Noise Level

The minimum average noise level was 83.5dB at Hari champa site while the maximum average noise level was 110.8 dB at Bharimata site. The high value was recorded at Bharimata site was due to two factors, the first one was the high traffic density with necessary or unnecessary blowing of horns by drivers, high speed. The second factor was high density from visitor people during 24hours of day. The minimum value was recorded at Hari champa because of low traffic density as well little plantation around with open space and garden in the vicinity of the 1km of the sampling site.

Several tests are designed to assess the auditory function in noise, and one of them is the acc- eptable noise level (ANL) test. This test was first developed in 1991 at Tennessee University by Nabelek et al. [3] and has been used for the central assessment of noise reception [4]. Since different levels of environmental noise affect amount and pattern of using HA [5], the NAL test was developed to assess the ability to hear in noise (tolerating the noise during listening to continuous speech); the test can also prospect the use of HA better than assessing the SPIN [1,5]. Hence, ANL denotes the amount of noise that one can tolerate during listening to speech in scalar quantity [3,6,7]. Few experimental stu- dies demonstrated that activities of subcortical regions such as the thalamus and limbic systems affected the scores of ANL test [8]. According to experiences of Plyler, after taking the medi- cine and receiving an effective dose, ANL scores were improved significantly in adults with attention deficit hyperactivity disorder (ADHD) [8], and the results indicated that subcortical regions affect scores in ANL test. To get ANL in most comfortable level (MCL), a recorded continuous speech (like a story) was presented to the patient and the noise ipsilate- rally was increased until the patient could foll- ow speech while hearing the maximum level of noise. The maximum level of acceptable noise called background noise level (BNL). The authors declared ANL in dB, and it is calculated using the following equation:

This project is to determine and identify the sequences of the NGV and merely focus it from the noise level area in the aspects of safety, durability and stability that might come from the usage of NGV. Even though the NGV has been proven to save the money and fuel respectively, there are still few researches on the safety, durability and stability mainly on the sound or noise level which can necessarily resulting in the sound pollution and other side effects which can probably reduces the vehicle’s performance.

Noise dosimeter and sound level meter with model 2310 SL and IEC 61672 type-2 factory calibrated with a resolution of 0.1dB were used. Measurements were taken one meter from the source of noise on each machine, and all the six (6) Machines were switched at the same time to determine the total noise generated. From the measurement of the noise, when the difference between the measured background noise level (that is when the machines are turned off), is equal to 10dB or more, the change in the resultant noise level after subtraction of the background noise level is negligible. But when less than 10dB, a correction is made to the noise level reading at a source to make the measured value valid using the addition and subtraction decibel scale. Measurements of sound level were done three times for each machine operation and the average reading was calculated and recorded in tables using Microsoft Excel spreadsheets.

Noise monitoring were carried out at all the locations during Peak hours (7.00 A.M to 11 A.M. in the morning and 5.00 P.M to 9.00P.M.in the evening). Sampling has been done at mid hour from 25 minute to 35 minute for 10 minutes duration. The noise level values are recorded at 15 second interval and hence for 10 minute duration, 40 data are recorded. The recording is done with the help of precision sound level meter of make „Bruel and kjaer‟ Denmark (2232) and in dB (A) weighting network. During the sampling process the distance from the centerline of the road was 10 meters and the height of sound level meter was 1.2 meter from the ground level.

