Statistical and spatio-temporal analyses of noise pollution level and its health impact.

Due to rapid urbanization and exponential growth in transportation; traffic noise has become a major area of concern. Noise not only disturbs our day-to-day life but also have severe adverse health effects over humans which further may lead to mortality. This paper focuses on the behavior of noise levels of Lucknow city over a decade and establishes its correlation with impact on human health in terms of annoyance and sleep disturbance. Apart from Leq, different noise parameters like L10, L50, L90, Traffic Noise Index (TNI), Noise Pollution Index (NPI), and Noise Climate (NC) have also been analyzed to understand the variation of noise. At all the locations, the noise level has been found exceeding their prescribed standards during day time and night time except at Amausi. Out of nine locations, TNI was found to be exceeding at three locations during day time and NPI exceeding at one location. However, during night time both values of TNI and NPL were observed within the limit at all the locations. From the noise map of the city during day time and night time, among all sampling locations, Charbagh has been found to be worst affected by noise pollution. A strong positive correlation has been observed among the total population, vehicular count, and day and night time noise data, which directly contribute to a higher percentage of sleep disturbance and annoyance among residents. Due to the increase in noise levels over a period of time, almost four times the population get affected by high annoyance and almost double the population get affected by sleep disturbance.

Auditory effect of noise exposures among commercial and non-commercial light motor vehicle drivers: A comparative cross-sectional study in Lucknow city.

CONTEXT: Noise-induced hearing loss, one of the most common and preventable occupational hazard, occurs due to repeated and continuous exposure of loud noise, A single exposure of an impulse of noise at the level of 130--140 dB or long and repeated exposures to loud sounds to an average level of 85 dB or higher for an 8-h period can cause permanent loss of hearing. AIMS: To study and compare hearing loss over different audiometric frequencies among autorickshaw and non-commercial institutional personal car drivers. SETTINGS AND DESIGN: This was a cross-sectional comparative study conducted at a tertiary medical college, located in Lucknow during October 2017-November 2018. METHODS AND MATERIALS: The sample size was calculated using EpiInfo7. We took a sample size of 300 drivers, out of which 150 three-wheeler autorickshaw drivers (Tempo), that is, group I and 150 non-commercial car drivers, that is, group II were selected. STATISTICAL ANALYSIS USED: For statistical analysis, "Chi-square test of independence" and student's t-tests were used. RESULTS: The mean age at which drivers in group I and group II started work was 23.91 ± 7.63 years an d 23.60 ± 5.58 years, respectively. The mean hearing loss in Group I was 21.15 ± 8.65 dB and in group II it was 13.34 ± 5.79 dB. CONCLUSIONS: Autorickshaw drivers who were exposed to louder noise, that is, autorickshaw drivers in group I had more sensory neural hearing loss than the non-commercial car drivers, that is, group II.

Characterization of PM2.5 in Delhi: role and impact of secondary aerosol, burning of biomass, and municipal solid waste and crustal matter.

Delhi is one among the highly air polluted cities in the world. Absence of causal relationship between emitting sources of PM2.5 and their impact has resulted in inadequate actions. This research combines a set of innovative and state-of-the-art analytical techniques to establish relative predominance of PM2.5 sources. Air quality sampling at six sites in summer and winter for 40 days (at each site) showed alarmingly high PM2.5 concentrations (340 ± 135 µg/m3). The collected PM2.5 was subjected to chemical speciation including ions, metals, organic and elemental carbons which followed application of chemical mass balance technique for source apportionment. The source apportionment results showed that secondary aerosols, biomass burning (BMB), vehicles, fugitive dust, coal and fly ash, and municipal solid waste burning were the important sources. It was observed that secondary aerosol and crustal matter accounted for over 50% of mass. The PM2.5 levels were not solely result of emissions from Delhi; it is a larger regional problem caused by contiguous urban agglomerations. It was argued that emission reduction of precursors of secondary aerosol, SO2, NOx, and volatile organic compounds, which are unabated, is essential. A substantial reduction in BMB and suspension of crustal dust is equally important to ensure compliance with air quality standards.