Analysis of the relationships between environmental noise and urban morphology

Streets classification models by urban features for road traffic noise estimation

Road traffic is the primary source of environmental noise pollution in cities. This problem is also spreading due to inadequate urban expansion planning. Hence, integrating road traffic noise analysis into urban planning is necessary for reducing city noise in an effective, adaptable, and sustainable way. This study aims to develop a methodology that applies to any city for the stratification of urban roads by their functionality through only their urban features. It is intended to be a tool to cluster similar streets and, consequently, traffic noise to enable urban and transportation planners to support the reduction of people's noise exposure. Three multivariate ordered logistic regression statistical models (Model 1, 2, and 3) are presented that significantly stratify urban roads into five, four, and three categories, respectively. The developed models exhibit a McFadden pseudo-R2 between 0.5 and 0.6 (equivalent to R2 >0.8). The choice between Model 1 or 2 depends on the scale of the city. Model 1 is recommended for developed cities with an extensive road network, while Model 2 is most suitable in intermediate and growing cities. On the other hand, Model 3 could be applied at any city scale but focused on local management of transit routes and for designing acoustic sensor installations, urban soundwalks, and identification of quiet areas. Urban features related to road width and length, presence of transport infrastructure, and public transport routes are associated with increased traffic noise in all three models. These models prove useful for future action plans aimed at reducing noise through strategic urban planning.

Urban park qualities driving visitors mental well-being and wildlife conservation in a Neotropical megacity

Green infrastructure has been widely recognized for the benefits to human health and biodiversity conservation. However, knowledge of the qualities and requirements of such spaces and structures for the effective delivery of the range of ecosystem services expected is still limited, as well as the identification of trade-offs between services. In this study, we apply the One Health approach in the context of green spaces to investigate how urban park characteristics affect human mental health and wildlife support outcomes and identify synergies and trade-offs between these dimensions. Here we show that perceived restorativeness of park users varies significantly across sites and is mainly affected by safety and naturalness perceptions. In turn, these perceptions are driven by objective indicators of quality, such as maintenance of facilities and vegetation structure, and subjective estimations of biodiversity levels. The presence of water bodies benefited both mental health and wildlife. However, high tree canopy coverage provided greater restoration potential whereas a certain level of habitat heterogeneity was important to support a wider range of bird species requirements. To reconcile human and wildlife needs in green spaces, cities should strategically implement a heterogeneous green infrastructure network that considers trade-offs and maximizes synergies between these dimensions.

Seeking the Nexus Between Building Acoustics and Urban Form: A Systematic Review

Purpose of Review

Noise is penetrating urban life pervasively and is imperative for demonstrating the factors behind it regarding built environment, aka buildings and urban form. So, this review aims to provide a better understanding of the association between building acoustics and urban form characteristics.

Recent Findings

There is a growing attention for building acoustics, including materials and simulation aspects with various increasing urban form attributes, i.e., the built and natural environment and transportation.

Summary

Building acoustics is a key aspect of urban life and falls within the interface of various urban form characteristics. While these two main attributes are not sufficiently addressed, they may adversely affect individuals; thus, all the more reason to explore this nexus. This study has evaluated 67 peer-reviewed journal articles after systematically reviewing the triple resources in assessing building acoustics and urban form between 2016 and 2022. This review separates the indoor and outdoor categories within the simulation, theory, building materials, facade, and the built environment sub-categories. The study does not only review the overall scope of present studies but also direct future directions of their associations.

Sixty Years of Frequency-Domain Monaural Speech Enhancement: From Traditional to Deep Learning Methods

Frequency-domain monaural speech enhancement has been extensively studied for over 60 years, and a great number of methods have been proposed and applied to many devices. In the last decade, monaural speech enhancement has made tremendous progress with the advent and development of deep learning, and performance using such methods has been greatly improved relative to traditional methods. This survey paper first provides a comprehensive overview of traditional and deep-learning methods for monaural speech enhancement in the frequency domain. The fundamental assumptions of each approach are then summarized and analyzed to clarify their limitations and advantages. A comprehensive evaluation of some typical methods was conducted using the WSJ + Deep Noise Suppression (DNS) challenge and Voice Bank + DEMAND datasets to give an intuitive and unified comparison. The benefits of monaural speech enhancement methods using objective metrics relevant for normal-hearing and hearing-impaired listeners were evaluated. The objective test results showed that compression of the input features was important for simulated normal-hearing listeners but not for simulated hearing-impaired listeners. Potential future research and development topics in monaural speech enhancement are suggested.

