment of cities. Environ Behav 1969;1 (1):49–70. https://doi.org/10.1177/001391656900100104. [2] ISO. Acoustics-soundscape-part 1: Definition and conceptual framework, International Organization for Standardization (ISO. FDIS 12913). . [3] Kang J, Aletta F, Gjestland TT, Brown LA, Botteldooren D, Schulte-Fortkamp B, Lercher P, van Kamp I, Genuit K, Fiebig A, Coelho JLB, Maffei L, Lavia L. Ten questions on the soundscapes of the built environment. Build Environ 2016;108:284–94. https://doi.org/10.1016/j.buildenv.2016.08.011. [4] Kang J. From dba to soundscape indices: managing our sound environment. Front Eng Manage 2017;4(2):184. https://doi.org/10.15302/J-FEM-2017026. [5] Lebiedowska B. Acoustic background and transport noise in urbanised areas: a note on the relative classification of the city soundscape. Transp Res Part D: Transp Environ 2005;10(4):341–5. https://doi.org/10.1016/j.trd.2005.03.001. [6] De Coensel B, Botteldooren D. The rhythm of the urban soundscape. Noise Vib Worldwide 2007;38(9):11–7. https://doi.org/10.1260/095745607782689827. [7] Jeon JY, Lee PJ, You J, Kang J. Acoustical characteristics of water sounds for soundscape enhancement in urban open spaces. J Acoust Soc Am 2012;131 (3):2101–9. https://doi.org/10.1121/1.3681938. [8] Oldoni D, De Coensel B, Boes M, Rademaker M, De Baets B, Van Renterghem T, Botteldooren D. A computational model of auditory attention for use in soundscape research. J Acoust Soc Am 2013;134(1):852–61. https://doi.org/ 10.1121/1.4807798. [9] Andringa TC, Weber M, Payne SR, Krijnders J, Dixon MN, Linden RV, De Kock EGL, Lanser JJL. Positioning soundscape research and management. J Acoust Soc Am 2013;134(4):2739–47. https://doi.org/10.1121/1.4819248. [10] Payne SR. The production of a perceived restorativeness soundscape scale. Appl Acoust 2013;74(2):255–63. https://doi.org/10.1016/j. apacoust.2011.11.005. [11] Mackrill J, Jennings P, Cain R. Exploring positive hospital ward soundscape interventions. Appl Ergonomics 2014;45(6):1454–60. https://doi.org/10.1016/ j.apergo.2014.04.005.
[12] Liu J, Kang J, Behm H, Luo T. Landscape spatial pattern indices and soundscape perception in a multi-functional urban area, Germany. J Environ Eng Landscape Manage 2014;22(3):208–18. https://doi.org/10.3846/ 16486897.2014.911181. [13] Chew YR, Wu BS. A soundscape approach to analyze traffic noise in the city of Taipei, Taiwan. Comput Environ Urban Syst 2016;59:78–85. https://doi.org/ 10.1016/j.compenvurbsys.2016.05.002. [14] Martin SB, Matthews M-NR, Macdonnell JT, Broker K. Characteristics of seismic survey pulses and the ambient soundscape in baffin bay and melville bay, west greenland. J Acoust Soc Am 2017;142(6):3331–46. https://doi.org/10.1121/ 1.5014049. [15] Li C, Liu Y, Haklay M. Participatory soundscape sensing. Landscape Urban Plann 2018;173:64–9. https://doi.org/10.1016/j.landurbplan.2018.02.002. [16] Zhang X, Ba M, Kang J, Meng Q. Effect of soundscape dimensions on acoustic comfort in urban open public spaces. Appl Acoust 2018;133:73–81. https:// doi.org/10.1016/j.apacoust.2017.11.024. [17] Xu C, Kang J. Soundscape evaluation: Binaural or monaural? J Acoust Soc Am 2019;145(5):3208–17. https://doi.org/10.1121/1.5102164. [18] Hong X, Jiang Y, Wu S, Zhang L, Lan S. Study on evaluation model of soundscape in urban park based on radial basis function neural network: a case study of shiba park and kamogawa park, Japan, vol. 300, Ordos, China, 2019.https://doi.org/10.1088/1755-1315/300/3/032036.. [19] Lin W, Wu Y-M, Lin H, Huang K-L. Objective approaches on urban soundscape perception in night market pedestrian street, vol. 11593 LNCS, Orlando, FL, United states, 2019, pp. 416–424.. [20] WHO. Environmental noise guidelines for the european region, Tech. rep., World Health Organization Regional Office for Europe, Copenhagen, Denmark; 2018.. [21] Garg S, Lim KM, Lee HP. An averaging method for accurately calibrating smartphone microphones for environmental noise measurement. Appl Acoust 2019;143:222–8. https://doi.org/10.1016/j.apacoust.2018.08.013.
