India has mitnessed an explosive growth of population accompanied by uncontrolled organization over the last five decades. The population growth has been mainly centered around cities. Much of urban migration driven by rural; pollution desires for the advantages that urban areas offer such as opportunities to receive education, health care and service such as entertainments. These results into the extension are small towns in all direction, dense pollution at important commercial places, and tremendous increase in vehicular population. Rapid organization gives rise to unrestrained noise pollution and associated health effects and can cause both short term and long term physiological and psychological disorders.
Noise is one of the most significant sources of environmental pollution in modern cities. It can be defined as an unpleasant and unwanted sound, which now becomes a serious threat to urban life. Noise is like a physical form of pollutants which does not harm directly to the life supporting system namely air, water and soil. But its effects are more directly on the receiver i.e. human being 1 . The major cause of increasing noise is rapid urbanization, industrialization and population growth. Most of the Indian cities and towns like Visakhapatnam, Kolhapur, Asansole and Balasore have also been facing serious trafficnoise pollution in last few decades due to substantial growth of new vehicles, low turnover of old vehicles, inadequate road network and urbanization 2,3,4,5 . Assessment of trafficnoise level is difficult in Indian cities due to the heterogeneity in traffic and environmental conditions e.g., mixed traffic, congestion, road conditions, frequent honking and lack of traffic sense 6,7 . Therefore, it is important to consider such diverse factors in monitoring and assessment of trafficnoise level in the Indian context. Various studies carried out in India have shown that most of the cities are under the grip of high noise level than the standards prescribed by CPCB and MoEF 8,9 . The main objective of the present study is to assess the noise levels of Hyderabad city at various locations, i.e. commercial zones, residential zones and silence zones particularly educational institutions, hospitals and nursing homes, due to vehicular traffic under heterogenic traffic conditions. For this purpose, classified traffic volume and noise level are measured at different zones on roadways. In this study, traffic volume is categorized in 2-wheelers, 3- wheelers, 4-wheelers and 6-wheelers & above. Noise levels are measured for Leq, Lmin, Lmax, L10, L50 and L90. The terms Leq, Lmin, Lmax, L10, L50 and L90 are define as below.
Road side noise (Trafficnoise) is a most notable source of environmental pollution. Now a day with increasing number of vehicles, the noise pollution also has been increased. The present article focuses on the survey of various impacts of trafficnoise on road side shop owners and traders. Different five locations were studied in Kolhapur city. Assessment was done among the 100 respondents residing near traffic signals. The survey was conducted on self- prepared questionnaire. Responses from the people regarding to their health were considered for analysis. The outcome from this study shows the various negative health issues including psychological, physiological, sleep disruption, interference between communication, working efficiency, auditory impacts and the percentage of preventive measures have been taken to minimize the impact of noise. .
In the present work, the variables, traffic volume (Q), number count of heavy and light vehicles (p) and average speed of vehicles (V), junction speed, have been considered using the trafficnoise prediction model, as these variables are known to significantly contribute to the overall trafficnoise level, as also confirmed by the variable importance study, described later. Experimental data sets of these variables and the equivalent continuous sound pressure level (Leq), have been extracted from the different trafficnoise studies on 14 sites in July 2016. The locations have straight and flat roads. The sound pressure level (Leq) has been measured using a sound level meter how is an acoustic measuring instrument with the main features of a conventional sound level meter and integrator averaging, storage analyzers, NF EN 61672 class 1, tested and calibrated. The average speed of the vehicles has been obtained by using videography. A fixed distance (10 m) was marked on the road and the time taken by a vehicle to cover this distance was noted from the video. Thus, the speed was calculated for 3 vehicles and then the average was taken.
This study is concerned of assessment of public transport demand for Amravati and identifies the major factors for performance evaluation of public transport routes based on the identified performance indicators. In this study, a methodology is proposes develops a hierarchical structure to identify performance indicators for evaluation of quality of service of public transport routes. The rout is taken as 1) Amravati University to Badnera Railway Station 2) V.M.V To Moti nagar 3) Badnera Railway Station To Amravati Bus Stand. The data collected from user perspectives of public transport service like comfort level, safety level, travel cost, travel time, accessibility, user facility etc. these data were analysed by formulating a graphical form which give the information about public demand related to travel cost, travel time, comfort , safety , accessibility , user facility.
The essential demographic and geographic aspects of Madurai city during the study period were: population as per 2011 census=10.17 lakh, geographical area=248km 2 , latitude=9º56‟0” N, and longitude=78º7‟0” E. Also, the sampling locations for monitoring of trafficnoise pollution in Madurai city consisted of six typical zones such as school (with three locations), commercial (with three locations), residential (with three locations), hospital (with three locations), signalised intersections (with six locations), and bus terminals (with three locations).