Environmental Noise Exposure and Sleep Habits among Children in a Cohort from Northern Spain

Environmental noise is considered the second most serious environmental risk factor in Europe. However, little evidence exists regarding its impact on health and sleep in children, and the results are inconclusive. In this study, we aim to analyse the effect of environmental noise exposure on 11-year-old children's sleep habits. Data were collected from 377 participants in the INMA-Gipuzkoa (INfancia y Medio Ambiente) cohort project using both parent-reported and actigraphic sleep measures. The results revealed that 60% of children have a day-evening-night environmental noise exposure (L_den) of above 55 dB, which is defined as a "high noise level". No differences in noise exposure were observed between different socioeconomic groups. However, no effect of environmental noise was found on sleep variables. The paper highlights the importance of studying how environmental noise may affect children's sleep.

Noise levels associated with urban land use types in Kigali, Rwanda

Noise pollution poses a serious threat to public health and continues to grow in extent, frequency, and severity due to the rapid population growth and urbanization, and this is of particular concern in developing countries such as Rwanda. However, data on noise pollution levels, noise laws and regulations are, however, lacking in Rwanda. We assessed the effect of land-use type during a two-month period at nine sites: three commercial sites, three passenger-car parking sites, two road junction sites, and one reference site (Car-Free Zone) in Rwanda. We collected data on noise pollution during weekdays (Monday, Wednesday, and Friday) and Weekends (Saturday and Sunday) in the morning (7h00–10h00), around noon (11h00–14h00), and in the evening (15h00–18h00). The mean noise levels were higher during weekdays (60–80) A-weighted decibels (dB) (A)) than during weekends (50–70 dB (A)). We recorded the lowest noise level at Kigali car-free zone in the morning (34.4 dB (A)) and the highest noise level at Nyabugogo passenger-car parks in the evening (111.2dB (A)). Spatial variation of noise levels interpolated for Kigali City shows higher noise levels (hotspot) in the outskirts of Kigali, Remera and Kimironko. Noise levels recorded in Kigali exceeded the World Health Organization permissible daytime limits during both weekdays and weekends at all land-use types except the car-free zone site. Our results indicate that Kigali residents are exposed to high levels of noise, and urgent development of noise pollution monitoring programs and control measures in Rwanda is required.

Can biodiverse streetscapes mitigate the effects of noise and air pollution on human wellbeing?

Most of the global population are urban, with inhabitants exposed to raised levels of pollution. Pollutants negatively impact human wellbeing, and can alter the structure and diversity of ecosystems. Contrastingly, urban biodiversity can positively contribute to human wellbeing. We know little, however, about whether the negative impacts of pollution on wellbeing could be lessened for householders living on more biodiverse streets, as the complex interlinkages between pollution, biodiversity and wellbeing have rarely been examined. Here, we used structural equation modelling to simultaneously test whether biodiversity (actual and perceived) mediates the relationship between traffic-related pollution (noise, dB; nitrogen dioxide, NO₂) or air pollution (PM_2.5) and wellbeing (mental wellbeing, happiness). In summer 2019, we conducted questionnaires and biodiversity surveys, and collected noise and air pollution data, from households (n = 282) across the streetscapes of Leeds, UK. Biodiversity (actual or perceived) showed no mediating effects. However, increased flowering plant richness was positively associated with mental wellbeing. Traffic-related pollution negatively affected pollinator and flowering plant richness, but not wellbeing. This could be because householders are not exposed to high levels of noise or NO₂ because they do not maintain front gardens on noisier streets. There was no measurable effect of air pollution on biodiversity or wellbeing. These findings shed light on the complex mechanisms through which biodiversity could improve human wellbeing. Enhancing the diversity of plant species in streetscapes would have a positive effect on wellbeing, further emphasising the important role that biodiverse urban streetscapes play in improving the liveability of cities.