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Assessment of acoustical environment condition at urban landscape Hsiao Mun Lee a,⇑, Yi Liu c, Heow Pueh Lee b,c a Center for Research on Leading Technology of Special Equipment, School of Mechanical and Electric Engineering, Guangzhou University, 230 Wai Huan Xi Road, Guangzhou 510006, PR China b Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117575, Singapore c National University of Singapore (Suzhou) Research Institute, No. 377 Linquan Street, Suzhou Industrial Park, Suzhou, Jiangsu, China
a r t i c l e
i n f o
Article history: Received 7 August 2019 Received in revised form 9 October 2019 Accepted 30 October 2019
Keywords: Acoustical environment Urban landscape Smartphone
a b s t r a c t Acoustical environment conditions of two famous landscapes at Suzhou, China were investigated. The studies were conducted through sound level measurements and questionnaire surveys at different zones at Guanqian area and Pingjiang Ancient Town. Measurement data showed that the sound levels at these two areas were considered safe for human because the maximum sound level measured from these areas was 80 dBA which was still under the permissible exposure limit (90 dBA) that recommended by Occupational Safety and Health Administration (OSHA). Negative linear relationship was found to be existed between the perceptions of quietness/comfort level and sound level at Pingjiang Ancient Town. The major sound sources at Guanqian area and Pingjiang Ancient Town were daily living and natural sounds, respectively. It was found that gender did not had significant effect on the perceptions of quietness and comfort level. It was also found that natural sound could let human felt more pleasant while machinery sound let human felt uncomfortable. Ó 2019 Elsevier Ltd. All rights reserved.
1. Introduction For a long time, the research on noise pollution is focused on the concept of ”noise” and researchers tried to improve the acoustical environment by reducing the sound pressure level (SPL) through noise control. However, some studies pointed out that the reduction of SPL cannot improve perception of people toward noise effectively and many factors such as psychological condition can affect this perception. Thus, the scope of the conventional noise control method has been widen so that human’s perception toward noise is accredited as the focus center in the method. In 1960s, the idea of soundscape was first introduced in order to improve the life quality and health of human [1]. In 2014, the International Organization for Standardization (ISO) defined soundscape as the sound environment experienced and perceived by individual or group of people in a particular context [2]. Great attention only has been paid in the field of community noise and environmental acoustics by researchers about two decades ago although the concept of soundscape was introduced about 50 years ago [3,4]. Lebiedowska [5] analyzed the interaction between transport noise and background noise in urban space. They proposed five types of urban soundscape which ranging from very quiet area to ⇑ Corresponding author. E-mail address: [email protected] (H.M. Lee). https://doi.org/10.1016/j.apacoust.2019.107126 0003-682X/Ó 2019 Elsevier Ltd. All rights reserved.
very loud area. Coensel and Botteldooren [6] proposed an indicator to study the temporal structure of the urban soundscape by drawing on the analogy with music and self-organization. They found that the indicator followed more closely the original ideas behind urban soundscape research by using the analogy with music. Jeaon et al. [7] conducted laboratory experiments to investigate which water sound was appropriate for masking urban noise. Their experimental results revealed that preference scores for the urban soundscape were affected by the visual images of water features and acoustical characteristics of water sounds. Oldoni et al. [8] developed a numerical model to classify the sounds that were presented in the soundscape and simulated how a typical listener would switch attention over time between different sounds. Listening evaluations were conducted by Andringa et al. [9] to analyze the role of suboptimal soundscapes and sound annoyance on the lives of individuals. They concluded that a good soundscape or more generally a good sensescape, was at the same time conductive as well as pleasant for the adoption of healthy habits. Payne [10] designed a Perceived Restorativeness Soundscape Scale (PRSS) to access perception of a soundscape’s potential to provide psychological restoration. They claimed that the PRSS was able to differentiate between soundscapes from different urban parks. Listening evaluations were conducted by Mackrill et al. [11] with 24 participants who rated their cognitive (Interest and Understanding) and emotional (Relaxation) responses to a variety
