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Previous studies have reported associations of noise and air pollution with breast cancer (BC) risk, but the causality remains unclear. This study aimed to explore the effects of noise and air pollution on BC from a genetic perspective. Genetic association study. We began our investigation by visualizing the development trends in this field through bibliometric analysis. Subsequently, we conducted Mendelian randomization analyses to assess the effects of noise (daytime and evening) and air pollution (NO 2 , NO x , PM 2.5 , PM 2.5–10 , and PM 10) on BC. Genetic variants extracted from genome-wide association studies (GWAS) robustly associated with noise and air pollution were used as instrumental variables. The GWAS data for BC in European and East Asian populations were obtained from the Breast Cancer Association Consortium and the Biobank Japan, respectively. The effects of noise and air pollution on BC are receiving increasing attention. In the European population, genetically predicted exposure to NO 2 (OR: 1.9381; 95% CI: 1.2873–2.9180; P = 0.0015) and PM 10 (OR: 1.4187; 95% CI: 1.0880–1.8500; P = 0.0098) were positively associated with overall BC risk. Subtype analyses showed that PM 10 was significantly related to the risks of both ER+ (OR: 1.6165; 95% CI: 1.1778–2.2186; P = 0.0030) and ER− (OR: 1.6228; 95% CI: 1.0175–2.5881; P = 0.0421) BC. Additionally, NO 2 only increased the risk of ER+ BC (OR: 1.7429; 95% CI: 1.0679–2.8444; P = 0.0262), but not ER− BC. In East Asians, genetically predicted NO 2 was positively related to BC risk (OR: 1.1394; 95% CI: 1.0082–1.2877; P = 0.0366). Our study gave new evidence from a genetic standpoint underscoring that improving the environmental quality of residential areas is conducive to reducing BC risk. [ABSTRACT FROM AUTHOR]

In this study, it was aimed to determine the effect of sound and light pollution on Zebra mussel (Dreissena polymorpha) by biomarker and nutritional composition. For this purpose, an experimental design was carried out in laboratory conditions where the model was exposed to live sound, light, and combined sound + light parameters for 30 min every hour over 96 h. Changes in the biomarkers superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) activities, as well as glutathione (GSH) and thiobarbituric acid (TBARS) levels, were assessed in the model organism exposed to sound, light, and sound + light pollution. The changes in protein and fat amounts were determined. When the changes in biomarkers were examined statistically compared to the control, there was no significant decrease in SOD activity (p < 0.05), a significant increase in CAT activity in sound and sound+light, but a significant decrease in light (p < 0.05), no significant difference in GPx activity (p > 0.05). It was determined that there was a significant increase in GSH and TBARS levels in all three parameters. Significant changes were also observed in the proximate composition. As a result, exposure to sound, light and sound+light pollution caused an increase in oxidative damage and decreases in protein and lipid composition were detected. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate an acoustic environment based on spatial configurations. To achieve this objective, two types of data were utilized. First, the urban acoustic data was collected from 96 measurements based on equivalent continuous A-weighted sound pressure levels across three different urban areas in Cairo, Egypt, during weekends and at night. The data was plotted on a contour map in an effort to investigate their distribution in the urban area. Secondly, the data was collected using DepthMapX software, and in this way, spatial analysis was produced with diverse spatial attributes. Moreover, on-site observations of pedestrian and traffic rates were made, and land use distribution was observed. Statistical analysis was also conducted using the Statistical Package for Social Sciences (SPSS). Our statistical analysis showed that the value of sound pressure level (L Aeq) is greatly influenced by spatial attributes in highly accessible spatial configurations, with Normalized Angular Integration (NAIN) being the most accurate predictor of sound pressure level. Our findings also verified the existence of a high correlation between commercial and mixed land uses and (L Aeq). Additionally, this study revealed that the urban sound model can predict sound pressure level (L Aeq) in an urban setting. This dataset functions as a valuable resource for future research, urban designers, and policymakers who are addressing sustainable issues pertaining to soundscape, noise pollution, and urban planning. [ABSTRACT FROM AUTHOR]

The growing severity of urban noise pollution poses a threat to the physical and mental health of residents, prompting the need for the development of effective sound-absorbing materials. Herein, we present a versatile method to fabricate ultralight and flexible graphene-based aerogels by introducing one-dimensional carbon fibers as reinforcements. These carbon nanofiber-reinforced graphene aerogels (CNF/GAs) were obtained by the carbonization of freeze-casted bacterial cellulose/graphene oxide (BC/GO). Our CNF/GAs possess a low apparent density (∼3.05 mg cm−3) and exhibit broad-band sound absorption performance with a superior noise reduction coefficient (NRC) as high as 0.65 at a thickness of 30 mm. Meanwhile, their excellent elasticity endows the CNF/GAs with strain-sensing capability, enhancing their capacity for detecting deformations when utilized as sound absorbers in engineering applications. Additionally, the highly porous structure makes the CNF/GAs excellent thermal insulators, with a thermal conductivity as low as 0.011 W m−1 K−1, further expanding their environmental reliability. Therefore, our approach develops CNF/GAs with excellent broad-band sound absorption performance and mechanical-environmental reliability, showing significant practical potential. [Display omitted] [ABSTRACT FROM AUTHOR]

Environmental stresses are increasingly recognized as significant risk factors for adverse health outcomes. In particular, various forms of pollution and climate change are playing a growing role in promoting noncommunicable diseases, especially cardiovascular disease. Given recent trends, global warming and air pollution are now associated with substantial cardiovascular morbidity and mortality. As a vicious cycle, global warming increases the occurrence, size, and severity of wildfires, which are significant sources of airborne particulate matter. Exposure to wildfire smoke is associated with cardiovascular disease, and these effects are underpinned by mechanisms that include oxidative stress, inflammation, impaired cardiac function, and proatherosclerotic effects in the circulation. In the first part of a 2-part series on pollution and cardiovascular disease, this review provides an overview of the impact of global warming and air pollution, and because of recent events and emerging trends specific attention is paid to air pollution caused by wildfires. [Display omitted] • Global warming and air pollution are associated with increased cardiovascular morbidity and mortality. • Global warming is also increasing the occurrence of wildfires, which further drives air pollution and promotes cardiovascular disease through mechanisms that involve oxidative stress, inflammation, atherogenic effects, and impaired cardiac function. • These issues underscore the urgent need to address global warming and air pollution. [ABSTRACT FROM AUTHOR]

Various forms of pollution carry a substantial burden with respect to increasing the risk of causing and exacerbating noncommunicable diseases, especially cardiovascular disease. The first part of this 2-part series on pollution and cardiovascular disease provided an overview of the impact of global warming and air pollution. This second paper provides an overview of the impact of water, soil, noise, and light pollution on the cardiovascular system. This review discusses the biological mechanisms underlying these effects and potential environmental biometrics of exposure. What is clear from both these pollution papers is that significant efforts and redoubled urgency are needed to reduce the sources of pollution in our environment, to incorporate environmental risk factors into medical education, to provide resources for research, and, ultimately, to protect those who are particularly vulnerable and susceptible. [Display omitted] • Increasing evidence suggests that water, soil, noise, and light pollution increase cardiovascular morbidity and mortality. • The mechanisms linking these sources of pollution to cardiovascular disease are diverse, making mitigation efforts challenging, but evolving methods to track these sources of pollution may point to new strategies. • Collectively, these data underscore the urgent need to address pollution in all its forms at a global level. [ABSTRACT FROM AUTHOR]