Remote work: Aircraft noise implications, prediction, and management in the built environment

The COVID-19 pandemic has greatly changed workplace management. Most workplaces have adopted the work-from-home policy to minimize the risk of community spread. Consequently, housing estates remain largely occupied during office hours. Since some housing estates are situated in the vicinity of an airport, noise pollution resulted from the takeoff and landing of aircraft is now more noticed by residents, causing annoyance. This problem would be most acute for those located directly under the flight path. Before the pandemic, such aircraft operations had lower effect on the residents because most of them were not at home but at workplaces. Evidently, it is timely that more emphasis should now be placed during urban planning to predict and minimize aircraft noise in the built environment. This article first defines the aircraft noise metrics commonly used to assess environmental impact. Preceded by an overview of how aircraft noise affects the built environment, this article reviews how various aircraft noise prediction models have been used in urban planning. Lastly, this article reviews how aircraft noise can be managed for better acoustic comfort of the residents. Anticipating the adoption of hybrid work arrangement moving forward, this article aims to provide urban planning professionals with an avenue to understand how aircraft noise can negatively affect the built environment, which, in turn, justify why prediction and management of aircraft noise should be emphasized from the outset of urban planning.

Do industrial parks generate intra-heat island effects in cities? New evidence, quantitative methods, and contributing factors from a spatiotemporal analysis of top steel plants in China

Industrial parks emit large amounts of anthropogenic heat and aggravate the urban heat island effect, which has become a severe environmental problem worldwide. Few studies explored if the warming effect generated by concentrated industrial facilities (i.e., steel plants in this study) produces an intra-heat island effect in urban built-up areas. Sufficient evidence of an industrial heat island (IHI) effect is lacking, and new quantitative methods are urgently needed to address these issues. Therefore, we proposed a new scheme to quantify the warming effect of large, heat-emitting urban objects versus complex surroundings, and the IHI effect was accordingly defined at a finer scale. This study separated the industrial park from other artificial lands and comprehensively estimated the IHI effects' spatiotemporal variation. The IHI intensities were measured based on varied natural and urbanized references, which provided new evidence for the existence of the IHI effect over space and seasons. The land surface temperature (LST) profiles delineated the downward trend in LST variation from inside to surroundings in the IHI cases on both spatial and temporal scales. The time-series analysis revealed that the IHI effects demonstrated more significant disparities regarding the LSTs between the industrial parks and their surrounding backgrounds during warm seasons than in cold seasons. And a more severe IHI effect was observed in spring and summer, and the weakest IHI intensity occurred in winter. Moreover, the IHI intensity is positively associated to the anthropogenic heat, indicating that the industrial activities contribute to the increased LSTs of the industrial park to a great extent. The rationale of the IHI effect can broaden insight for understanding how urban industrial heat sources influence the regional thermal environment, especially at a finer scale.

Community daytime noise pollution and socioeconomic differences in Chicago, IL

Environmental noise may affect hearing and a variety of non-auditory disease processes. There is some evidence that, like other environmental hazards, noise may be differentially distributed across communities based on socioeconomic status. We aimed to a) predict daytime noise pollution levels and b) assess disparities in daytime noise exposure in Chicago, Illinois. We measured 5-minute daytime noise levels (L_{eq, 5-min}) at 75 randomly selected sites in Chicago in March, 2019. Geographically-based variables thought to be associated with noise were obtained, and used to fit a noise land-use regression model to estimate the daytime environmental noise level at the centroid of the census blocks. Demographic and socioeconomic data were obtained from the City of Chicago for the 77 community areas, and associations with daytime noise levels were assessed using spatial autoregressive models. Mean sampled noise level (L_{eq, 5-min}) was 60.6 dBA. The adjusted R² and root mean square error of the noise land use regression model and the validation model were 0.60 and 4.67 dBA and 0.51 and 5.90 dBA, respectively. Nearly 75% of city blocks and 85% of city communities have predicted daytime noise level higher than 55 dBA. Of the socioeconomic variables explored, only community per capita income was associated with mean community predicted noise levels, and was highest for communities with incomes in the 2^nd quartile. Both the noise measurements and land-use regression modeling demonstrate that Chicago has levels of environmental noise likely contributing to the total burden of environmental stressors. Noise is not uniformly distributed across Chicago; it is associated with proximity to roads and public transportation, and is higher among communities with mid-to-low incomes per capita, which highlights how socially and economically disadvantaged communities may be disproportionately impacted by this environmental exposure.