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of hospital ward soundscape clips across three interventions (steady state, natural and written sound sources). They claimed that a repeated measured ANOVA revealed that the ’Relaxation’ response was significantly influenced by the intervention with natural sound producing a 10.1% more positive response. Soundscape data on specifically defined temporal and spatial scales were evaluated and observed by Liu et al. [12] in a multi-functional urban area in Rostock, Germany. Their results showed that urban soundscapes were characterised by artificial sounds (mechanical, human and traffic sounds) overwhelming the natural sounds (geophysical and biological sounds). Chew and Wu [13] conducted spatial-temporal analysis by the integration of sound amplitude, frequency and time to show how various types of traffic noise dominated urban landscape soundscape during different time periods. They found that taxis and cars were the dominant sources of noise in commercial and residential areas in the afternoon and evening. Martin et al. [14] conducted a seismic survey campaign involving four vessels in Baffin Bay, West Greenland. Their results showed that the soundscape of Baffin Bay was typical for open ocean environments and Melville Bay’s soundscape was dominated by glacial ice noise. Li et al. [15] analyzed the sound comfort level relationships with each class of sound sources, land use, subjective evaluation, sound harmoniousness, sound level, age and gender using shared data for over a year. They claimed that women were higher-quality data providers where they exhibited better performance than man and adults (19–40 years old) with respect to data integrity. Zhang et al. [16] studied the effects of relaxation, spatiality, communication and dynamics on acoustic comfort in urban open public spaces. They found that the perceived dominance of sound sources had a significant effect on relaxation, spatiality, communication and dynamics. Xu and Kang [17] explored the performance of monaural and binaoral recordings in soundscape evaluation. Monaural and binaural recordings were simultaneously made at twelves sites with different acoustic scenarios. They found that the two recording methods presented good agreement on most soundscape evaluation indicators included acoustic comfort, overall impression, pleasantness, loudness and eventfulness. Hong et al. [18] developed a objective and subjective transformation model of soundscape in urban park (Shiba Park and Kamogawa Park in Japan) based on radial basis function neural network. They found that the model had higher accuracy for subjective evaluation value where it was up to 91.23% for average prediction accuracy rate. Lin et al. [19] analyzed the sound environment at Feng Chia night market in Taiwan where this market had large number of visitors and was close to high density residential area. Their research outcomes could provide a reference for urban planning project as quieter environment is required by most of the community nowadays. From reported studies, it can be seen that in addition to noise level, many subjective factors also have strong effect on the quality of urban acoustical environment. With the expansion of the city and development of economy, urban environmental pollution has become more serious especially noise pollution. Long term noise exposure can lead to non-auditory and auditory effects on human health such as cognitive impairment in children, annoyance, cardiovascular disease, sleep disturbance and tinnitus [20]. Therefore, in order to obtain deeper insight into acoustical environment in urban area, this study will investigate the soundscapes at Guanqian area and Pingjiang Ancient Town. These two locations are located at Suzhou, China and they are famous landscapes and commercial streets in Suzhou. At first, the real-time noise levels at these locations were recorded using smartphone. After that, questionnaire survey was conducted to investigate the subjective perception of the respondents. It is expected that the outcome of the current studies can provide some noise control inputs to the urban planning project. Consequently, comfort level of residents or visi-
tors in the urban area with proper noise control plan could potentially be improved. 2. Methods 2.1. Sound sources and zone distributions at Guanqian area and Pingjiang Ancient Town The maps and pictures of Guanqian area and Pingjiang Ancient Town are shown in Figs. 1 and 2, respectively. These two areas are well-known commercial zones and historical sites in Suzhou with rich landscape compositions. The areas of Guanqian area and Pingjiang Ancient Town are large and thus, the soundscapes at these two places vary greatly among different regions. Through observation of the sound environment conditions and landscape characteristics at these two areas, these two areas were divided into different zones for the purpose of data collection in order to have more accurate and in-depth grasp towards acoustical environments of these two areas. In addition, from the on-site observation, the sound sources at these two areas were summarized and were classified into three categories where they were machinery, natural and living sounds. Machinery sound sources included sounds from car, bus, van, bicycle or electric bicycle, airplane, road cleaning machine, lawn mowing, entertainment facilities and so on. Natural sound sources included sounds from bird, god, insect, wind, rain, leaf rubbing, and so on. Living sound sources included sounds from footsteps, hawking, knocking silver and so on. Guanqian area was divided into six zones as shown in Fig. 3. Zone 1 was close to traffic road and it was quite crowded (see Fig. 4(a)). Its sound source mainly consisted of machinery and daily living sounds included traffic sound and voice of pedestrians. Zones 2 and 3 were commercial districts (see Fig. 4(b) and (c)), they basically consisted of daily living sound. Zones 4 and 5 were located in Xuanmiao Temple (see Fig. 4(d) and (e)). There were many tourists in these two zones and these two zones basically consisted of daily living and natural sounds. Zone 6 was located at the commercial center of Guanqian Street, so this zone was very crowded. Distinctive sound of Guanqian Street also existed in this zone - sound of knocking silver (see Fig. 4(f)). Pingjiang Ancient Town was divided into five zones as shown in Fig. 5. Zone 1 was close to traffic road (see Fig. 6)) and its sound source mainly consisted of machinery and daily living sounds. Zones 2, 3, 4 and 5 were located at residential or tourist attractions areas (see Fig. 6(b)(b) to (e)), they basically consisted of daily living and natural sounds. 