Evaluation and Analysis of Road Traffic Noise in Asansol: An Industrial Town of Eastern India

Banerjee, Dibyendu; Chakraborty, Subrata; Bhattacharyya, Sidhakam; Gangopadhyay, Aniruddha

doi:10.3390/ijerph5030165

Cited by 67 publications

(39 citation statements)

References 3 publications

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“…Asansol, an urban-industrial city situated in West Bengal state of eastern India, with an area of 127 km 2 and a population density of 3737/km 2 has witnessed a sharp growth in vehicular population in the last five years, ensuing a significant, unrestrained noise pollution across the area as reported in previous works (Banerjee and Chakraborty, 2005;Banerjee et al, 2008a). The impact identification and quantification due to such exposure to road traffic noise has been done in such preceding works and it has been observed that such noise levels in the area are much above the prescribed limits (Banerjee et al, 2008b).…”

Section: Study Areamentioning

confidence: 73%

Appraisal and mapping the spatial-temporal distribution of urban road traffic noise

Banerjee¹,

Chakraborty²,

Bhattacharyya

et al. 2009

Int. J. Environ. Sci. Technol.

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ABSTRACT:The present study aims to compute the temporal and spatial distribution of road traffic induced noise pollution in an urban environment by monitoring and mapping. The study area was the entire Asansol city of West Bengal, India. A total of 35 locations were selected for collection of data, classified as industrial, commercial, residential, sensitive and mixed areas according to the national regulatory standards. Noise recordings were conducted during morning and night hours. Day time L eq level ranged between 51.2 and 89.0 dB(A), whereas it ranged between 43.5 and 81.9 dB(A) during night. The average L dn value was 73.28 ± 8.51 dB(A) (Range: 55.1-87.3); The traffic noise index was 80.62 ± 15.88 dB(A) (Range: 49.4-115.8). The computed data were mapped by utilization of Geographic information system methodology that allowed the visualization and identification of the extent and distribution of sound pollution across the study area. This proves to be an ideal tool for carrying out noise impact assessments in urban settings. The study reveals that present noise level in all the locations exceeds the prescribed limit. Based on the finding, it can be mentioned that the population in this industrial town are exposed to significantly high noise level, which is caused mostly due to road traffic. The study reveals that vulnerable establishments like schools and hospitals are subjected to significantly high noise level throughout the day and immediate mitigatory measures are required to alleviate the problem.

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Section: Study Areamentioning

confidence: 73%

Appraisal and mapping the spatial-temporal distribution of urban road traffic noise

Banerjee¹,

Chakraborty²,

Bhattacharyya

et al. 2009

Int. J. Environ. Sci. Technol.

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“…An EF of > 1 indicates that the traffic noise level was in excess of the daytime commercial area standard prescribed by the CPCB in both seasons. Traffic noise levels greater than the prescribed standard in Indian cities has been reported by a number of researchers (24)(25)(26)(27). The average EF for PM 2.5 concentration (EF-PM 2.5 ) was 7.34 ± 1.74 post-monsoon and 3.35 ± 0.89 pre-monsoon.…”

Section: Ef Of Traffic Noise and Concentrations Of Air Pollutantsmentioning

confidence: 88%

Assessment of Seasonal Variations of Average Traffic Pollution Levels in Curbside Open-Air Microenvironments in Kolkata, India

2016

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Background: Traffic is a source of both noise and air pollution, contributing more than 50% of the total environmental noise and air pollution load of urban areas. Objectives: The objective of the research was evaluation of seasonal variations of the average traffic pollution level (ATPL) in terms of traffic noise and concentrations of PM 2.5 and NO 2 in curbside open-air microenvironments in Kolkata, India. Materials and Methods: Number of total motorized vehicles (TMV) traffic noise, and PM 2.5 and NO 2 concentrations were monitored repeatedly in the microenvironments of 21 major roads between 08:00 a.m. and 08:00 p.m. in the post-monsoon (winter) and premonsoon (summer) seasons. Simultaneous data on air temperature, relative humidity, and wind speed were collected from a roof-top automated weather monitoring station. The exceedance factor (EF) was calculated for traffic noise level and concentrations of PM 2.5 and NO 2 . The average exceedance factor (AEF) was calculated to determine ATPL of the microenvironments in terms of traffic noise level and air pollutant concentrations. Interseasonal variations between the same variables were assessed with post-monsoon to pre-monsoon (W/S) ratio and correlation analysis. Results: ATPL was 3.35 times higher in the post-monsoon and 1.83 times higher in the pre-monsoon season than the permissible limits prescribed by the central pollution control board of India with respect to traffic noise level and PM 2.5 and NO 2 concentrations. W/S ratio and interseasonal correlation were 1.03 and 0.95, respectively, for TMV; 1.00 and 0.68 for traffic noise level; 2.40 and -0.11 for PM 2.5 concentration; 1.74 and 0.19 for NO 2 concentration; and 1.92 and 0.01 for AEF. Conclusions: ATPL was higher in the post-monsoon season. W/S ratio and correlation analysis revealed interseasonal homogeneity of TMV and traffic noise levels and interseasonal heterogeneity of air pollutant concentrations and ATPL in the city microenvironments.

