Curr Pollution Rep (2017) 3:220–229 DOI 10.1007/s40726-017-0062-8
NOISE POLLUTION (PH ZANNIN, SECTION EDITOR)
Environmental Noise in India: a Review Shreerup Goswami 1 & Bijay K. Swain 2
Published online: 24 June 2017 # Springer International Publishing AG 2017
Abstract Purpose of Review This article reviews the literature on research carried out during the last two decades on noise impacts in India to demonstrate the current status of noise pollution research in India and gaps in studies. It also summarizes future perspectives of acoustic research. Recent Findings The noise pollution studies over the years have focused on the monitoring, recording, modeling, geospatial mapping, and exposure-effect relationship. The review of papers demonstrated that road traffic noise is the predominant cause for annoyance among the respondents. The evidence comes mostly from studies focusing on health impacts. Only 10% of articles enumerated zone-specific noise pollution. 44.89% of articles reported details of subjective response data with the help of a questionnaire tool, while 14.3% of articles reported details about the noise in workplaces of different areas of India. Ten percent of articles attributed to the harmful effect of festive noise. Studies in relation to the physiological and sleep disturbances in Indian condition are negligible. Summary Noise pollution limits are being breached in almost all Indian cities. Violations are the worst in urban areas. The laws should be properly implemented in India to control this ever-growing menace. The government is now working on devising new noise pollution standards. City-wise noise pollution mitigation strategies should be worked out at all levels. This article is part of the Topical Collection on Noise Pollution * Shreerup Goswami
[email protected]
1
P.G. Department of Earth Sciences, Sambalpur University, Jyoti Vihar, Burla, Odisha 768019, India
2
D.I.E.T, Remuna, Balasore, Odisha 756019, India
It is concluded that coordinated and long-term integrated noise pollution research (comprising assessment of noise descriptors, noise mapping, prediction by noise modeling, and experimental studies to demonstrate exposure-effect relationship, advanced study on acoustic absorption material) is the need of the hour. Keywords Road traffic noise . Festive noise noise . Noise modeling . Zone-specific noise
. Workplace . India
Introduction We love silence like one and all. On the other hand, we, Indians, equally enjoy noise pollution. Our marriage and even burial processions/cremation must be accompanied by bands, twists, and Bhangras. Spiritual celebrations must be heard by one and all, day and night. Akhand paths, Harinam Sankirtan, Azan in India must use loudspeakers and amplifiers. We also make the environment noisy by bursting crackers on the occasions of marriages, on Dussehra, Deepawali, especially on the processions of idol immersions, winning an election, and in many other festivals. We, Indians, do not care of the noise, while immersing thousands of idols of Mother Durga, Saraswati, Laxmi, Kali, Lord Biswakarma, Kartika, and Ganesh in water bodies making ceremonial farewell and procession with film songs and drinking country liquors. Unless we do not blow away our eardrums, we are not happy. A measure of happiness is expressed here in India by creating loud noises. Even childbirth is informed by the crackling sounds. In almost all old Indian cities, we have congested roads and busy slow-moving traffic having hundred of motorbikes, rickshaws, bicycles, cars, and heavy vehicles. Nevertheless, we use air horns even in motorbikes, bicycles, rickshaws, and cars. Too much honking of the horn is our regular practice in
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these congested roads. Such crowded traffic contains irregular peaks and varied noise levels. Poor urban planning in old cities gives rise to acute noise pollution. In modern times, noise is recognized as a serious health problem. Annoyance caused by noise has been known since antiquity, but it is only during recent times that the importance of environmental factors is taken into consideration in transport planning decisions. In fact, of the environmental pollution factors that are affected by the use of transportation means, noise is perhaps the most commonly cited [1–3]. The technical problems associated with the design of quiet vehicles are still not solved. It is also imperative to consider the subjective human sensitivity to noise exposure. For instance, halving the acoustic power of a sound source results in only a 3 dB reduction of the noise level, and this is scarcely noticeable to the average listener. In urban areas, the contribution of traffic noise is 55% of the total environmental noise [4–6]. Long-term exposure to traffic noise is found to be associated with cardiovascular disease, cognitive impairment, sleep disturbance, tinnitus, annoyance, increased risks of mortality, mental health impairment, central obesity, and non-Hodgkin lymphoma in general population. Daytime traffic noise level is more than 50 dB (A) (the guideline recommended by World Health Organization for day time for the outdoor living area) in different cities of the world. Most of the Indian cities and towns have also been facing serious traffic noise pollution in the last few decades due to a substantial growth of new vehicles, low turnover of old vehicles, inadequate road network, and urbanization. This Review depicted that the average road traffic noise is more than 70 dB (A) in most of the Indian cities. Appraisal of traffic noise level is complicated in Indian cities due to the heterogeneity of traffic environment having overcrowded vehicles of all kinds, different road conditions, and lack of traffic sense [7, 8]. In this study, the noise pollution of different parts of India is discussed hereunder.