2.2. Sound measurements One Samsung A9 smartphone and One ZTE AXON M smartphone were used in the present studies for sound measurements. Noise Explorer software was installed in these smartphones and was used for data acquisition. A specific averaging method was used to calibrate both smartphones [21]. After the calibration, by comparing sound level data measured by these two smartphones with the data measured by PCB Piezotronics class 1 type microphone (model 377B02), both smartphones were proved to be able to achieve accuracy up to ±0.7 dB. In the present studies, each zone had five data collection points. Equivalent sound pressure level (LAeq ) was recorded at each point and it is defined as:
LAeq ¼ 10 log
! n X SPLi ti 10ð 10 Þ ;
ð1Þ
i¼1
where t i is the fraction of the time period that the noise has a sound level of SPLi . The sampling time at each point was about 1 min. One sound sample was collected at each point during morning (9am and
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Fig. 1. (a) Map of Guanqian area (b) real view of Guanqian area.
Fig. 2. (a) Map of Pingjiang Ancient town (b) real view of Pingjiang Ancient Town.
2.3. Questionnaire survey
Fig. 3. Map of the six data collection zones at Guanqian area.
10am), afternoon (2 pm and 3 pm) and evening (7 pm and 8 pm). The data were collected twice a month (one weekday and one weekend) during October and November in 2018 and March and April in 2019. Therefore, the total sound recording time at Guanqian area and Pingjiang Ancient Town were about 24 and 20 h, respectively.
The questionnaire used in the present studies is shown in Table 6 in appendix. According to the needs of the research, the questionnaire included the interview time, venue of the interview, zone of the venue, gender and age of the interviewee, perceptions of comfort level and quietness of the interviewee towards the environmental sound and sound sources in the particular zone. The score for perceptions of quietness and comfort level is shown in Table 1. At each data collection point, one interviewee was asked to fill in the questionnaire on around 9.30 am, 2.30 pm and 7.30 pm. This is the timing where the first sound recording on that particular session was completed (9 am, 2 pm and 7 pm) and before the second sound recording was started (10 am, 3 pm and 8 pm). The questionnaires were distributed on the same day when sound recording was conducted which means twice a month (one weekday and one weekend) during October and November in 2018 and March and April in 2019. Therefore, about 720 and 600 interviewees were asked to fill in the questionnaires at Guanqian area and Pingjiang Ancient Town, respectively. There are 302 male and 418 female interviewees at Guanqian area and 318 male and 282 female interviewees at Pingjiang Ancient Town. The gender ratio of interviewees at these two areas is shown in Fig. 14 in the appendix. The age distribution of interviewees at these two areas is shown in Fig. 7. The order of the age from highest to lowest proportion for both areas are the same where they are youth!middle age!old age!under age (the proportions for under age and old
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Fig. 4. Real view of the six data collection zones at Guanqian area. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5 (f) zone 6.
3. Results and discussion 3.1. Sound data
Fig. 5. Map of the five data collection zones at Pingjiang Ancient Town.
age are the same at Guanqian area). These results are reasonable as youth people normally is the major group of people who working, visiting or living in commercial district and tourist attraction area.
Fig. 8 shows the average LAeq measured at the six data collection zones at Guanqian area from 9am to 8 pm over weekday and weekend. Average LAeq is obtained by averaging all LAeq measured at the particular zone and timing among four months time. Generally, the average LAeq at Guanqian area during weekend is higher than that of weekday for all zones. The trends of the average LAeq at zone 1 are similar for both weekday and weekend (see Fig. 8(a)). Zone 1 is located near a main traffic road, so no matter weekday and weekend, there are always a lot of vehicles and pedestrians passing by the main traffic road. Therefore, the average LAeq at zone 1 for both weekday and weekend are generally higher than all other zones except zone 6. In the morning (9 am and 10 am), most of the shops at zone 1 are not open yet, consequently, the crowd is relatively rare on these timings. In addition, the volume of traffic is also low in the main road on these two timings as the heavy traffic flow normally happens from 8 am to 9 am. Therefore, the average LAeq on 9 am and 10 am are the lowest compared to other timings. After the shops are opened, the number of people increases gradually and thus, the average LAeq also increases during afternoon and reaches its peak value on 7 pm where this is the timing when heavy traffic flow happens in the main road. On 8 pm, peoples are leaving this zone and thus, the average LAeq decreases gradually. Zones 2 and 3 are located at commercial districts, so their average LAeq during weekend increase gradually with time
Fig. 6. Real view of the five data collection zones at Pingjiang Ancient Town. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5.