The ongoing expansion of e-commerce has exacerbated the costs and inefficiencies of last-mile delivery. The growing demand for goods and services is concentrated in cities, which apply increasing constraints to reduce urban externalities. The paper aims to contribute to the development of a bottom-up approach where all stakeholders are involved in the design of efficient strategies for e-commerce last-mile delivery through the understanding of their priorities and perspectives. It applies a multi-stakeholder approach to evaluate the feasibility, strengths, and weaknesses of different policy measures to enhance e-commerce distribution. To this aim, two subsequent surveys were launched online. The first one was addressed to 25 experts, while 202 respondents from different European cities fulfilled the second survey. According to the results, increasing the number of parcel lockers in the city center would receive more support among stakeholders. Members of the public administration and citizens agree on prioritizing environmental aspects for implementing strategic solutions for LMD. On the other hand, consumers argue that economic criteria should be prioritized. In general, the results suggest that no single solution fulfils or satisfies all stakeholders' objectives. However, all stakeholders express their consent to prioritize city liveability and they consider noise pollution as a secondary issue. In line with the outputs of the research, including multi-stakeholder perspectives from the early stage it is crucial in the planning of LMD policy measures in city centers. Governments and actors involved in LMD should select suitable policy measures for a comprehensive strategy to address urban sustainability targets. • On-line Multi-stakeholder evaluation that expands its applicability. • The strengths and weaknesses of different policy actions are evaluated. • Low-cost method to include multiple stakeholders for efficient LMD planning. • Stakeholders consider parcel lockers as a suitable policy measure for urban deliveries. • City liveability is a common priority for all stakeholders. [ABSTRACT FROM AUTHOR]

A major public health challenge facing local administrations is reducing the preventable burden of non-communicable diseases making cities more resilient against environmental threats. The objective of this work was to conduct a synthesis of scientific evidence relating to the local context and implement a translational process to support the Department of the Environment in order to improve integration with concurrent policy sectors to urban health and sustainability goals. The first phase reviewed the studies on the association between environmental risk factors and human health and on the contamination levels of the environmental matrices; the second phase synthesised the data in key messages according to the concerns formulated with the collaboration of the Environmental Department. A total of 31 studies were assessed: 21 investigated environmental risk factors, and 9 measured the presence of pollutants in the environmental matrices. The findings identified air and noise pollution as the most important threats associated with respiratory and cardiovascular diseases, together with significant contamination levels of the urban environment from microplastics and hydrocarbons. Based on the review findings, a layman's report for the City Council and the citizens, explicitly addressing emerging issues, was made publicly accessible. A lack of specific, updated and exchangeable data for city health profiling in a deteriorated environmental context represented the main barrier to a resilient community. The suggested recommendation for the local administration was to adopt an environmental policy integration framework to strengthen the monitoring of the impact on citizens' health. • Systematic review in environmental health was promoted to improve local decision-making. • Air and noise pollution were identified as the most important environmental risk factors in Pisa. • Collaboration between researchers and policymakers leveraged the adoption of an EPI framework. • Scientific evidence drove the sustainable transition in urban governance. • Strategic environmental action should be based on citizen health-related indicators. [ABSTRACT FROM AUTHOR]

Sound vibrations caused by chewing herbivores are used by plants as a general cue to activate their defense machinery, prompting the suggestion that other ecological sound cues exist (e.g., in mutualistic plant–animal interactions). Similar to animals, plant species may operate within a set frequency and sound intensity range. Sound frequencies and intensities outside this range may potentially have negative effects on plants. Sound produced by humans (i.e., highway or industrial noise) can prevent plants from perceiving important environmental information. Noise pollution could therefore be a factor that should be taken into account both in ecological and agronomic settings. Some data suggest involuntary sound-based plant–plant communication, but a deliberate sound production and sound-based communication mechanism may also exist. In addition to positive effects on plant growth and resilience, sound alerts plants of potential danger and aids in defense. Sound guides plants towards essential resources, like water, through phonotropic root growth. Sound also facilitates mutualistic interactions such as buzz pollination. Molecularly, sound induces Ca2+ signatures, K+ fluxes, and an increase in reactive oxygen species (ROS) levels in a mechanosensitive ion channel-dependent fashion. We review the two major open questions in the field of plant acoustics: (i) what is the ecological relevance of sound in plant life, and (ii) how is sound sensed and transduced to evoke a morphophysiological response? We highlight the clear need to combine the ecological and molecular perspectives for a more holistic approach to better understand plant behavior. [ABSTRACT FROM AUTHOR]

The demand for transit is linked to a country's economic and population growth. As per the Ministry of Road Transport and Highways (MORTH), from 2009 to 2019, India witnessed an average growth rate of 9.9% per annum in registered vehicles. Even though the vehicle ownership is often viewed as a symbol of economic prosperity, the associated negative externalities (congestion, air pollution, road crashes, noise pollution, etc.) are substantial. To counter this, carpooling has been proposed as a solution globally. However, there is a paucity of literature for analysing the difference in travel characteristics of car-poolers among other private vehicle users. The present study aims to bridge this gap by comparing the demographic and travel characteristics of existing car-poolers with two-wheelers and single-occupant car users in Gurugram in the national capital region of India. Using an unsupervised machine learning clustering method (two-step cluster), the findings of the present study indicate that the profile of single-occupant car (SOC) users and car-poolers are highly distinguished from two-wheeler users. However, car-poolers have similar characteristics to single-occupant car users, except for travel cost, income level, and gender, suggesting that SOC users are potential car-poolers. A comparative study of this kind would help city planners and policymakers identify prospective car-poolers, and formulate policies to encourage SOC users to adopt carpooling and promote urban transportation sustainability. • The present study intends to compare the demographic profile and travel characteristics of carpoolers with other private vehicle users. • Using a Compared to two-wheeler users, single occupancy car (SOC) users are more likely to switch to carpooling. • Carpoolers have almost the same characteristics as single-occupant car users, except for travel costs, income levels. [ABSTRACT FROM AUTHOR]

While previous studies have pointed to their economic significance, terminal operations are frequently ignored in transport appraisal and policy analysis. This paper develops a generic model framework for estimating noise emissions from container terminal operations to derive key metrics for port policy analysis. A novel microeconomic production model that accommodates basic acoustics is proposed. Based thereon, abatement costs are derived using optimization and marginal external costs and efficiency scores are estimated using panel data frontier estimation. The virtues of the modeling approach are illustrated using noise meter readouts combined with port activity and meteorological data from the port of Oslo, Norway. • Fills research gap regarding marginal external noise costs of terminal operations. • First treatment of non-material pollutants in environmental production analysis. • Development of a generic production analysis framework for noise pollution. • Empirical analysis of container handling within the port of Oslo, Norway. • Estimation of marginal external and abatement costs and environmental efficiency. [ABSTRACT FROM AUTHOR]

• A moving model system of the HST-noise barrier is established. • Fully- and semi-enclosed city-oriented noise barriers are compared. • The temporal and spatial characteristics of the aerodynamic pressure are compared. • The dominant frequency of the train-induced aerodynamic pressure is investigated. Two types of city-oriented noise barriers, i.e., fully-enclosed noise barrier and bilateral inverted l -shaped semi-enclosed noise barrier, have been gradually adopted in city centres along high-speed railways to reduce noise pollution. The aerodynamic impacts of high-speed trains present a threat to the long-term durability of the city-oriented noise barriers. To promote the usage and increase the sustainability of city-oriented noise barriers, a moving-model experiment system with city-oriented noise barriers and HST with a scale ratio of 1:16.8 is established. The train type is CRH380A and the train speed is up to 350 km/h. A systematic comparative study on the aerodynamic performance of the two types of city-oriented noise barriers is conducted. The similarities and differences of transient pressure time–histories, spatial distribution of pressure peaks and spectral characteristics of aerodynamic pressure acting on the two types of noise barriers are compared and discussed. Moreover, the influence of train speed on the characteristics of the train-induced aerodynamic pressure is also investigated. The results show that the pressure fluctuation of the two types of noise barriers is caused by different reasons. Compared with the fully-enclosed noise barrier, the transient pressure of the semi-enclosed noise barrier is more sensitive to train speeds. The research results may provide a reference for the engineering design of city-oriented noise barriers on high-speed railways. [ABSTRACT FROM AUTHOR]