Methods Altogether, 49 articles (47 journal articles and 2 conference proceedings) published in last 20 years were reviewed to reveal the status of environmental noise and its impact in India. Methods described by Omlin et al. [9] were adopted for conducting this review of literature. The related articles were searched by Bstring search^ in search engines, Bdatabase search^ (Google Scholar, Pub-Med, SCOPUS, Taylor Francis, Springer, Wiley online library, Elsevier etc.), Bconference proceedings search,^ and Bauthors’ library search.^ String searches included few keywords, such as Broad traffic,^ Bnoise pollution,^ Broad traffic noise,^ Btransportation noise,^ BVehicular noise,^ BImpact of noise on health,^ Bnoise in offices, banks, hospitals, educational
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institutions,^ Bfestival noise,^ Bsleep disturbance,^ Bannoyance,^ Broad traffic noise modeling,^ Bnoise mapping,^ Bnoise and traffic policeman,^ and Bnoise impact assessment.^ All the relevant and identified articles and papers were read in full and used for information extraction and stored in the database with details of publication particulars, study location, period, approach, methodology for assessing noise exposure, sampling, results of exposure-effect, and major conclusion. To interpret the status and quality of work carried out in India, the methodology described by Omlin et al. [9] has been undertaken with some modifications to suit the purpose and objective of the review. The norms adopted to evaluate the quality of the articles included the following: a. Well-defined population study (i.e., age, gender, and number) b. Precise description of subjective exposure to noise (viz.; location, specific time, and duration of noise monitoring, traffic volume, audiometric study, questionnaire survey) c. Declaration of statistical methods used d. Sample size: small (less than 50), medium (50–200), and large (more than 200) e. Random sample selection Accordingly, 49 relevant articles on noise and its impact in India were preferred for necessary review. For data analysis, a narrative synthesis is used in this review, as there are too much heterogeneity studies that preclude any meaningful statistical summary. In the case of the narrative synthesis, the summary of the findings is a narrative one instead of a statistical summary. The primary methodologies of the studies were tabulated (Table 1). Similarities and differences between studies were investigated. Studies with Special Emphasis on Road Traffic Noise Chakraborty et al. [10] reported the status of vehicular noise pollution and community response in Kolkata in different seasons (1998). Based on the annoyance survey, regression association of noise parameters and percent of the highly annoyed population were developed along with mean dissatisfaction score (MDS) predictions. It was reported that 30% of the respondents were highly annoyed with vehicular noise. Singh and Davar [11] studied noise pollution and its effect on human health of the people in Delhi. It also revealed that reduced efficiency due to interference with communication and sleeplessness was one of the imperative effects of acute noise pollution. Eighty-three percent of respondents were affected by noise emanating from the loudspeakers. Fifty-eight percent of respondents claimed that noise originating from religious functions affects them. Fifty-four percent of respondents acknowledged the adverse effect of noise generated by neighborhoods. Thirty-five percent reported the deafness and
Jaipur Jaipur Jaipur Amravati Bhadrak Bhubaneswar Cuttack Kolkata Kolkata Delhi Yavatmal Agra-Firozabad Angul Sambalpur Coimbatore Rourkela Balasore NH 316 Raygada Baripada Puri
