Nowadays transportation noise becomes a major problem. There are some noises sources like motor-cycle, bus, trains, aero planes and cars. Roadtraffic has been the major source of annoyance. It is due to the large number of automotive vehicle in comparison with other machines. The mechanism of radiation of noise to outside from a vehicle has been different from the generation of noise inside the vehicle. The noise pass off depends on the relative levels, characteristics and the interaction of the directly spread noises from the vehicles. The most important noise source of the vehicles is the engine and its accessories. According to WHO the most important effects regarding trafficnoise are: psychological & physiological effects, work-related stress and increased risk of accidents. Environmental noise caused by traffic, industrial and recreational activities as their main local environmental problem especially in urban areas. It has been estimated that around 20 present of inhabitants in Indian suffer from noise levels that health experts consider to be insufferable, where most people become irritated. The same survey showed a significant rise in the public's willingness to take action to reduce noise.
 Pal and Bhattacharya(2012) examined the problems of reduction of individual’s efficiency in his/her respective working places because of roadtrafficnoisepollution in Agartala due to rapidly growing vehicular traffic. This paper deals with monitoring and modeling of the disturbances caused due to vehicular roadtraffic interrupted by traffic flow conditions on personal work performance. A relationship was developed between different trafficnoise parameters and its harmful impact on work competency of individuals. Regression equations developed to predict the percentage of high annoyance among the individuals are fit based on noise parameters and parameters related to traffic movements. In addition, statistical analysis was also carried out between measured and predictive values of the percentage of highly annoyed group of individuals. The present model will draw the attention of the State Government and will help the policy maker to take the necessary steps to reduce this problem.
7, 8, 14, 4, and 10]. Table 1 different standards of noise Level for various areas of a community. However, the recognition of trafficnoise as one of the main sources of environmental pollution has led to the development of mathematical models that enable the prediction of se level from fundamental variables such as the flow and velocity of vehicles among others. Trafficnoise prediction models are commonly needed to predict sound pressure levels, specified in terms of The models are also required as aids in design of roads and sometimes in assessment of existing, or envisaged changes in trafficnoise conditions. Some of the trafficnoise models that were designed to analyze the impact of noise in an
Within the last few years, concern about the protection of the environment has grown rapidly as it has become generally recognized that steady rise in pollution of all kinds cannot be allowed to continue indefinitely. The acoustic environment has likewise suffered from the increase in use and power of the machines in the workplace, increasing roadtraffic, larger aircrafts etc. To combat this, many countries have introduced legislation making it a legal requirement to measure noise levels to reduce noise from vehicles at the source and maintain acceptable noise levels in factories to prevent hearing loss. India has emerged as fast developing country resulting in an in- crease in activity of the workforce. In 1989, Central Pollution Control Board (CPCB) , promulgated the Ambient Air Quality Standards for Noise, hereby establishing the noise limits for residential, commercial and silence zone areas. For assessing the urban noise problem and suggesting the mitigation measure, it is imperative that accurate data be obtained/measured of the noise levels at different locations at different times of the day.
Conservative bias is expected from the latter, where those with missing data generally had lower socioeco- nomic status and thus higher rates of mental health pro- blems. In terms of the measures used, the parent-rated version of the SDQ may underreport internalising disor- ders , however, a self-report version is not available for this age group and may be less reliable , thus the parent-rated version represents the most appropriate measure under such circumstances. An additional tea- cher-rated SDQ would have improved the identification of externalising disorders but was not possible because of teacher burden [23,25]. The early biological risk vari- able combined information on gestation and birth weight preventing assessment of the individual contribu- tions of each variable, however such variables are likely to be highly related. Further, the early biological risk variable relied upon parental reports. Parents of children with early biological risk may be sensitised to perceive vulnerability in their children which could lead to increased reports of mental health problems for such children. Roadtraffic is a source of both noisepollution and air pollution which have both been linked to mental health outcomes [12,26]. This study did not adjust for the effects of air pollution which may act as a confoun- der or have a synergistic effect when coupled with noise . Despite these limitations this study benefits from the fact that a range of noise levels were investigated and that the findings adjusted for multiple sociodemo- graphic status factors.
