Methods for Noise Event Detection and Assessment of the Sonic Environment by the Harmonica Index

Noise annoyance depends not only on sound energy, but also on other features, such as those in its spectrum (e.g., low frequency and/or tonal components), and, over time, amplitude fluctuations, such as those observed in road, rail, or aircraft noise passages. The larger these fluctuations, the more annoying a sound is generally perceived. Many algorithms have been implemented to quantify these fluctuations and identify noise events, either by looking at transients in the sound level time history, such as exceedances above a fixed or time adaptive threshold, or focusing on the hearing perception process of such events. In this paper, four criteria to detect sound were applied to the acoustic monitoring data collected in two urban areas, namely Andorra la Vella, Principality of Andorra, and Milan, Italy. At each site, the 1 s A-weighted short LAeq,1s time history, 10 min long, was available for each hour from 8:00 a.m. to 7:00 p.m. The resulting 92-time histories cover a reasonable range of urban environmental noise time patterns. The considered criteria to detect noise events are based on: (i) noise levels exceeding by +3 dB the continuous equivalent level LAeqT referred to the measurement time (T), criteria used in the definition of the Intermittency Ratio (IR) to detect noise events; (ii) noise levels exceeding by +3 dB the running continuous equivalent noise level; (iii) noise levels exceeding by +10 dB the 50th noise level percentile; (iv) progressive positive increments of noise levels greater than 10 dB from the event start time. Algorithms (iii) and (iv) appear suitable for notice-event detection; that is, those that (for their features) are clearly perceived and potentially annoy exposed people. The noise events detected by the above four algorithms were also evaluated by the available anomalous noise event detection (ANED) procedure to classify them as produced by road traffic noise or something else. Moreover, the assessment of the sonic environment by the Harmonica index was correlated with the single event level (SEL) of each event detected by the four algorithms. The threshold value of 8 for the Harmonica index, separating the “noisy” from the “very noisy” environments, corresponds to lower SEL levels for notice-events as identified by (iii) and (iv) algorithms (about 88–89 dB(A)) against those identified by (i) and (ii) criteria (92 dB(A)).

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Prediction of L10 and Leq Noise Levels Due to Vehicular Traffic in Urban Area Using ANN and Adaptive Neuro-Fuzzy Interface System (ANFIS) Approach

International Journal of Business Data Communications and Networking ◽

10.4018/ijbdcn.2019070106 ◽

2019 ◽

Vol 15 (2) ◽

pp. 92-105

Author(s):

Vilas K Patil ◽

P.P. Nagarale

Keyword(s):

Noise Level ◽

Urban Areas ◽

Road Traffic ◽

Traffic Noise ◽

Road Traffic Noise ◽

Vehicular Traffic ◽

Noise Levels ◽

Anfis Model ◽

Neuro Fuzzy ◽

Interface System

Recently in urban areas, road traffic noise is one of the primary sources of noise pollution. Variation in noise level is impacted by the synthesis of traffic and the percentage of heavy vehicles. Presentation to high noise levels may cause serious impact on the health of an individual or community residing near the roadside. Thus, predicting the vehicular traffic noise level is important. The present study aims at the formulation of regression, an artificial neural network (ANN) and an adaptive neuro-fuzzy interface system (ANFIS) model using the data of observed noise levels, traffic volume, and average speed of vehicles for the prediction of L10 and Leq. Measured noise levels are compared to the noise levels predicted by the experimental model. It is observed that the ANFIS approach is more superior when compared to output given by regression and an ANN model. Also, there exists a positive correlation between measured and predicted noise levels. The proposed ANFIS model can be utilized as a tool for traffic direction and planning of new roads in zones of similar land use pattern.

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Traffic Noise Level Assessment in the Residential Area around Different Road Functions in Malang City, East Java, Indonesia

Pertanika Journal of Science and Technology ◽

10.47836/pjst.29.3.05 ◽

2021 ◽

Vol 29 (3) ◽

Author(s):

Ngudi Tjahjono ◽

Imam Hanafi ◽

Latipun Latipun ◽

Suyadi Suyadi

Keyword(s):