Anthropogenic noise pollution has detrimental effects on wildlife, but its impacts on diseases are largely unknown. We provide a conceptual overview on how noise can affect wildlife diseases. Noise may change the probability of host exposure to parasites through changes in host behaviour and distribution. Additionally, host-seeking behaviour of parasites can be disrupted by noise. Noise-induced stress often induces immunosuppression which can increase host susceptibility to infection. Similarly, the impacts of noise on parasites could reduce their infectivity. It is likely that there are synergistic and antagonistic effects between noise and disease impacts on host mortality, development, and reproduction. Our review of the literature suggests that there is a high potential for noise effects on wildlife diseases. It is important to determine the spread and occurrence of these effects on wildlife health. There is a global rise in anthropogenic noise and a growing awareness of its negative effects on wildlife, but to date the consequences for wildlife diseases have received little attention. In this paper, we discuss how anthropogenic noise can affect the occurrence and severity of infectious wildlife diseases. We argue that there is potential for noise impacts at three main stages of pathogen transmission and disease development: (i) the probability of preinfection exposure, (ii) infection upon exposure, and (iii) severity of postinfection consequences. We identify potential repercussions of noise pollution effects for wildlife populations and call for intensifying research efforts. We provide an overview of knowledge gaps and outline avenues for future studies into noise impacts on wildlife diseases. [ABSTRACT FROM AUTHOR]

Freight transportation is one of the largest contributors to the transportation sector's greenhouse gases (GHG) and noise pollution. The adverse effects of the industry are not distributed equally due to large spatial disparities, with minority and low-income populations more prone to live near freight-related facilities and truck routes. However, equity analysis focusing on freight transport is limited since empirical analysis requires costly data collection processes, and analysis in large-scale areas is challenging. The principal objective of this study is to conduct an equity analysis of the impact of freight-related trips in the Atlanta-Chattanooga-Knoxville region using a large-scale agent-based simulation framework. The main results show that low-income (less than $52k) and more heavily non-white population neighbourhoods are disadvantaged neighbourhoods in terms of noise and GHG emissions. The results and methods presented in this paper can be used to provide tools to develop transportation equity and social justice analysis in large networks and can be used to develop policies and regulations to reduce the impact of freight transportation on disadvantaged populations. [ABSTRACT FROM AUTHOR]

• Urban noise impacts mental well-being, with hyperacusis showing auditory effects. • PLS-SEM and audiometry revealed the critical impacts of noise on teachers' well-being. • Poor classroom acoustics and physiological strain affect teachers' mental well-being. • Teachers do face mild to moderately severe hearing loss from chronic noise exposure. • Noise exposure among teachers may affect their teaching efficiency and students' learning. Urban noise pollution significantly impacts public health, particularly affecting those in constant exposure, such as schoolteachers in urban areas. This study addresses the critical gap in understanding how persistent traffic noise impacts teachers' auditory and mental health, a key concern given their essential role in educational outcomes. The necessity of this research is underscored by the potential for noise-induced disturbances to impair teaching effectiveness and teachers' quality of life. The research question investigates the specific auditory and mental health outcomes for teachers working in noise-polluted environments. The study quantitatively measures hearing acuity and assesses mental well-being among teachers in five urban schools adjacent to high-traffic areas using audiometric assessments and a socio-acoustic questionnaire. Findings indicate a varied degree of noise-induced hearing loss (NIHL), with 36% of the participants exhibiting mild while 8% showing moderate hearing loss. The obtained value of hearing handicap ranges from 2.1 to 14.4%. However, these results for hearing handicaps were found to be less significant, indicating the non-considerable impact of classroom noise on the auditory health of teachers. Furthermore, through exploratory factor analysis (EFA) and principal component analysis (PCA), five critical factors impacting teachers' well-being were identified: Physiological Impact, Acoustics, Ambient Environment, Social Awareness, and Mental Well-being. Subsequent analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM) revealed that physiological impact and classroom acoustics, with path coefficients of 0.45 and 0.28, respectively, exerted a substantial and decisive influence on the mental well-being of schoolteachers, highlighting the critical role of environmental factors in shaping their psychological health. These insights underscore the pressing need for immediate interventions in school design and urban planning to effectively reduce noise pollution and protect the well-being of teachers. [ABSTRACT FROM AUTHOR]

• Loudness of low-frequency tonal noises were evaluated using an adjustment method. • The increase in loudness was greater for the low-frequency dominant sound stimuli. • A-weighted sound level may not match well with psychological loudness. • The loudness levels described in ISO 532-1 and 532-2 showed better correspondence with subjective loudness. Recently in Japan, noise from wind turbines and domestic heat sources have caused an increase in noise annoyance due to their low-frequency tonal components. The purpose of this study is to investigate the effects of tonal components on the loudness of environmental noise. An auditory test was conducted to evaluate the loudness of the tonal noise using an adjustment method. The stimuli were composed of a broadband noise and a low-frequency tonal component. For the tonal noises, a pure tone was added to the noise. The frequency of the tone was either 40, 50, 100, or 200 Hz. The tonal audibility was either 0, 5, or 15 dB. Loudness was evaluated using the A-weighted sound pressure level (L A) and the loudness levels according to the Zwicker loudness model and the Moore and Glasberg loudness model. The results show that the increase in loudness depends on the spectrum of the background noise and tonal frequency. When tone was added to low-frequency dominant noise, the L A may not fit the psychological loudness of the stimuli used in our experiment. [ABSTRACT FROM AUTHOR]

Anthropogenic noise is a global pollutant that negatively affects a wide range of wildlife, both on land and in water. It has long been recognized that there are marked variations in animals' sensitivity to noise disturbance across individuals and species and behavioral contexts for the same individuals. For biodiversity conservation and management, it is important to understand the underlying mechanisms for the subject- and context-dependent responses of wildlife to human disturbances. Here we used meta-analysis and statistical models to understand the biological and ecological traits that may explain the differential responses of bats to anthropogenic noise. Bats, the second-largest order of mammals, play indispensable ecological roles but face various human threats. The literature survey revealed that only 33 studies had investigated the effects of anthropogenic noise on 60 bat species, representing approximately 4 % of the total bat species and being largely (92 %) restrained to the families Vespertilionidae and Molossidae. The statistical analyses revealed that transportation and urban noise were the more disturbing to bats. Bat species that forage in narrow and edge spaces were more sensitive to anthropogenic noise than those that forage in open spaces. Bat species using longer echolocation calls were more sensitive to noise disturbance. Furthermore, compared to orienting and vocalizing bats, foraging bats were more sensitive to noise disturbance. These data indicated that anthropogenic noise, particularly traffic noise, needs to be carefully managed for forests and other types of vegetation used by foraging bats. • Bats are under-represented mammals for which anthropogenic noise effects have been examined. • Bats are generally sensitive to low-frequency anthropogenic noise disturbance, despite their reliance on ultrasonic sounds. • Habitat preference helps to explain the varied effects of anthropogenic noise on bats. • Bats that use forests and other types of vegetation as habitats should be prioritized for managing the impacts of anthropogenic noise. [ABSTRACT FROM AUTHOR]

