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.
Noise is unacceptable level of sound that creates annoyance, hampers mental and physical peace, and may induce severe damage to the health. Transportation operations are major contribution to in the modern urban environment; trafficnoise is generated by the engine and exhaust systems of vehicle, by aerodynamics friction and by the interaction between vehicles and its support system rail interactions). trafficnoise, thus, is a very important element in environmental impact studies, since car is one of the most used transportation mean in developing t is one of the harmful agents for citizenships; therefore many countries have n limits for vehicles and s to reduce roadtrafficnoise E1, 9, 13, showing an alarming rise and it exceeds the prescribed levels in most of the urban cities of developing countries like Nigeria and Akure in particular. Noise in big cities is considered by the World Health Organization (WHO) to be the third most hazardous type of pollution, right after air and Investigation in several countries shown that noise has adverse effect on human health, living in close proximity to
Data was analysed using MLwiN multilevel modelling software, where a random intercept model was used to take account of the hierarchical nature of the data, with pupils clustered in schools. Four models were run for each of the mental health outcomes; emotional symp- toms, conduct problems, hyperactivity and overall SDQ. Model 1 (unadjusted) contained early biological risk, air- craft and roadtrafficnoise at school; model 2 (adjusted) was the same as Stansfeld et al.  and included air- craft and roadtrafficnoise at school plus the potential confounding factors: country, gender, age, employment status, crowding at home, home ownership, mother’s educational attainment, long-standing illness, main lan- guage spoken at home, parental support for school work and classroom glazing type. Model 3 was the same as model 2 but with the addition of early biological risk as a main effect. Model 4 further added an interaction term between noise exposure at school (either aircraft or roadtrafficnoise) and early biological risk. Statistical significance was tested by comparing the goodness of fit of a model with, and without the variable, using a chi- square test of deviance. None of the models were affected significantly by the school level variance (level 2 variance).
The first is the potential for greater differences be- tween external noise levels and internal noise levels as a result of the extensive use of air-conditioning in Hong Kong’s subtropical climate. Exposure-response curves are constructed on roadtrafficnoise levels incident on the external façade, but there is logic in considering that the response may be shaped by the levels experienced inside the dwelling. Hong Kong has near universal installation of air-conditioning in dwellings—only 4% of the survey respondents reported their dwelling had none—and some 90% had air-conditioners fitted in their bedrooms, 93% in the living rooms. It is not that the acoustic properties of the window/façade material in air- conditioned premises would consistently be different to those of dwellings in other climatic zones, but the be- haviour of residents with respect to ventilation may be. There is a lack of empirical data, but anecdotally the op- eration of air conditioning tends to be associated with complete closure of windows whereas, with the heating of dwellings in temperate climates, a high proportion of the community is known to crack windows slightly open for ventilation during sleep . Complete window clos- ure would result in lower internal noise for a given external noise exposure, potentially shifting an annoyance- response curve downwards. Future studies in both tropical and temperate climates need to measure, diurnally and seasonally, detailed window-closing behaviour.
policy purposes we suggest that health costs should be eval- uated by means of the impact pathway approach (IPA) since it is sanctioned in the EU, but more importantly, is supe- rior to the alternative approach of relating the total estimated social cost to WTP estimates (as suggested by ASEK). More importantly, though, we believe that more research is neces- sary not only to study the relationship between annoyance and health effects, but also what effects are unintended and thereby not part of the individual’s WTP. The approach of adjusting the WTP estimates assumes that house owners are indeed unaware of the negative health effects and do not bear the full cost of noise related health effects. This is, as outlined above, in line with the general view among ana- lysts and policy makers. However, as also pointed out, the empirical evidence is limited. Therefore, if evidence instead suggests that house owners are well informed, and that the COI related to these health effects is negligible, the esti- mates from the hedonic price regression analysis should be left unadjusted.
