Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105906
Title: Noise indicators for size distributions of airborne particles and traffic activities in urban areas
Authors: Jeon, Jin Yong
Hong, Joo Young
Kim, Sung Min
Kim, Ki-Hyun
Keywords: Noise Pollution
Air Pollution
DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Jeon, J. Y., Hong, J. Y., Kim, S. M. & Kim, K.-H. (2018). Noise indicators for size distributions of airborne particles and traffic activities in urban areas. Sustainability, 10(12), 4599-. doi:10.3390/su10124599
Series/Report no.: Sustainability
Abstract: The aim of this study was to explore the relationships among the particle number concentration (PNC), noise, and traffic conditions. Field measurements were conducted to measure the temporal variabilities of the noise levels and PNC over 24 h in a location adjacent to three main traffic roads in Seoul, Korea. The PNC was measured in the range of 0.3 to 10 µm. The noise data was measured by utilizing both the overall levels and spectral characteristics. Traffic data including volumes and speeds of vehicles on the roads were also collected. The results showed that the correlations among the three key parameters varied depending on changes in the noise frequency and particle size. The noise levels at 100–200 Hz were positively correlated with traffic volume and submicron particles. In contrast, they exhibited inverse correlations with the traffic speed and the number of larger particles (>2.5 µm). Compared to noise levels at 100–200 Hz, noise levels at 1–2 kHz exhibited reverse relationships between the traffic and PNC. Submicron particles (0.3–1.0 µm) tended to be more strongly associated with noise levels during the daytime, while those greater than 2.5 µm maintained relatively stable correlations with the noise throughout the day. The findings address the importance of temporal and spectral-specific monitoring of air and noise pollutants for a better understanding of the exposure of the community to air and noise pollution.
URI: https://hdl.handle.net/10356/105906
http://hdl.handle.net/10220/47900
DOI: 10.3390/su10124599
Schools: School of Electrical and Electronic Engineering 
Rights: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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