IJSRR, 7(4) Oct. – Dec., 2018 Page 279 selected locations during 7:00am – 10:00 am, 12:00 noon – 3:00 pm and 4:00 pm – 8:00 pm. The noise level data are recorded with Data Logging Sound Level Meter (Model 407764, EXTECH Instruments) at the interval of 2 second intervals during the 10 minutes‘ exposure time for assessment of Noise Levels due to vehicular traffic flow peak (7:00am – 10:00 am and 4:00 pm – 8:00 pm) and non-peak hours (12:00 noon – 3:00 pm). This sound level meter measures the sound pressure level in dB (A) i.e. decibels in A-weighted scale which denotes the time weighted average of the sound pressure level on scale ‗A‘ which is Ambient sound levels are being compared with the prescribed standards of CPCB, India. The National Ambient Air Quality Standard in respect of Noise as specified under the Noise Pollution (Regulation and Control) Rules, 2000 is being referred for the present study. The sound level meter is placed at a height of 1.5 m above the ground level and at a distance of approximately 10 m from the centre line of the road. For each zone, one set of reading is taken during the stated three different periods of the day. Three sets of reading are taken at each zone on different week days for each time interval. Sound level meter is calibrated before taking reading in every day.
Road traffic conditions in India are getting worse day by day. About 65% of freight and 80 % passenger traffic is carried by the roads. The average number of vehicles in India is growing at the annual rate of 10.16% since last five years. Spending hours in traffic jam has become part of metropolitan life style, leading to health and environmental hazards. Unpredictable travel-time delays in Indian road networks due to traffic problems like congestion, road- accidents etc., are becoming a serious concern. This is the crucial reason why travel time reliability has received much attention from researchers and practitioners. It not only affects driver route choice behavior but also it is used in the assessment of transportation system performance. In past few years, the reliability of transport systems has been widely recognized as a key issue in transport planning. Travel time reliability is significant to many transportation system users, whether they are vehicle drivers, transit riders, freight shippers, or even air travelers. A personal and business traveler values the reliability because it allows them to make better use of their own time. Shippers and freight carriers require predictable travel times to remain competitive. Travel-time variability (TTV) has been defined in the literature as the variance in travel times of vehicles travelling similar trips However; the definition is better suited for measuring private rather than public transport, as confusion arises in the definition of “similar trips.” While private transport vehicles are treated as homogenous to some extent, public transport vehicles are noticeably different. By stopping at only selected stops, express routes are significantly faster than local routes, questioning the definition of “similar trips” particularly for practical purposes. Conversely, the availability of individual travel-time data of each transit vehicle will provide
Delays can be avoided or minimized when their causes are clearly identified. The aim of this report was to identify the delay factors in Road construction projects, since delays are considered to be a serious problem in the construction industry. According to the findings above, following points can be recommended in order to minimize and control delays in road construction projects: A. During study it was found that Personal conflicts between labors and management team or among labors should be minimized
Most alarming situation is with high noise levels in the silence zone of the city. According to “The Noise Pollution (Regulation and Control) Rules, 2000, the silence zone is an area comprising not less than 100 meters around hospitals and educational institutions. But from this study, it has been found that most of the hospitals, Nursing homes and educational institutions are established in either commercial places or nearby heavy traffic plying roads. Consequently, most of the hospitals, Nursing homes and educational institution premises are in the grip of higher trafficnoise levels than the prescribed noise standards of 50 dB (A) and they are not safe from noise induced disturbances.
Mishra et al., (2008) studied the adverse impacts of noise on male and female population comprising of different age groups in Roorkee. The analysis indicated that automobiles and loud speakers are major sources of noise pollution. Significant adverse impacts such as effect on hearing, interference with communication, annoyance, sleep disturbance, deafness, are noticeable from the respondents. Public awareness and education are some of the probable solutions suggested for mitigating the problems. Vidyasagar and Nageswar Rao (2006) studied ambient noise levels in Visakhapatnam, an industrial and sea port city in coastal Andhra Pradesh. Ambient noise levels measured at six different locations representing residential, industrial, commercial, and silence zones indicated high sound levels which is alarming. Ambika et al. (2015) mapped noise levels in Mumbai, which is considered as commercial capital of India with massive development projects pertaining to infrastructural and commercial sectors that will be continuing on a regular basis, and observed that the noise levels in the city, on the whole, were very high and above the permissible limits. Balashanmugam et al., (2013) studied the ambient sound levels in Chidambaram at various locations and found that they are higher than permissible limits. Vehicular traffic and air horns are found to be the main reasons for these high noise levels. Sundarakumar (2011) studied ambient noise levels in Vijayawada, a commercially busy city located along Krishna river in Andhra Pradesh. Thirty four noise samples analyzed in urban and rural areas indicated that the noise levels are elevated in urban areas compared to suburban areas. Balashanmugam et al. (2013) studied the noise levels at different locations belonging to four zones viz., residential, commercial, industrial and silence, in Cuddalore, Tamilanadu and opined that the ambient noise levels are exceeding the prescribed limits. Rapid and unplanned urbanization resulting in great influx of people from all parts of the region and country, improper management of town roads and traffics, lack of sufficient parking spaces and exponential growth of both private and public vehicles in the city are identified as the major reasons.
