The architecture of functional brain network modulated by driving under train running noise exposure.

A noisy environment can considerably impact drivers' attention and fatigue, endangering driving safety. Consequently, this study designed a simulated driving experimental scenario to analyse the effects of noise generated during urban rail transit train operation on drivers' functional brain networks. The experiment recruited 16 participants, and the simulated driving scenario was conducted at noise levels of 50, 60, 70, and 80 dB. Functional connectivity between all electrode pairs across various frequency bands was evaluated using the weighted phase lag index (WPLI), and a brain network based on this was constructed. Graph theoretic analysis employed network global efficiency, degree, and clustering coefficient as metrics. Significant increases in the WPLI values of theta and alpha frequency bands were observed in high noise environments (70 dB, 80 dB), as well as enhanced brain synchronisation. Furthermore, concerning the topological metrics of brain networks, it was observed that the global efficiency of brain networks in theta and alpha frequency ranges, as well as the node degree and clustering coefficients, experienced substantial growth in high noise environments (70 dB, 80 dB) as opposed to 50 dB and 60 dB. This finding indicates that high-noise environments impact the reorganisation of functional brain networks, leading to a preference for network structures with improved global efficiency. Such findings may improve our understanding of the neural mechanisms of driving under noise exposure, and thus potentially reduce road accidents to some extent.

Research on sound quality prediction of vehicle interior noise using the human-ear physiological model.

In order to improve the prediction accuracy of the sound quality of vehicle interior noise, a novel sound quality prediction model was proposed based on the physiological response predicted metrics, i.e., loudness, sharpness, and roughness. First, a human-ear sound transmission model was constructed by combining the outer and middle ear finite element model with the cochlear transmission line model. This model converted external input noise into cochlear basilar membrane response. Second, the physiological perception models of loudness, sharpness, and roughness were constructed by transforming the basilar membrane response into sound perception related to neuronal firing. Finally, taking the calculated loudness, sharpness, and roughness of the physiological model and the subjective evaluation values of vehicle interior noise as the parameters, a sound quality prediction model was constructed by TabNet model. The results demonstrate that the loudness, sharpness, and roughness computed by the human-ear physiological model exhibit a stronger correlation with the subjective evaluation of sound quality annoyance compared to traditional psychoacoustic parameters. Furthermore, the average error percentage of sound quality prediction based on the physiological model is only 3.81%, which is lower than that based on traditional psychoacoustic parameters.

Studying the factors that affect urban road noise-case study: El-Tahrir Street, Al-Dokki Cairo, Egypt.

Expanding road networks to accommodate various activities has significantly increased urban noise pollution, adversely affecting human health and quality of life. Numerous factors influence the noise level in urban areas, including road characteristics, traffic characteristics, surrounding buildings, and weather conditions. While previous studies have considered many of these factors individually, this study aims to integrate all relevant variables to comprehensively monitor and analyze their combined effects on noise levels. The objective is to determine the most influential factors that could be incorporated into effective noise reduction strategies. This research focuses on Cairo, one of the most densely populated cities in the world, where high noise levels are a persistent issue. A detailed case study of Tahrir Street in Dokki, Cairo, provides the basis for this investigation. One of the most crowded areas is El-Tahrir Street in Al-Dokki, which was selected as a case study in this research. This area experiences high traffic volume, with up to 1700 vehicles passing through within a 15-min interval. This significant traffic volume is the primary driver of the elevated noise levels in the area. Traffic and noise level monitoring was conducted using a field survey using the sound level meter. Consequently, a statistical analysis was conducted to investigate the correlation between different factors and the noise level and determine the most influential factors. The study revealed that traffic volume and congestion are the most significant factors influencing noise levels on Tahrir Street, exhibiting strong positive correlations (R = 0.38). Additionally, the study found an inverse relationship between vehicle speed and noise level due to high traffic volumes and identified that building characteristics and wind direction also play roles, albeit to a lesser extent.

Noise barriers as a mitigation measure for highway traffic noise: Empirical evidence from three study cases.

