Spatio-temporal changes of road traffic noise pollution at ecoregional scale

Iglesias-Merchán, Carlos; Laborda-Somolinos, Rafael; González-Ávila, Sergio; Elena-Rosselló, Ramón

doi:10.1016/j.envpol.2021.117291

Cited by 22 publications

(11 citation statements)

References 47 publications

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“…Environmental noise pollution is a key global issue for all humans living on the earth (Iglesias-Merchan et al, 2021). According to the World Health Organization (WHO) definition, noise pollution is the third most impact on society after air and water pollution (Basu et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Influence of Urban Green Spaces on Road Traffic Noise Levels: - A Review

Wickramathilaka

Ujang

Azri

et al. 2022

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Ninety per cent of urban areas' total noise pollution is caused by traffic. Green areas are a very important factor for noise reduction. They will absorb noise from 5dB (A) to 10 dB (A). Nonetheless, some major concerns can be addressed, such as: how can green areas be established in the urban city?, how trees absorb noise?, what are the equations to calculate noise absorption by trees?, and what are the best survey methods to measure the trees' properties?, and is it possible to visualize trees in three-dimensional (3D) space?. Thirty-five (35) research papers were selected under the subtopics, green spaces and urban forms, noise absorption by green spaces, and green spaces visualization in 3D to find solutions for the above problems. The review has identified how to increase green spaces in urban forms like core, star, satellite, and linear. Next, the leaves are the main possible part to absorb noise, and depend on the leaves' surface area, tree depth, and noise absorption coefficient. These parameters must be considered to formulate an equation to identify sound absorption by leaves. Furthermore, the Light Detection and Ranging (LiDAR) technique can be used for determining the surface area of leaves and tree depth, due to its high resolution of point clouds. The Digital Surface Model (DSM) is not applicable for visualizing green areas, because it represents the only top view of trees, and tree depth cannot be identified properly. Proper visualization of green spaces in 3D will convey a significant point of view to visualize noise absorption accurately in a 3D urban city.

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Section: Introductionmentioning

confidence: 99%

Influence of Urban Green Spaces on Road Traffic Noise Levels: - A Review

Wickramathilaka

Ujang

Azri

et al. 2022

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…It has been shown that noises from trucks, cars, and motorcycles can be louder than 50 dBA around roads in urban ecosystems during the day and night (Barber et al, 2010 ; D’Alessandro & Schiavoni, 2015 ). In most rural and natural ecosystems, human‐induced noise doubles the level of background noise, inducing a marked shift in the patterns of the soundscape (Buxton et al, 2017 ; Iglesias‐Merchan et al, 2021 ). Adverse effects of anthropogenic noise on health and other fitness components have been demonstrated in a variety of organisms (Barber et al, 2010 ; Jerem & Mathews, 2021 ; Kleist et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Airport noise disturbs foraging behavior of Japanese pipistrelle bats

Wang

Gao

et al. 2022

Ecology and Evolution

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The expansion of anthropogenic noise poses an emerging threat to the survival and reproductive success of various organisms. Previous investigations have focused on the detrimental effects of anthropogenic noise on the foraging behavior in some terrestrial and aquatic animals. Nevertheless, the role of airport noise in impairing foraging activities of most wild animals has been neglected. Here, we aimed to assess whether foraging behavior in free‐living Japanese pipistrelle bats ( Pipistrellus abramus ) can be disturbed by airport noise. We used audio recording to monitor foraging activities of bats at 11 sites around the runway of a municipal airport. We quantified noise level and spectra, aircraft activity, habitat type, nightly temperature, wind speed, and moon phase for each site. The analysis revealed that noise level and aircraft activity were significant negative predictors for the number of bat passes and feeding buzzes around the runway, even after controlling for the effects of other environmental factors. There was no marked spectral overlap between bat echolocation pulses and airport noise in the presence and absence of low‐flying aircraft. The spectro‐temporal parameters of echolocation vocalizations emitted by bats were dependent on noise level, aircraft activity, and habitat type. These results provide correlative evidence that airport noise can reduce foraging activities of wild pipistrelle bats. Our findings add to the current knowledge of adverse impacts of airport noise on foraging bats in artificial ecosystems and provide a basis for further research on the mechanisms behind noise pollution near airports.

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“…However, the current fossil fuel-driven road transport has a large carbon footprint [2,3]. It pollutes the environment locally and globally, causes noise and congestion, is a source of additional expense to society, adversely affects people's health, and, in certain circumstances, leads to traffic crashes, some of which cause serious injuries or death [4][5][6][7]. These crashes are the eighth leading cause of death for people of all ages and the first leading cause of death for people between the ages of 5 and 29 [8].…”

Section: Introductionmentioning

confidence: 99%

Revealing the Spatial Pattern of Weather-Related Road Traffic Crashes in Slovenia

et al. 2021

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Despite an improvement in worldwide numbers, road traffic crashes still cause social, psychological, and financial damage and cost most countries 3% of their gross domestic product. However, none of the current commercial or open-source navigation systems contain spatial information about road traffic crash hot spots. By developing an algorithm that can adequately predict such spatial patterns, we can bridge these still existing gaps in road traffic safety. To that end, geographically weighted regression and regression tree models were fitted with five uncorrelated (environmental and socioeconomic) road traffic crash predictor variables. Significant regional differences in adverse weather conditions were identified; Slovenia lies at the conjunction of different climatic zones characterized by differences in weather phenomena, which further modify traffic safety. Thus, more attention to speed limits, safety distance, and other vehicles entering and leaving the system could be expected. In order to further improve road safety and better implement globally sustainable development goals, studies with applicative solutions are urgently needed. Modern vehicle-to-vehicle communication technologies could soon support drivers with real-time traffic data and thus potentially prevent road network crashes.

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Spatio-temporal changes of road traffic noise pollution at ecoregional scale

Cited by 22 publications

References 47 publications

Influence of Urban Green Spaces on Road Traffic Noise Levels: - A Review

Influence of Urban Green Spaces on Road Traffic Noise Levels: - A Review

Airport noise disturbs foraging behavior of Japanese pipistrelle bats

Revealing the Spatial Pattern of Weather-Related Road Traffic Crashes in Slovenia

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