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“…The comparison of ambient noise levels observed in 2015 with those observed in 2011 for the 35 stations revealed that, for some sites like Indira Nagar, PGI Hospital of Lucknow city; Kasba Gole park, Patauli and New Market site of Kolkata city; ASHP and MPCB headquarters of Mumbai city; Abids and Jeedimetla site of Hyderabad city; Eye hospital, Perambur, T. Nagar and Triplicane sites in Chennai city registered a higher increment (5 dB(A)) in ambient noise levels. This may be primarily due to the substantial growth of new vehicles, low turnover of old vehicles, inadequate road network and urbanization [19][20][21][22][23][24] . Table 5 shows the frequency distribution of L day and L night ; L dn and L Aeq,24 h in dB(A) for seven major cities (70 sites) in 2015.…”

Section: Overall Noise Scenariomentioning

confidence: 99%

Study on the Establishment of a Diversified National Ambient Noise Monitoring Network in Seven Major Cities of India

et al. 2017

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We describe the diversified National Ambient Noise Monitoring Network (NANMN) set up across 7 major cities of India and covering 70 stations for continuous noise monitoring throughout the year. The annual average L day (06-22 h) and L night (22-06 h) values observed in 2015 for these 70 locations are described. Of these, 25 locations are in commercial zones, 12 in industrial, 16 in residential and 17 in silence zones. Each city has 10 noise monitoring stations installed for analysing environmental noise pollution levels round the clock (24  365 h). The long-term noise monitoring shows that ambient noise levels are very high compared to the recommended standards for some sites and thus noise abatement measures are essentially required for controlling these levels. The present study is focused on evaluation, analysis and reporting of environmental noise pollution in seven major cities of India and is instrumental in planning for the noise abatement measures for controlling noise pollution in these cities. Such a noise monitoring network established in India is unique and one of the largest noise monitoring networks of its kind across the globe. Keywords: Day equivalent level, day-night average sound level, National Ambient Noise Monitoring Network, night equivalent level.NOISE pollution has become a serious concern over the past several years in India. With growing vehicular population and urbanization, it is imperative to monitor the ambient noise levels and devise suitable measures for control to avoid health hazards and annoyance faced by the community. The evidence for effects of environmental noise on health is strongest for annoyance, sleep and cognitive performance in adults and children. The occupational noise exposure also shows some association with high blood pressure 1 . There have been many such studies conducted so far on the noise exposure and correlation with human blood pressure 2-5 . Meta-analyses have been carried out to derive the exposure-response relationships that can be used for quantitative health impact assessments 6 . The meta analysis of 24 cross-sectional studies on the relationship between road traffic noise and prevalence of hypertension reported an odds ratio (OR) of 1.07 (95% confidence interval (CI) = 1.02-1.12, P < 0.05) per 10 dB increase of 16 h day-time average road traffic noise level (L Aeq,16 h ) in the range of <50 to >75 dB (refs 7, 8). In India, there have been limited studies carried out on correlating the effect of noise on human health. A recent study provides evidence that road traffic noise is a serious cause of concern 9 . The study infers that association between transportation noise exposure and cardiovascular disease is evident, but not at significant level. A similar study suggests epidemiological evidence that exposure to road traffic noise of

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Evaluation and Analysis of Road Traffic Noise in Asansol: An Industrial Town of Eastern India

Cited by 67 publications

References 3 publications

Appraisal and mapping the spatial-temporal distribution of urban road traffic noise

Appraisal and mapping the spatial-temporal distribution of urban road traffic noise

Assessment of Seasonal Variations of Average Traffic Pollution Levels in Curbside Open-Air Microenvironments in Kolkata, India

Study on the Establishment of a Diversified National Ambient Noise Monitoring Network in Seven Major Cities of India

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