and/or reasoning [2]. According to DSM-IV, children with learning disabilities are diagnosed when their achievement on individually admini- stered standardized tests in reading, mathema- tics or written expression is significantly below than expected for age, schooling and level of intelligence [3]. Children with LD have more difficulty in listening performance in the pre- sence of background noise than children without LD [4-7]. Learning disorder in children is the results of neurophysiological differences in the brain structure and function which affect a per- son’s ability in receiving, storing, processing, retrieving, or communicating information [8]. Acceptable noise level (ANL) which has been introduced by Nabelek et al. measures the amo- unt of background noise individuals are willing to accept while listening to the words of the story without becoming anxious or tense [9]. ANL is calculated by difference between the most comfortable level (MCL) for running spe- ech adjusted by listener and the highest self- chosen background noise level (BNL) that a listener will accept (ANL=MCL-BNL) [9]. ANL also can be administered by the examiner for the pediatric population (i.e. examiner turns intensity dial for the children) [10]. Studies have shown that ANL can predict hearing aid use [9,11]. People with small ANL are willing to accept more background noise and they would be successful hearing aid users, however, indi- viduals with large ANL are going to choose less background noise and they will be either unsuc- cessful or rejecter hearing aid users [9,11]. ANL is not correlated with hearing sensitivity, how- ever, it is mediated by more central regions of the auditory system [12]. ANL has been con- ducted among normal children in 2006, and it showed that measured ANL features in children appear to behave in the same way with ANL characteristics measured in adults [10]. In fact, ANL is a quick test which takes only 2-4 min- utes [10].

The requirements regarding the interior noise level of a cab for wheeled agricultural or forestry tractors are controlled by EEC regulations. A new prototype of tractor cab has been designed for new types of tractors, in which interior noise levels were measured using different types of isolation materials. Measure- ments were carried out while all openings of the tractor were closed, and also while all openings were left open. The speed of the tractor and the r.p.m. of the engine’s governor were held under defined limits. The interior noise level of the cab was moderated by using adequate absorbing and isolating materials for a defined frequency range. Lower interior noise levels were achieved by using elastic suspension between the tractor’s chassis and cab. To reduce interior noise levels some measures of modernization of the tractor’s chassis and cab were analyzed.

Abstract: Noise pollution is the excessive noise that may harm the activity or balance of human being. The sources of the most noise worldwide is mainly caused by atmospheric noise/environmental noise/occupational noise such as industrial machines, transportation systems and indoor noise generated by machines (particularly in some workplaces), building activities, domestic appliances and music performances etc. The main purpose of this study is to assess the impact and effect of noise emitted by traffic on the various links in the surrounding areas of an upcoming international airport. This study presents on site noise level measurement at 10 locations situated at 10 Km. radius from the Airport Reference Point (ARP) and on the various links around the airport. Noise monitoring was carried out at all locations for 24 Hours (Leq) in residential, commercial, Industrial and silence zone located in the surrounding areas of Kushinagar (U.P.) (India) airport during December-March 2017. FHWA model has been used for the prediction of noise level. The results show that noise pollution on various links are higher than the prescribed limits given by CPCB.

ABSTRACT: In order to significantly remove noise, most existing denoising algorithms simply assume the noise level is known. Moreover, even with given true noise level, the denoising algorithms still cannot achieve the best performance, especially with rich texture. In this paper, we recommend a patch based noise level estimation algorithm. Our approach includes the process of selecting low rank weak textured patches without high frequency components. The selection is based on the gradients of the patches and their statistics. The noise level is estimated from the selected patches using principal component analysis. Then we perform the denoising algorithm by using bilateral filter. We demonstrate experimentally that the proposed noise level estimation algorithm outperforms the state of the art algorithm.

Pollutant is a term used to denote a substance introduced into our natural environment that has a potential to cause harm to the living and non living constituents of our ecology. The pollutant may be a chemical substance when introduced into air causing air pollution, when introduced into water causing water pollution or when introduced into land causing land pollution or issues of solid waste management. The pollutant may also be in the form of energy causing noise pollution, thermal pollution or radiation pollution. Noise pollution is underrated mostly due to the fact that it can neither be seen, smelled nor touched. But the effects of Noise pollution on human health has been profound and WHO (World Health Organisation) has recognized it has the third hazardous threat to earth after air and water pollution. Noise pollution of urban area is increasing day by day due to increase in vehicular traffic and industrialization. To study the effect of noise pollution or for that matter any pollution the first step is to quantify the pollutant. So an attempt has been made through this paper to publish the results of a survey conducted to measure the noise level in Bharuch city of Gujarat state.