82.28 dB, Leq ranges from 92.29 dB- 95.15 dB and TNI ranges from 118.52-138.26. The data recorded from all the different commercial sites were then compared with the standards prescribed by CPCB and BIS and was found to exceed the limits. There is no such city road where vehicles can run smoothly with optimum speed i.e. 45-50 km since there is always an obstruction either due to digging of road, construction of road, violation of traffic rules by pedestrian, cross the road as and when required without zebra line, disobeying the traffic lights, creation of traffic jam to both the sides at railway crossings, stray animals specially cows, oxen, dogs, pigs, poor condition ofthe road; and old vehicles, opening of shops along the roads, road encroachment, congested road. Competitive driving of the maxi cabs, the main transport system of Allahabad carrying only 10 persons/ vehicle. Since vehicular population of Allahabad is increasing enormously every year.
Due to the increasing population of vehicles on road, the noisepollution levels have risen beyond limits. No longer can a person travel from one place to another without being subjected to high intensity noise coming from vehicles. This noise can have varying effects on a person,such as hearing imparity, high blood pressure, stress etc. At traffic signals or traffic jams, people tend to horn relentlessly adding nothing but noise to the environment. This paper tries to solve this problem by proposing an IoT-Based solution. With the use of an ESP-8266 microchip and a sound sensor, the noise produced in the traffic can be reduced by cutting down on the unnecessary honking by drivers. Reduction in the levels of noisepollution helps to increase productivity, reduce stress etc.
Children of parents who live apart tend to split time between households, but only information on mothers address was available. To address this potential problem, we ran a sensitivity analysis were only children living with both parents were included. We also did sensitivity analyses where we excluded children who, according to the mothers, had been referred to a physician or psych- ologist due to attentional problems (to account for pos- sible diagnosis of ADHD). Further analyses compared estimates for roadtrafficnoise with and without rail trafficnoise included, with and without air pollution, and with and without children born preterm or with a birth weight of less than 2500 g. In only a few cases, not all the items were filled out. For these children, the sum score was divided by the maximum attainable score of those items completed (i.e., 7 completed items would have given a maximum score of 21). These incomplete cases were included in sensitivity analyses.
Lars Järup, who sadly passed away in 2010, was the principal investigator of the HYENA project. Other members of the study team are Maria Chiara Antoniotti, Salvatore Pisani, Alessandro Borgini, Federica Mathis, Giorgio Barbaglia, Matteo Giampaolo, Jessica Kwekkeboom, Oscar Breugelmans. Sean Beevers from Environmental Research Group, King ’ s College London provided air pollution data for London; Wim Blom provided air pollution data for Netherlands and SLB-analys provided air pollution data for Sweden. HYENA was funded by a grant from the European Commission (Directorate General Research) in Fifth framework programme, Quality of Life and Management of Living Resources, Key Action 4 Environment and Health (grant QLRT-2001-02501). This work was supported by the Economic and Social Research Council (grant ES/F038763/1) with additional funding from the European Network for Noise and Health (ENNAH, EU FP7 grant number 226442). The funders had no role in the study design, in the collection, analysis, and interpretation of data, in the writing of the article, and in the decision to submit the article for publication.
Vehicular noise is one of the most prevalent forms of pollution. Trafficnoise annoyance has become a major issue with the advent of fossil fuels and development in vehicle technology. Vehicular noise is dramatically increasing with the increased number of vehicle population, especially due to speeding vehicles. Amongst all the sources of noisepollution, vehicular noise has been identified as the most annoying and health impairing one. Therefore, it had become important to check the trafficnoise and enhance the environmental condition along the transportation corridor. This study attempts the development of roadtrafficnoise model for Indian condition. A statistical regression model for predicting roadtrafficnoise is developed based on A-weighted equivalent noise levels.
points data collected in the field using calibrated sound level meters CELL-450 and Quest-2900. Preliminary traffic information was obtained through city authorities. Measurements were done at the traffic peak time and also when the traffic was at its minimum, during three successive months. The numbers of crossing vehicles as well as their speeds were documented. All data processing was carried out in ArcGIS, and SPSS-W software environment. The study area of this research was the first district of Tehran, the capital city of Iran that is located in latitude 35° 45', North and Longitude: 51° 30', East (Fig. 1). The district faces a heavy traffic jam, and as such all major roads are the subjects of this research. In the 20th century, Tehran faced a large migration of people from all around Iran such that the city population reached to 11 million people in 2006. More than 3 million cars are running in the city now. A survey of urban noise was done to determine the positions of measurements using the available city maps and Ikonos imagery. Four types of survey practices were identified: receptor-oriented, source-oriented, randomly chosen, and density-oriented sampling methods [ 10]. In order to reduce any systematic tendencies, random sampling was exercised in this research.