Recursive three-step filters are often used for state estimation of systems with unknown input direct feedthrough, that is, systems where the unknown input simultaneously affect the state equation and measurement equation. However, when the system is disturbed by non-Gaussian noise, especially heavy-tailed impulsive noise, the performance of such recursive three-step filters will deteriorate. This paper proposes a maximum correntropy recursive three-step filter that can effectively handle non-Gaussian measurement noise pollution. The derivation of this filter is based on the traditional recursive three-step filter and utilizes a maximum correntropy criterion and a fixed-point iterative algorithm to simultaneously estimate the unknown input and state. It is shown that when the kernel bandwidths approach infinity, the derived maximum correntropy recursive three-step filter will degenerate into the traditional recursive three-step filter. Finally, the effectiveness and reliability of the proposed algorithm are demonstrated through simulation experiments. • Based on RTSF, the MCRTSF is a parallel version of MCKF. • MCRTSF performs better when the system is contaminated by non-Gaussian measurement noise. • MCRTSF can reduce to traditional RTSF when kernel bandwidths approach infinity. [ABSTRACT FROM AUTHOR]

In recent years, noise pollution has significantly affected marine organisms, necessitating the implementation of certain restrictions and safety protocols. The primary objective of these restrictions is to reduce the noise produced by human-operated vehicles in aquatic environments. For this reason, hydroacoustical studies are increasingly being integrated into design processes. This study aims to introduce an innovative approach to the design of hydrofoils, which are regarded as a critical component in hydroacoustic design. The focus of this approach is to develop an advanced optimization tool by integrating machine learning with hydroacoustic performance calculations. This study presents the 3D viscous-based Noise-GAN method, which innovatively combines Generative Adversarial Networks (GAN) algorithms with hydroacoustic performance calculations, enhanced by 3D viscous-based performance calculators. In contrast to the inviscid-based versions, this method, which incorporates 3D and viscous effects, allows for a comparative analysis of the impacts of these effects on the optimization process. Particularly, the performance of optimal geometries obtained through both 3D and 2D solvers will be compared, elucidating the role of 3D effects in the optimization process. This study addresses the drawbacks of 2D profile solutions in the optimization process, which generally offer a rapid solution in the field of machine learning for shape optimization. The effects have been examined at three different angles of attack (AoA). Thus, the positive and negative impacts on the optimization process under challenging environmental conditions have been identified. Additionally, cavitation constraints have been incorporated into the optimization process, ensuring that only profiles devoid of cavitation risk under the specified conditions are considered. Through the utilization of GAN algorithms, innovative profile geometries that do not present cavitation hazards at various angles of attack have been developed. The performance of the obtained optimal geometries has been compared to the widely utilized NACA0009 profile. By comparing the performance of the newly derived geometries with that of a profile with average performance, meaningful insights have been drawn. The results from the 3D viscous-based Noise-GAN method have been presented alongside the outputs derived from the 2D viscous-based method and the performance results of the NACA0009 profile under different Angle of Attack (AoA) conditions in this study. • The 3D viscous-based Noise-GAN, has been developed to generate hydroacoustically optimized hydrofoils. • 3D effects, viscous effects, and cavitation constraints have been successfully integrated into the optimization process. • The results were compared with those from the 2D viscous-based Noise-GAN version. • The 3D viscous-based Noise-GAN generated hydrodynamically and hydroacoustical efficient and distinctive geometries. • The optimization results were obtained at various angles of attack, demonstrating the significant potential of method. [ABSTRACT FROM AUTHOR]

[Display omitted] • A deep learning model of TPDNet based on the FA module and the self-attention mechanism is proposed, which can effectively identifies and separates noisy and target points from offshore drilling platform point cloud data. • The datasets were constructed using a combined filtering algorithm combining KNN_PCF and Hy_WHF to separate the outlier points, and the noise points of the cluttered objects point cloud (such as cluttered lines) are extracted with manual labeling. At the same time, in order to balance the ratio of the noise, Gaussian noise is introduced to increase the number of outlier points. • An application of a surface reconstruction method for the point cloud data of an offshore drilling platform based on the deep neural network using contextual prior information is implemented. The complex working environment of offshore drilling platforms makes the acquisition of point cloud data susceptible to noise pollution. To address this issue, this paper proposes a denoising network for point cloud data of offshore drilling platforms, called TPDNet. TPDNet utilizes the feature abstraction module to aggregate local features in point clouds and employs a self-attention mechanism for feature extraction, thereby enabling the effective identification of noisy point clouds. This paper also presents an offshore drilling platform point cloud dataset for training and testing deep learning models. It demonstrates the reconstruction of 3D surfaces of equipment on offshore drilling platforms using the target point cloud data obtained by TPDNet. The result validates the practicality of TPDNet. Consequently, this paper provides technical support for point cloud data processing, which has promising practical applications in the field of ocean engineering. [ABSTRACT FROM AUTHOR]

Noise is one of the greatest environmental health risks causing health issues via stress, deteriorated sleep, and annoyance. Noise annoyance is partially explained by measurable sound characteristics, and partially by other environmental, situational, and individual factors. Greenery might decrease noise annoyance via hiding the noise source, facilitating psycho-physiological restoration, and masking noise. However, whether greenery near home and some individual traits moderate the effect of road traffic noise on noise annoyance has been rarely assessed in everyday life. Using cross-sectional Environmental Health survey (n = 7321) collected at the Finnish capital region in 2015–16, we analysed the interactions between road traffic noise, green space, tree cover density, green view from home, noise sensitivity and nature relatedness on noise annoyance, using logistic regression modeling. Covariates included age, gender, socio-economic indicators, living floor, and the direction of windows. More green space and greater tree coverage around home were associated with lower odds of road traffic noise annoyance when road traffic noise was < 60 dB L den but increasingly higher odds at higher noise levels. No other interactions were found. Green view was only tentatively associated with lower odds of noise annoyance. Noise sensitivity and nature relatedness were related to greater odds of noise annoyance. In conclusion, greenery might mitigate noise annoyance at low-to-moderate road traffic noise levels. At higher noise levels, greenery may even increase noise annoyance. This could be due to incongruency between expected and actualised soundscapes in greener areas. However, more studies, especially interventions, are needed to confirm this. • We study how greenery near home affects annoyance by road traffic noise. • Higher road traffic noise was consistently associated with greater noise annoyance. • Green space and tree coverage predicted less annoyance at low traffic noise levels. • Green view was associated with less likely high noise annoyance. • Noise sensitivity and nature relatedness were associated with more noise annoyance. [ABSTRACT FROM AUTHOR]

The assessment of the exposure to road traffic noise pollution and of associated health conditions is usually based on energy-average noise levels. However, the number of noise events to which an individual is exposed has proven essential to the prediction of annoyance and sleep disturbance. Unfortunately, no standard method has been adopted for the counting of noise events. To address this shortcoming, Brown and De Coensel designed, in 2018, a generalised algorithm for the detection of road traffic noise events. The authors evaluated the performance of this algorithm for multiple sets of input parameters, but the setup employed for this testing was simplistic. The present study thus aims to benchmark the proposed parameter sets for the noise event detection algorithm in a controlled but realistic environment, consisting of a calibrated microscopic traffic simulation in the entire city of Tartu, Estonia, which includes interrupted traffic conditions and urban infrastructure. The performance assessment of a parameter set is shown to be highly dependent on context, i.e. , location and time of day, making definitive, universally applicable conclusions unrealistic. Rather, this study enables comprehensive insights that guide the selection of adapted parameter sets for various traffic situations, including the number of parameter sets, suitable detection thresholds, and recommended time gaps to implement. • Multiple parameter sets for a noise event detection algorithm are benchmarked. • The tests are conducted in a real urban area, using simulated microscopic traffic. • Contextual parameters, e.g. location, are essential in the choice of a parameter set. • Certain parameter sets exhibit superior performance for general monitoring. [ABSTRACT FROM AUTHOR]

