Electric Vehicles and Urban Noise Control Policies

Maffei, Luigi; Masullo, Massimiliano

doi:10.2478/aoa-2014-0038

Cited by 24 publications

(21 citation statements)

References 17 publications

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“…The measures that can be taken by the local government are as follows (Environmental Noise Directive 2002 ; Maffei and Masullo 2014 ; Mahler and Bohli 2015 ; Penton 2016 ; Dimitrijević 2017 ; Jacyna et al 2017 ; Jena et al 2018 ; Boren 2019 ; Ferrini et al 2020 ; EU-European Commission 2020a , b ): Ensuring that the new buildings to be built in the region comply with the "Protection of Buildings Against Noise” regulation. Replacing traditional asphalt pavement with more efficient alternative options (this is more effective than other options in reducing traffic noise), Increasing the number of noise-protected pedestrian zones by restricting vehicle traffic and unloading at certain times of the day, Increasing cycling paths, Regular maintenance of municipal vehicles, In the long term, preferring procurement of hybrid or electric vehicles for municipal services, In the long term, switching to hybrid or electric public transport vehicles.…”

Section: Discussionmentioning

confidence: 99%

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GIS-based mapping and assessment of noise pollution in Safranbolu, Karabuk, Turkey

Esmeray

Eren

2021

Environ Dev Sustain

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In this study, it is aimed to determine and map the noise pollution levels in Safranbolu District Center, especially in the regions where motor vehicle and/or pedestrian traffic is intense. Forty-seven measurement points were selected for noise level measurements at the district center. Measurements were conducted at morning (8 a.m.–10 a.m.), lunchtime (12 p.m.–2 p.m.) and evening (6 p.m.–8 p.m.) hours of weekdays and weekends throughout the seasons of summer 2017 and winter 2018. The summer season weekdays noise level ranges from 41.3 to 71.2 dBA in the morning period, 40 to 71.2 dBA in the noon period and 40.6 to 73.1 dBA in the evening. The summer season weekend noise level ranges from 45.3 to 69.1 dBA in the morning period, 44.7 to 71.4 dBA in the noon period and 41.6 to 70.9 dBA in the evening. The result showed that the level of summer season weekday and weekend noise pollution in the morning, noon and evening is close to each other. In addition, the winter season weekdays noise level ranges from 32.3 to 68.5 dBA in the morning period, 30.8 to 73.3 dBA in the noon period and 37.4 to 72.9 dBA in the evening. The winter season weekend noise level ranges from 37.2 to 65.8 dBA in the morning period, 40 to 71.3 dBA in the noon period and 40.5 to 69.7 dBA in the evening. The result showed that the level of winter season weekdays and weekend noise pollution in the noon is generally higher than morning and evening. The obtained data are compared with the limit values specified in the Environmental Hazard Assessment and Management Regulation. The hazardous noise level, which is considered as the threshold for causing physiological problems on humans, was determined to be exceeded at many locations. This situation may cause significant negative consequences on human health, quality of life and tourism sector. Obtained data were processed, and noise pollution levels for the city of Safranbolu were mapped using a geostatistical analysis software. In total, 16 noise pollution maps were drawn for different situations (e.g., weekdays, weekend, daytime, noon, night, summer season, winter season, etc.). Obtained noise level results demonstrate that the overall quality of the acoustic environment in our study area was medium level, which means that exposure to these levels over a long period can affect human health and quality of life. Finally, the results of a survey conducted as a part of this study were given, and possible measures and suggestions to reduce these noise levels in the district down to the desired limit values were discussed. Supplementary Information The online version contains supplementary material available at 10.1007/s10668-021-01303-5.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

GIS-based mapping and assessment of noise pollution in Safranbolu, Karabuk, Turkey

Esmeray

Eren

2021

Environ Dev Sustain

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“…To meet today's rising demand for mobility in the era of technological advancement boosted the use of electric vehicles [9,[35][36][37][38]. As the electric vehicles have a large number of added advantages, it is becoming popular in society.…”

Section: Discussionmentioning

confidence: 99%

Investigation of Perceived Risk Encountered by Electric Vehicle Drivers in Distinct Contexts

Patil¹,

Khairnar²

2021

Applied Engineering Letters

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Not only pollution concerns, but also the rising prices of fuel used in conventional vehicles are enforcing people to make use of electric vehicles. In spite of numerous advantages such as pollution-free, noiseless smooth drive; there may be the new possibility of difficulties occurring due to the quiet nature of electric vehicles (EVs). To examine this, it was intended to conduct an extensive questionnaire survey with 398 driver participants to acquire technical data at Mumbai Metropolitan Region (MMR). The analysis used a well-proven driver behaviour questionnaire (DBQ) built on a six-point scale to statistically evaluate driver behaviour responses to perceived risk. This study aims to evaluate the perceived risk encountered by drivers that influence road safety by considering age group, driving experience, and gender. A systematic ANOVA approach was employed to evaluate the significant factors. The results show that the perceived risk is different based on the gender of the driver, especially when parking the vehicle (p=0.000, F=10.11716>Fcrit). The moderate difficulty level for identifying the presence of electric vehicles is present in almost all situations; however, no significant difference was recorded based on gender, age, and driving experience in the rest of the cases. The outcome of the proposed work would be useful while designing the safety policy for electric vehicles.

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“…Although numerical noise models are the preferred tool for noise mapping, [10,11], undertaking noise measurements is an essential task for: calibrating noise map modelling tools [12,13], evaluating the effect of local noise reduction strategies such as green zones [14][15][16], obtaining results in complex environments where the traffic is not the main noise source [17] or traffic data is not available [13], and obtaining more accurate results [18]. The use of experimental noise measurements is a highly demanding task that is usually simplified using sampling strategies that, as a drawback, could lead to significant differences between the estimated and the actual annual values.…”

Section: Introductionmentioning

confidence: 99%

Annual traffic noise levels estimation based on temporal stratification

Quintero

Balastegui

Garbí

2018

Journal of Environmental Management

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This paper proposes a temporal sampling strategy that increases the accuracy of long-term noise level estimation and allows to establish the estimation error according to the number of sampled days. Days of the week are stratified into working days and weekend days. This research shows how to use measurements of L on working days to estimate the corresponding values for weekend days. This is possible because working days have higher noise levels and less variability than weekend days. The improvement in accuracy allows for a reduction in the number of required sampled days compared to taking samples randomly, which would help to reduce the uncertainty in environmental noise assessment. As a reference, to obtain a 90% confidence interval of ±1 dB for L, the proposed sampling strategy reduces the required measurement days by more than 38%. For L, the reduction is close to 18% of the total number of days. The proposed strategy could be adapted to different environments by simply changing a few parameters.

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Electric Vehicles and Urban Noise Control Policies

Cited by 24 publications

References 17 publications

GIS-based mapping and assessment of noise pollution in Safranbolu, Karabuk, Turkey

GIS-based mapping and assessment of noise pollution in Safranbolu, Karabuk, Turkey

Investigation of Perceived Risk Encountered by Electric Vehicle Drivers in Distinct Contexts

Annual traffic noise levels estimation based on temporal stratification

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