As per FHWA guidance (December 2011) basically highway trafficnoise depends on volume of traffic, speed of the traffic and the number of trucks in the flow of traffic. Highway noise consists of total noise produced by all the moving vehicles on the highway which depends on the individual vehicles, type of the vehicle, mode of operation, characteristics of the vehicle flow and the relative proportions of the vehicle types included in the flow (Subramani et al., 2012). Traffic is a major source of noisepollution in Delhi and was surveyed by Singh and Davar (2004) using questionnaire survey. The design of urban noise surveys should take into account that the underlying structure of urban noise is largely determined by the disposition of transportation, and in particular, roadtraffic, noise sources (Brown and Lam, 1987). Effect of trafficnoise can be classified into three categories such as subjective effect (annoyance, disturbance, dis-satisfaction and noisiness), behavioral effect (interference with sleep, speak or any general task) and physiological effects (fright phenomena). For a long period of exposures to noise may produce deafens and further continuous noise causes cardiovascular effects, increases blood pressure and heart rates (Marathe, 2012). Pathak et al. (2008) studied that 85%
Roadtraffic is the most widespread source of noise in all countries and the most prevalent cause of annoyance and interference. It is directly proportional to the volume of vehicles. Increasing of population is increasing of vehicles and hence increasing of Noisepollution. The major sources of noise in automobiles are exhaust, intake, engine and fan, and tires at high speed. The noise output of all components increases with speed. The Roadtrafficnoise not only depends on volume of vehicles and also depends on several factors; some of them are Road conditions, Traffic clearance, Condition of vehicles, Speed of the vehicle and the people living near roadside (highway) are mainly exposed. For example the study conducted around the main roads inside the urban perimeter of Curitiba, simultaneous measurements were done regarding noise levels, vehicle flow and traffic composition and thus some mathematical models have been developed in order to estimate those sound pressure levels. It was confirmed that people living or working in these areas are exposed to noise levels beyond the legislated norms (Calixto et al., 2003) and the two models for predicting in-city road-trafficnoisepollution of Mashhad were obtained by Rahmani et al., (2010). Rail TrafficNoise
Abstract: The road activity is one of the noteworthy supporters of noise in the present decade causing undesirable living condition in urban domain. The issue of noise contamination has effectively crossed the danger point and is undermining as a slow agent of burden of disease. The present investigation is intended to review about the noise impact close to the fringe of the road in Vadodara city, Gujarat which is an eye-opener for the disgusting impact noted by both individual male and female respondents all around layout. It is suggested that Dynamic campaign is needed against noise for the successful reduction. Keywords: Noise, Urbanization, Effect, Respondents
Abstract- Noise, defined as unwanted or excessive sound, is an undesirable by-product of our modern way of life. In world health organization (WHO) statements, “large city noise is considered to be the third most hazardous pollution”. Amravati is the seventh most populous metropolitan city in Maharashtra state. Apart from Amravati district itself- Akola, Yavatmal, Buldhana, Washim, these district also comes under Amravati Division. The city is located on the national highway NH-6 leading to Mumbai in the west and Kolkata in the east. Several trips were required to identify enough sites that would meet the criteria and be appropriate for the measurement methods. In front of PRMIT&R, crossing at kondeswar square, crossing at MIDC, these three spots are taken into account for study. Noise barriers and building insulation are probable implications. In the study, the minimum and maximum noises level observed were 52.9 dB and maximum 104.5 dB. Basing on the findings in the study, it can be inferred that there is an urgent need to set up noise standards in the country to minimize the noisepollution.
The accuracy and quality of our proposal were confirmed through a comparison of results achieved in a previously estimated application. This improved methodology presented here ensures a well-founded weighting of the variables involve in the prioritization of road-traffic stretches, allowing a high extrapolation/generalization ability of the method. The methodology was implemented in a review of the Noise Action Plan for the Andalusian Road Network within the province of Almería (southern Spain). In fact, the methodology lends objectivity and rigor to the decision-making process in road stretch prioritization, supporting valuable arguments for the adoption and implementation of the Noise Action Plan, as well as public opinion (as required by European Environmental Noise Directive).