Psychological Health ◽

Noise Level ◽

Urban Areas ◽

Negative Impact ◽

Heavy Traffic ◽

Traffic Noise ◽

Sound Level ◽

Noise Levels ◽

Significant Difference ◽

Motorized Vehicles

Noise due to motorized vehicles is a major problem in urban areas which can interfere with physiological and psychological health. This study aims to determine the extent of noise levels outside and inside the house around the function of different roads in Malang City, East Java, Indonesia. The study was conducted by measuring the traffic noise level using a sound level meter. Measurements were taken in the afternoon between 16.00-21.00 during the peak of heavy traffic and outside working hours when residents were already at home. Statistical Student’s t-test analysis was used to test differences in the average noise level outside and inside the house on each road function. Variance analysis was used to compare noise levels around primary arterial roads, secondary arteries, primary collectors, secondary collectors, primary local, and secondary local. From the measurement results, it is known that the noise due to motorized vehicles is 84.28 dB on average. This exceeds the threshold based on the Decree of the State Minister for the Environment Number 48 of 1996. There was a significant difference in noise level between outside and inside the house on each road function. There was no significant difference in noise level between the functions of the road segments both outside and inside the house. The results of the study concluded that the traffic noise level at 16:00 to 21:00 hours on all roads that were targeted for research exceeds the national threshold. It is recommended that the level of traffic noise around roads in the city of Malang can be reduced to minimize the negative impact on physiological and psychological health.

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Environmental noise levels and noise annoyance in Novi Sad, 2012-2016

European Journal of Public Health ◽

10.1093/eurpub/ckz186.256 ◽

2019 ◽

Vol 29 (Supplement_4) ◽

Author(s):

E Zivadinovic ◽

M Jevtic ◽

N Dragic ◽

S Bijelovic

Keyword(s):

Public Health ◽

Human Health ◽

Noise Level ◽

Urban Areas ◽

Road Traffic ◽

Public Health Problem ◽

Road Traffic Noise ◽

Residential Areas ◽

Novi Sad ◽

The Impact

Abstract Objective Increased noise level represents a significant public health problem in urban environments. The aim of this paper is to examine the annoyance of the population by road traffic noise in the City of Novi Sad. Methods The results of 161 24-hour noise measurements in Novi Sad were analyzed. Measurements were done by Public Health Institute of Vojvodina, according to accredited and standardized national methodology during 2012 - 2016. Results Total noise indicator (Lden) / night noise indicator (Lnight) ranged from 61,1 dB / 50,7 dB in residential, up to 66,3 dB / 58,1 dB in recreation / hospital areas, 68,0 dB / 60,3 dB in city traffic areas and 70,2 dB / 62,7 dB in business and residential areas. Taking into account the results and using methodology prescribed by national regulations, the percentage of highly annoyed population (% HA) was found to be in the range 11-25% during the day, and 6-13% during the night. Using ISO 1996-1:2016, prevalence of a population highly annoyed (PHA) was established to be in the range 9,2-33,9% in residential; 18,4-45,7% in recreation / hospital areas 22,9-50,6 in city traffic; 27,7-55,4% in business and residential areas. Conclusions The results confirm that urban noise seriously disturbs people. It was established that about a half of the population was highly annoyed which poses a serious challenge for public health. The results have social, health and economic importance for the population. Activities to reduce the noise level could also stimulate economic, health, social and community programs for sustainable development aiming to preserve and improve human health. Acknowledgment: Supported by the Ministry of Education and Science of the Republic of Serbia - Project “Biosensing Technologies and Global System for Continuous Research and Integrated Management”, No.43002 Key messages Continous noise monitoring is important for understanding the impact of noise on human health. About a half of the population was highly annoyed by noise, which poses a big challenge for public health in urban areas.

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Road Traffic Noise on the Santa Marta City Tourist Route

Applied Sciences ◽

10.3390/app11167196 ◽

2021 ◽

Vol 11 (16) ◽

pp. 7196

Author(s):

Dámaris A. Jiménez-Uribe ◽

Darwin Daniels ◽

Zoë L. Fleming ◽

Andrés M. Vélez-Pereira

Keyword(s):

Traffic Flow ◽

Noise Level ◽

Road Traffic ◽

Traffic Noise ◽

Environmental Noise ◽

Time Of Day ◽

Road Traffic Noise ◽

Sampling Point ◽

Heavy Vehicles ◽

Noise Levels

The objective of this study was to determine the influence of vehicular traffic on the environmental noise levels of the Santa Marta City tourist route on the Colombian coast. An analysis of vehicle types and frequencies at various times of the day over nearly a year helped to track the main sources of environmental noise pollution. Five sampling points were selected, which were distributed over 12 km, with three classified as peripheral urban and two as suburban. The average traffic flow was 966 vehicles/h and was mainly composed of automobiles, with higher values in the peripheral urban area. The noise level was 103.3 dBA, with background and peak levels of 87.2 and 107.3 dBA, respectively. The noise level was higher during the day; however, there were no differences between weekdays and weekends. The results from the analysis of variance showed that the number of vehicles and the noise levels varied greatly according to the time of day and sampling point location. The peak and mean noise levels were correlated with the number of automobiles, buses and heavy vehicles. The mean noise levels were similar at all sample points despite the traffic flow varying, and the background noise was only correlated for automobiles (which varied much more than the heavy vehicles between day and night).

