scholarly journals Urban Noise Pollution Assessment Techniques

10.5772/9561 ◽  
2010 ◽  
Author(s):  
Fernando A. N. Castro Pinto
Keyword(s):  
Pollution Assessment ◽  
Noise Pollution ◽  
Urban Noise ◽  
Assessment Techniques

scholarly journals Urban Noise Pollution Assessment and its Non-Auditory Health Effects on the Residents of Chiniot and Jhang, Punjab, Pakistan

2021 ◽  
Author(s):  
Zia Ur Rahman Farooqi ◽  
Iftikhar Ahmad ◽  
Nukshab Zeeshan ◽  
Predrag Ilic ◽  
Muhammad Imran ◽  
...  
Keyword(s):  
Health Effects ◽  
Physiological Stress ◽  
Pollution Assessment ◽  
Noise Pollution ◽  
Strong Relationship ◽  
Sound Level ◽  
Survey Study ◽  
Traffic Density ◽  
Urban Noise ◽  
Noise Data

Abstract Noise pollution is an emerging global problem therefore, it is imperative to determine noise level especially in the urban environment and its implications on human health. The objectives of this study were i) to assess the urban noise pollution and traffic density of Chiniot and Jhang and ii) to determine non-auditory health effects of noise pollution on the residents of both cities. Noise pollution was examined from 181 locations (103 from Jhang and 78 from Chiniot) and categorized into hospitals, educational, religious and recreational, residential, industrial areas, and traffic intersections. Noise levels measurements were taken using integrated sound level meter. The urban noise data showed 82% of the sites in Jhang and 95% in Chiniot exceeded the noise limits set by NEQS-Pak and WHO. Moreover, higher intensity of noise pollution (≥ 100 dB) was recorded in Chiniot (17 sites) than in Jhang (1 site). Regression analysis showed relatively strong relationship of traffic density with noise at Chiniot (R2 = 0.48) compared to Jhang (R2 = 0.31). However, spatial variability of noise with traffic density was observed at both cities. Survey study revealed that all the respondents in Jhang and Chiniot suffered from many noise related health problems such as annoyance (53 and 51%), depression (45 and 47%), dizziness (61 and 65%), headache (67 and 64%), hypertension (71 and 56%), hearing loss (53 and 56%), physiological stress (65 and 65%), sleeplessness (81 and 84%), and tinnitus (70 and 62%) due to noise, respectively. It is concluded that noise pollution is higher in Chiniot due to high traffic density resulted from higher population density and cottage industry. It is recommended that vehicles maintenance, family and urban planning could be effective measures to reduce urban noise pollution.

Approaches to Urban Noise Management in India

2012 ◽  
Author(s):  
Neelima S. Naik
Keyword(s):  
Urban Areas ◽  
Central Government ◽  
Environmental Concern ◽  
Noise Pollution ◽  
Noise Levels ◽  
Urban Noise ◽  
Master Plans ◽  
The Past ◽  
Metropolitan Cities

Noise pollution in urban areas is recognized as a major environmental concern in India. The lack of infrastructure and fast paced life in major metropolitan cities of India has made the urban environment extremely crowded, busy as well as noisy and as a result the millions of people living in the major metropolitan areas are suffering from the impacts of noise pollution. Noise levels are escalating at such a rate that it has become a major threat to the quality of human lives. Direct links between noise and health have been established by research conducted over the past few decades. There are several causes for urban degradation such as population migration, environmental considerations not adequately being incorporated into master plans, uncoordinated and haphazard development, weak implementation of plans and laws and inadequate institutional competences and resource crunch. This paper discusses the causal factors, impacts and the different approaches adopted by the Central Government as well as some major State Pollution Control Boards to curb the urban noise problem and the need for looking into non-conventional solutions such as Ecocity programme to bring in visible environmental improvement.

scholarly journals Status of noise pollution in urban area of Dharan Sub- Metropolitan City and Inaruwa Municipality of Sunsari District, Nepal

2017 ◽  
Vol 7 (1) ◽  
pp. 35-40
Author(s):  
Ranij Shrestha ◽  
Alankar Kafle ◽  
Kul Prasad Limbu
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Pollution Assessment ◽  
Noise Pollution ◽  
Pressure Level ◽  
Noise Levels ◽  
Night Time ◽  
Level Measurement ◽  
Standard Value ◽  
Autumn And Winter

The environmental noise level measurement in Dharan and Inaruwa cities of eastern Nepal were conducted and compared with the ambient noise standards provided by Government of Nepal. The noise pollution assessment was performed in autumn and winter seasons by the indicator average day time sound pressure level (Ld, during 7.00 to 22.00 hrs) and average night time sound pressure level (Ln, during 22.00 to 7.00 hrs). The Ld and Ln values at the commercial, silence and residential zones of Dharan were 78 to 82 and 72 to 73, 65 to 73 and 60 to 70, 65 to 76 and 62 to 64 dB(A) in autumn and 78 to 79 and 72 to 76, 64 to 71 and 58 to 68, 63 to 74 and 60 to 62 dB(A) in winter, respectively whereas for Inaruwa, measurement were 75 to 77 and 73 to 75, 59 and 57, 67 and 60 dB(A) in autumn and 66 to 70 and 63 to 68, 55 and 53, 65 and 58 dB(A) in winter, respectively. The results showed that noise levels exceeded the standard value at most of the sites.