Impact of urban expansion on vegetation: The case of China (2000-2018)

Extensive urbanization leads to the degradation of vegetation, which aggravates the deterioration of many ecological environments. However, the research on the impact of urbanization on vegetation change mainly focuses on cities. But the research on urban agglomeration is relatively scarce. The impact of urbanization on vegetation is explored by quantifying the changes in construction land and normalized difference vegetation index (NDVI) in China's urban agglomerations from 2000 to 2018. Results showed that in China, 72.73% of the regional NDVI presented a significant increasing trend, and 2.05% of the regional NDVI presented a significant downward trend. Vegetation degradation occurred in urban areas, but there was an improvement in vegetation in the urban centers of 2000. In urban agglomerations, the shift of the center of gravity of construction land can affect the direction of the transfer of NDVI cold spots or hot spots. Urbanization intensity in most urban agglomerations was negatively correlated with vegetation cover and showed a downward trend along the intensity gradient. However, NDVI in areas covered by complete vegetation showed an upward trend. Based on these findings, we suggest that vegetation protection and restoration should be strengthened, and effective urban landscape planning should be carried out to promote vegetation greening.

Mobile surveys and machine learning can improve urban noise mapping: Beyond A-weighted measurements of exposure

Urban noise pollution is a major environmental issue, second only to fine particulate matter in its impacts on physical and mental health. To identify who is affected and where to prioritise actions, noise maps derived from traffic flows and propagation algorithms are widely used. These may not reflect true levels of exposure because they fail to consider noise from all sources and may leave gaps where roads or traffic data are absent. We present an improved approach to overcome these limitations. Using walking surveys, we recorded 52,366 audio clips of 10 s each along 733 km of routes throughout the port city of Southampton. We extracted power levels in low (11 to 177 Hz), mid (177 Hz to 5.68 kHz), high (5.68 to 22.72 kHz) and A-weighted frequencies and then built machine-learning (ML) models to predict noise levels at 30 m resolution across the entire city, driven by urban form. Model performance (r²) ranged from 0.41 (low frequencies) to 0.61 (mid frequencies) with mean absolute errors of 4.05 to 4.75 dB. The main predictors of noise were related to modes of transport (road, air, rail and water) but for low frequencies, port activities were also important. When mapped to the city scale, A-weighted frequencies produced a similar spatial pattern to mid-frequencies, but did not capture the major sources of low frequency noise from the port or scattered hotspots of high frequencies. We question whether A-weighted noise mapping is adequate for health and wellbeing impact assessments. We conclude that mobile surveys combined with ML offer an alternative way to map noise from all sources and at fine resolution across entire cities that may more accurately reflect true exposures. Our approach is suitable for noise data gathered by citizen scientists, or from a network of sensors, as well as from structured surveys.

Temporal variability of noise pollution attenuation by vegetation in urban parks

The present study proposed a novel approach to investigate variability in the acoustic behavior of a number of deciduous tree-dominated narrow and long urban parks in Isfahan city, central Iran, between winter leaf fall and summer foliage. Noise levels (Lq30 in dB) were measured along two adjacent sides of the parks: along the road-adjacent side (Ro transect) and the relatively calmer river-adjacent side of the parks (Ri transect) during 4-17 January 2018 and 7-14 August 2019. Using Sentinel-2 images, two NDVI maps were also produced for these two periods to determine how changes in green biomass were associated with changes in noise levels. Using ANOVA, a significant difference was found in Ri-Lq30 and NDVI maps between winter and summer (p = 0.0), while the difference was insignificant for Ri-Lq30 (p = 0.1). We also developed two multiple linear regressions, one for each season, to assess the dependency of Ri-Lq30 to the intensity of vegetation and Ro-Lq30 and compare the two seasons by performing a t test analysis on the intercept and slope of the models, with results suggesting there is a significant difference in the association of green biomass and noise levels measured inside the parks between leaf fall and foliage time (p = 0.04). Our results indicated the temporal variability of park characteristics in providing calmer urban landscapes throughout the year.

Exploring the Effects of “Smart City” in the Inner-City Fabric of the Mediterranean Metropolis: Towards a Bio-Cultural Sonic Diversity?