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H.M. Lee et al. / Applied Acoustics 160 (2020) 107126 Table 1 Score for perceptions of quietness and comfort level. Score
1
2
3
4
5
Quietness Comfort level
Very noisy Very comfortable
Not quiet Comfortable
Medium Medium
Relatively quiet Uncomfortable
Very quiet Very uncomfortable
Fig. 7. Age distribution of interviewees at (a) Guanqian area and (b) Pingjiang Ancient Town.
Fig. 8. Average LAeq measured at the six data collection zones at Guanqian area from 9 am to 8 pm over weekday and weekend. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5 (f) zone 6.
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Fig. 9. Average LAeq measured at the five data collection zones at Pingjiang Ancient Town from 9 am to 8 pm over weekday and weekend. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5.
(see Fig. 8(b) and (c)) as the number of people also increases gradually with time. However, during weekday, peoples are leaving after 7 pm, so the average LAeq at these two zones also decrease after 7 pm. Zone 4 is located inside a temple, visitors normally will lower down their voices when visiting the temple, so average LAeq at this zone during both weekday and weekend are the lowest compared to all other zones except zone 5 (see Fig. 8(d)). During weekend, number of visitor increases during afternoon, so peak average LAeq is observed on 2 pm. After that, visitors are leaving gradually and the average LAeq also decreases gradually. Zone 5 also located inside a temple, but it is located at the rear side of the temple, so its average LAeq during weekday and weekend are similar as shown in Fig. 8(e) as the number of visitor did not
increase during weekend. Zone 6 is located at the commercial center of Guanqian Street, it is very crowed and thus, this zone has the highest average LAeq for both weekday and weekend compared to all other zones. Fig. 9 shows the average LAeq measured at the five data collection zones at Pingjiang Ancient Town from 9 am to 8 pm over weekday and weekend. Similar to the results at Guanqian area, the average LAeq at Pingjiang Ancient Town during weekend is generally higher than that of weekday for all zones. Zone 1 is located at the highway near the entrance of the town. It can be observed from Fig. 9(a) that its average LAeq increases with the increasing of time for both weekday and weekend. This is because at this zone, the number of visitor of the town and the number of vehicle in the
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Fig. 10. Average LAeq measured at the six and five data collection zones at (a) Guanqian area and (b) Pingjiang Ancient Town, respectively, from 9 am to 8 pm over weekend.
Fig. 11. Proportions of the sound sources at (a) Guanqian area and (b) Pingjiang Ancient Town.
highway increase with the increasing of time even after 7 pm. Zones 2 and 3 are located at historical scenic spots. These two zones have lesser human activities in the morning and evening. Visitors normally appear in these two zones during afternoon and thus, the average LAeq at these zones reach their peak values during afternoon as shown in Fig. 9(b) and (c). Zone 4 is located at residential area, most of the residents go out from their homes for daily activities on 7 pm, so peak average LAeq also appears on 7 pm no matter weekday or weekend (see Fig. 9(d)). Zone 5 is located at a business district, many peoples come this zone for shopping from 10am to 7 pm. Some of the shops close after 7 pm, so numbers of people decrease after 7 pm and consequently, the average LAeq also decrease after 7 pm for both weekday and weekend as shown in Fig. 9(e). In order to have an overview about the changes of average LAeq among different zones within a same area, Fig. 10 is plotted to compare the average LAeq measured at all data collection zones at Guanqian area and Pingjiang Ancient Town. Only data over weekend are compared because the sound levels at these two area over weekend are higher than weekday and the trend differences between weekday and weekday are not very significant. At Guanqian area (see Fig. 10(a)), among these six zones, zone 6 is the most noisy place as it is located at the commercial center of Guanqian Street. The second noisy place is zone 1 as it is located near to a main traffic road. For all other zones, the differences of sound levels among them are very small in the morning. These differences keep increasing with time and become largest during evening time especially in between zones 2/3 and zones 4/5. This is because not much people would like to visit temple (zones 4 and 5) during evening time but commercial districts (zones 2 and 3)