Carsharing is a valuable concept of the sharing economy to address today's mobility challenges such as traffic congestion, noise pollution, and CO 2 emissions. Therefore, carsharing is increasingly expanded beyond metropolitan areas. However, lower population densities, higher vehicle ownership, and accessibility concerns lead to lower demand, resulting in an increased need for optimization and municipal support. This study investigates the role of access distance in carsharing user behavior in less densely populated areas as a basis for municipal planning and policy. To this end, it draws on descriptive analysis and predictive modeling of the real-world data of a municipal carsharing program. The results indicate that users' access distance is highly relevant for predictions of travel behavior (i.e., usage duration) and strategic decision-making (e.g., station locations and service areas). More trips than in metropolitan areas are made by users with long access distances (i.e., 3 km or more) to their nearest station, while trips with longer access distances are also made by a higher proportion of public transport subscribers, more often made with special types of vehicles (i.e., vans and nine-seaters), and result in longer average trip distances. • Carsharing access distance is relevant for municipal planning in small urban areas. • Access distance affects carsharing travel behavior. • Access distance increases prediction accuracy of vehicle usage duration. [ABSTRACT FROM AUTHOR]

Finding a kind of sustainable high-strength sound insulation eco-building material is the key to alleviating the energy crisis and noise pollution. In this study, coconut wood, a widely cultivated and fast-growing but untapped renewable natural material, was transformed into a lightweight sound insulation material with high mechanical strength through a simple but effective top-down strategy. This material possesses tensile strength of 584.6 MPa, flexural strength of 377.9 MPa, and impact toughness of 7.4 J cm−2, which surpasses most building materials (e.g., cement, steel, and alloys). Moreover, it demonstrates superior sound insulation performance with an average sound transmission loss of up to 57.6 dB. This coconut wood-based material may find wide applications in the eco-building material field. [Display omitted] • Coconut wood, a widely cultivated but untapped renewable waste resource. • The D-CW has higher strength and toughness than cement, most steels, and alloys. • The D-CW is moisture resistance and dimensionally stable. • The D-CW boards demonstrate superior sound insulation performance. [ABSTRACT FROM AUTHOR]

• A three-dimensional texture model, extrapolated from two-dimensional features both parallel and perpendicular to the concrete pavement surface, has been formulated. • The relationship between tire-pavement noise and pavement texture is found to be frequency-dependent. • A tire-pavement noise prediction model, predicated on texture parameters at velocities of 60 km/h and 80 km/h, has been established. In rapidly urbanizing regions, tire-pavement interaction is increasingly recognized as a significant contributor to traffic noise pollution. Cement concrete pavements, widely used in urban roadways, are known for their durability and load-bearing capacity, but they also contribute significantly to traffic noise. This noise stems from the pavement's inherent rigidity, which enhances vibrations when tires come into contact, and its smooth surface, which reflects sound waves back into the environment, amplifying the overall noise level. To mitigate this issue, researchers have turned to innovative texture techniques to produce quieter surfaces. This study introduces a 3D modeling technique for concrete pavement surfaces, analyzing textures in multiple driving directions using 2D profile data. Texture profiles are extracted from the wheel tracks, and average profile levels are calculated from eight test sites. Through correlation analysis between measured tire-pavement noise and texture profile levels, the high-frequency texture, mid-frequency texture, and low-frequency texture are considered as indicators of tire-pavement noise. A multivariate regression model links these noise levels to specfic texture profile levels:high: L tx , 0.2 1.25 , mid: L tx , 1.6 8 , and low: L tx , 10 40. By incorporating noise assessments from concrete pavements into the design process, the model contributes to the optimized design and construction of quieter pavement textures. [ABSTRACT FROM AUTHOR]

• The noise reduction mechanism of hydrofoils with leading edge protrusions was analyzed. • The monophonic noise in low-frequency bands reduced after adding leading-edge protuberances. • The flow instability and cavity collapse become the main sources of noise when cavitation occurs. • The leading-edge protuberances effectively suppress the formation and development of cavities, reducing cavitation instability. Cavitation leads to an increase in noise for high-speed ships, propellers, etc., which exacerbates ocean noise pollution. The objectives of this paper are to investigate the sound generation mechanism of cavitation noise and explore the noise reduction mechanism for the leading-edge protuberances. The large eddy simulation (LES) and the Zwart cavitation model were used to predict the unsteady cavitating flow around the National Advisory Committee for Aeronautics (NACA) 0012 baseline hydrofoil and the modified hydrofoil with the leading-edge protuberances. The load noise was predicted using the Ffowcs Williams–Hawkings (FW-H) acoustic simulation method from the flow field results, while the cavitation noise was calculated using the Sound radiation theory for spherical cavity. The noise reduction characteristics were analyzed in combination with the evolution characteristics of cavities and vortices. The leading-edge protuberances prevent the formation of large-scale shedding vortices, significantly reducing the pressure fluctuation amplitude on the suction surface of the hydrofoil. The flow instability and cavity collapse become the major sources of noise when cavitation occurs. Cavitation not only leads to an increase in radiated noise but also affects the characteristic frequency of noise. The modified hydrofoil effectively suppresses the formation and development of cavities, reducing cavitation instability. The modified hydrofoil can effectively reduce monophonic noise in low-frequency bands, resulting in a reduction of approximately 10.5 dB in peak monophonic noise. The high-frequency broadband noise between 300 and 500 Hz is reduced by approximately 7.58 dB. This research provides a reference for noise reduction optimization of hydraulic machinery. [ABSTRACT FROM AUTHOR]

[Display omitted] • Prior evidence has linked air pollution, noise, and greenspace to dementia risk. • However, the mechanisms connecting physical environment and dementia are unproven. • Reduced total brain volume explained 8% of PM 2.5abs and dementia risk. • Reduced grey matter mediated associations between pollution and dementia subtypes. • Brain volumes did not mediate associations between greenspace or noise and dementia. Although there is increasing evidence that environmental exposures are associated with the risk of neurodegenerative conditions, there is still limited mechanistic evidence evaluating potential mediators in human populations. UK Biobank is a large long-term study of 500,000 adults enrolled from 2006 to 2010 age 40–69 years. ICD-10 classified reports of dementia cases up to 2022 (Alzheimer's disease, vascular dementia, dementia in other classified diseases, and unspecified dementia) were identified from health record linkage. Estimates of residential air pollution, traffic noise, and greenspace exposure have been modelled. Structural brain MRI was conducted from 2014 to 2022, with brain volumes relevant to dementia identified a priori. Associations between environmental exposures, brain volumes, and dementia cases (diagnosed post-MRI) were tested using linear and logistic regression and adjusted for age, sex, household income, ethnicity, education, smoking, and area-level deprivation. Mediation of exposure-outcome associations by plausible brain volumes (those associated with both environmental exposure and dementia outcomes) were modelled using the quasi-Bayesian Monte Carlo method (N = 34,817–39,772). Small but significant mediating effects (2%-8% of relationships mediated) were observed between PM 2.5abs exposure and dementia risk by reduced total brain volume, NOx and Alzheimer's disease risk by reduced peripheral cortical grey matter, PM 2.5abs and vascular dementia risk by reduced peripheral cortical grey matter, PM 2.5abs and other dementia risk by reduced total grey matter, and PM 10 and other dementia risk by reduced total grey matter. Greenspace and noise were not associated with dementia outcomes in the subset of the cohort providing brain imaging data. This study adds to existing evidence of associations between environmental exposures and dementia outcomes. Our findings provide novel evidence that differences in brain volume may mediate these relationships. Future research is required to prove this mechanism and establish the other mechanisms through which exposure to air pollution might increase dementia risk. [ABSTRACT FROM AUTHOR]