“Smart city”, driven by digital technology is not only a technological but also a social, cultural and political project. A socially and culturally significant new urban ideal is born. This research paper is based on the narrative that the city appears as a palimpsest of interventions of all natures. History and shared memory, composition and superimposition, coherence and divergence are fundamental for its evolution. It is thus evident that ”Smart city” as a rather new urban ideal, but also as a disruptive innovation process, cannot be conceived nor implemented all at once; it must follow analogous processes of buildup and stratification. On the other hand, sounds are part of cities, of their sensory landscape, of their identity. They are one of the urban markers, along with the visual landscape. In this context, the paper focuses on the sound identity of the inner-city areas of the Mediterranean metropolis, posing the following research question: What are the transformations that “Smart city” can cause to the sound identity of a city? In dense urban fabric with high-rise buildings, high rates of exploitation, frequent transgressions of the legal construction and least free space in private plots, what can be the prospects of using “smart transport”, for enriching the city with positive soundscapes, thus improving its environmental quality? Following the metaphor of urban and acoustic palimpsest, we examine narratives of replacement of conventional cars with autonomous vehicles (AVs) and of private cars with car-pooling systems. The article concludes that spatialized intelligence can substantially and positively transform the sound identity of the Mediterranean metropolis and be the spearhead for an increase in bio-cultural sonic diversity. At least during the era when the city still appears as a palimpsest of interpositions, evoking the historic time.

Statistical Road-Traffic Noise Mapping Based on Elementary Urban Forms in Two Cities of South Korea

Statistical models that can generate a road-traffic noise map for a city or area where only elementary urban design factors are determined, and where no concrete urban morphology, including buildings and roads, is given, can provide basic but essential information for developing a quiet and sustainable city. Long-term cost-effective measures for a quiet urban area can be considered at early city planning stages by using the statistical road-traffic noise map. An artificial neural network (ANN) and an ordinary least squares (OLS) model were developed by utilizing data on urban form indicators, based on a 3D urban model and road-traffic noise levels from a normal noise map of city A (Gwangju). The developed ANN and OLS models were applied to city B (Cheongju), and the resultant statistical noise map of city B was compared to an existing normal road-traffic noise map of city B. The urban form indicators that showed multi-collinearity were excluded by the OLS model, and among the remaining urban forms, road-related urban form indicators such as traffic volume and road area density were found to be important variables to predict the road-traffic noise level and to design a quiet city. Comparisons of the statistical ANN and OLS noise maps with the normal noise map showed that the OLS model tends to under-estimate road-traffic noise levels, and the ANN model tends to over-estimate them.

Dynamic stiffness of road pavements: Construction characteristics-based model and influence on tire/road noise

Tire/pavement noise is produced by the interaction between a tire and the road surface. Complex noise generation mechanisms are involved in this process. Dynamic stiffness (or mechanical impedance) is considered as a related reduction/amplification mechanism. Despite its potential importance, in conventional hot bituminous mixtures this mechanism has little influence on tire/pavement noise. This is because the dynamic stiffness of tire treads is significantly lower than that of the hot bituminous mixes (conventional road surfaces). This paper presents a field assessment of the dynamic stiffness of five experimental sections with different characteristics: from the environmentally friendly mixes such as the Cold-In place-Recycled (CIR) pavement to the gap graded hot bituminous mixtures with crumb rubber (CR) from end of life tires (ELTs). The obtained dynamic stiffness spectra are fitted using a Boltzmann Sigmoid function. The relationships between the fitting coefficients and a few pavement construction characteristics are assessed in order to model the pavement dynamic stiffness as a function of these characteristics. In addition to dynamic stiffness, several surface characteristics such as the Close ProXimity (CPX) sound levels from the tire/pavement interaction, macrotexture in terms of the Mean Profile Depth (MPD), unevenness in terms of the International Roughness Index (IRI), and acoustic absorption are studied. According to our results, lower dynamic stiffness values are related to lower noise levels at high frequencies. No relationship was observed between the low dynamic stiffness values and noise attenuation at medium frequencies in this research work.

How does transit-oriented developments (TODs) deviate noise pollution of buildings? A comparative study of TODs and non-TODs

Scholarly debates on the unique features of transit-oriented developments (TODs) have surged over the last decade. Studies have examined their amenities and disamenities; however, lacking is exploring the relationship between TOD sound levels and buildings. Understanding this relationship has implications for communities and the urban form from environmental pollution aspects. This study explores the implications of sound on TOD buildings in the Dallas-Fort Worth metropolitan area by comparing them with non-TODs, specifically the relationship between buildings and street characteristics, and sound, as well as the potential effects of this relationship on TOD residents. Data include sound pressure levels through TOD buildings and streets compared with non-TOD buildings and streets. Using a two-level hierarchical linear model (HLM) help examine such characteristics at both micro and macro levels. The findings show that buildings located within TODs are exposed to higher sound levels with 1.4 dB(A) difference. The study provides insights into the relationship between sound, environmental pollution, building science, and transportation-featured elements of the built environment.