Noise barriers are path interventions between noise sources and human receivers used mainly along road corridors to improve the acoustic environment for affected residents. Despite their widespread use, the impact of these interventions on community perception is still insufficiently investigated. This paper presents findings from a longitudinal study evaluating the efficacy of noise barriers in three residential areas alongside highways, compared to a reference case in a relatively quiet area. Noise exposure was objectively quantified via acoustic measurements and noise modelling, while socio-acoustic surveys measured the residents' subjective response in terms of noise annoyance as well as other aspects of quality of life. While noise exposure (Lday) decreased on average by 4.4-11.7 dBA at near-barrier points, direct reductions in pre to post-intervention noise annoyance were observed only in one case. Additionally, only in this particular case were the appraisals of the acoustic environment restored to a condition similar to low-level noise emissions (reference case). Contextual factors potentially downgrading the interventions' effectiveness are discussed, such as the history of complaints and coping, mistrust towards road authorities, high expectations, and the impacts of the COVID-19 pandemic. While noise exposure reductions did not directly lead to noise annoyance decreases, an ordinal regression pooling all cases revealed that larger reductions in noise exposure were associated with a higher likelihood of residents reporting decreased traffic noise annoyance in the post-survey. No evidence was found regarding noise barriers' impact on the subjective assessment of other aspects of quality of life, such as health complaints, concentration disturbance, and sleep quality.

Road traffic noise exposure and its impact on health: evidence from animal and human studies-chronic stress, inflammation, and oxidative stress as key components of the complex downstream pathway underlying noise-induced non-auditory health effects.

In heavily urbanized world saturated with environmental pollutants, road traffic noise stands out as a significant factor contributing to widespread public health issues. It contributes in the development of a diverse range of non-communicable diseases, such as cardiovascular diseases, metabolic dysregulation, cognitive impairment, and neurodegenerative disorders. Although the exact mechanisms behind these non-auditory health effects remain unclear, the noise reaction model centres on the stress response to noise. When exposed to noise, the body activates the hypothalamic-pituitary-adrenal axis and the sympathetic nervous system, leading to the secretion of stress hormones like catecholamines and cortisol. Prolonged exposure to noise-induced stress results in chronic inflammation and oxidative stress. This review underscores the role of inflammation and oxidative stress in the progression of noise-induced vascular dysfunction, disruption of the circadian rhythm, accelerated aging, neuroinflammation, and changes in microbiome. Additionally, our focus is on understanding the interconnected nature of these health outcomes: These interconnected factors create a cascade effect, contributing to the accumulation of multiple risk factors that ultimately lead to severe adverse health effects.

Road traffic noise pollution and prevalence of ischemic heart disease: modelling potential association and abatement strategies in noise-exposed areas.

In many developing countries with surging vehicular traffic and inadequate traffic management, excessive road traffic noise exposure poses substantial health concerns, linked to increased stress, insomnia and other metabolic disorders. This study aims to assess the linkage between sociodemographic factors, traffic noise levels in residential areas and health effects using a cross-sectional study analyzing respondents' perceptions and reports. Noise levels were measured at 57 locations in Srinagar, India, using noise level meter. Sound PLAN software was employed to generate noise contour maps, enabling the visualization of noise monitoring locations and facilitating the assessment of noise levels along routes in proximity to residential areas. Correlation analysis showed a strong linear relationship between field-measured and modelled noise (r2 = 0.88). Further, a questionnaire-based survey was carried out near the sampling points to evaluate the association of ischemic heart disease with traffic noise. Residents exposed to noise levels (Lden > 60 dB(A)) were found to have a 2.24 times higher odds ratio. Compared to females, males reported a 16% higher prevalence of the disease. Multi-faceted policy strategies involving noise mapping initiatives, source noise standards, traffic flow urban mobility optimization, smart city initiatives and stringent litigatory measures could significantly reduce its detrimental impact on public health. Finally, this study envisions a region-specific strong regulatory framework for integrating noise pollution mitigation strategies into the public health action plans of developing nations.

Machine learning based method for analyzing vibration and noise in large cruise ships.

Cruise ships are distinguished as special passenger ships, transporting passengers to various ports and giving importance to comfort. High comfort can attract lots of passengers and generate substantial profits. Vibration and noise are the most important indicators for assessing the comfort of cruise ships. Existing methods for analyzing vibration and noise data have shown limitations in uncovering essential information and discerning critical disparities in vibration and noise levels across different ship districts. Conversely, the rapid development in machine learning present an opportunity to leverage sophisticated algorithms for a more insightful examination of vibration and noise aboard cruise ships. This study designed a machine learning-driven approach to analyze the vibration and noise data. Drawing data from China's first large-scale cruise ship, encompassing 127 noise samples, this study sets up a classification task, where decks were assigned as labels and frequencies served as features. Essential information was extracted by investigating this problem. Several machine learning algorithms, including feature ranking, selection, and classification algorithms, were adopted in this method. One or two essential noise frequencies related to each of the decks, except the 10th deck, were obtained, which were partly validated by the traditional statistical methods. Such findings were helpful in reducing and controlling the vibration and noise in cruise ships. Furthermore, the study develops a classifier to distinguish noise samples, which utilizes random forest as the classification algorithm with eight optimal frequency features identified by LightGBM. This classifier yielded a Matthews correlation coefficient of 0.3415. This study gives a new direction for investigating vibration and noise in ships.