Noise pollution is becoming more and more serious, and the environmental friendliness of building materials could be better. To solve these problems, waste hemp fibers were used as reinforcement and polylactic acid (PLA) fibers as matrix. Sustainable biodegradable sound-absorbing composites with different bionic structures were prepared by carding and hot press molding process. The sound absorption properties of bionic structural composites with smooth surface,triangular wedge surface, trapezoidal prismatic surface, sinusoidal wave surface,cylindrical pit surface, and rectangular raised surface were tested. Composites were 30 mm in thickness and 100 mm in diameters.The bionic sound structure models was constructed according to the extracted bionic structure. The sound performance of the sound-absorbing composites was analyzed by finite element method simulation. The effects of bionic structure and sound characteristic parameters on the sound absorption performance of the composites were investigated and the sound absorption mechanism of the sound composites with bionic structures was revealed. Then the model of the cylindrical pit surface was used as a research object further to optimize the sound absorption performance. The results revealed that the optimized bionic structural composite materials had a sound absorption performance grade of II, with a sound absorption average (SAA) coefficient in the mid-frequency range of 27.16 % higher than that of the smooth surface composites. The noise reduction coefficient was 0.603, and the SAA coefficient was 0.583.The results not only find a new way to recycle the waste hemp fibers, but also provide an experimental basis and theoretical basis for the optimization of sound absorption composites in building applications. • Sound absorbing composites with bionic structures were prepared on waste hemp fibers. • The sound-absorbing performance was improved after the import of bionic structure. • The bionic sound-absorbing structure model was established. • The sound absorption mechanism was revealed by finite element method. • Wide sound absorption frequency band and high efficiency sound absorption. [ABSTRACT FROM AUTHOR]

[Display omitted] • The PUI/MA aerogels were prepared by hydrothermal synthesis and ambient drying. • The PUI/MA aerogels have a core–shell structure and a second skeleton. • The PUI/MA aerogels have hydrophobicity and significant mechanical strength. • The PUI/MA aerogels have superior broadband sound absorption in the 180–6600 Hz band. • The JCA model was employed to analyze sound absorption of PUI/MA aerogels. Noise pollution has been recognized as having negative impacts on human psychological and physiological health. Common porous sound-absorbing materials are often limited by low sound absorption coefficient (SAC), excessive thickness, and poor moisture resistance or mechanical properties. Herein, poly(urethane-imide) and melamine foam (MF) were successfully combined for the first time using hydrothermal synthesis and ambient drying to fabricate a poly(urethane-imide)/melamine (PUI/MA) aerogel with a multi-stage pore structure and a core–shell framework. The introduction of PUI reduces pore size and increases tortuosity, thereby enhancing thermal and viscous losses of sound waves. Compared to unmodified MF, the noise reduction coefficient of PUI/MA aerogel achieves an 80 % improvement. Furthermore, numerical microstructural modeling calculations show that the JCA model's predictions are more consistent with the SACs of PUI/MA aerogels. In addition to significantly improving SAC, the core–shell structure endows the composite aerogels with a compressive Young's modulus up to 30 times that of MF, a water contact angle over 120°, and a thermal conductivity of less than 60 mW/m/K at 150 °C. The facile and cost-effective fabrication process, superior broadband sound absorption, and excellent fundamental properties suggest that PUI/MA aerogel is a promising candidate for noise mitigation in residential, rail transport, and industrial applications. [ABSTRACT FROM AUTHOR]

Artificial light at night (ALAN) and noise pollution in urban ecosystems change the behavior of birds in many ways, one of these being in their singing. These changes are crucial because singing is highly important in bird communication. As birds rely on the spread of acoustic information, they were found to modify their singing activity in urban areas under the influences of artificial light at night and noise. They can adjust their behavior to the rhythm of night and day (e.g., by timing their dawn song according to changing light intensities or shifting their singing to higher frequencies to prevent possible masking of the signal by noise). In this study, we assessed the effects of light pollution, noise, day in the year, and meteorological variables on the morning and evening timing and duration of singing in blackbirds. We found that light and noise pollution significantly affect the onset of blackbird dawn singing. Blackbirds started singing earlier in localities with ALAN and noise pollution. The effects of light and noise pollution on the morning song of the blackbird diminish through the breeding season after peaking at the beginning of the nesting season; and they are only minimal on the evening vocal activity of this species. With growing intensity of noise pollution, the influence of light pollution also increases. Light and noise pollution have greater influence on the morning vocal activity of blackbirds than do current weather conditions. • Light and noise pollution significantly affect blackbird singing activity. • Effect on blackbird's morning song diminishes through the breeding season. • Increasing noise pollution amplifies the influence of light pollution. • Light and noise pollution are more influential than are current weather conditions. • Impact on singing activity is strong in morning, minimal in evening. [ABSTRACT FROM AUTHOR]

• The strictest office room acoustic regulations were applied in Finland in 2018. • Occupant benefits of surpassing the regulation were inspected in our study. • Experience, performance and stress were examined with an experiment in two countries. • Room acoustic solution meeting the regulation improved experience and performance. • For best occupant experience even stricter room acoustic solutions are beneficial. Working during task-irrelevant speech influences workers. Adequate room acoustic design can reduce the negative effects in open-plan offices, but harmonized target values do not exist. Our purpose was to examine the effects of room acoustic design levels on a working person during the exposure to task-irrelevant speech. The Finnish room acoustic regulation was chosen as a reference, as it is one of the strictest worldwide. Three room acoustic conditions were examined: regulation violated (Reg-) (Speech Transmission Index, STI=0.71), regulation fulfilled (Reg0) (STI=0.37), and regulation surpassed (Reg+) (STI=0.16). To examine the generalizability of the results, a similar experiment was performed in two countries (two languages and laboratories): Finland and Germany (FinGer study, N = 98). Experience was measured with questionnaires, performance with visual and auditory serial recall tasks, and physiological stress with heart rate variability. Results did not depend on the country, suggesting that our findings could be similar also in other countries. Speech annoyance and perceived concentration difficulty differed in each condition. With other experience measures, only Reg+ improved experience compared to the two other conditions. Visual serial recall performance was more accurate and faster in Reg+ than in Reg-. Accuracy was also improved in Reg0 compared to Reg-. The physiological stress levels did not depend on the condition. Our study shows that Reg0 was better than Reg- with respect to experience and performance but experience was further improved from Reg0 to Reg+. Therefore, it is beneficial to design room acoustics better than the Finnish regulation to maximize work performance and experience. [ABSTRACT FROM AUTHOR]

Artificial light at night (ALAN) and urban noise are increasing globally and can have a range of impacts on wildlife. While ALAN and noise often co-occur and can affect wildlife in similar ways, their impacts have generally been studied in isolation. Information about possible interactive impacts, which can be more serious, is critical to guide conservation. We studied how noise and ALAN impact a common urban waterbird (Eurasian coot Fulica atra) around the city of Melbourne in south-eastern Australia. We aimed to examine: (1) the individual and (2) interactive impacts of noise and ALAN on abundance, and (3) the relative influence of these stressors and other environmental predictors. To do so, we used data from a large-scale (1,463 surveys across an area of 9,250 km2 with significant heterogeneity in noise and ALAN conditions), long-term (2008–2018) monitoring program, overlaid with georeferenced noise and light data. We used generalized linear mixed effects models and boosted regression trees to model individual and interactive effects of ALAN and noise on abundance. Abundance was negatively correlated with noise and ALAN individually. Furthermore, the two stressors had a negative synergistic effect, ultimately resulting in the absence of coots at the highest observed ALAN and noise levels. We also estimate that the combined influence of the two stressors on abundance was larger than that of other examined environmental factors. Our findings that noise and ALAN have detrimental interactive impacts is worrying for two reasons. First, Eurasian coots are thought to be tolerant to urbanisation, so impacts may be more severe for less tolerant species. Second, noise and ALAN commonly co-occur around cities, so similar impacts are likely elsewhere. By adopting more biologically and ecologically realistic analytical frameworks, future studies can better estimate the cumulative impacts of multiple stressors to facilitate improved conservation and management. [Display omitted] • Noise and light pollution negatively impact waterbird abundance, in isolation. • Noise and light interact to have stronger, negative synergistic effects on birds. • Simultaneous higher exposures of noise and light result in absence of birds. • Managing multiple stressors depends on understanding their interactive impacts. [ABSTRACT FROM AUTHOR]

