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Measuring Sub-23 Nanometer Real Driving Particle Number Emissions Using the Portable DownToTen Sampling System
Published on: May 22, 2020
City-Scale Assessment of Non-Exhaust PM10 from Emissions to Exposure using a Coupled Chemistry-CFD Framework
Seon-Young Park1, Eunbi Kim1, Myeong-Gyun Kim1
1Department of Environmental Engineering and Energy, Myongji University, Yongin 17058, Republic of Korea.
Abstract:
As tailpipe exhaust emissions decline under increasingly stringent vehicle-emission regulations, non-exhaust particulate matter (PM10) from brake, tire, and road wear is becoming an increasingly important source of urban air pollution. However, how uncertainty in non-exhaust emission factors influences urban PM10 and relative outdoor activity-weighted exposure remains poorly understood. We integrated two non-exhaust emission-factor frameworks with a three-dimensional city-scale coupled CFD-chemistry model and population activity data to evaluate how emission-factor assumptions affect PM10 concentrations, source partitioning, and exposure. The EMEP/EEA Guidebook and the Korea Institute of Machinery and Materials (KIMM) emission factors were implemented in the Fine-scale Air Quality Simulation Unit (FASU) for a densely built urban district of Seoul. Both emission-factor frameworks produced similar total non-exhaust PM10 concentrations but markedly different source partitioning. Brake wear dominated in the EMEP/EEA scenario, whereas road wear was the major contributor in the KIMM scenario. Non-exhaust PM10 contributed modestly to domain-mean concentrations but accounted for up to 70% of total PM10 in near-road and densely built urban areas. Incorporating the 2022 Seoul Time-Activity Profile showed that outdoor activity-weighted contributions reached approximately 9-10% in commercial and traffic areas and exceeded the corresponding concentration-based estimates because peak traffic emissions coincided with elevated outdoor activity. These findings demonstrated that similar non-exhaust PM10 concentrations could mask substantial differences in source composition and mitigation priorities. They further highlighted the importance of integrating emission-factor uncertainty with city-scale CFD-chemistry simulations and population activity to identify hotspot-prone areas and exposure-relevant periods and to support exposure-oriented urban air-quality management.