Sleep Disturbance Caused by Step Changes in Railway Noise Exposure and Earthquakes.

Kyushu Shinkansen and conventional railway lines run parallel in the areas 5 km north of Kumamoto Station (northern area) and 12 km south of the station (southern area). Following the operation of the Kyushu Shinkansen Line in 2011, the adjacent conventional railway line in the north was elevated, a new station was operated in the south, and large earthquakes struck the Kumamoto area from March to April 2016. Sleep disturbances were compared before and after the interventions and earthquakes based on noise source (Shinkansen and conventional railways), area (northern and southern), and house type (detached and apartment) through socio-acoustic surveys from 2011 to 2017. The Shinkansen railway caused significantly less sleep disturbances in detached houses in the north after compared to before the earthquakes, presumably due to more frequent closures of bedroom windows in northern detached houses following the earthquakes. The Shinkansen railway caused significantly more sleep disturbances in apartments in the south after compared to before the earthquakes, presumably because the Shinkansen slowed down immediately after the earthquakes and returned to normal speed during the survey, suddenly increasing the noise exposure. There was no significant difference in the other six cases investigated. Overall, the interventions may not have caused significant differences in sleep disturbances. This article expands on the congress paper by Morihara et al. presented in the "Community Response to Noise" session at the 52nd International Congress and Exhibition on Noise Control Engineering in Makuhari, Japan, organized by the International Institute of Noise Control Engineering.

Correlation between Long-Term Exposure to Traffic Noise and Risk of Type 2 Diabetes Mellitus.

OBJECTIVE: This study aimed to probe the correlation of long-term exposure to traffic noise with the risk of type 2 diabetes mellitus (T2DM). METHODS: The data of 480 community residents collected from April 2017 to April 2018 were retrospectively analyzed. Exposure levels for traffic noise were defined using 24-h mean traffic noise. Logistic regression calculated the association between long-term exposure to traffic noise and the risk of T2DM. RESULTS: Overall, 480 enrolled participants were divided into T2DM (n = 45) and non-T2DM (n = 435) groups. Participants with T2DM were older and more likely to be male, had higher BMI, and were frequent drinkers (P < 0.001). The T2DM group displayed higher exposure to traffic noise than the non-T2DM group (P < 0.001). According to quartiles of traffic noise, all participants were categorized into four groups: Q1 (<51.5 dB), Q2 (51.5-<53.9 dB), Q3 (53.9-<58.0 dB), and Q4 (≥58.0 dB). Prevalence of T2DM was 5.4% in Q1, 7.7% in Q2, 10.3% in Q3, and 14.1% in Q4 groups. Multifactor regression analysis showed that age, BMI, drinking history, and traffic noise exposure are risk factors for T2DM (P < 0.05), whereas sex does not seem to have a significant impact on T2DM (P > 0.05). CONCLUSION: Long-term exposure to traffic noise may elevate the risk of T2DM. This suggests that long-term exposure to high levels of traffic noise can increase the incidence of diabetes mellitus, which deserves further consideration.

Urban network noise control based on road grade optimization considering comprehensive traffic environment benefit.

A double-decision optimization model based on the road grade optimization strategy and considered comprehensive traffic environment benefit is proposed to control the traffic noise. The upper-level model maximizes the comprehensive traffic environment benefit, including network noise emission and traffic efficiency. Adjusting the emphasis on noise optimization benefits and traffic efficiency in road network planning through setting weights. The lower-level resolves the question of network traffic flow assignment using a stochastic user-equilibrium model. The increase of traffic environment demand, network noise emissions decrease and travel time rises. In the case, with a low environmental requirement (weighting with 1.1), the sound pressure emission of the network decreases by 9.23% with only a 4.01% increase in travel time. Under the high environmental requirement (weighting with 0.2), the sound pressure decreases by 26.8%, but the travel time rises by as high as 30.9%. The network is optimized towards road grade degradation and is the first to optimize the arterial roads. In addition, it is found that the influence of speed on traffic noise is greater than that of traffic volume through case validation. This method proposing traffic noise optimization strategies at the road network planning level provides technical support for the proactive governance of traffic noise pollution and the improvement of traffic sound environment quality.