Today there is large growth in industrialization; therefore industrial noise has become a big environmental Problem. The noise that is generated by machines in industries is termed as industrial noise. This noise interferes with communication between supervisors and staff. Continuous exposure to noise can cause fatigue, which often results in accidents and reduces the pace and quality of work. Noise affects negatively on the day today life of surrounding people, who have faced with many problems mentally and physically. Workers are exposed to continuous noise throughout the workday, might results in some injuries such as hearing loss (temporary or permanent), weakness in nerves, pain in internal tissues, heart problems, and even higher blood pressure in long term. It is seen from the experimentation that a long exposure to noise over 85 dB might be a dangerous factor for high blood pressure (BP), and it may induce major problems amongst the sensitive individuals and hence more focus is required on noise control. Therefore, noise control is one of the major requirements to improve the living environment. Developed countries use sensible techniques to reduce the nuisance barrier walls, soundproof curtains, duct, acoustic panelling, sound enclosures for industrial machinery and different similar noise management treatments that area unit put in close to the supply to effectively cut back the sound level. However, India has not however yielded a lot of into this issue as noise reduction strategies area unit expensive. Therefore, it is necessary to find out cost effective methods to control industrial noise. This study emphasizes the vital role of algae dust, bamboo leaves, Coconut Coir Fiber, saw wood dust etc as natural sound reduction material, to give a solution for the existing industrial noise problems and also aimed to identifying the best practices in industries.

Similarly, residential zone (Jubilee Hills) of Hyderabad city have shown higher noise levels than the prescribed noise standard 55 dB (A). It has been observed that the variations of noise level, Leq in residential zone of the city is ranged from 72.5 dB (A) to 76.1 dB (A) in 1 st May 2011; 75.3 dB (A) to 76.1 dB (A) in 1 st May 2012; 74.6 dB (A) to 76.4 dB (A) in 1 st May 2013; 71.8 dB (A) to 77 dB (A) in 1 st May 2014; 77.6 dB (A) to 80.9 dB (A) in 1 st May 2015; 76.4 dB (A) to 78.4 dB (A) in 1 st May 2016 and 76.3 dB (A) to 88.2 dB (A) in 1 st May 2017 during 7:00 am, 10:00 am, 12:00 pm, 3:00 pm and 8:00 pm respectively. The noise levels of all times are above permissible limit 65 dB (A). This due to all types of crowded vehicle, narrow roads and poor traffic management.

From the noise survey, It has been observed that the variations of noise level, Leq in commercial zone of the city is ranged from 84.5 dB (A) to 88.2 dB (A) in 1 st May 2011; 83.5 dB (A) to 88 dB (A) in 1 st May 20112; 83 dB (A) to 87.4 dB (A) in 1 st May 2013; 81.9 dB (A) to 87.6 dB (A) in 1 st May 2014; 84.5 dB (A) to 89.4 dB (A) in 1 st May 2015; 85 dB (A) to 89.3 dB (A) in 1 st May 2016 and 85.4 dB (A) to 90.9 dB (A) in 1 st May 2017 during 7:00 am, 10:00 am, 12:00 pm, 3:00 pm and 8:00 pm respectively. The noise levels of all times are above permissible limit 65 dB (A). This due to all types of crowded vehicles mostly commercial, narrow roads and poor traffic management.

In order to evaluate the impact of the selection method (in- cluding the denoising procedure) we compare the results of Thorpe analyses without and with the selection procedure. Figure 5 shows histograms of the number of occurrences of inversions (blue-filled) and overturns (red-transparent) as a function of their sizes for all the LR profiles. The distri- bution of the detected inversions (blue-filled histogram) re- sults from the original potential temperature profiles (vertical resolution ∼ 6 m), without applying any denoising and selec- tion procedure. The distribution of the selected overturns for the same LR data (red-transparent histogram) results from the denoised (undersampled and filtered) profiles at a verti- cal resolution of ∼ 12 m. The selection procedure shows that only 11 % of the detected inversions can be regarded as over- turns. Consequently, due to both the noise level of RS data and the average stability of the troposphere, most of the de- tected inversions (91 %) are only due to instrumental noise! It is therefore necessary to apply a selection procedure in or- der to identify real overturns, at least in the troposphere.