normally still full of peoples during evening time. At Pingjiang Ancient Town (see Fig. 10(b)), zone 1 is the most noisy place followed by zone 5 as these two zones are located at the highway and business district, respectively. Among all other three zones, sound level at zone 4 (residential area) during 7 pm is highest where this is the timing when most of the residents go out from their homes to conduct daily activities. 3.2. Survey data 3.2.1. Proportions of the sound sources From the survey data, proportions of the sound sources at Guanqian area and Pingjiang Ancient Town are computed and are shown in Fig. 11. For more detailed analysis of sound sources at these two areas, further computations of sound source proportions for all zones are conducted and the results are shown in Figs. 12 and 13. It can be seen that sounds at Guanqian area (see Fig. 11 (a)) are mostly composed by daily living sound (53%) followed by natural sound (32%) and then by machinery sound (15%). Daily living sound has the highest proportion at Guanqian area because zones 2, 3 and 6 are mostly composed by daily living sound where their proportions are as high as 79%, 51% and 72%, respectively (see Fig. 12. Among six zones at Guangqian area, natural sound has the highest proportion at zones 4 and 5 which are about 53% and 57%, respectively, as shown in Fig. 12(d) and (e). Machinery sound has the lowest proportion at Guanqian area because among its six data collection zones, only sound in zone 1 is mostly composed by machinery sound (56%) (see Fig. 12(a)). While at all other zones, the highest proportion of this type of sound is only as low as 11% at zone 2 (see Fig. 12(b)). Different with the case of Guanqian area,
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Fig. 12. Proportions of the sound sources for the six data collection zones at Guanqian area. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5 (f) zone 6.
the sounds at Pingjiang Ancient Town are mostly composed by natural sound (45%) followed by daily living sound (33%) and then by machinery sound (22%) as shown in Fig. 11(b). Zones 3 and 4 at this area are mostly composed by natural sound which are about 72% and 55%, respectively, as shown in Fig. 13(c) and (d). For daily living sound, it has its highest proportion at zones 2 and 5 which are about 45% and 47%, respectively (see Fig. 13(b) and (e)). Similar with the case of Guanqian area, among five zones at Pingjiang Ancient Town, only zone 1 is mostly composed by machinery sound which is about 49% as shown in Fig. 13(a). 3.2.2. Score of perceptions for quietness and comfort level Table 2 shows the score of perceptions for quietness and comfort level at Guanqian area. It is found that zone 4 has the highest score of quietness which is about 4.1. This result is consistent with the objective data shown in Fig. 10(a) where zone 4 also has the minimum average LAeq among all six zones. Zone 5 obtains second highest score of quietness which is about 3.8 and this zone also obtains second lowest average LAeq among all six zones (see Fig. 10(a)). Similar phenomenons are observed for zones 3 and 2 where their subjective data are also consistent with objective data. However, this phenomenon does not hold true for zones 6 and 1
where zone 6 has the highest average LAeq while it does not has the lowest score of quietness. The order of comfort level from highest to lowest score for the six zones at Guanqian area is zones 4 ? 2 ? 3 ? 5 ? 6 ? 1. This order is almost the same with the order of quietness (zones 4 ? 5 ? 3 ? 2 ? 6 ? 1). The only difference is the switch of ranking for zones 5 and 2 compared with that of quietness. Consequently, for score of comfort level, only result at zones 4 is consistent with objective data shown in Fig. 10(a). It should be take note that the major sound source at zones 4 and 1 are natural and machinery sounds, respectively. Table 3 shows the score of perceptions for quietness and comfort level at Pingjiang ancient town. The order of quietness from highest to lowest score for the five zones at Pingjiang ancient town is zones 3 ? 2 ? 4 ? 5 ? 1. This order is consistent with the objective data shown in Fig. 10(b) where the order of the average LAeq from highest to lowest value is zones 1 ? 5 ? 4 ? 2 ? 3. For comfort level at Pingjiang ancient town, its order from highest to the lowest score is exactly same with that of quietness which is also zones 3 ? 2 ? 4 ? 5 ? 1. Same with the case at Guanqian area, major sound sources at zones 3 and 1 are natural and machinery sounds, respectively. Thus, it can be concluded here that natural sound make human feels more pleasant while machinery sound
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Fig. 13. Proportions of the sound sources for the five data collection zones at Pingjiang Ancient Town. (a) Zone 1 (b) zone 2 (c) zone 3 (d) zone 4 (e) zone 5.