ABSTRACT: Anthropogenic noise is debatably one of the most common threats to national parks' resources. Park visitors and workers generally suffer from adverse effects of noise from on- and off-road vehicles. The parks, studied here, are located in strictly urban areas, surrounded by streets with intense vehicle traffic. This study assesses the soundscape of urban parks in two cities of Odisha State, on the basis of acoustic field measurements and interviews. Noise descriptors in and around three different parks in Bhubaneswar and Puri cities have been measured and analyzed. A field experiment has been conducted with 330 participants in three parks, representing urban natural environment. The questionnaire comprised identification of the interviewee, characteristics of the user's profile in terms of his/her use of the park, and aspects of individual‘s perception of the soundscape and environmental quality of the park. Positive correlation has been established among the noise levels of these three parks. The present study reveals that the acoustic sound levels of all the investigated parks are more than 50 dB (A) [permissible limit, established by Central Pollution Control Board (CPCB) for green parks]. Considering the urban elements and acoustical characteristics, it can be concluded that all the parks are affected by several factors such as urban planning, land use, main traffic routes, type of public transportation, and its internal sounds.
Noise is an inevitable part of everyday life-a plane flying overhead, faulty muffler of the passing car, the television, dog barking, children playing. Mild noise can be annoying, excessive noise can destroy a person hearing. People do not easily become accustomed to noise. The slightest unwanted sound can become very annoying if it is continued for some time. Sound is the form of energy that is transmitted by pressure variation which human ear can detect. Sound waves need to travel through a medium such as solid, liquid or gas. The sound waves move through each of these mediums by vibrating the molecule in the matter. Factor such as the magnitude, characteristics, duration and time of occurrence may affect ones subjective impression of the noise.
Journal of the Acoustical Society of America, Volume 140 (2), August 2016, 978 987 Page In agreement with the distances from a road, when birdsong loudness increases (i.e., from 37.5 to 52.5 dBA), the masking effects become more significant in terms of Naturalness, Annoyance and Pleasantness. It is surprising that when the birdsong is 52.5dBA, the Perceived Loudness of the quiet trafficnoise environment is slightly lower than that when the birdsong is 37.5dBA, although they are not significantly different statistically. This phenomenon may be explained by examining the responses of an interview session after the experiment: when people heard birdsong, they described the sound environment with words as “natural” and “pleasant” rather than “loud”, suggesting that naturalness and pleasantness may distract people’s attention from loudness. Louder birdsong was evaluated to have higher naturalness and pleasantness 50 , which may result in less attention on loudness. Irrespective of masker loudness, Annoyance due to the trafficnoise environment increases and Pleasantness decreases sharply when the trafficnoise is louder than 47.5 dBA. Annoyance increases with an increase in the sound pressure level of birdsong when the trafficnoise is loud (higher than 57.5 dBA). Therefore this data suggests that adding natural masking sounds alone without attenuating trafficnoise level is ineffective in improving soundscape quality.
nighttime equivalent noise level, 2300–0700 h) was modeled for the most exposed façade of the building and assigned to each participant’s home address using geographic coordinates. The noise levels were calculated by the City of Oslo according to the Nordic Prediction Method for RoadTraffic and Railway Noise, respectively [29–32]. Geographic information system (GIS) method- ology was applied in the software package CadnaA . The grids for the noise calculations were 5 × 5 m and calculation height was 4 m above terrain. Within each grid, the noise level was interpolated at points along the façade with 3 m distance. Roadtraffic data included in the model (traffic counts, percentage heavy vehicles, speed limits, diurnal distribution) were obtained from the Norwegian Public Roads Administration and the City of Oslo. Other inputs to the model were digitalized terrain data in 3D including topography, soft vs. hard ground, location of buildings, and noise screens. For railway noise, input data included traffic frequency, signed speed, and train type obtained from the Norwe- gian state-owned company, Bane NOR, responsible for traffic management of railway property. Similar data for tram and subway traffic was obtained from Sporveien Oslo AS, a municipally owned public transport operator in Oslo.
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 noise pollution 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 noise pollution 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 noise pollution 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
Many researches are carried out to model trafficnoise so that it can be predicted in advance and preventive and mitigation measures can be taken for reducing noise impact. TrafficNoise Prediction Models aid in the design of environmentally friendly roads. Noise models can be used to determine the noise levels and its impact on an existing highway or on a proposed highway. Modelling of trafficnoise dated back to 1950’s. Post World War II witnessed a boom in the automobile population and this led to a serious concern in the field of trafficnoise prediction. Traffic prediction models in 1950s and 60s dealt with the modelling of single vehicle  based on constant speeds. It is assumed that the first noise model, considering volume and distance as parameters, was given in 1952 Handbook of Acoustic Noise Control. Later developments included different parameters like percentage of heavy vehicles, speed, composition, etc., for developing noise models which can be simple or complex [2-6]. Some noise models were developed using simple regression while others used fuzzy integrals or neural network [7-8] approach with a huge input data requirements. Simulation techniques were used in other cases for noise modelling . The noise models were developed for measurement and analysis of ambient noise levels on existing roadways, noise emission from vehicles and for before-after studies of infrastructure development. Dynamic models require a detailed set of database including the spatial characteristics and condition of each vehicle type. Considering the data requirement and limitation in time, multiple linear regression method was chosen for modelling trafficnoise.