Agarwal and Swami [19] Agarwal and Swami [20] Agarwal and Swami [21] Patil et al. [22] Swain et al. [23] Swain et al. [24] Swain and Goswami [25] Chowdhury et al. [26]
Chowdhury et al. [27] Mishra et al. [28] Parbat et al., [29] Arora and Moshahari [30] Pradhan et al. [31] Pradhan et al. [32] Subramani et al. [33]
Goswami et al. [34]
Swain and Goswami [35] Swain et al. [36] Sahu et al. [37] Swain and Goswami [36] De et al. [39]
Field survey
Asansol Balasore Balasore
Banerjee et al. [16]
Goswami [17] Goswami et al. [18]
Field survey Field survey Field survey
Ahmedabad Dehradun Asansol
Tripathi and Tiwari [13] Ziauddin et al. [14] Banerjee et al. [15]
Field survey
Field survey Field survey Field survey Field survey Field survey
Field survey
Field survey Field survey Field survey Field survey Field survey Field survey Field survey
Field survey Field survey Field survey Field survey Field survey Field survey Field survey Field survey
Field survey Field survey
Field survey
Delhi Jalgaon
Field survey
Calcutta
Singh and Davar [11]
Field survey
Nagpur
Chakraborty et al. [10]
Ingle and Pachpande [12]
Field survey
Chennai
Kalaiselvi and Ramachandraiah [7] Vijay et al. [8]
Journal article Journal article Journal Article Journal article Journal article
Journal article
Journal article Journal Article Journal article Journal article Journal article Journal article Journal Article
Journal article Journal Article Journal article Journal article Journal article Journal article Journal article Journal article
Journal article Journal article
Journal article
Journal article Journal article Journal article
Conference article
Journal article
Journal article
Journal article
Journal article
Type of study Data source
Location (study area)
Indian studies on different aspects of environmental noise from 1998 to current
Author
Table 1
Yes Yes Yes Yes Yes
Yes
Yes Yes Yes Yes Yes Yes Yes
Yes Yes Yes No Yes Yes Yes Yes
Yes Yes
Yes
Yes Yes Yes
Yes
Yes
Yes
Yes
Yes
Noise measurement
No No No Questionnaire No
No
No Questionnaire No No Questionnaire Questionnaire No
Questionnaire Questionnaire Questionnaire Questionnaire Questionnaire Questionnaire Questionnaire No
Questionnaire Questionnaire
No
Questionnaire No No
Questionnaire
Questionnaire, audiometric studies Questionnaire
No
No
Measurement of effects
Yes Yes Yes Yes No
Yes
Yes Yes Yes Yes Yes Yes Yes
Yes Yes Yes No Yes Yes Yes Yes
Yes Yes
Yes
Yes No Yes
No
Yes
Yes
Yes
Yes
Statistical method applied
Yes Yes Yes Yes Yes
Yes
No Yes Yes Yes Yes Yes Yes
No No No No No Yes No No
No No
No
No No Yes
No
No
No
No
No
Modeling used
No No No 351 No
No
No 350 No No 578 502 No
450 350 550 500 202 539 614 No
136
No
86 No No
Not reported
150
1100
No
No
Sample size
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Baripada Arati steel plant, Odisha Seragarh, Nilgiri, Remuna and Mitrapur Balasore Cuttack Balasore Jalgaon city Birbhum, Burdwan Meerut Balasore Raipur Balasore Kolhapur
Goswami and Swain [44] Keretta et al. [45]
Goswami and Swain [47] Swain and Goswami [48] Swain et al. [49] Pachpande et al. [50]
Mondal and Das [51] Singh and Joshi [52] Goswami et al. [53] Ahirwar and Bajpai [54]
Swain et al. [55]
Saler and Vibhute [56]
Goswami and Swain [46]
Field survey
Field survey
Field survey Field survey Field survey Field survey
Field survey Field survey Field survey Field survey
Field survey
Field survey Field survey
Field survey Field survey
Balasore Bhadrak
Goswami and Swain [42] Goswami [43]
Datta et al. [41]
Thiruvananthapuram, Field survey Kochi and Kozhikode Burdwan Field survey
Sampath et al. [40]
Journal article
Journal article Journal Article Journal article Conference article Journal article
Journal article Journal article Journal Article Journal article
