Rapid estimation of tire-wear particle concentration in road dust using PM10 and traffic data in a ternary plot

Sohee Jeong; Hyeokjin Shin; Hyeongjeong Ryu; Min Gyu Lee; Jaehwan Hong; Jung-Taek Kwon; Jaewoong Lee; Younghun Kim

doi:10.1016/j.scitotenv.2023.167227

Rapid estimation of tire-wear particle concentration in road dust using PM₁₀ and traffic data in a ternary plot

Sci Total Environ. 2023 Dec 20:905:167227. doi: 10.1016/j.scitotenv.2023.167227. Epub 2023 Sep 19.

Authors

Sohee Jeong¹, Hyeokjin Shin¹, Hyeongjeong Ryu¹, Min Gyu Lee¹, Jaehwan Hong¹, Jung-Taek Kwon², Jaewoong Lee², Younghun Kim³

Affiliations

¹ Department of Chemical Engineering, Kwangwoon University, Seoul 01897, South Korea.
² Risk Assessment Division, Environmental Health Research Department, National Institute of Environmental Research, Incheon 22733, South Korea.
³ Department of Chemical Engineering, Kwangwoon University, Seoul 01897, South Korea. Electronic address: korea1@kw.ac.kr.

PMID: 37734610
DOI: 10.1016/j.scitotenv.2023.167227

Abstract

Air pollution, a pressing global issue, is significantly exacerbated by airborne particulate matter (PM), affecting air quality and human health. Urban vehicular activities majorly contribute to PM rise through both exhaust and non-exhaust emissions. Despite strides in managing exhaust emissions, non-exhaust particles, such as tire wear particles (TWP) remain under-addressed. This research proposes a method for estimating TWP concentrations using PM₁₀ data and traffic activity, which could offer a valuable tool for controlling roadside fine particles and TWP. This paper introduces a ternary plotting technique and step-by-step procedure to estimate TWP levels in road dust using only PM₁₀ and traffic data. Traditional analysis of TWP via pyrolysis-gas chromatography-mass spectrometry is complex and time-consuming. Hence, our proposed approach presents an alternate method that leverages readily accessible PM and traffic data, providing critical information for road management interpretation. The triangular plot analysis demonstrated a linear correlation: [log(Traffic) + 2]-[250,000/TWP-13]-0.18PM₁₀. While the resulting correlation may vary based on specific road conditions, the method can be tailored to different regions, offering insights into efficient estimation of TWP concentrations and promoting improved roadside pollution management.

Keywords: Particulate matter; Road dust; Ternary plot; Tire-wear particle; Traffic.