We estimated the joint effect of particulate matter ≤ 2.5 µm in diameter (PM 2.5), nitrogen dioxide (NO 2), seasonal temperature, noise, greenness, light at night, and neighborhood socioeconomic status (NSES) on body mass index (BMI) in a mixture context among 194,966 participants from the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII) over 30 years. BMI was calculated from self-reported weight and height. Single- and multi-exposure generalized estimating equations models were used to estimate the difference in BMI per interquartile range (IQR) increase of environmental factors, and quantile g-computation methods were used to estimate joint associations. In both cohorts, we consistently observed positive associations of BMI with PM 2.5 and NO 2 concentrations as well as negative associations with light at night and NSES regardless modeling approach. A positive association with noise was only observed in NHS. Negative associations with greenness and winter temperature were only observed in NHSII. Overall, the changes in BMI per quintile increase in all eight exposures were −0.11 (−0.13, −0.08) in NHS and −0.39 (−0.41, −0.37) in NHSII, which were largely driven by air pollution and nighttime noise (18–45 %) in the positive direction and NSES (>70 %) in the negative direction. Future intervention on environmental factors, especially reducing PM 2.5, NO 2 and noise or improving the NSES, might be helpful to lower BMI. [Display omitted] • We performed a longitudinal study of 200,000 adults in two nationwide US cohorts. • Associations between mixtures of eight environmental factors and BMI were assessed. • The joint positive association with BMI was largely driven by air pollution and noise. • The joint negative association with BMI was largely driven by NSES. • The joint association of all eight environmental factors changed from negative to positive when removing NSES. [ABSTRACT FROM AUTHOR]

With the rapid increase in the number of automobiles, the noise pollution caused by car horns is attracting more attention. In order to accurately identify car horn sounds in traffic noise and strengthen traffic law enforcement, research on car horn sound recognition is becoming increasingly important. In this paper, using Principal Component Analysis (PCA) to optimize and reduce the dimensionality of extracted Mel Frequency Cepstral Coefficients (MFCC), feature vectors are input into four models: Support Vector Machine (SVM), Back Propagation (BP) Neural Network, Extreme Learning Machine (ELM), and Random Forest (RF). These models are utilized to classify and identify car horn sounds from traffic noise. The impact of feature dimensions and Signal-to-noise ratio(SNR) on recognition performance is analyzed. The results show that under this method, the recognition rates of the four models can be increased by increasing the number of Mel filters and feature dimensions in MFCC, which can improve recognition performance, especially when the SNR is lower. The SVM model exhibits the most significant improvement in recognition rate. They achieve the best recognition rates for measured car horn sounds of 98.66 %, 93.98 %, 89.44 %, and 95.12 %, respectively. Experimental results demonstrate that the proposed method has good recognition performance and can be effectively applied to the supervision of car horn usage on actual roads. [ABSTRACT FROM AUTHOR]

An accurate understanding of noise perception is important for urban planning, noise management and public health. However, the visual and acoustic urban landscapes are intrinsically linked: the intricate interplay between what we see and hear shapes noise perception in the urban environment. To measure this complex and mixed effect, we conducted a mobility-based survey in Hong Kong with 800 participants, recording their noise exposure, noise perception and GPS trajectories. In addition, we acquired Google Street View images associated with each GPS trajectory point and extracted the urban visual environment from them. This study used a multi-sensory framework combined with XGBoost and Shapley additive interpretation (SHAP) models to construct an interpretable classification model for noise perception. Compared to relying solely on sound pressure levels, our model exhibited significant improvements in predicting noise perception, achieving a six-classification accuracy of approximately 0.75. Our findings revealed that the most influential factors affecting noise perception are the sound pressure levels and the proportion of buildings, plants, sky, and light intensity. Further, we discovered non-linear relationships between visual factors and noise perception: an excessive number of buildings exacerbated noise annoyance and stress levels and diminished objective noise perception at the same time. On the other hand, the presence of green plants mitigated the effect of noise on stress levels, but beyond a certain threshold, it led to worsened objective noise perception and noise annoyance instead. Our study provides insight into the objective and subjective perception of noise pressure, which contributes to advancing our understanding of complex and dynamic urban environments. [Display omitted] • Data on dynamic noise exposure and subjective noise perception were collected. • An interpretable machine learning model was used to analyze the audio-visual environment. • The influences of visual factors showed non-linear relationships. • The model can effectively predict noise perception in different areas. [ABSTRACT FROM AUTHOR]

Tire-pavement noise is a major contributor to traffic noise pollution, impacting human health and well-being. The advent of 3D printing and prefabrication technologies makes it feasible to economically produce delicate concrete pavement textures for noise mitigation. However, relationships between the noise and texture characteristics (e.g., cavity shape, width, depth, and spacing) remain unknown. This study developed an analytical model for tire-pavement noise and calibrated/validated the model using On-board Sound Intensity tests on a purposely constructed road section with manufactured texture configurations. These textures were found to be capable of reducing the noise level by 8–15 dB(A) over conventional concrete textures, and the model prediction closely matched experimental data. Subsequently, the model was used to investigate the texture-noise relationships and identify those major influencing factors. This study contributes to tire-pavement noise modeling and offers insights for building quieter concrete pavements and enhancing the urban living environment. [ABSTRACT FROM AUTHOR]

We investigate the impact of dedicated loading–unloading zones (LUZs) in emerging markets, focusing on their effects on air quality and noise pollution. We conduct a field experiment in downtown area of Zapopan, Mexico. We use a quasi-experimental difference-in-difference approach to analyze changes in air quality and noise pollution before and after implementing the dedicated LUZs. The results indicate a significant reduction of up to 3.55% in CO 2 levels in the mornings and a 14% decrease in noise following the establishment of LUZs. Moreover, insights into the composition of companies involved in last-mile distributions reveals a predominant reliance on micro and small businesses, often utilizing personal vehicles for cargo transport, with a significant portion of freight vehicles being over a decade old. We contribute to the existing literature by providing evidence of the impact of LUZs on mitigating negative externalities associated with last-mile operations, particularly in a developing city. [ABSTRACT FROM AUTHOR]

Online adaptive bone/air-conducted speech fusion is a very promising and attractive technique for real time speech communication in noisy environments. This paper firstly demonstrates that conventional bone/air-conducted speech fusion systems may degrade significantly, despite that only a tiny narrowband noise pollution persists in bone-conducted speech by extensive simulations and experiments. To address this issue, a robust nonlinear system is proposed that successfully enhances the speech contaminated by the harsh narrowband noise. The penetrated narrowband noise is extracted by an adaptive linear prediction filter from an extra reference signal that is capture by a non-contacted bone sensor, and then fed to the parallel adaptive noise cancellers to reconstruct a cleaner error feedback for the speech recovery system. Due to this combination, the proposed system enjoys both attractive robustness against the harsh additive noise and strong real-time capability. Simulations as well as application to a real factory noise are conducted to demonstrate the superior performance of the proposed system. [ABSTRACT FROM AUTHOR]

