Noise pollution

About: Noise pollution is a research topic. Over the lifetime, 4455 publications have been published within this topic receiving 67192 citations.

A retrospective assessment of occupational noise exposures for a longitudinal epidemiological study.

Abstract: Objectives: Chronic exposure to high levels of noise may be associated with increased risk of cardiovascular disease. We therefore undertook a quantitative retrospective exposure assessment using predictive statistical modelling to estimate historical exposures to noise among a cohort of 27 499 sawmill workers as part of an investigation of acute myocardial infarction mortality. Methods: Noise exposure data were gathered from research, industry and regulatory sources. An exposure data matrix was defined and exposure level estimated for job title/mill/time period combinations utilising regression analysis to model determinants of noise exposure. Cumulative exposure and duration of exposure metrics were calculated for each subject. These were merged with work history data, and exposure–response associations were tested in subsequent epidemiological studies, reported elsewhere. Results: Over 14 000 noise measurements were obtained from British Columbia sawmills. A subset, comprising 1901 full-shift dosimetry measurements from cohort mills was used in producing a predictive model (R2 = 0.51). The model was then used to estimate noise exposures for 3809 “cells” of an exposure data matrix representing 81 jobs at 14 mills over several decades. Various exposure metrics were then calculated for subjects; mean cumulative exposure was 101 dBA*year. Mean durations of employment in jobs with exposure above thresholds of 85, 90 and 95 dBA, were 9.9, 7.0 and 3.2 years, respectively. Conclusions: The utility of predictive statistical modelling for occupational noise exposure was demonstrated. The model required input data that were relatively easily obtained, even retrospectively. Remaining issues include adequate handling of the use of hearing protectors that likely bias exposure estimation.

Construction noise prediction and barrier optimization using special purpose simulation

Abstract: Construction projects produce serious environmental pollution and great annoyance to the neighbouring community due to construction noise. This paper presents an application of the special purpose simulation (SPS) language using Simphony software to predict the noise levels generated by construction equipment, tools and machinery at a given reception point for a certain barrier length, as well as the related cost of the barrier wall. To illustrate an application of the developed model, an example has been developed for different noise sources and different activities. The information obtained from the simulation model output will help to utilize the model as a planning tool for optimizing the length and location of noise barriers around a construction site. The tool can be useful for a contractor to develop a noise-control plan using mitigation measures that are acceptable to the owner.

The noise hazard in a large health care facility.

Abstract: A noise-level survey, dosimetry, and audiometric testing were conducted in a large health care facility to determine the areas with hazardous noise levels, the number of employees at risk, and the prevalence of noise-induced hearing loss (NIHL) among the exposed. Nine high-risk areas were identified, with readings of up to 110 dBA recorded. In the work force of approximately 6,000 employees, 321 were identified as exposed to potentially hazardous noise levels. Abnormal hearing patterns were observed in 59 (19%) of the 308 workers screened, with 36 cases of NIHL documented. The findings showed that noise is a serious hazard in many areas, that some cases of NIHL have developed from occupational exposure in this hospital, and that a control program is essential.

Spatio-temporal Analysis of Noise Pollution near Boston Logan Airport: Who Carries the Cost?

Abstract: Airports are often located near densely populated residential areas, affecting a large number of people. Thus, knowing socio-demographic characteristics of the noise-affected areas is important for the development of policies on noise control and abatement. This study proposes a new methodology that combines airport noise models with spatial statistics and geographical information systems to identify spatial clusters of socio-demographic characteristics in relationship to the noise level. Statistically significant ‘hot’ and ‘cold’ socio-demographic clusters represent spatial concentrations of certain social groups, corresponding to various levels of vulnerability to environmental impacts. Results show that the population ‘paying’ for the cost of noise from Logan International Airport in Boston, USA, is highly vulnerable as there are more minority and lower-income populations, and lower house prices in the noise-affected areas. These results should draw the attention of policy-makers and the public as poli...