Journal article
Journal article Journal article
Yes
Yes
Yes Yes Yes Yes
Yes Yes Yes Not reported
Yes
Yes Yes
Yes Yes
Yes
Journal Article Journal article Journal Article
Yes
Noise measurement
Journal article
Type of study Data source
Location (study area)
Author
Table 1 (continued)
No
No
No Questionnaire No Questionnaire, audiometric studies Questionnaire No No No
No
No No
Questionnaire Questionnaire
No
No
Measurement of effects
No
Yes
Yes No Yes No
Yes Yes Yes No
Yes
Yes No
Yes No
Yes
No
Statistical method applied
No
No
No No No No
No No No No
No
No No
No No
No
No
Modeling used
No
No
No 102 No Not reported 138 No No No
No
No No
317 256
No
No
Sample size
Curr Pollution Rep (2017) 3:220–229 223
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mental breakdown due to noise pollution. Annoyance by loudspeakers during festivities and honking of vehicles was felt by age groups of 20–40 years. Ingle and Pachpande [12] conducted a community survey on traffic noise among residents of Jalgaon city. The audiometric study depicted mild hearing impairment in both the target groups (exposed and unexposed population). The moderate hearing loss was reported in many exposed inhabitants. It was observed that the self-reported hearing loss using the screening questions and rating scale were the moderately good measure of hearing impairment in comparison to audiometric assessment. It was reported that 81% of those surveyed were affected by noise from the highway in comparison to the unexposed group (61%). It was concluded that the exposure of the population to higher noise levels had affected the hearing capability of the inhabitants of this area. Tripathi and Tiwari [13] reported attitude of traffic personals towards transportation noise in a study in Ahmedabad. No traffic noise monitoring was reported for this study. The questionnaire survey of the policemen revealed that 11.6% respondents grumbled of regular tinnitus, whereas 62.8% had experienced tinnitus during working hours only. It was inferred that self-assessed prevalence of reduced hearing was found only in two (2.3%) respondents. Ziauddin et al. [14] monitored Leq and traffic density in Dehradun city and found acute traffic noise pollution. Maximum noise pollution level was 102.7 dB and Leq was 83.7 dB. Banerjee et al. [15, 16] monitored different noise descriptors to depict the impact of road traffic noise on the local inhabitants of Asansol town. Formulation of noise risk zones, analysis of noise impact, and noise maps were worked out. The relationship between traffic noise levels and annoyance was studied using correlation, linear, and multiple linear regression analyses. The mean value of percent of population highly annoyed (HA) due to road traffic noise was 26.50 ± 3.37 (19.44–33.2), whereas the MDS was 2.96 ± 0.90 (1.04–4.45). The study demonstrated that noise index-based models endowed with better annoyance predictions in comparison to vehicular input-based models. The study identified two direct impacts of traffic noise pollution, namely speech interference during the day and sleep disturbance during the night. Mean Ldn value ranged between 55.1 and 87.3 dB (A). It was reported that the maximum Leq level for daytime and night time was 89.0 dB (A) and 81.9 dB (A), respectively. It was concluded that the monitored noise level in all the locations exceeded the limit prescribed by CPCB. The populations in this industrial town were exposed significantly towards high noise level, which is caused predominantly due to road traffic. The study revealed the fact that type of zone, geographic features, landscape, and topography are also imperative factors on which noise emission and transmission depends.