Fig 4 shows the time weighted average noise level (TWA) which is obtained from 30 students who are carried out their work project at construction workshop in IKBN, Hulu Langat. These hand tools activities were included in impulse noise because the occurrence is not continuously. The result shows the maximum and minimum of TWA is 88 dB (A) and 46 dB (A) respectively.

Buffer zones are undeveloped, open spaces which border a highway. Buffer zones are created when a highway agency purchases land or development rights, in addition to the normal right- of-way, so that future dwellings cannot be constructed close to the highway. This prevents the possibility of constructing dwellings that would otherwise have an excessive noise level from nearby highway traffic. An additional benefit of buffer zones is that they often improve the roadside appearance. However, because of the tremendous amount of land that must be purchased and because in many cases dwellings already border existing roads, creating buffer zones is often not possible.

Noise Level that over a given time expends the same amount of energy as the fluctuating level over the same time period. (MPCB, 2005.,P. Saler, 2012).The readings noted in fractions, were rounded off to nearest integer in the observation tables. To detect the actual rise in the noise level a set of readings was taken on a normal working day. To get better understanding of noise range noise climate (NC) index (Pathak, 2008) was calculated using following formula:

One of the functions of exhaust muffler is to reduce the engine exhaust noise without affecting engine performance. In recent years automotive industries are focusing on achieving sound signatures. The exhaust system is developed to control not only the vehicle pass- by-noise but also the vehicle interior noise. The structure borne noise created through the exhaust system also a major contributor to the overall exhaust performance level. The radiation noise from the exhaust in certain frequency affects the rear seat passenger ear noise level which should be avoided. The radiation noise targets differ from vehicle to vehicle and will differ based on engine capacity, fuel type, vehicle application etc. so a standard development methods should be depicted for controlling radiation noise. The exhaust system design should be focused on tail pipe noise and shell orifice noise reduction. This paper will be focused on depicting tactical solutions to control shell radiation noise with precise technological methods without affecting the exhaust performance and achieve desirable outcomes during the process of exhaust system design.

These researchers investigated ATTS in a military context: what ATTS would be expected in US Air Force personnel exposed to continuous noise during a flight mission lasting as long as 48 hours? The threshold shift at 4 kHz, widely acknowledged as the most noise-sensitive frequency of human hearing, was used to determine a noise level which might produce no ATTS, in other words, a value of Effective Quiet. Groups of subjects were exposed to pink noise (with equal Sound Pressure Levels for the octave bands ranging from 125 Hz to 4 kHz) at 80, 85 and 95 dB(A) for periods of 24 hours and 48 hours. TTS was measured throughout each exposure period, for comparison with each individual’s pre-test audiogram. For each exposure condition, the TTS increased rapidly over the first few exposure hours, to approach the asymptotic TTS.

Abstract: Level of vehicular noise pollution is one of the major factors to choose pedestrian mode of transportation among other modes of transportation. Transportation systems and their related outcomes are responsible for ensuring safe travel options, including walking people of all ages and different abilities. This study will provide an opportunity to quantify the environmental impact in terms of noise level for future development and planning of pedestrian infrastructure in India. It will also help in modal shifting towards walking, improvements in energy efficiency, and the impact of specific contaminants on health. Exposure of high noise level can cause annoyance and severe stress on auditory and nervous system of pedestrians. Most of the Indian cities have noise level above than acceptable limits because of rapid urbanization with increasing number of vehicular traffic. The objective of this study is to study response of pedestrians towards noise pollution in Roorkee at different locations based on different land use. Roorkee is a medium size city with a population of 2.73 lakhs (Roorkee Metropolitan areas, 2011 census), situated in Uttarakhand, India. It is a city with large number of educational institutions and sizable numbers of student population. Noise level study has been carried out at ten locations on NH-58 near Indian Institute of Technology Roorkee. Noise data was collected at an interval of 30 seconds. Design implications for future improvement of pedestrian infrastructure have been presented in this paper considering traffic noise as an environmental factor. It is expected that the study outcome shall be useful in understanding positive effect of low traffic noise encouraging increased usage of pedestrian facilities within urban transport network.