Table 2 Score of perceptions (quietness and comfort level) at Guanqian area. Zone
1
2
3
4
5
6
Quietness Comfort level
1.3 2.8
2.5 3.0
3.6 3.2
4.1 3.6
3.8 3.3
2.3 3.1
Table 3 Score of perceptions (quietness and comfort level) at Pingjiang ancient town. Zone
1
2
3
4
5
Quietness Comfort level
1.8 2.7
3.6 4.1
3.8 4.2
3.4 3.8
2.6 3.6
Table 4 How gender ranks quietness and comfort level at Guanqian area.
Table 5 How gender ranks quietness and comfort level at Pingjiang Ancient Town.
Gender
Quietness
Comfort level
Gender
Quietness
Comfort level
Male Female
2.9 3.2
3.2 4.3
Male Female
3.8 3.8
4.0 3.8
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make human feels more uncomfortable. Lastly, how gender ranks quietness and comfort level at Guanqian area and Pingjiang Ancient Town are shown in Tables 4 and 5, respectively. At both areas, the scores given by female and male for quietness and comfort level are similar. Only slightly big difference exists between male and female for the score of comfort level at Guanqian area. It is found that the score of comfort level given by male is lower than that of female. This might be due to the reason where the major sound source at Guanqian area is daily living sound as male normally has lower tolerance towards daily living sound compared to female.
Appendix A Table 6, Fig. 14.
Table 6 Questionnaire for the survey at Guanqian area and Pingjiang Ancient Town. 1) Time:
4. Conclusions Soundscape studies were conducted at Guanqian area and Pingjiang Ancient Town (Suzhou, China). They are famous landscapes and commercial streets in Suzhou. The studies were conducted through sound level measurements and questionnaire surveys at the six and five zones at Guanqian area and Pingjiang Ancient Town, respectively. The sound levels that measured during weekend were generally higher than that during weekday at both areas and at all zones. The sound levels at these two areas were considered safe for visitors and residents because the maximum sound level measured from these areas was 80 dBA which was still under the permissible exposure limit (90 dBA) that recommended by OSHA. The order of sound levels from highest to lowest value at Guanqian area and Pingjiang Ancient Town were zones 6 ? 1 ? 3 ? 2 ? 5 ? 4 and 1 ? 5 ? 4 ? 2 ? 3, respectively. Negative linear relationship existed between the perceptions of quietness/ comfort level and sound level at Pingjiang Ancient Town. Although this exact negative linear relationship did not existed at Quanqian area, but zone 4 with lowest environment sound level still was selected by the interviewees as the most quiet and most comfortable zone. The major sound sources at Guanqian area and Pingjiang Ancient Town were daily living and natural sounds, respectively. It was found that gender did not had significant effect on the perceptions of quietness and comfort level. It was also found that natural sound could let human felt more pleasant while machinery sound let human felt uncomfortable. From the results of the present studies, it is suggests that natural sounds such as sounds from bird and insect can be used to mask out daily living and machinery sounds in an environment where peoples are always disturbed by unpleasant outdoor environment sound. Sounds from bird and insect can be introduced into a landscape by building some new parks surrounded the particular landscape. In addition, sound from water fountain is also an another good option for masking out unpleasant sound in a particular area. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgement This research was funded by National Natural Science Foundation of China [51908142] and Natural Science Foundation of Guangdong Province [2019A1515012223, 2018A030313878]. We would like to thank the Jilin University for providing administrative supports to this study.
2) Location:
3) Zone:
4) Gender:
Weekday morning Weekday afternoon Weeknight Weekend morning Weekend afternoon Weekend night Guanqian area Pingjiang Ancient Town 1 2 3 4 5 6 Male Female
5) Age:
Under age (10–17 years old) Youth (18–30 years old) Middle age (31–50 years old) Old age (Above 50 years old)
6) How do you feel about the environmental sound in this zone?
Very comfortable Comfortable Medium Uncomfortable Very uncomfortable
7) Please rate the quietness of the environmental sound in this zone:
Very quiet Relatively quiet Not noisy and not quiet Not quiet Very noisy
8) Please choose the sound that you can hear in this zone (multiselect):
People Talking Footsteps Hawking Knocking silver Other daily living sound Car, bus or van Bicycle or electric bicycle Airplane Road cleaning machine Lawn mowing Entertainment facilities Other machinery sound Bird Dog Insect Wind Rain Leaf rubbing Other natural sound
H.M. Lee et al. / Applied Acoustics 160 (2020) 107126
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Fig. 14. Gender ratio of interviewees at (a) Guanqian area and (b) Pingjiang Ancient Town.
