Outdoor Noise Pollution Mapping Case Study: A District of Tehran

2014 ◽  
Vol 13 (04) ◽  
pp. 1450027 ◽  
Author(s):  
Mohammad Reza Monazzam ◽  
Elham Karimi ◽  
Parvin Nassiri ◽  
Lobat Taghavi ◽  
Samaneh Karbalaei

The main objective of this study was to investigate the noise levels at different land uses of District 14 in Tehran. For this purpose, a total number of 91 sampling stations were selected. Afterwards, the equivalent sound pressure level in each station was measured at three occasions of morning (7–9 am), noon (12–3 pm), and evening (5–8 pm). Based on the conformability requirement of each land uses, noise levels was divided in three zones wherein the land uses are exposed to different noise levels was estimated. The obtained results indicated that 8.79% of 78 land uses (residential, recreational and medical) in the Zone 1 were exposed to acceptable range of sound pressure level while the rest suffers from unacceptable noise levels. Among 10 land uses of Zone 2 (commercial–residential), 2.19% were within the acceptable range and 8.78% were in unacceptable range. None of the three land uses in Zone 3 were within the acceptable range. Accordingly, the Zone 3 was recognized to be in a critical condition. In other words, about 88.99% of the total and uses in the Zone 3 is exposed to unaccepted able noise level. Comparing with the standard equivalent sound pressure level of 55 dB(A) presented, the residential land use with the equivalent sound pressure level of 19.27 dB(A) accounted for the highest standard deviation. This is due to proximity of most of the residential areas to the crowded highways and streets.

2017 ◽  
Vol 7 (1) ◽  
pp. 35-40
Author(s):  
Ranij Shrestha ◽  
Alankar Kafle ◽  
Kul Prasad Limbu

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.


Jurnal Zona ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 91-106
Author(s):  
Eko Hendi Saputra ◽  
Yusni Ikhwan Siregar ◽  
Hafidawati Hafidawati

This study aims to determine the level of noise caused by flight activities at Sultan Syarif Kasim II Airport Pekanbaru, analyze noise levels that occur due to flight activities at Sultan Syarif Kasim II Airport Pekanbaru and analyze efforts to control the negative impact of airport noise on the living environment of community settlements. around Sultan Syarif Kasim II Airport Pekanbaru. This research uses field observation method, which is making direct observations at the research location by looking at the condition of the location and the suitability of the location which is the sampling point of the study (the noise level boundary at Sultan Syarif Kasim II Airport). Observations were made for 16 hours (Ls) at an interval of 06.00 - 22.00. Measurement of sound pressure level is carried out on holidays (Sunday) and weekdays (Monday), which starts on November 1, November 2, November 8, and November 9, 2020, which is carried out in residential areas around Sultan Syarif Kasim II Airport Pekanbaru, which are spread across 6 measurement points where the measurement of sound pressure level is done in duplicate, namely: Jl. Kaswari (point 1), Jl. Rawa Indah II (Point 2), Jl. Rawa Indah III (Point 3), Jl. Cinnamon (Point 4), Jl. Pahlawan Kerja gg.Pala 49 (Point 5) and Jl. Nur Asiyah (Point 6) The results of the processing of noise measurement data were made of a mapping model using surfer 11 software and to clarify the noise description at the sampling location, the map of the results of surfer 11 software processing was plotted on the airport area map.     Based on the results of measurements of noise levels around Sultan Syarif Kasim II airport, it is known that the location of point 1 (Jl. Rawa Indah II) experienced the highest noise exposure. These results indicate the location of point 1 should receive serious attention for the people who live around the airport, because the impact of airport noise has the potential to negatively affect the lives of residential communities. From the observations, it was also known that the level of noise attenuation was still low, both in terms of trees around the settlement and height, walls and fences were still not effective at reducing noise.         Based on the results of measurements of noise levels around Sultan Syarif Kasim II airport, it is known that the location of point 1 (Jl. Rawa Indah II) experienced the highest noise exposure. These results indicate that the location of point 1 should receive serious attention for the people who live around the airport, because the impact of airport noise has the potential to negatively affect the lives of residential communities. From the observations, it was also known that the level of noise attenuation was still low, both in terms of trees around the settlement and height, walls and fences were still not effective at reducing noise.         From the results of the research that has been done, several mitigation strategies can be formulated to reduce noise levels around Sultan Syarif Kasim II airport. Planting plants in accordance with the needs of controlling or reducing noise in human settlements. Tree categories suitable for planting in residential areas around the airport are: shady trees that can be planted tightly or with lots of leaves that can grow to a height of about 4 - 15 m (such as acacia, mahogany, flamboyant, ironwood or banyan trees, bamboo or cypress)