High-resolution urban land-cover mapping and landscape analysis of the 42 major cities in China using ZY-3 satellite images

Detailed and precise urban land-cover maps are crucial for urban-related studies. However, there are limited ways of mapping high-resolution urban land cover over large areas. In this paper, we propose an operational framework to map urban land cover on the basis of Ziyuan-3 satellite images. Based on this framework, we produced the first high-resolution (2 m) urban land-cover map (Hi-ULCM) covering the 42 major cities of China. The overall accuracy of the Hi-ULCM dataset is 88.55%, of which 14 cities have an overall accuracy of over 90%. Most of the producer's accuracies and user's accuracies of the land-cover classes exceed 85%. We further conducted a landscape pattern analysis in the 42 cities based on Hi-ULCM. In terms of the comparison between the 42 cities in China, we found that the difference in the land-cover composition of urban areas is related to the climatic characteristics and urbanization levels, e.g., cities with warm climates generally have higher proportions of green spaces. It is also interesting to find that cities with higher urbanization levels are more habitable, in general. From the landscape viewpoint, the geometric complexity of the landscape increases with the urbanization level. Compared with the existing medium-resolution land-cover/use datasets (at a 30-m resolution), Hi-ULCM represents a significant advance in accurately depicting the detailed land-cover footprint within the urban areas of China, and will be of great use for studies of urban ecosystems.

Using Smart City Tools to Evaluate the Effectiveness of a Low Emissions Zone in Spain: Madrid Central

Population concentration in cities brings new risks as an increase in pollution, which causes urban health problems. In order to address this problem, traffic reduction measures are being implemented as pedestrianization areas; they are the definition of Low Emissions Zones (LEZs). When the effectiveness of these types of measures is in doubt, smart city tools provide data that can be used to scientifically asses their impact. This article analyzes the situation of Madrid Central (Spain), a LEZ subject to controversy. We apply statistical and regression analyses to evaluate the effectiveness of this measure to reduce air pollution and outdoor noise. According to the results, this LEZ was able to significantly reduce NO 2 , PM 2.5 , and PM 10 concentration locally, having the same positive impact in the rest of the city. In terms of noise, this measure was able to mitigate background noise levels generated by road traffic.

Characteristics and evaluation of urban soundscapes worthy of preservation

Improvement of the sound environment is essential for improving the overall quality of the urban environment and for reflecting the characteristics of a city. Unfortunately, some soundscapes in cities are gradually being destroyed by the rapid development. Therefore, it would appear that the preservation of soundscapes is as necessary and crucial as noise control in cities. In this paper two field studies were carried out at two stages to explore the types and characteristics of urban soundscapes that should be preserved, based on the example of Tianjin, China. At stage one, 2504 respondents participated in social surveys to recommend the soundscapes worthy of preservation in the city. At stage two, a group soundscape walk with twenty-three participants was carried out to explore the characteristics of soundscapes worthy of preservation suggested by the respondents at the first stage. The following results were obtained: (1) regarding the attitude towards the urgency of soundscape preservation, 79% of the respondents thought it was urgent or very urgent, with an average score of 4.04 (five-point numeric scale was used and five meant very urgent). (2) The majority of soundscapes worthy of preservation were located in urban parks and historic districts with respective proportions of 66% and 20%. The top three sound source categories of these soundscapes were social/communal sounds (talking, bells, laughter, and sounds from human activities), animal sounds (birdsong and sounds from non-domesticated animals) and water sounds. (3) Relaxation, vibrancy, representativeness, strength, and richness were principal characteristics of the soundscapes worthy of preservation. (4) Based on their characteristics, these soundscapes were classified into five clusters using hierarchical cluster analysis (HCA). They were clusters of relaxing nature soundscape, vibrant nature soundscape, vibrant human activity soundscape, culture-related soundscape and traditional soundscape. The dominant characteristic of each cluster was driven by its sound mark rather than the dominant sound.