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Urban Noise Modelling in Boka Kotorska Bay

PROMET - Traffic&Transportation ◽

10.7307/ptt.v26i2.1331 ◽

2014 ◽

Vol 26 (2) ◽

pp. 151-157

Author(s):

Aleksandar Nikolić ◽

Danilo Nikolić ◽

Emilija Nikolić ◽

Vesna Vujačić

Keyword(s):

Noise Level ◽

Urban Areas ◽

Road Traffic ◽

Noise Source ◽

Empirical Methods ◽

Noise Levels ◽

Sound Effects ◽

Noise Assessment ◽

A Site ◽

The Village

Traffic is the most significant noise source in urban areas. The village of Kamenari in Boka Kotorska Bay is a site where, in a relatively small area, road traffic and sea (ferry) traffic take place at the same time. Due to the specificity of the location, i.e. very rare synergy of sound effects of road and sea traffic in the urban area, as well as the expressed need for assessment of noise level in a simple and quick way, a research was conducted, using empirical methods and statistical analysis methods, which led to the creation of acoustic model for the assessment of equivalent noise level (Leq). The developed model for noise assessment in the Village of Kamenari in Boka Kotorska Bay quite realistically provides data on possible noise levels at the observed site, with very little deviations in relation to empirically obtained values.

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Prediction of L10 and Leq Noise Levels Due to Vehicular Traffic in Urban Area Using ANN and Adaptive Neuro-Fuzzy Interface System (ANFIS) Approach

10.4018/978-1-6684-2408-7.ch027 ◽

2022 ◽

pp. 597-611

Author(s):

Vilas K Patil ◽

P.P. Nagarale

Keyword(s):

Noise Level ◽

Urban Areas ◽

Road Traffic ◽

Traffic Noise ◽

Vehicular Traffic ◽

Noise Levels ◽

Anfis Model ◽

Neuro Fuzzy ◽

Interface System ◽

Artificial Neural Network Ann

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Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Traffic Noise

Journal of Advanced Transportation ◽

10.1155/2018/7949574 ◽

2018 ◽

Vol 2018 ◽

pp. 1-11 ◽

Cited By ~ 7

Author(s):

Mohammad Maghrour Zefreh ◽

Adam Torok

Keyword(s):

Traffic Flow ◽

Noise Level ◽

Urban Areas ◽

Road Traffic ◽

Traffic Noise ◽

Urban Traffic ◽

Road Traffic Noise ◽

Traffic Lights ◽

Urban Road ◽

Traffic Conditions

Road traffic noise is one of the most relevant sources in the environmental noise pollution of the urban areas where dynamics of the traffic flow are much more complicated than uninterrupted traffic flows. It is evident that different traffic conditions would play the role in the urban traffic flow considering the dynamic nature of the traffic flow on one hand and presence of traffic lights, roundabouts, etc. on the other hand. The main aim of the current paper is to investigate the effect of different traffic conditions on urban road traffic noise. To do so, different traffic conditions have been theoretically generated by the Monte Carlo Simulation technique following the distribution of traffic speed in the urban roads. The “ASJ RTN-Model” has been considered as a base road traffic noise prediction model which would deal with different traffic conditions including steady and nonsteady traffic flow that would cover the urban traffic flow conditions properly. Having generated the vehicles speeds in different traffic conditions, the emitted noise (LWA) and subsequently the noise level at receiver (LA) were estimated by “ASJ RTN-Model.” Having estimated LWA and LA for each and every vehicle in each traffic condition and taking the concept of transient noise into account, the single event sound exposure levels (SEL) in different traffic conditions are calculated and compared to each other. The results showed that decelerated traffic flow had the lowest contribution, compared to congestion, accelerated flow, free flow, oversaturated congestion, and undersaturated flow by 16%, 14%, 12%, 12%, and 10%, respectively. Moreover, the distribution of emitted noise and noise level at receiver were compared in different traffic conditions. The results showed that traffic congestion had considerably the maximum peak compared to other traffic conditions which would highlight the importance of the range of generated noise in different traffic conditions.

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Influence of Honking on the Road Traffic Noise Generated at Urban Rotaries for Heterogeneous Traffic

Environmental and Climate Technologies ◽

10.2478/rtuect-2020-0002 ◽

2020 ◽

Vol 24 (1) ◽

pp. 23-42

Author(s):

Kamineni Aditya ◽

Venkaiah Chowdary

Keyword(s):