Author(s):  
Mohammad Javad Zare Sakhvidi ◽  
Hamideh Bidel ◽  
Ahmad Ali Kheirandish

 Background: Chronic occupational exposure to noise is an unavoidable reality in the country's textile industry and even other countries. The aim of this study was to compare the sound pressure level in different parts of the textile industry in Yazd and in different parts of the textile industry. Methods: This cross-sectional study was performed on 930 textile workers in Yazd. A questionnaire was used to obtain demographic information and how to use protective equipment. Then, to obtain the sound pressure level of each unit and device and to use the measurement principles, a calibrated sound level meter was used. Then the results were analyzed using SPSS Ver.29 software. Results: The participants in this study were 714 males and 216 females with a mean age of 35.27 and 33.63 years, respectively. Seven hundred fifty-six participants (81.29%) were exposed to sound pressure levels higher than 85 dB. Among the participants, only 18.39% of the people used a protective phone permanently. Except for factory E, with an average sound pressure level of 77.78 dB, the rest of the factories had an average sound pressure level higher than the occupational exposure limit. The sound measurement results of different devices show that the sound pressure levels above 90 dB are related to the parts of Dolatab, Ring, Kinetting (knitting), Chanel, Autoconer, Dolakni, Open End, MultiLakni, Tabandegi, Texture, and Poy. Conclusion: Based on the results of the present study, noise above 90 dB is considered as one of the main risk factors in most parts of the textile industry (spinning and weaving), which in the absence of engineering, managerial or individual controls on it causes hearing loss in becoming employees of this industry


2021 ◽  
Vol 263 (4) ◽  
pp. 2550-2554
Author(s):  
Timothy Van Renterghem ◽  
Pieter Thomas ◽  
Dick Botteldooren

Excessive road traffic noise exposure in (sub)urban parks hinders its restorative function and will negatively impact the number of visitors. Especially in such green environments, noise abatements by natural means, well integrated in the landscape, are the most desired solutions. Although dense vegetation bordering the park or raised berms could come first in mind, local landscape depressions are typically underused. In this work, a case-study of a small suburban park, squeezed in between two major arterial roads, is analyzed. The spatially dependent road traffic noise exposure in the park is assessed in detail by mobile sound pressure level measurements. Local reductions of up to 6-7 dBA are found at landscape depressions of only a few meters deep. It can therefore be concluded that this is an efficient measure and should be added to the environmental noise control toolbox for noise polluted parks.


Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 903 ◽  
Author(s):  
Juan M. Navarro ◽  
Raquel Martínez-España ◽  
Andrés Bueno-Crespo ◽  
Ramón Martínez ◽  
José M. Cecilia

Wireless acoustic sensor networks are nowadays an essential tool for noise pollution monitoring and managing in cities. The increased computing capacity of the nodes that create the network is allowing the addition of processing algorithms and artificial intelligence that provide more information about the sound sources and environment, e.g., detect sound events or calculate loudness. Several models to predict sound pressure levels in cities are available, mainly road, railway and aerial traffic noise. However, these models are mostly based in auxiliary data, e.g., vehicles flow or street geometry, and predict equivalent levels for a temporal long-term. Therefore, forecasting of temporal short-term sound levels could be a helpful tool for urban planners and managers. In this work, a Long Short-Term Memory (LSTM) deep neural network technique is proposed to model temporal behavior of sound levels at a certain location, both sound pressure level and loudness level, in order to predict near-time future values. The proposed technique can be trained for and integrated in every node of a sensor network to provide novel functionalities, e.g., a method of early warning against noise pollution and of backup in case of node or network malfunction. To validate this approach, one-minute period equivalent sound levels, captured in a two-month measurement campaign by a node of a deployed network of acoustic sensors, have been used to train it and to obtain different forecasting models. Assessments of the developed LSTM models and Auto regressive integrated moving average models were performed to predict sound levels for several time periods, from 1 to 60 min. Comparison of the results show that the LSTM models outperform the statistics-based models. In general, the LSTM models achieve a prediction of values with a mean square error less than 4.3 dB for sound pressure level and less than 2 phons for loudness. Moreover, the goodness of fit of the LSTM models and the behavior pattern of the data in terms of prediction of sound levels are satisfactory.