The noise originates from human activities, especially the urbanization and the development of transport and industry. Though, the urban population is much more affected by such pollution, however, small town/villages along side roads or industries are also victim of this problem. Noise is becoming an increasingly omnipresent, yet unnoticed form of pollution even in developed countries. According to Birgitta and Lindvall (1995), roadtraffic, jet planes, garbage trucks, construction equipment, manufacturing processes, and lawn mowers are some of the major sources of this unwanted sounds that are routinely broadcasted into the air. Though noisepollution is a slow and subtle killer, yet very little efforts have been made to ameliorate the same. It is, along with other types of pollution has become a hazard to quality of life. Kiernan (1997) finds that even relatively low levels of noise affects human health adversely. It may cause hypertension, disrupt sleep and/or hinder cognitive development in children. The effects of excessive noise could be so severe that either there is a permanent loss of memory or a psychiatric disorder (Bond, 1996). Thus, there are many an adverse effects of excessive noise or sudden exposure to noise. In India, the problem of noisepollution is wide spread. Several studies report that noise level in metropolitan cities exceeds specified 60dB. Murli and Murthy (1983) also found that trafficnoise in Vishakhapatnam exceeds 90dB even in morning hours that acts as a source of nuisance. The noisepollution is not a unique problem for developing countries like India only. In China, till third century B.C., instead of hanging men for dangerous crimes, noise was used for their torturing. The worrisome effects of noise are dangerous enough that noise problem is considered next to crime by certain countries (Kapoor
The increasing number of motorized vehicles in the roads especially in the populated area are the major contributor for noisepollution. This research aimed to study the problem of trafficnoise in the town of Tanjong Malim, Perak Darul Ridzuan. For this purpose, a total of nine randomly selected research stations covering the main streets, business center, school and the populated areas were randomly selected. Measurement and observation of level of noise parameters have been using the equipment called Integrating Sound Level data logger Extech Instruments Model 407780. The observations made were at least ten minutes for every observation time for the morning (between 8.00 am-10.00 am), noon time (between 12.00 noon-2.00 pm), evening (between 5.00pm-7.00pm) and night (between 10:00 pm-12.00malam) which covers weekdays and the weekends. The results showed that all value at the all stations is exceeded the standards set by the Department of Environment Malaysia; the noise level 65 dBA for the daytime and 55 dBA for the night-time. Passage area in front of North Gate UPSI recorded the existing Leq 76.6 dBA the highest existing Leq values compared to other nine stations on weekdays observation. Weekend observations recorded value almost similar to the days of the highest noise level recorded in the same way in front of the main door UPSI (74.8 dBA). Various other factors also contribute to trafficnoise in the town of Tanjong Malim, such as the proximity of a close to main roads, the higher number of heavy vehicles routing, the estate of vehicle engine and so on. Various mitigation measurement should be considered to negotiate this problem including the sound management aspect, awareness campaign through education, physical construction of natural fortress such as by planting trees between the noise provenance and receiver, efficient traffic management and by law enforcement.
Further research should inspect deeper connections between noise and health problems of the population. In the meantime, in order to improve managing noise levels, it is necessary to: identify the so-called black, gray and white acoustic zones; carry out a sharper control of redirecting heavy vehicles to the roads around the city, increase control of the noise emitted by motor vehicles during the technical inspection and daily traffic; continue with extending the network of streets with automatic traffic regulation and synchronization of traffic lights in certain directions; introduce time pieces on traffic lights that last more than 1 minute, especially at intersections with magistral significance; plan the installation of green and protective belts and arrange multi-storey plantations of various woody along traffic roads in order to reduce the level of municipal noise.
Noise map is an outstanding tool for controlling noise level in urban areas and thus helps greatly in town planning and is regarded as a useful tool to improve the level of environmental noisepollution. Noise map is considered as a power full tool to get the visual acoustic behavior of any geographical region, hence it is helpful to improve to environmental conditions regarding noisepollution and better town planning. So we made a noise map which is not only based on the data of that sixty location but besides that we have collected the data of thirty other locations.