Traffic Noise Pollution Assessment in Major RoadJunctions of Imphal City, Manipur (India)

2021 ◽  
Author(s):  
WAZIR ALAM ◽  
Ramtharmawi Nungate
Keyword(s):  
Noise Level ◽  
Noise Exposure ◽  
Traffic Noise ◽  
Pollution Assessment ◽  
Noise Pollution ◽  
Pollution Level ◽  
Night Time ◽  
Noise Mapping ◽  
Noise Parameters ◽  
Spatial Noise

Abstract Noise pollution assessment was carried out in selected traffic junctions of Imphal city of Manipur, India. The noise pollution assessment was carried out using noise parameters and indices such as L10, L50, L90, Leq for selected traffic junctions during the different periods of the day, i.e., morning, noon, and evening hours. The study of equivalent noise level (Leq), noise parameters, and various noise indices have enabled the evaluation of the overall traffic noise environment of the city. The traffic noise indices such as traffic noise index (TNI), noise climate (NC), traffic noise pollution level (LNP), noise exposure index (NEI) along with day time (LD), night time (LN) average, and day-night (Ldn) noise levels were assessed for the selected traffic junctions. Moreover, spatial noise mapping was carried out using the geostatistical interpolation technique to evaluate the changes of traffic noise scenarios during the different time zones of the day. The Leq values in few traffic junctions exceeded the required noise standards. The study shows equivalent noise level ranging between 52.2–69.9 dB(A) during the morning (7–10 am), 52.4–69.3 dB(A) during noon (12 noon-2 pm), and 54.6–71.1 dB(A) during the evening (4–7 pm) hours, respectively.

Urban Noise Inference Model Based on Multiple Views and Kernel Tensor Decomposition

2021 ◽  
pp. 2150027
Author(s):  
Junlan Nie ◽  
Ruibo Gao ◽  
Ye Kang
Keyword(s):  
Noise Pollution ◽  
Tensor Decomposition ◽  
Prediction Algorithm ◽  
Kernel Matrix ◽  
Multiple Views ◽  
Tensor Factorization ◽  
Urban Noise ◽  
Model Based ◽  
Factorization Model ◽  
Kernel Distance

Prediction of urban noise is becoming more significant for tackling noise pollution and protecting human mental health. However, the existing noise prediction algorithms neglected not only the correlation between noise regions, but also the nonlinearity and sparsity of the data, which resulted in low accuracy of filling in the missing entries of data. In this paper, we propose a model based on multiple views and kernel-matrix tensor decomposition to predict the noise situation at different times of day in each region. We first construct a kernel tensor decomposition model by using kernel mapping in order to speed decomposition rate and realize stable estimate the prediction system. Then, we analyze and compute the cause of the noise from multiple views including computing the similarity of regions and the correlation between noise categories by kernel distance, which improves the credibility to infer the noise situation and the categories of regions. Finally, we devise a prediction algorithm based on the kernel-matrix tensor factorization model. We evaluate our method with a real dataset, and the experiments to verify the advantages of our method compared with other existing baselines.

Urban noise pollution in the city of Curitiba, Brazil

2002 ◽  
Vol 112 (5) ◽  
pp. 2375-2375
Author(s):  
Paulo H. T. Zannin ◽  
Fabiano B. Diniz
Keyword(s):  
Noise Pollution ◽  
Urban Noise ◽  
The City

An interdisciplinary study of urban noise pollution

1992 ◽  
Vol 42 (2-3) ◽  
pp. 201-214 ◽  
Author(s):  
Mario Rene Serra ◽  
Carlos A. Frassoni ◽  
Ana Maria Verzini de Romera ◽  
Ester Cristina Biassoni de Serra
Keyword(s):  
Noise Pollution ◽  
Urban Noise ◽  
Interdisciplinary Study

A study of the accuracy of mobile technology for measuring urban noise pollution in large scale participatory sensing campaigns

2017 ◽  
Vol 117 ◽  
pp. 219-226 ◽  
Author(s):  
Pierre Aumond ◽  
Catherine Lavandier ◽  
Carlos Ribeiro ◽  
Elisa Gonzalez Boix ◽  
Kennedy Kambona ◽  
...  
Keyword(s):  
Mobile Technology ◽  
Large Scale ◽  
Noise Pollution ◽  
Participatory Sensing ◽  
Urban Noise
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