Noise pollution

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

Automated classification of urban locations for environmental noise impact assessment on the basis of road-traffic content

Abstract: Sampled urban locations are grouped into 4 clusters according to HV and MM content.SMO-models outperform MLP-models in correctly classifying obtained clusters.Attribute evaluation algorithms achieve better results than subset evaluation algorithms.Environment variables, LF sound levels and Leq are the most influential input variables. Urban and road planners must take right decisions related to urban traffic management and controlling noise pollution. Their assessments and resolutions have important consequences on the annoyance of population exposed to road-traffic-noise and controlling other environmental pollutants (e.g. NOx or ultrafine particles emitted by heavy vehicles). One of the key decisions is the selection of which noise control actions should be taken in sensitive areas (residential or hospital areas, school areas etc), that could include costly measures such as reducing the overall traffic, banning or reducing traffic of heavy vehicles, inspection of motorbikes sound emission, etc. For an efficient decision-making in noise control actions, it is critical to classify a given location in a sensitive area according to the different prevailing traffic conditions.This paper outlines an expert system aimed to help urban planners to classify urban locations based on their traffic composition. To induce knowledge into the system, several machine learning algorithms are used, based on multi-layer Perceptron and support vector machines with sequential minimal optimization. As input variables for these algorithms, a combination of environment variables was used. For the development of the classification models, four feature selection techniques, i.e., two subset evaluation (correlation-based feature-subset selection and consistency-based subset evaluation) and two attribute evaluation (ReliefF and minimum redundancy maximum relevance) were implemented to reduce the models' complexity. The overall procedure was tested on a full database collected in the city of Granada (Spain), which includes urban locations with road-traffic as dominant noise source. Among all the possibilities tested, support vector machines based models achieves the better results in classifying the considered urban locations into the 4 categories observed, with values of average weighted F-measure and Kappa statistics (used as indicators) up to 0.9 and 0.8. Regarding the feature selection techniques, attribute evaluation algorithms (ReliefF and mRMR) achieve better classification results than subset evaluation algorithms in reducing the model complexity, and so relevant environmental variables are chosen for the proposed procedure. Results show that these tools can be used for addressing a prompt assessment of potential road-traffic-noise related problems, as well as for gathering information in order to take more well-founded actions against urban road-traffic noise.

Associations of blood pressure and arterial compliance with occupational noise exposure in female workers of textile mill.

Abstract: BACKGROUND There are few studies on the arterial compliance of noise exposure. The purpose of this study was to understand the relationship between hearing loss, blood pressure and arterial compliance of female workers who exposed to occupational noise in a textile mill. METHODS The noise levels in the workplace were measured with a HS6288 sound level meter. Cumulated noise exposure (CNE) was calculated according to the noise intensity and the exposure period. Hearing ability and arterial compliance were measured in 618 noise exposed workers. The database was set up with EpiData and the statistical analysis was performed with SAS software 9.1.3. RESULTS The noise levels were 80.1dB (A) to 113.5dB (A), of which the levels at 92.5% of the noise monitoring sites were over the national standard. The incidence of high frequency hearing loss (HFHL) was 24.43% and language frequency hearing impairment (LFHI) was 0.81%. The incidence of hypertension was 7.93%. Both systolic blood pressure (SBP) and diastolic blood pressure (DBP) in the high frequency hearing loss group were significantly higher than those in the normal hearing group (P < 0.05), while C(1) (large artery compliance) and C(2) (small artery compliance) were significantly lower (P < 0.05). The high frequency hearing threshold (HFHT) of the hypertension group was significantly higher than in the normal blood pressure group (P < 0.05), while C(1) and C(2) were significantly lower (P < 0.05). C(1) and C(2) had a negative correlation with HFHT, SBP, DBP, mean of arterial pressure (MAP), pulse pressure (PP) and pulse rate (PR) (P < 0.05). The multiple regression analyses showed that blood pressure and PR were the main influencing factors on C(1) and C(2). LFHT was an influence on C(2) and HFHT on C(1). CONCLUSIONS Textile mill noise pollution is very serious and has an obvious influence on worker's auditory function. The female workers with low artery compliance or with high blood pressure might be suffering from hearing loss; those with noise induced hearing loss might be suffering from hypertension if she is constantly exposed to loud industrial noise.

Effect of noise pollution on human being : its prevention and control

Abstract: Now a day, noise pollution is not a new problem for common man, especially in most of the industrial towns and metropolitans cities. Noise pollution means any sound that is undesired by the recipient. The effect of sound on human depends upon its frequency. Human ear are known to be sensitive to an extremely wide range of intensity varied from 0 to 180 dB. The noise is generated by the human through various ways. In present research article, various sources of noise pollution, measurement of noise, dB scale, equipments used in the measurement of noise levels, impacts of noise, adverse health effects of noise pollution, control of indoor noise, control technologies available for noise pollution and Indian penal codes to prevent noise pollution are the main points of focus of attention. Noise must be controlled and prevented by using various effective techniques at the source itself is today’s need. The objective of this research work is to know about the various ways of generation of noise, their effects on human, its prevention and control.

A cross-modal effect of noise: the disappearance of the alarm reaction of a freshwater fish

Abstract: Anthropogenic noise pollution is recognized as a major global stressor of animals. While many studies have assessed the unimodal impacts of noise pollution with a focus on intraspecific acoustic communication, little is known about noise pollution on the perception of visual and chemical information. The 'distracted prey hypothesis' posits that processing noise interferes with processing other information in the brain. Here, we found evidence for such a cross-modal effect of noise on the antipredator behaviour of a freshwater prey fish, the fathead minnow, Pimephales promelas. In laboratory trials, exposure to noise from a motorboat caused the total absence of the classical fright reaction of minnows to conspecific alarm cues, whereas an ambient noise control had no such impact. In natural habitats, the impairment of such antipredator behaviour due to noise pollution could have major fitness consequences. We discuss how our findings translate to animal ecology and the need for future studies that target specific management decisions regarding noise pollution.