Increasing noise pollution and ramie fibers waste resource problems need to be solved urgently. In order to resolve the problems, the porous sound-absorbing composites with high sound-absorbing performance were prepared by using waste ramie fibers as reinforcement materials, vinyl acetate copolymer (EVA) as matrix materials, azodicarbonamide(AC) as foaming agent, ZnO as auxiliary foaming agent, and dicumyl peroxide (DCP) as cross-linking agent, which were mixed in a two-stick mixer according to a certain ratio and then hot-pressing process. The process conditions were optimized using single factor analysis. Under the optimal process conditions, the sound-absorbing composites had a maximum sound absorption coefficient (SAC) of 0.72, an average SAC of 0.37, and a noise reduction coefficient (NRC) of 0.41. The sound absorption performance grade reached level III, and the sound absorption performance was excellent in the frequency range of 600 ∼ 6300 Hz. The introduction of foaming agents made the composites with more pores, and the average SAC of foamed composites increased by 346 %(compared with the unfoamed composites). Then, the sound-absorbing mechanism was analyzed. This study presents a novel approach to the recycling and reusing of the waste ramie fibers. It also provides a theoretical and experimental basis for the development of sound-absorbing composites with wider sound absorption band, larger (sound absorption coefficient) SAC and wider application, which is of great significance for sound absorption in the building fields. [Display omitted] • Low-cost porous sound-absorbing composites using waste ramie fiber. • The sound absorption performance was improved by mixing and foaming process. • The preparation process conditions were optimized. • The sound-absorbing mechanism of the porous sound-absorbing composites was analyzed. • The composites have a wider sound absorption band and broader range of applications. [ABSTRACT FROM AUTHOR]

• The effects of high-pass filters on acoustic index values derived from PAM recordings are not well documented. • High-pass filtering treatments did not consistently strengthen associations between acoustic indices and species richness. • ACI, AR, and CB demonstrated greater resistance to modifications caused by high-pass filters. • CityBioNet (CB) had a notably high correlation with species richness compared to the other examined acoustic indices. High-pass sound filters are a common form of audio manipulation that attenuates or removes low frequency sounds from audio recordings. While high-pass filters are used to reduce anthropogenic noise, there is limited guidance on their optimal application and their effects on acoustic indices—numerical values derived from passive acoustic monitoring (PAM) recordings to summarize acoustic information. Here, we investigated the effects of three high-pass filter treatments (482 Hz, 1 kHz, and 2 kHz) on eight commonly implemented acoustic indices and one less-commonly used convolutional neural network metric. Specifically, we used simulated soundscapes with three levels of traffic noise interference and then applied the filter treatments to field recordings collected throughout Illinois, USA during May 2022–July 2023 and derived acoustic indices to further understand these effects. Our analysis revealed that interactions between acoustic filtering and vehicular noise pollution have diverse effects on the nine acoustic indices, both in simulated soundscapes and empirical PAM recordings. In general, a 1 kHz or 2 kHz filter was necessary in order to produce significant changes in acoustic index values. However, none of the applied filtering treatments consistently strengthened correlations between the examined acoustic indices and avian species richness. The Acoustic Complexity Index (ACI), Acoustic Richness Index (AR), and CityBioNet (CB) demonstrated greater resistance to biologically non-informative changes caused by filter implementation, with CB showing a notably higher correlation with species richness compared to the other examined indices. Our findings suggest that ACI, AR, and CB may be better suited to studies of avian species richness in soundscapes with high levels of anthropogenic noise. Future research is needed to establish best practices for acoustic filtering, understand the behavior of acoustic indices under various environmental contexts, and explore alternative methodologies for avian monitoring in human-modified contexts. [ABSTRACT FROM AUTHOR]

Noise pollution in process of feature selection greatly reduces the classification efficacy of multilabel data, and the estimation of label descriptions is insufficient because of the lack of label enhancement for label distribution learning. To overcome the limitations, this work presents a noise-resistant fuzzy multineighbourhood rough set-based feature selection methodology with label enhancement and its application for multilabel classification. First, under the fuzzy T -equivalence relation, to construct new adaptive fuzzy neighbourhood class, the multineighbourhood radius set on feature space is integrated with fuzzy neighbourhood radius via sample interval on label space; then, the adaptive fuzzy multineighbourhood granules are obtained. Second, by integrating the parameterized fuzzy decision of labels and adaptive fuzzy multineighbourhood granules, noise-resistant lower and upper approximations via fuzzy multineighbourhood are constructed. A noise-resistant multilabel fuzzy multineighbourhood rough set model and its noise-resistant approximate accuracy can be proposed. Third, the description degree of label is computed to design label proportion after label enhancement. Certain fuzzy multineighbourhood entropy measures are developed to obtain label enhancement-based mutual information. When the algebraic and information perspectives are fused, label enhancement-based mutual information with fuzzy multineighbourhood via approximate accuracy is presented to evaluate the final association relationship between the features and label sets. Finally, a multilabel feature selection strategy via label enhancement will be constructed to obtain the best feature subset. The experimental results applied to 14 multilabel datasets indicate that this algorithm is significant. • Adaptive fuzzy neighbourhood class under fuzzy T-equivalence relation is designed via integrating feature and label spaces. • The noise-resistant multilabel fuzzy multineighbourhood rough set model and noise-resistant approximate accuracy are studied. • Label enhancement-based mutual information with fuzzy multineighbourhood via approximate accuracy can assess the association. • A multilabel feature selection scheme via label enhancement-based mutual information is designed for the best feature subset. [ABSTRACT FROM AUTHOR]

Formalized in ISO 12913, the "soundscape" approach is a paradigmatic shift towards perception-based urban sound management, aiming to alleviate the substantial socioeconomic costs of noise pollution to advance the United Nations Sustainable Development Goals. Focusing on traffic-exposed outdoor residential sites, we implemented an automatic masker selection system (AMSS) utilizing natural sounds to mask (or augment) traffic soundscapes. We employed a pre-trained AI model to automatically select the optimal masker and adjust its playback level, adapting to changes over time in the ambient environment to maximize "Pleasantness", a perceptual dimension of soundscape quality in ISO 12913. Our validation study involving (N = 68) residents revealed a significant 14.6 % enhancement in "Pleasantness" after intervention, correlating with increased restorativeness and positive affect. Perceptual enhancements at the traffic-exposed site matched those at a quieter control site with 6 dB(A) lower L A,eq and road traffic noise dominance, affirming the efficacy of AMSS as a soundscape intervention, while streamlining the labour-intensive assessment of "Pleasantness" with probabilistic AI prediction. • AI-based automatic masker selection system (AMSS) boosted "Pleasantness" by 14.6%. • AMSS elevated soundscape quality of traffic-exposed site equivalent to a quieter site. • AMSS achieved intended "Pleasantness" boost without inadvertently modifying "Eventfulness". • Restorative indicators were elevated despite only optimizing AMSS to increase "Pleasantness". • (Psycho)acoustic metrics were not correlated with AMSS's soundscape quality improvements. [ABSTRACT FROM AUTHOR]

• Gauge amount and visibility of exposure to green space at the granularity of activity episodes. • The amount of greenness boosts activity satisfaction. • NDVI indirectly promotes activity satisfaction by reducing perceived air pollution. • Real-time air and noise pollution have significant mediating effects on wellbeing. • Clear patterns of environmental injustice emerge for the disadvantaged groups. Understanding how mobility-based green space exposure influences momentary wellbeing is vital to promote life quality. Based on a survey conducted in 2017 characterizing residents' daily activities and environmental pollution exposure in Meiheyuan Community of Beijing, we use Normalized Difference Vegetation Index (NDVI) and Green View Index (GVI) to gauge the amount and visibility of exposure to green space at the granularity of activity episodes. Structural equation models are formulated to examine direct influences of green space on activity satisfaction, mediating effects of real-time environmental pollution, and environmental justice under a dynamic activity context. Our results show that the amount of greenness boosts activity satisfaction, and that the direct relationship between green visibility and activity satisfaction follows an inverted U-shaped curve. NDVI indirectly affects activity satisfaction by reducing perceived air pollution. GVI influences both objective and subjective noise pollution, thereby inducing indirect effects on activity satisfaction. Moreover, clear patterns of environmental injustice emerge: individuals with lower monthly incomes, renters, and the unemployed face heightened environmental pollution, when compared to their more affluent, homeowner, and employed counterparts. These findings underscore the significance of larger parks and green spaces for direct satisfaction enhancement, while street vegetation reduces perceived noise pollution and promotes wellbeing. [ABSTRACT FROM AUTHOR]