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Goswami [17] studied road traffic noise in Balasore town and undertook a questionnaire survey to reveal impact of vehicular noise. The study of Goswami et al. [18] demonstrated that the noise levels along the road connecting two campuses of Fakir Mohan University, Balasore, are more than 70 dB. The questionnaire survey among the local inhabitants of Remuna depicted that they were suffering from tinnitus, bad temper, hearing problem, and loss of concentration due to traffic noise levels. Agarwal and Swami [19] made a correlation between annoyance level and different noise indices of traffic noise in Jaipur city. A quantitative point scale of MDS was introduced to evaluate noise annoyance. A set of regression equations were developed between mean noise index (Leq, L10, Lmax, Ldn, and TNI) and percentage of the person highly annoyed (HA) and MDS. It was observed that among the subjects, the reported percent of HA ranged between 17.07 and 39.69%. It was concluded that a strong correlation existed between the percentage of persons highly annoyed and various noise indices. Agarwal and Swami [20, 21] examined the problems of noise pollution and its impact in terms of annoyance in urban areas in Jaipur city. Prediction of noise annoyance due to vehicular road traffic was carried out in these studies. In this studies, the relationship between linear and multiple regression equations with the help of different traffic noise parameters (Ldn, TNI, Lmax, Leq, Q, Qh, Q2w, and Vs) and its impact on exposed individuals were assessed. It was concluded that the regression model was satisfactorily applied with a deviation of −1 dB (A) to 7 dB. A questionnaire survey revealed that 52, 46, and 48.6% of the respondents were suffering from frequent irritation, hypertension, and sleep disturbances due to vehicular noise, respectively. Kalaiselvi and Ramachandraiah [7] assessed equivalent sound level values LAeq 24 h and LAeq 1 h of Chennai city and found the noise levels were more than 80 dB. The study also depicted that construction of flyovers resulted in a decrease in 3 dB (A) Leq along the road. The study concluded that auto-rickshaws were the main cause of traffic noise pollution than other vehicles. The different noise levels in different parts of the city are attributed to different geomorphology, vehicular density, and poor urban planning of the city. Patil et al. [22] carried out a questionnaire survey on traffic noise and its impact on health in and around Amravati town (2011). The majority of the respondents felt interference of traffic noise in their day to day activities. The study depicted that the maximum annoyance (47%) was highest during the midday and afternoon. It also revealed that 50% of respondents are suffering from headache, nervousness, and hearing difficulties due to overexposure to noise. Swain et al. [23, 24] and Swain and Goswami [25] studied the road traffic noise assessment in Bhadrak, Bhubaneswar, and Cuttack by assessing most of the noise descriptors along the traffic squares. They also conducted the questionnaire
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survey in these three cities of Odisha. Noise assessment of these cities depicted that the minimum values of Leq, Noise Pollution Level (NPL), and Traffic Noise Index (TNI) were more than the permissible limit (70 dB). The study demonstrated that traffic noise was ranked in first place among the most frequently identified types of sound in these cities. The reasons for traffic noise pollution were evaluated as frequent honking of air horns followed by congested traffic and silencer and engine. Chowdhury et al. [26] reported the daytime traffic noise of Kolkata city along the two types of road network (RN-1:oneway traffic in single or double lane and RN-2: both-way traffic in the single lane). It was reported that the ratio (RN-1/) of the averages of road width and traffic volume of two types of the road network was 2.28 and 1.89. They reported the ratio of the average L10, L90, Leq, NC, and TNI of two types of road networks and concluded that the RN-1 type of road network was wider and also had higher traffic volume in comparison with the RN-2 type of road network. On the other hand, RN-1 type of road network was quieter and less annoying in comparison with the RN-2 type of road network. Chowdhury et al. [27] also assessed highly annoying noise levels, Leq, TNI, and NC at curbside open-air microenvironment of Kolkata city under heterogeneous environmental conditions. It was reported that the Leq at the microenvironment was in excess of 12.6 ± 2.1 dB(A) from the daytime standard of 65 dB(A) for commercial area recommended by the Central Pollution Control Board (CPCB) of India. A correlation analysis showed that prevailing traffic noise level of the microenvironment had a very weak positive (0.19; p < 0.01) and weak negative (−0.21; p < 0.01) correlation with relative humidity and air temperature, respectively. Lack of correlation between traffic volume and the equivalent noise was reported due to vehicular speed, road geometry, and frequent honking along the roads of Nagpur city by Vijay et al. [8]. Again, frequency analysis showed that honking contributed an additional 2 to 5 dB noise and was quite significant. The statistical method of analysis of variance (ANOVA) confirmed that frequent honking (p < 0.01) and vehicular speed (p < 0.05) had a substantial impact on traffic noise apart from traffic volume and type of road. The study reported that honking was an imperative module in traffic noise assessment.
