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Roadside Vehicle Particulate Vertical Dispersion Model for Friction Course Materials: A Case of Hong Kong

Mak, Kai Long, Loh, Wai Keung Anthony, Kwan, Chun Kit Wilson, Ma, Ka Yee (2024) Roadside Vehicle Particulate Vertical Dispersion Model for Friction Course Materials: A Case of Hong Kong. Trends in Applied Sciences Research, 19 (1). pp. 170-179. ISSN 1819-3579. E-ISSN 2151-7908. (doi:10.3923/tasr.2024.170.179) (KAR id:107049)

Abstract

Background and Objective: The rapid urban development has caused various pollution in Hong Kong. However, the current measures adopted are aimed at controlling the surface level emission, while the vertical dispersion of pollutants is less investigated. This research project aims to identify the vertical dispersion patterns of particulate matter and noise emitted from road traffic and their decay rates with increasing vertical distance from the source and examine the possible correlation between traffic noise frequency levels and vehicle-emitted particulate. Materials and Methods: Three sets of equipment have been installed at three different heights on building facades perpendicular to the road surface, facing traffic to monitor PM concentrations (PM1, PM2.5, PM4.25 and PM10), noise frequencies and other environmental data namely temperature, relative humidity and wind speed. Results: The study anticipates uncovering a positive relationship between vehicular particulate matter emissions and traffic-related noise on lower floors, specifically at an 800 Hz noise frequency. Analysis of the three dimensional plots indicates that pollutant concentrations are highest at lower levels. Notably, PM1, PM2.5 and PM4.25 demonstrate relatively high R-squared values (PM1 = 0.674, PM2.5 = 0.649 and PM4.25 = 0.538), indicating a satisfactory fit of these models to the data. Conclusion: By highlighting the often-overlooked vertical transmission of particulate matter and noise from vehicles, this research contributes to a deeper understanding of air and noise pollution levels in high-rise urban environments. These insights hold the potential to inform future urban planning initiatives aimed at enhancing public health outcomes.

Item Type: Article
DOI/Identification number: 10.3923/tasr.2024.170.179
Uncontrolled keywords: Vertical dispersion; particulate matters (PM); urban planning; air pollution; noise pollution; pollutant dispersion
Subjects: Q Science > Operations Research - Theory
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Funders: University of Kent (https://ror.org/00xkeyj56)
Depositing User: Ricky Mak
Date Deposited: 30 Aug 2024 11:07 UTC
Last Modified: 04 Sep 2024 02:46 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/107049 (The current URI for this page, for reference purposes)

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