The Relationship between Sound and Amenities of Transit-Oriented Developments

Experts in diverse fields have investigated sound in cities throughout the United States. This research aims to examine sound levels and determine its contributors at the transit-oriented development (TOD) station and neighborhood levels by studying selected Dallas Area Rapid Transit (DART) light rail stations. A multilevel analysis was performed to model the likelihood of TOD stations and neighborhoods affecting sound levels, controlling for station amenities, socio-demographics and built environment characteristics. Sound measurements were sampled in three time intervals with 15 min sampling over weekdays and weekends at TOD and non-TOD stations by a type II SPL meter that was mounted on a small camera tripod at a height of 1.5 m, at a distance of 1.5 m from rails and curbs. The research team found that amenities, built environmental characteristics, and neighborhood features have significant implications on sound levels at both the TOD station and the neighborhood level, which affects quality of life (QoL). TOD stations that include more amenities have a greater level of significance on sound levels. Additionally, neighborhoods with a pervasive street grid configuration, public facilities, and built environment densities are significantly associated with a likelihood of high sound levels. Conversely, higher population densities and intersection densities decrease the likelihood of a high sound level environment. These patterns provide an arena for transportation, urban, and environmental planning and policymaking to generate transformative solutions and policies.

Traffic noise exposure of high-rise residential buildings in urban area

Noise pollution is a major factor of environmental complaints in many cities, which has significant impacts on human health. As a dominating source of environmental noise, the impact of road traffic noise is increasing. Residents living in high-rise buildings along the main road are severely affected by traffic noise. In order to assess the noise level of urban area along the main road in Guangzhou, three buildings were selected to conduct traffic noise measurements, and the questionnaire about traffic noise impact on human being was completed. Through the questionnaire, around 70% of participants consider the traffic noise has negative effect, and about 60% of participants consider the noise has moderate or much higher impact on physical comfort. Around 65% of participants consider the noise had moderately or much higher impact on their psychological comfort. By analyzing the measured data, all of the measured noise levels in three buildings exceed the recommended limit of 55 dB (A) in the daytime and 45 dB (A) in the night for residence, and the exceeded value can be up to 16 dB (A). By comparing the fitting curve of noise level transfer function on each floor relative to the reference floor, the quadratic polynomial was selected to plot the transfer function rather than cubic polynomial.

Temporal and spatial stratification for the estimation of nocturnal long-term noise levels

Noise pollution in cities is mainly caused by the vehicular traffic but, depending on the place under assessment, it could be affected by the land use. For noise assessment and strategic noise mapping, the night period equivalent level (L_night), which evaluates sleep disturbance, is one of the requirements of the European Directive 2002/49/EC to be presented for the equivalent time of one year. This research aims to find the influence of the land use in the weekdays stratification to improve the accuracy of the long-term noise level estimation for the night period. It is found that depending on the land use of the place under assessment, the weekdays temporal and spatial stratification could be affected by leisure activities. From a statistical analysis based on a clustering procedure of L_night samples in 19 points, it is observed that both, temporal and spatial stratification depend on the intensity of the surrounding leisure activity, and not on traffic. Following these stratification criteria, a sampling method is presented that reduces by 47% the number of days needed to estimate the annual levels with respect to random sampling.

Influence of Contextual Factors on Soundscape in Urban Open Spaces

The acoustic environment in urban open spaces has played a key role for users. This study analyzed the different effects of contextual factors, including shop openness, season, and commercial function, on the soundscape in two typical commercial pedestrian streets. The following observations were based on a series of measurements, including crowd measurements, acoustic environment measurements, and a questionnaire survey. First, the number of talkers in Central Avenue was greater than the number of talkers in Kuan Alley in cases with the same crowd density, while there was no significant difference in the sound pressure level. When the crowd density increased, acoustic comfort trended downward in Kuan Alley, while the value of acoustic comfort in Central Avenue took a parabolic shape. Second, there was no significant difference between the number of talkers in summer and the number of talkers in winter; however, when crowd density increased by 0.1 persons/m2, the level of sound pressure increased by 1.3 dBA in winter and 2.2 dBA in summer. Acoustic comfort took a parabolic shape that first increased and then decreased in both winter and summer. Regarding commercial function, as the crowd density increased, the number of talkers and the level of sound pressure both increased, while acoustic comfort decreased in three zones with different commercial functions. In addition, a cross-tab analysis was used to discuss the relationship between the number of talkers and the level of sound pressure, and it was found to be positive.