Studies with Special Emphasis on Noise Modeling Mishra et al. [28] assessed road traffic noise at different bus stops of Delhi and conducted a questionnaire survey. The relationship between different noise parameters and annoyance level was quantified using linear and multiple regressions. In this study, FHWA model was applied to infer the noise level. The respondents identified hearing loss (64%),
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blood pressure (56%), depression (48%), agitation (36%), and fatigue (12%). Parbat et al. [29] studied the evaluation of noise measurement of vehicular traffic flow at interrupted flow condition in intermediate Yavatmal city of Vidarbha region of Maharastra. In this study, artificial neural network modeling was performed, and accordingly, noise prediction was carried out. It was reported that there was no significant difference between the observed noise level and predicted noise level. In this study, motorbike (53.29%) was the most leading mode of transport, followed by bicycles (28.36%), four wheelers (14.54%), trucks/busses (02.18%), and others (01.63%). Arora and Moshahari [30] studied the single-layer Artificial Neural Network (ANN) modeling of noise due to road traffic in Agra-Firozabad highway and used the data on traffic volume, the speed of heavy vehicles, and their number for the noise prediction. It was reported that percentage of heavy vehicles, the speed of vehicles, and traffic flow were the prominent factors and had a significant impact on public health. The study concluded that the Levenberg-Marquardt algorithm (LMA) is the best BP algorithm with a minimum mean squared error (MSE) for cross-validation. Pradhan et al. [31, 32] assessed different noise descriptors (L10, L50, L90, Leq, TNI, NPL, NC, Traffic Volume, TruckTraffic Mix Ratio, and Lden) and studied model calibration of traffic noise pollution of Angul and Sambalpur towns, respectively. They also conducted a questionnaire survey. The minimum values of Leq, NPL, and TNI were more than the prescribed limit in both the cities. Burgess traffic noise model was applied in these studies to predict the Leq and yielded consistent results close to that by direct measurement. Subramani et al. [33] assessed traffic noise in Coimbatore city along NH-209. In this study, a mathematical model was established by considering traffic volume, vehicle speed, atmospheric and surface temperature, and humidity for prediction of L10 and Leq. Leq was predicted by obtaining the regression equation, i.e., Leq = 75.58 + 0.0024Q − 0.0064 V + 0.0469Ta − 0.00451Ts + 0.0306H. It was concluded that the value of R2ranges from 0.1 to 0.7. The nominal distribution at 5% level of significance demonstrated that there is no difference between measured and predicted noise level. Goswami et al. [34] analyzed the road traffic noise pollution in Rourkela city. The episodic and impulsive noise was also analyzed in this study. Analysis of variance depicted that the obtained values were not significant at 5% level of significance. The noise level was well predicted using Lyons empirical model. Swain and Goswami [35], Swain et al. [36], Sahu et al. [37], and Swain and Goswami [38] studied highway noise along NH-5 (from Remuna Golei square to Seragarh), NH316 (Bhubaneswar to Puri), and road traffic noise in Rayagada and Baripada, respectively. Noise prediction models such as Annon, Burgess, Griffth and Langdon, CSTB2, CSTB1 and
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RLS90 were applied in these studies and the predicted noise levels were compared with the observed noise levels. All these studies inferred that the transportation sector was the major contributors to environmental noise. De et al. [39] concluded that few people have adaptive ability to ignore the effect of noise pollution within considerable limits. Thus, an adaptive traffic noise model over the vulnerable society of a specific noise-prone zone was developed. A fuzzy logic was calibrated to depict risk evaluation by comparing with the odds ratio of the experimental data. The graphical illustrations were presented for validation of the model. Studies with Special Emphasis on Zone-Specific Noise Monitoring Sampath et al. [40] assessed the ambient noise levels in three major cities of Kerala (Thiruvananthapuram, Kochi and Kozhikode). The noise measurements were carried out in silence and commercial areas and noise levels were more than the permissible limit. Announcements from vehicles fitted with public address systems caused sound levels above 100 dB at distance of 10 to 15 m. The Leq value during the election campaign was 95 dB and maximum noise level was 120 dB. Datta et al. [41] monitored noise level in silence, commercial, and industrial zones of Burdwan town. The maximum noise level at silence zone was reported as 90 dB. The study depicted that the noise caused both pathological and psychological disorders in human beings. Goswami and Swain [42], Goswami [43] and Goswami and Swain [44] studied the soundscape of Balasore, Bhadrak, and Baripada towns and also carried out a questionnaire survey. The noise was appraised in four different zones (namely silence zone, residential zone heavy traffic zone, and commercial zone). Noise descriptors like Lmax, Lmin, L10, L50, L90, Leq, NPL, and NC were assessed and reported that these levels were more than the prescribed limit. Analysis of variance was computed and concluded that noise levels of such zones did not differ significantly at the peak hour. Studies with Special Emphasis on Noise in Workplaces Kerketta et al. [45] studied the outdoor noise levels from the different workplaces of the Arati steel plant of Odisha. Maximum attenuation of noise level was reported at workers colony and was due to ground absorption. The maximum outdoor noise was 84 dB, while in the plant, it was 92 dB (A). Goswami and Swain [46] studied the occupational exposure in 13 stone crusher industries located at Seragarh, Nilgiri, Remuna, and Mitrapur with special reference to noise. In this study, it was reported that the values of all the noise descriptors were more than the prescribed limit. It was also reported
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that none of the workers of the industry was using any personal protective equipment. Goswami and Swain [47] and Swain and Goswami [48] monitored different noise descriptors (L10, L50, L90, Leq, NPL, NC) in 20 commercial banks of Balasore and 21 banks of Cuttack, respectively. The noise levels in different banks were more than the prescribed permissible limit (50 dB). Swain et al. [49] assessed the noise levels in different offices of Balasore town. The reported maximum equivalent noise level, NPL, and NC value were 83.4, 96.6, and 26.5 dB, respectively. It was concluded that excess noise level reduced the work efficiency of the employees and caused bad temper, headache, hearing problem, and loss of concentration during working hours. One of the most annoying aspects of noise was that it interferes with speech. The studies concluded that due to speech interference between employees and people, the employees were generally irritated. Pachpande et al. [50] conducted the assessment of hearing loss among school teachers and students exposed to highway traffic near Jalgaon city. Audiometric analysis and questionnaire survey revealed that 92% of students and 84% of teachers reported hearing difficulty. In the audiometric testing, mild hearing loss, in the range of 25–35 dBHL (hearing level), was reported in both the subject groups. Mondal and Das [51] studied the attitude of trainee teachers of two educational institutions of Birbhum and Burdwan towards the environmental noise. In this study, it was noticed that both male and female teacher trainee knew the basic concept of noise and was non-significant among them (p < 0.05). It was reported that 50.36% of respondents believed that noise-induced hearing loss happened when noise level exceed 85 dB. Thirty-nine percent of respondents opined that there should be the minimum level of noise in the academic institutes and hospitals, etc. Ninety-eight percent of respondents agreed that traffic noise caused irritation in the urban area. 94.16% of respondents believed that their sleep had been interfered by the vehicular noise during the night. 14.59% of the total samples agreed that noise had an effect on blood pressure. Studies with Special Emphasis on Noise During Festivities Singh and Joshi [52] studied the noise pollution at different places of Meerut city on the night of festival of crackers, Deepawali, and an average of 83 dB was recorded in the commercial area, whereas it was 85 dB in the residential area. The noise levels in the year 2009 decreased significantly than 2007 and 2008 due to growing environment awareness. Goswami et al. [53] assessed the noise levels during Deepawali in Balasore during two consecutive years of 2010 and 2011. The Lmax and Leq values were more than 110 dB during both the years. It was also reported that the noise level of 2011 was found decreased in comparison to 2010. Ahirwar and Bajpai [54] assessed the noise levels
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during Deepawali festival at commercial, residential, and silence zones of Raipur city. The recorded noise levels were higher than the prescribed noise level. Due to increased public awareness, people preferred to celebrate this festival of crackers without sound. Swain et al. [55] assessed the noise levels during the Dussehra festival in Balasore town. The noise descriptors such as L10, L50, L90, Leq, NPL, and NC were assessed for 5 days. All the observed noise levels were more than the prescribed noise level of Central Pollution Control Board, India. Another reason for higher noise was that all the monitored sites belonged to the commercial zone. Saler and Vibhute [56] studied the noise pollution and its effects during Ganesh festival at Kolhapur city of Maharastra. Noise levels were monitored in different day and night time intervals. The noise pollution level was more than the permissible limit and caused severe annoyance to exposed people. It is concluded from this review that a limited number of studies on the exposure-effect of road traffic have been carried out in India during the last two decades.