Evaluation of flow, supply, and demand for noise reduction in urban area, Hamadan in Iran.

Noise pollution is one of the consequences of urbanization that can cause environmental disturbances in urban areas. Urban ecosystems provide noise reduction services through Urban Green infrastructures (UGIs). Many studies have been conducted to evaluate and model traffic noise, but none have addressed the flow, supply, and demand of noise reduction ecosystem services. The main purpose of this paper is to present a new methodology for estimating flow, supply, and demand for noise reduction in Hamadan city that has not been mentioned in any paper so far. UGIs were classified into six main categories: agricultural lands, gardens, parks, abandoned lands, single trees, and street trees. A total of 57 sampling stations for sound measurement were made in August 2018. The current map of noise pollution (flow) was created using the Kriging method. The amount of supply was measured up to a distance of 50 meters from the main roads based on two approaches (the distance effect and the sound barrier effect). To quantify the demand, the current sound intensity level in the noise-sensitive land uses was compared with standards. Zonal statistics was used for spatial analysis of supply-demand in the urban neighborhood as a working unit. Results showed that at distances of 5m, 10m, 15m, and 20m, the average noise reduction was found to be 1.61, 2.83, 3.92, and 5.33 dB, respectively. Sound barriers at distances of 5m and 10m resulted in an average sound reduction of 1.61 and 2.83 dB, respectively. Individual trees, strip trees, abandoned lands, parks, and gardens led to a decrease in traffic noise by 0.3, 1, 0.1, 3.5, and 4.5 dB, respectively. The clustering analysis revealed a significant spatial clustering of noise pollution in Hamedan. The results and new methodology of this research can be used in similar areas to estimate the supply and demand of noise reduction and also for decision-makers to take management actions to increase supply and meet the demand for noise reduction service.

Development of web-based software for environmental impact assessment focusing on road traffic noise.

In the Republic of Korea, Environmental Impact Assessment (EIAs) precedes development projects to predict and analyze potential environmental effects. Generally, EIA noise evaluations utilize 2D noise prediction equations and correction coefficients. This method, however, offers only a sectional noise evaluation and has limitations in complex environments with diverse noise sources. Moreover, the determination of various variables during the EIA process based on subjective human judgment raises concerns about the reliability of the results. Thus, this study aims to develop software accessible via a web environment for user-friendly EIA noise evaluations. This software supports integrated data management and generates a 3D noise prediction model for more precise and realistic analysis of noise impacts, specifically focusing on road-traffic noise at this stage of development. The 3D noise prediction model and noise map generated by the developed software have been validated against through comparison with the results of onsite noise measurements and commercial EIA software, SoundPLAN. This validation aimed to assess the practical utility of the application.

Long-term exposure to transportation noise and diabetes mellitus mortality: a national cohort study and updated meta-analysis.

BACKGROUND: Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort. METHODS: During 15 years of follow-up (2001-2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined). RESULTS: HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively). CONCLUSIONS: This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion.

Long-term exposure to air pollution and road traffic noise and incidence of dementia in the Danish Nurse Cohort.

INTRODUCTION: We examined the association of long-term exposure to air pollution and road traffic noise with dementia incidence in the Danish Nurse Cohort. METHODS: Female nurses were followed for dementia incidence (hospital contact or medication prescription) from 1993/1999 to 2020. Air pollution and road traffic noise levels were estimated at nurses' residences, and their associations with dementia were examined using Cox regression models. RESULTS: Of 25,233 nurses 1409 developed dementia. Particulate matter with a diameter of ≤2.5 µm (PM2.5) was associated with dementia incidence, after adjusting for lifestyle, socioeconomic status, and road traffic noise (hazard ratio [95% confidence interval] 1.35 [1.15-1.59] per interquartile range of 2.6 µg/m3). There was no association of PM2.5 with dementia in physically active nurses. Association with road traffic noise diminished after adjusting for PM2.5 (1.02 [0.93-1.11] per 7.6 dB). DISCUSSION: Long-term exposure to air pollution increases risk of dementia, and physical activity may moderate this risk. HIGHLIGHTS: Long-term exposure to air pollution was associated with increased risk of dementia among female nurses from the Danish Nurse Cohort. Association of air pollution with dementia was independent of road traffic noise. Association of road traffic noise with dementia diminished after adjusting for air pollution. Physical activity moderated adverse effects of air pollution on dementia.