References [1] Southworth M. The sonic environment of cities. Environ Behav 1969;1 (1):49–70. https://doi.org/10.1177/001391656900100104. [2] ISO. Acoustics-soundscape-part 1: Definition and conceptual framework, International Organization for Standardization (ISO. FDIS 12913). . [3] Kang J, Aletta F, Gjestland TT, Brown LA, Botteldooren D, Schulte-Fortkamp B, Lercher P, van Kamp I, Genuit K, Fiebig A, Coelho JLB, Maffei L, Lavia L. Ten questions on the soundscapes of the built environment. Build Environ 2016;108:284–94. https://doi.org/10.1016/j.buildenv.2016.08.011. [4] Kang J. From dba to soundscape indices: managing our sound environment. Front Eng Manage 2017;4(2):184. https://doi.org/10.15302/J-FEM-2017026. [5] Lebiedowska B. Acoustic background and transport noise in urbanised areas: a note on the relative classification of the city soundscape. Transp Res Part D: Transp Environ 2005;10(4):341–5. https://doi.org/10.1016/j.trd.2005.03.001. [6] De Coensel B, Botteldooren D. The rhythm of the urban soundscape. Noise Vib Worldwide 2007;38(9):11–7. https://doi.org/10.1260/095745607782689827. [7] Jeon JY, Lee PJ, You J, Kang J. Acoustical characteristics of water sounds for soundscape enhancement in urban open spaces. J Acoust Soc Am 2012;131 (3):2101–9. https://doi.org/10.1121/1.3681938. [8] Oldoni D, De Coensel B, Boes M, Rademaker M, De Baets B, Van Renterghem T, Botteldooren D. A computational model of auditory attention for use in soundscape research. J Acoust Soc Am 2013;134(1):852–61. https://doi.org/ 10.1121/1.4807798. [9] Andringa TC, Weber M, Payne SR, Krijnders J, Dixon MN, Linden RV, De Kock EGL, Lanser JJL. Positioning soundscape research and management. J Acoust Soc Am 2013;134(4):2739–47. https://doi.org/10.1121/1.4819248. [10] Payne SR. The production of a perceived restorativeness soundscape scale. Appl Acoust 2013;74(2):255–63. https://doi.org/10.1016/j. apacoust.2011.11.005. [11] Mackrill J, Jennings P, Cain R. Exploring positive hospital ward soundscape interventions. Appl Ergonomics 2014;45(6):1454–60. https://doi.org/10.1016/ j.apergo.2014.04.005.
[12] Liu J, Kang J, Behm H, Luo T. Landscape spatial pattern indices and soundscape perception in a multi-functional urban area, Germany. J Environ Eng Landscape Manage 2014;22(3):208–18. https://doi.org/10.3846/ 16486897.2014.911181. [13] Chew YR, Wu BS. A soundscape approach to analyze traffic noise in the city of Taipei, Taiwan. Comput Environ Urban Syst 2016;59:78–85. https://doi.org/ 10.1016/j.compenvurbsys.2016.05.002. [14] Martin SB, Matthews M-NR, Macdonnell JT, Broker K. Characteristics of seismic survey pulses and the ambient soundscape in baffin bay and melville bay, west greenland. J Acoust Soc Am 2017;142(6):3331–46. https://doi.org/10.1121/ 1.5014049. [15] Li C, Liu Y, Haklay M. Participatory soundscape sensing. Landscape Urban Plann 2018;173:64–9. https://doi.org/10.1016/j.landurbplan.2018.02.002. [16] Zhang X, Ba M, Kang J, Meng Q. Effect of soundscape dimensions on acoustic comfort in urban open public spaces. Appl Acoust 2018;133:73–81. https:// doi.org/10.1016/j.apacoust.2017.11.024. [17] Xu C, Kang J. Soundscape evaluation: Binaural or monaural? J Acoust Soc Am 2019;145(5):3208–17. https://doi.org/10.1121/1.5102164. [18] Hong X, Jiang Y, Wu S, Zhang L, Lan S. Study on evaluation model of soundscape in urban park based on radial basis function neural network: a case study of shiba park and kamogawa park, Japan, vol. 300, Ordos, China, 2019.https://doi.org/10.1088/1755-1315/300/3/032036.. [19] Lin W, Wu Y-M, Lin H, Huang K-L. Objective approaches on urban soundscape perception in night market pedestrian street, vol. 11593 LNCS, Orlando, FL, United states, 2019, pp. 416–424.. [20] WHO. Environmental noise guidelines for the european region, Tech. rep., World Health Organization Regional Office for Europe, Copenhagen, Denmark; 2018.. [21] Garg S, Lim KM, Lee HP. An averaging method for accurately calibrating smartphone microphones for environmental noise measurement. Appl Acoust 2019;143:222–8. https://doi.org/10.1016/j.apacoust.2018.08.013.