similar. Sample sizes of these surveys are also different from each other. Thus, it is a herculean task to conduct a metaanalysis of these articles for necessary review. It is found that the authors have studied different types of noise pollution in different cities/towns of India and their consequences. This study demonstrates that most of the researchers (77.5) have used statistical methods and drawn conclusion on the basis of their result. Nevertheless, the application of statistical tools to evaluate the data of all the aforesaid articles was not feasible because of the heterogeneity of the topic and variability of the methodology.
Discussion
&
In 46.9% of the studies discussed above, the population (age, gender, and number) was well defined, while in 49% of the studies, harmful effects of exposure to noise were methodically summarized. Except for 13 studies, statistical methods were applied in the rest of the discussed studies. In 14 studies, noise modeling and noise mapping were carried out. In 22 studies, an exposure-effect relationship was established. Among these 22 studies, only in two studies, the exposure-effect relationship has been inferred on the basis of audiometric records, and in the rest of the studies, questionnaire surveys have been undertaken to reveal the effect of exposure to noise. The sample size of questionnaire surveys varied widely. In most of the cases, the sample size is more than 200 (large sample (>200) = 14 studies and medium sample (n > 50 < 200) = 5 studies). Moreover, in four of the bigger studies, random sample selection was reported. It is observed that 28.57% of the articles reported of using a large sample, which is statistically better. Only 10 and 14.3% of articles, special emphasis has been given to zone-specific noise pollution monitoring and noise monitoring in workplaces, respectively. 44.89% articles reported details of subjective response data with the help of a questionnaire tool, while 10% of articles endorsed the harmful effect of festive noise. Though few articles adopted similar methodologies, but there were different study designs in the abovementioned 49 articles. Different statistical methods and different models were used in these studies. Even questions in the 20 questionnaire surveys conducted by the different authors were not
&
Conclusion Review of research papers of the last two decades demonstrated gaps in research. Accordingly, it also revealed the following future perspectives of noise pollution research. &
& &
Future investigators should empathetically focus the research on the exposure-effect relationship by undertaking audiometric studies. Noise-annoyance curve should be plotted for better interpretation of the effect of exposure. Geospatial noise mapping should be carried out to identify noise hotspots of an urban area. Simultaneously, peace and quiet places can also be identified by such mapping. It will make people a little easier to find such places. Modeling-based studies should be undertaken so that it will be helpful for local bodies to execute better land use planning and to take precautionary measures in advance. Each upcoming study must methodically work out the evaluation of noise emission and its risk, ranking of noise sources, assessment of exposure to noise, and noise control strategy.
It is not possible to completely avoid noise pollution in a country like India, but some preventive measures can be taken to abate its extent of pollution. As per the BThe Air (Prevention and Control of Pollution) Act^ implemented in 1981, the noise is termed as an Bair-pollutant.^ Subsequently, under the Environmental Protection Act, 1986, the Government of India came up with Noise Pollution (Regulation and Control) Rules 2000. However, no definite penalty or punishment is defined in this rule. Central Pollution Control Board established the noise pollution monitoring network in 35 major cities in India in the year 2011 as a part of the National Environmental Policy adopted in 2006. Nevertheless, noise pollution limits are being violated in every nook and corner of India in general and during festivities in particular [57, 58]. The laws should be properly implemented here in India to abate noise pollution. Unfortunately, all regulations, policies, and programs are only
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in pen and paper. The government is now working on devising new noise pollution standards. There is no city-wise noise pollution mitigation plan. The focus of research must be on abatement of noise at specific sources, like loudspeakers and firecrackers. However, there is no monitoring of ambient noise levels 24 × 7, like what we do with air quality. Thus, now is the time for the State Pollution Control Boards to come up with integrated strategies and sustainable planning to minimize harmful effects of noise. Compliance with Ethical Standards Conflict of Interest There is no conflict of interest.
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