noise of 60–64 dB, and a much lower proportion to the lower levels (<55 dB). We have explained this as a conse- quence of the high-rise built form of Hong Kong where there is both high population and high traffic density. The exposure-annoyance response relationship for road trafficnoise in Hong Kong falls well within the tolerance limits of the Miedema and Oudshoorn  synthesized exposure- annoyance curve for the percentage of the population highly annoyed with road trafficnoise. Fit within a toler- ance interval, rather than a confidence interval, is appropri- ate in comparing the exposure-response relationship from a single new study with the results of a prior synthesis of exposure-response relationships. The percentages of the Hong Kong population who reported they were highly sleep disturbed by road trafficnoise also closely follows the exposure-response relationship for high self-reported sleep disturbance based on the pooled data used by Miedema and Vos . There has been a Western bias, and a temperate-climate bias, in the studies used in prior meta- analyses of human responses to road trafficnoise. How- ever, the exposure-response relationships for annoyance and self-reported sleep disturbance reported from the high-density, high-rise, sub-tropical city of Hong Kong are not inconsistent with these. This is an important finding for future urban planning and trafficnoise management of many of the projected mega-cities in the world that will be located in non-temperate climatic zones in Asia and else- where and whose urban forms can be expected to reflect that of Hong Kong more than of cities in the west.
In this study recording were taken in seven hospitals in Dire-Dawa city including public hospitals, private and one health center. Figure 1 shows that the average noise measured for eight days during morning from 9:00 to 11:00 AM and in the afternoon from 18:00 to 20:00 PM. The major sources are vehicles like bajaj and forces. The minimum average noise recorded near to Dire health center 56.7 dB in the afternoon; whereas the peak noise was recorded in the afternoon near to Delchora Hospital has a magnitude of 86.91 dB. The results we observed during the morning and night are above the recommended limit set by . The results confirm that in all cases near to hospitals the magnitudes of noise levels are high. This will not give comfort for patients in the hospitals, which aggravated their health problems. In most of the areas the noise levels is exorbitant with more than 80 dB average prevailing across the city during both morning and afternoon. This is mainly attributed towards congested traffic area and unplanned construction of hospitals. Most of hospitals were constructed near to the main lines of traffic and they are affected severely by noise pollution. It is considered as the best indicator of physiological and psychological impact on patients and workers within these hospitals.
Noise is an inevitable part of everyday life - the television, a plane flying overhead, a faulty muffler on the passing car, dogs barking, children laughing. Mild noise can be annoying; excessive noise can destroy a person's hearing. People do not easily become accustomed to noise. The slightest unwanted sound can become very annoying if it continues for any length of time. While some nearby residents may ignore the continuous hum of a busy freeway, others will never be able to ignore it and increasingly will find it irritating. Sound is a form of energy that is transmitted by pressure variations which the human ear can detect. When one plays a musical instrument, say a guitar, the vibrating chords set air particles into vibration and generate pressure waves in the air. People nearby May then hear the sound of the guitar when the pressure waves are perceived by the ear. Sound can also travel through other media, such as water or steel.
Johnson and Wood (1971) in their study have mentioned that periodical noisestudy is most appropriate and less expensive of course, continuous noisestudy is desirable but not necessary and is more expensive. On the basis of their study they have proved that use of 15 second sampling rates for 5 minutes would permit an accurate and efficient investigation of the sound level of the given area. Also, according to Code BS: 3425-1966, Measurement of noise emitted by motor vehicles, the sample time should be in between 5 minute to 55 minute.