Psychophysiological effects of walking in forests and urban built environments with disparate road traffic noise exposure: study protocol of a randomized controlled trial.

BACKGROUND: Stress is a widespread phenomenon and reality of everyday life, entailing negative consequences for physical and psychological wellbeing. Previous studies have indicated that exposure to greenspaces and nature-based interventions are promising approaches to reducing stress and promoting restoration. However, an increasing percentage of the population lives in urban regions with limited opportunities to spend time in greenspaces. In addition, urban settings typically feature increased levels of noise, which represents a major environmental stressor. Although various studies have compared the effects of exposure to greenspaces versus urban built environments, evidence of the effects of noise in this context is very limited. Psychophysiological benefits of exposure to greenspaces compared to urban built environments reported in earlier studies might be less (or at least not only) due to features of the greenspaces than to additional stressors, such as road traffic noise in the urban built environment. Hence, differences in the effects attributed to greenness in previous studies may also be due to potentially detrimental noise effects in comparison settings. This paper reports the study protocol for a randomized, controlled intervention study comparing the effects of walking in forest versus urban built environments, taking road traffic noise exposure during walks in the respective settings into account. METHODS: The protocol envisages a field study employing a pretest-posttest design to compare the effects of 30-min walks in urban built environments and forests with different road traffic noise levels. Assessments will consist of self-reported measures, physiological data (salivary cortisol and skin conductance), an attention test, and noise, as well as greenness measurements. The outcomes will be restoration, stress, positive and negative affect, attention, rumination, and nature connectedness. DISCUSSION: The results will inform about the restorative effect of walking in general, of exposure to different types of environments, and to different noise levels in these sites. The study will provide insights into the benefits of walking and nature-based interventions, taking into account the potential detrimental effects of noise exposure. It will thus facilitate a better understanding of low-threshold interventions to prevent stress and foster wellbeing. TRIAL REGISTRATION: ISRCTN48943261 ; Registered 23.11.2023.

Diurnal rail noise measurement, analysis, and evaluation of associated health impacts on residents living in the proximity of rail track area.

In India, railway is the major transportation mode for carrying goods and people. The tracks for the movement of the rail were initially constructed in the city for the pre-eminence and expediency of the vantage of the people. Rapid modernization and increasing population in the city crammed the area around the railway tracks. Moving rail on the tracks passing through the city is not compatible, which is creating problems for the nearby residents. In the urban and suburban regions, the railway noise has become a major problem. This study was conducted to examine the perception of the physiological and psychological effects of railway noise in the nearby areas of railway stations in Delhi, India. For this purpose, 10 sites near the railway station were selected for the study. To assess the impact of railway noise pollution on the health of humans, a questionnaire survey was conducted. The data of 344 individuals were collected through the questionnaire survey and analyzed to get the perception towards railway noise. Noise level was monitored by a Sound Level Meter (SLM) and the equivalent noise level (Leq) in dB(A) was used to compute the noise pollution in three shifts, i.e., morning, noon, and evening time. Results showed that 57.65% of female and 86.11% of male respondents in the survey reported the disturbance due to railway noise. The level of noise pollution was found higher in the evening time as compared to the noon and morning period, which exceeds the limit set by the Central Pollution Control Board (CPCB) at all the monitored locations. Findings of the study show that the primary cause of the health problems is railroad noise, which is negatively impacting the health of the residents, who are living in the proximity of the rail track region. The perception survey reported that headache, sleep disturbance, irritation, and stress are common health issues among the locals residing around the railway track proximity in Delhi.

Vessels and aircraft are chronic sources of anthropogenic noise in coastal marine and terrestrial soundscapes on Long Island, New York.