Noise pollution is a form of air pollution and it should be control to improve policies and procedures in Health Impact Assessment (HIA). Noise control measures should consider acoustic performance, costs, effectiveness, durability, visual intrusion and safety. HIA is a tool to improve decision- making, to weigh the policy options in different sectors (Kumar et al., 2011). It’s a challenge to incorporate health into the capacity of planners and engineers to work with health professionals to conduct HIAs. Few criteria of policies and procedures were met Bangladesh, India, and Nepal likely 26 to 50% and Indonesia, Sri Lanka and Thailand met 51 to 75% (Caussy et al., 2003). Sharma et al. (2010) studied that the noise barrier and green belt can be designed to check the propagation of the noise due to traffic, industry and any new development and construction activities. Based on the existing noise level, Mishra et al. (2010) suggested for installation of barrier at BRTS corridor to reduce noise level.
Sound is define as the vibration that travel through the air or another medium and can be heard when they reach a person’s or animal’s ear. Noise is unwanted and unpleasant sound .In developing country like INDIA suffering from several environmental problems. These environmental problems include water, air, and noise pollution. Out of three, noise pollution is one of a major issue for people residing in urban areas. The factor contributing high noise levels because of increase in population, urbanization and increase in the traffic volume. For example the difference between normal conversation (65 dB) and someone shouting (80 dB) is only 15 dB but the shouting is 30 times as intensive. Trafficnoise is create a problem for a people who residing near highway.
Abstract: Noise can have negative impact on health. Hearing damage, annoyance, sleep disturbance, high blood pressure, poor cardiovascular health is all linked to community noise. Children, people with existing physical and mental illness and elderly people are most susceptible to community noise. High level of noise from sources such as busy traffic can adversely affect the health of the people living near road highways. It is therefore desirable to model a roadtrafficnoise that predicts well the trafficnoise near highways so that the people living near highways who are highly exposed by everyday trafficnoise can be protected from noise exposure to some extent . Measurement of noise level ( dB(A) ) by noise analyzer will be conducted on road segment of Tirupati town at different locations. In the present paper a roadtrafficnoise prediction model for Indian conditions is developed using regression analysis which is based on Microsoft Excel. Data collected has been analyzed and compared with the values predicted by analytical models . After comparison of results it was observed that Developed Model could be satisfactorily applied for Tirupati town conditions as they give accepted results with a good value.
exposure were based on published exposures measured in homes in urban areas, it is possible that in-home expo- sures in NYC are higher than other areas due to factors such as population density, housing stock quality, and street traffic volumes. Similarly, since exposure to envir- onmental hazards is a function of an individual ’ s daily ac- tivities and patterns, we have likely missed important variability in the durations of exposure to specific noise sources. Our measures of exposure durations for time spent in various activities rely completely on self-report, and time spent on streets or in noisy areas may have been subject to recall bias. This bias may be especially import- ant relative to other sources, as the amount of time spent on streets is much smaller than the amount of time sub- jects were exposed to the other five sources of noise we considered. It is also possible that the source of our sam- ple – adults surveyed at a street fair – may reduce the generalizability of our estimates of time spent on streets, as individuals who attend street fairs may spend more time on streets than those who do not. Data related to firearms noise among individuals who fire weapons for recreational or occupational purposes were not collected; while these exposures are expected to affect a small frac- tion of our sample, for those individuals who do use fire- arms this is likely their dominant exposure. If weekend noise levels in NYC differ substantially from weekday levels, our estimates of street noise exposures are biased high, and the true contribution of street noise to total noise exposure is lower than reported here. Finally, our noise level data were based on only short-term (10-mi- nute) measurements of daytime noise, however, Gan et al. noted that short-term noise samples are highly correlated with noise models and are therefore an acceptable method for assessing exposure to noise . Additional, longer- term, multi-day measurements are clearly needed to fully characterize the NYC environment.