Noise Level ◽

Road Traffic ◽

Noise Analysis ◽

Traffic Noise ◽

Heterogeneous Traffic ◽

Road Traffic Noise ◽

Good Precision ◽

Heavy Vehicles ◽

Noise Levels ◽

Noise Data

AbstractThis paper presents a study conducted at major rotaries for quantifying the traffic noise levels by considering the vehicle volume and their respective honking as governing parameters for heterogeneous traffic. Traffic volume and traffic noise data was collected using a digital video camera and a class 1 sound level meter, respectively. The traffic noise data was analysed using noise tools for identifying the noise level variation. The data collected was subjected to statistical analysis for light, medium and heavy vehicles, and their contribution towards noise levels is proven to be effective with the forthright fact that, heavy vehicles and their corresponding honking were majorly affecting the equivalent noise level compared to other vehicular proportion. An equivalent noise level [LAeq (dB)] rise of 2 to 6 dB (A) is solely caused by heavy vehicles, which is an important observation to be considered for traffic noise analysis at the rotaries. Based on the obtained results from one of the rotaries, noise prediction model is developed for estimating the LAeq (dB), which is able to predict the noise levels with good precision when validated with the data collected at second rotary intersection for different vehicle volumes.

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DETERMINATION OF DIVERSE ENVIRONMENTAL POLLUTION LEVEL FROM SELECTED AREAS OF RAWALPINDI, PAKISTAN

Journal of Mountain Area Research ◽

10.53874/jmar.v2i0.25 ◽

2017 ◽

Vol 2 ◽

pp. 16

Author(s):

S. Pervez ◽

M. S. Siddique ◽

H. Y. Abdullah ◽

A. Zahra ◽

N. K. Khanzada ◽

...

Keyword(s):

Heavy Metals ◽

Noise Level ◽

Urban Areas ◽

Power Plants ◽

Road Traffic ◽

Winter Season ◽

Ambient Air ◽

Sound Level ◽

Pollution Level ◽

Coal Consumption

Anthropogenic contaminants arising from both stationary (power plants, industries and residential heating) and mobile sources (road traffic) can harm ambient air quality in urban areas. Depending upon their physical state, these pollutants are classified as liquid and vapor phases and are subsequently transported to the Earth’s surface through dry and wet deposition. After the deposition of these pollutants onto the surface of earth various health effects caused by these pollutants occurred like cardiovascular diseases and hypertension. In this study four different locations/sites were selected from the Rawalpindi city depending upon the population, traffic rush and industries to examine the noise level, concentration of carbon dioxide and heavy metals. Air sampler was used for the collection of air sample to analyze the heavy metal concentration, Quest electronic sound meter for measuring sound level and SIBATA for CO2 measurement. The study findings revealed that noise level was higher at all selected locations as described by WHO limit (70 dB) being highest at Industrial area due to heavy machinery and lowest at green area. Concentration of all four heavy metals were high as compared with the prescribed limits. CO2 level reaches up to 300 ppm because of coal consumption during the winter season. The threshold values of all these selected parameters well above the prescribed limits defined by the authorities so to combat with this situation we should move towards more energy efficient fuels, proper maintenance of vehicles and machineries, traffic management and installation of noise barriers in industries as well as installation of catalytic convertors in vehicles to stop further air pollution.

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Spatial Mapping of Traffic Noise Levels in Urban Areas

Journal of the Transportation Research Forum ◽

10.5399/osu/jtrf.47.2.1711 ◽

2011 ◽

Vol 47 (2) ◽

Cited By ~ 1

Author(s):

Mohammed Taleb Obaidat

Keyword(s):

Noise Level ◽

Urban Areas ◽

City Planning ◽

Traffic Noise ◽

Sound Level ◽

Signalized Intersections ◽

Mapping Technique ◽

Residential Areas ◽

Noise Levels ◽

High Traffic Volume

This paper combines field data with an analytical approach to spatially map noise levels due to traffic movements at relatively high traffic volume signalized intersections utilizing the potential of Geographic Information Systems (GIS). Noise data were collected using a discrete mapping technique at 29 signalized intersections, as well as between intersections, and at their respective neighborhood areas in Amman, capital of Jordan. Data were collected in three different highly congested traffic peak periods: 7:30 a.m.-9:00 a.m., 1:30 p.m.-3:00 p.m., and 9:00 p.m.-11:00 p.m. A portable precision sound level meter capable of measuring noise levels from 34 to 134 decibels (dB) was used during the data collection process. The highest recorded noise level at some signals was 80 dB, while the lowest was 34 dB. In fact, some signalized intersections showed higher noise levels than the acceptable or the standard ones, i.e., 65 dB for daytime and 55 dB for nighttime in residential areas at city center. Two-dimensional (2D) vector and raster maps of noise levels, at different time periods for signals' areas and neighborhoods, were spatially displayed. Results showed that the developed GIS maps could be useful for city planning and other environmental management applications for the purpose of: 1) temporal monitoring and queries of noise level changes as a function of time, 2) spatial queries to find the highest noise disturbance location and its time of the day, 3) development of an online noise information system, 4) using noise level based spatial maps as indicators of variation in land prices, and 5) forecasting and current assessment of the acoustic climate of urban areas.

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