Passive acoustic data collected during 2020 and 2021 were used to monitor changes in both terrestrial and underwater soundscapes, as well as human activity from aircraft and vessels. Passive acoustic data were collected at two artificial reefs south of Long Island, as well as along ocean beaches in Southampton, NY. At the artificial reefs, vessel noise was recorded more frequently during 2020 than in 2021. Commercial vessels and multi-user charter fishing vessels were more abundant during 2020. Peaks in power spectral density occurred at 60, 90 and 120 Hz in 2020 and 2021, which are frequencies consistent with noise generated by commercial vessels, suggesting that vessels are a significant contributor to the soundscape of the artificial reefs. In the terrestrial environment, noise generated by aircraft was more common during 2021. Peaks in power spectral density were measured around 160 and 290 Hz at one of the ocean beach sites. These frequencies are consistent with noise generated by aircraft. This study documents the chronic extent of anthropogenic noise in both the underwater and terrestrial environments of Long Island, NY, as well as quantifies the occurrence of various noise sources in these habitats.

Association of transportation noise with cardiovascular diseases.

This comprehensive article delves into the intricate and multifaceted issue of noise pollution, shedding light on its diverse sources, profound health implications, and the economic burden it imposes on societies. Noise pollution is an increasingly prevalent environmental challenge, impacting millions of people worldwide, often without their full awareness of its adverse effects. Drawing from a wealth of scientific research, the article underscores the well-established links between noise pollution and a spectrum of health issues, including cardiovascular diseases, sleep disturbances, and psychological stress. While exploring the sources and consequences of noise pollution, the article highlights the urgent need for a holistic and collaborative approach to mitigate its impact. This entails a combination of regulatory measures, technological innovations, urban planning strategies, and public education campaigns. It is increasingly evident that the detrimental effects of noise pollution extend beyond physical health, encompassing mental and social well-being. The article also addresses the synergistic relationship between noise pollution and other environmental stressors, emphasizing the importance of considering noise in conjunction with factors like air pollution and access to green spaces. It examines the potential of green spaces to mitigate the effects of noise pollution and enhance overall health.

Traffic Noise Impacts Glucocorticoid Response, Activity, and Growth in Two Species of Tadpoles.

There is a large body of evidence linking increased noise to negative health effects for animals. Anthropogenic noise induces behavioral and physiological reactions across a range of taxa and increased traffic noise affects glucocorticoid (GC) hormones associated with the stress response in amphibians. GCs help to maintain homeostasis while balancing energetic trade-offs between reproduction, growth, and activity. Stressors during early development can impact fitness at later life stages. We measured growth, activity, and GCs in response to high levels of traffic noise in two tadpole species that differ in life history: Acris crepitans and Rana berlandieri. We predicted that earlier exposures to traffic noise will slow down the development and alter the behavior and GC concentrations differently than later exposures. Subjects were initially either exposed to natural levels of traffic noise for 8 days (early exposure) or a white noise control (later exposure), then the treatment was switched. Activity was measured via focal sampling and tadpoles were categorized as active if movement was detected. Tadpoles exposed to white noise initially maintained mass and activity throughout the experiment and early exposure to traffic noise had a greater impact on mass, activity, and GCs. Tadpoles exposed to traffic noise initially lost mass, with A. crepitans regaining mass but not R. berlandieri. When exposed earlier to traffic noise, R. berlandieri increased movement when shifted to the white noise treatment while A. crepitans did not significantly change activity. Acris creptians had higher corticosterone release rates compared to R. berlandieri, and in both species, release rates were higher for tadpoles exposed to noise earlier. The longer-lived R. berlandieri allocated more of their energetic resources into activity, while the shorter-lived A. crepitans allocated energy toward growth. Rana berlandieri and A. crepitans utilized different coping strategies to contend with early exposure to traffic noise, potentially due to differences in life histories. Our findings suggest that these tadpoles employ different coping mechanisms to modulate stress responses in noise-polluted environments, and these mechanisms could influence their fitness later in life. Further study is needed to understand the impact in more sensitive tadpole species.

Pre- and postnatal noise directly impairs avian development, with fitness consequences.

Noise pollution is expanding at an unprecedented rate and is increasingly associated with impaired reproduction and development across taxa. However, whether noise sound waves are intrinsically harmful for developing young-or merely disturb parents-and the fitness consequences of early exposure remain unknown. Here, by only manipulating the offspring, we show that sole exposure to noise in early life in zebra finches has fitness consequences and causes embryonic death during exposure. Exposure to pre- and postnatal traffic noise cumulatively impaired nestling growth and physiology and aggravated telomere shortening across life stages until adulthood. Consistent with a long-term somatic impact, early life noise exposure, especially prenatally, decreased individual offspring production throughout adulthood. Our findings suggest that the effects of noise pollution are more pervasive than previously realized.