This paper is an attempt for enhancing the roadtraffic model so that it could be used up in order to give much accurate results then the other conventional methods which are used until now. It is found that Calixto model mainly relies over the roadtraffic data in order to generate the levels of noise. But besides this road dimension factors also play a key role in the generation of noise levels. The RTM been discussed takes into account both the roadtraffic data along with the road dimensions aspects thus, is able to provide much accurate results. Thus, on the basis of the result been discussed above we could easily prefer RTM over Calixto model for the generation of noise levels. Thus, we could use RTM in Indian scenarios for much better results of generation. These results are obtained while carrying comparison on the basis of the value of average efficiency and 𝑅 2 (Coefficient of Determination).
Measurements are carried out at peak and lean traffic flow. Field measurements are made by using the Norsonic sound level meter for 15 minutes duration. The sound level meter is calibrated prior to each measurement using a Norsonic sound calibrator type 1251. Sound level meter is mounted on a tripod The distance of the microphone line was different for different sites, depending on the width of footpath and road. The distance of microphone from the plying traffic center-line for each site has been given in Table (ii). Vehicles are divided into five two wheelers, Three wheelers, car, bus and truck. Counts of number of vehicles crosses the point of measurement from either direction on the road is recorded with a video camera. Speeds are measured with a hand held radar gun along with the noise level. A typical measurement site is shown in the fig (i). The average A-weighted noise emitted of the individual vehicles plying on the roads is determined at six different measurement locations with an individual vehicle of each category running at its free speed.
The relationship between transport and land-use can be regarded as a two-way process. Firstly transport systems and investment can affect land-uses by altering accessibility and by altering environmental quality and conditions. These effects are not easy to measure and the major conclusion reached by numerous authors is that the impact of transport on land-use is relatively weak leading mainly to relatively localised redistribution of activities. Thus whilst availability of transport may be a necessary requirement for new development it is not, in isolation, sufficient to generate new land- use patterns. The second part of the relationship, namely the effect of land-use on transport, suggests itself to be more significant. This conclusion has arisen, in part from a recognition that the greatest proportion of the growth in roadtraffic over the past 20 years has arisen from people making longer journeys, primarily in the journey to work. The reasons for this trend are not altogether understood. In part it results from the migration and loss of employment in many of the densely populated urban areas but also due to people choosing to migrate away from urban areas, to the siting of new facilities such as retail facilities, hospitals etc, to changes in patterns of leisure activities and to a reduction in real terms in the marginal costs of motoring.
The role of transport in our daily activities cannot be overemphasized and without it, the necessities of life would be difficult to achieve. As wonderful as the role of transport may be in our daily activities, it has been noted to possess myriads of negative effects. This is why in the literature transport is describes as the maker and breaker of the cities. Ogunsanya (2002) confirmed how transport has built cities over the year in some urban areas in Nigeria and how it has gradually destroyed them. Filani (2002) stated that inadequate and poorly maintained infrastructure facilities, accident; the relative immobility of the disadvantage, waiting for a long period at the bus-stop, pollution from transportation; traffic congestion and parking problems are becoming acute in the city. Road vehicular accidents have been so frequent and common to everyday life.
Satellite Town ( Near Police Station), Satellite Town ( Jilani Khan Road), Sariab Link Road, Haji Yousif Home Street, SariabRoad,JanMuhammad Road, Sirki Road, Jan Muhammad Road, Faquire Muhammad Road, Kasi Road (Tin Town), Joint Road, Junction of Patail & Shahwak Shah Road, Kasi Road (near Kasi Kala ), Prince Road, Fatimah Jinnah Road, Alamdar Road, M.A. Jinnah Road, Toghi Road, Dr. Ghalam Nabi Road (near Govt. Muslim Abad High School), Circular Road (near White Road), Ghalib Road, Share- e-Gulistan Road (near Govt. Girls Degree College), Near Lourds, Manu-Jan Road, Hali Road, Zerghun Road, Jail Road (near Central Jail Quetta), Sammungli Road (near Shahbaz Town), Sammungli Road (near White Road),