Abstract— New development sites can impact the surrounding roadway system by adding to existing traffic volumes or altering traffic patterns. In addition to designing appropriate access for proposed developments, planners and developers should strive to maintain a satisfactory level of transportation service and safety for all roadway users. The Traffic Impact Study will provide guidance for site access, on site circulation, parking, and offsite improvements necessary to permit the street system to operate at a satisfactorily level of service. The present study presents a new trip generation equations and distribution model for traffic impact analysis for site development. The trip rate for proposed development is computed and trip distribution has been carried out using a correlation coefficient distribution model that is evaluated by the traffic patterns of the total trips generated from study area and the inbound or outbound traffic passing through the street link. The objectives of the study is to assess (i) whether the development will meet the City’s Minimum Transportation Standards for roadway capacity and safety; and (ii) Mitigating measures necessary to alleviate the capacity and safety impacts so that Minimum Transportation Standards are met using the correlation coefficient distribution model.
Abstract– Noise pollution is a problem increasingly acknowledged by authorities and governments around the globe. Geographical Information Systems (GIS) can conveniently be adapted together, analyze and present noise information. GIS provide framework to integrate noise calculation models with spatial data that can be used for building noise maps. Noise maps can be used to assess and monitor the influence of noise effects. In the reality, noise travels in all directions. Residents living in high rise buildings are also severely affected by trafficnoise. It is therefore important to develop noise maps that can show influence of noise in all direction. A case study was illustrated using noise maps for Chennai city. The quality of the results of noise effect studies depends on the quality of the data and models used. The integration of GIS and noise maps makes it possible to increase the quality of noise effect studies by automating the modeling process, by dealing with uncertainties and by applying standardized methods to study and quantify noise effects. It is found that the noise level in most places are above standard levels.
Abstract: Developing countries like India are climbing the ladder of development very fast. So in relation to the development there is rapid increase in traffic volume. Mainly traffic in developing country is heterogeneous nature that means it consist of vehicles that move with different speed, have different size, have different operating characteristics and vehicle spacing may also vary. There is acute need of an efficient and intelligent traffic system to deal with problems arising due to heterogeneous nature of traffic .Traditionally in India whatever design equations are used to design roads, considered the traffic nature as homogeneous but as said earlier Indian traffic conditions are heterogeneous in nature .This paper reviews the mixed traffic in cities and finds out which factor need to be considered in such mixed traffic conditions. In this paper we considered the microscopic parameters such as speed, flow, density at a signalized intersection, which intern will help to develop new equations for heterogeneous traffic conditions in Indian cities.
A study done by Mishra (2010) on traffic police in Indian population revealed high level of noise exposure in these individuals. They were found to be exposed to equivalent noise level in the range of 75 to 80 dB and maximum sound level of 103 dB at various traffic points. According to a study done by Shrestha et al (2011) in Nepal, they reported traffic police personal are in constant risk of NIHL. Similarly a study done by Corrêa Filho et al (2002) observed that risk of NIHL is even greater for long route bus drivers if they are in service for more than 6 years. Further, the study done by Gupta et al (2014) showed that a majority of traffic police were oblivious to the harmful effects of noise and did not consider it as an occupational hazard. Kumar et al (2005) showed high prevalence of hearing loss in tractor drivers. Santos and Castro Júnior (2009) reported changes in brainstem auditory- evoked potential latencies an early functional injury of the first auditory pathway afferent neuron. A study by Andrea et al. (2012) on drivers showed that the occurrence of hearing loss in the absence of complaints. Drivers of Public transport vehicles were exposed to excess equivalent noise on roads and 65% among them were having NIHL as reported by Muhammad et al (2007). Abdelmoneim (2003) reported that more hearing impairment and higher prevalence of hypertension among long route bus drivers than their counterparts operating in the city. From the above background, it is well evident that though there are sporadic studies carried out in growing cities of India, still there is a dearth of information regarding noise induced hearing loss among tempo drivers in north India.
Continued analyses of noise exposure may better eluci- date the relationship between the spatial patterns observed and their impacts on low income, different eth- nic populations, and children, particularly for these high density areas. In the US, noise issues are typically evalu- ated at the project level as part of the Environmental Impact Assessment process. However, in other countries noise impacts are increasingly evaluated within a Health Impact Assessment (HIA) process that considers more broadly the overall health of communities. The goal of HIA is to analyze and consider the direct and indirect health effects of public policy ranging from urban plan- ning and transportation to agriculture, energy and natural resources management. The GIS-model presented here for San Francisco can serve as an example of one quantitative tool within the HIA toolbox for the US. Considerable work remains to develop quantitative tools for HIA that can account for the numerous transportation-related health effects. Such tools can serve as a way to track the health of a community over time as it develops. Here, we have established a baseline for noise, which is essential for evaluating current and future changes in annoyance. Our estimate of 17% of the population at risk of being highly annoyed by noise is of considerable concern. Such high rates of annoyance highlight the seriousness of the noise problem for US cities.