2015 ◽  
Vol 4 (1) ◽  
pp. 196
Author(s):  
Nader Mohammadi ◽  
Kami Mohammadi

The objective of this study is to identify the sources of acoustic noise (noise pollution) in the Noor-Abad gas compressor station and then to prioritize the station equipment based on noise pollution. First, the key locations inside the station as well as in the surrounding residential area, aka the study area, are determined for the measurement of sound pressure level. Then, the sound pressure level is measured at those points, and the related noise map is produced. Based on the noise map, the noise condition in the study area is evaluated by comparing the measured acoustic parameters with allowable standard values. Dangerous regions and critical points are thus identified. The major noise sources consist of main blowdown, units’ blowdowns, scrubbers, and turbo-compressors. The sound pressure level of main blowdown is measured at two intervals from its position: 80 m inside the station and 600 m outside the station (at the edge of the surrounding residential area). Also, the sound pressure level for a unit blowdown and a scrubber is measured at respectively 25 m and 40 m from their positions. Finally, the station equipment is prioritized based on noise pollution. The analysis of measurement results showed that the main noise sources are, respectively, the station main blowdown, units’ scrubbers, units’ blowdowns, turbo-compressors, and gas pipelines.


Author(s):  
Hadi ALIMORADI ◽  
Ruhollah FALLAH MADAVARI ◽  
Mahsa NAZARI ◽  
Reza JAFARI NODOSHAN ◽  
Mohammad Javad ZARE SAKHVIDI ◽  
...  

Introduction: Loud noise is one of the harmful factors that affects industry workers seriously. In the steel industry, a wide range of equipment and machinery are used in the production processes, which are considered as the sources of annoying noise. Sound has immediate and delayed harmful effects on the process of concentration and increases blood pressure. The aim of this study was to investigate the effect of noise in two different ranges in the control and case groups within the authorized (between 60 to 85 dB) and unauthorized (above 85 dB) categories in the steel industry. Methods: This cross-sectional study was conducted among 300 workers in Isfahan Steel Industries. Environmental sound assessment was performed to determine the distribution of sound pressure level according to the ISO 9612 standard in the company's production units. In this method, the number of exposed people, the exposure time, and the weight factor corresponding to the sound pressure level were calculated in 30 minutes. The DASS-42 and Harmon Jones (DARQ) questionnaires were used to predict the mental state of the participants and to measure the severity of mood swings and arousal. The collected data were analyzed using SPSS statistical software (ver22). Results: Based on the findings, age had a significant effect on depression, marital status had a significant effect on anxiety, and work shift had a significant effect on the level of stress and cognitive dissonance of employees. The stress mean was significantly higher in the case group (14.40 ± 1.66) than the control group (p <0.001). This indicates the effect of sound intensity level on the increase of stress and cognitive dissonance of workers in a noisy environment. With increasing exposure to sound, the participants’ stress decreased (p <0.05). Conclusion: Considering the positive and significant relationship of noise level with stress and cognitive inconsistency of workers in the case group, it is necessary to take effective preventive measures to prevent psychological harm and maintain the workers' health in this industry. In order to reduce noise, a number of applicable solutions have been proposed including spatial planning, selection of suitable materials, control of noise pollution related to outdoor construction, control of noise pollution related to indoor construction, and training.


2021 ◽  
Vol 69 (6) ◽  
pp. 518-529
Author(s):  
Changyong Jiang ◽  
Xiang Liu ◽  
Stephany Y. Xu ◽  
Shangyu Zhang

In this paper, the efficacy of porous ceiling treatment to reduce noise levels inside a typical tunnel is examined with a validated modal-based prediction method. It is found that, for a point source, the effect of increasing porous ceiling thickness on sound pressure level (SPL) attenuation along the tunnel is limited. A porous ceiling with thickness of 0.3 m is comparable with an infinite porous ceiling in middle and high frequency ranges. For a line source, the effect of ceiling thickness on SPL reduc- tion in this typical tunnel is limited. Sound pressure level reduction of 4 dBA is real- ized with 0.3 m porous ceiling, which is the same as infinite ceiling and only 1 dBA smaller than the theoretically optimized value. These results suggest that, in the event only ceiling treatment is considered, 0.3 m porous material is sufficient for noise re- duction in this typical tunnel.


2018 ◽  
Vol 34 (6) ◽  
pp. 921-927
Author(s):  
Martin Pšenka ◽  
Štefan Mihina ◽  
Matti Järvi ◽  
Marie Šístková ◽  
Viera Kažimírová ◽  
...  

Abstract. The aim of this article is to evaluate the noise levels of different milking systems. Noise was measured at 15 dairy farms in Slovakia, Finland, and the Czech Republic. Out of these, there were three herringbone, three tandem, three side-by-side, and three rotary milking parlors, and three automatic milking systems (AMS). Brüel&amp;Kjær type 2270 sound analyser was used for measuring noise levels. Equivalent sound pressure level (LAeq), maximum sound pressure level (LAFmax), and peak values (LCPk) have been recorded in each milking system during the entire herd milking session. Keywords: Animal welfare, Dairy cows, Milking device, Noise exposure.


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