Mobile measurements for distribution and attribution of particulate matter in urban environments

0580042 - ÚVGZ 2024 RIV GB eng J - Journal Article
Harr, L. - Sinsel, T. - Simon, H. - Torbenson, M. - Esper, Jan
Mobile measurements for distribution and attribution of particulate matter in urban environments.
Atmospheric Environment. Roč. 315, DEC (2023), č. článku 120164. ISSN 1352-2310. E-ISSN 1873-2844
R&D Projects: GA MŠMT(CZ) EF16_019/0000797
Research Infrastructure: CzeCOS IV - 90248
Institutional support: RVO:86652079
Keywords : air-quality * electric vehicle * particle mass * pm * emissions * fine * technologies * pollution * ultrafine * exposure * Tyre and brake abrasion * Traffic emission * Mobile measurement * grimm 11-r * Cargo bicycle * Emission sources * Particle number concentration
OECD category: Meteorology and atmospheric sciences
Impact factor: 5, year: 2022
Method of publishing: Limited access
https://www.sciencedirect.com/science/article/pii/S1352231023005903?via%3Dihub

Particulate matter (PM) sources differ in urban environments and may show spatiotemporal distinct patterns for varying particle aerodynamic diameters (D-P). We here assess such patterns using high-resolution PM <= 10 mu m data recorded with a cargo bike along a 14 km route through urban, suburban, and rural areas in Mainz (Germany). The measurements conducted twice a day between May and August 2021 reveal decreasing particle number concentration (PNC) with increasing DP including similar to 6000 times higher particle numbers at D-P 0.22-0.25 mu m compared to D-P 4-5 mu m. Total mass concentration is bi-modally distributed and dominated by particles <0.3 mu m and from 3 to 5 mu m representing 36 and 22% of the entire air load, respectively. PM concentrations in Mainz are significantly higher in the morning than in the afternoon, and PM1 and PM10 are 13 and 31% higher in urban compared to surrounding suburban and rural areas. The high-resolution measurements also revealed 30% higher PM concentrations at D-P 3-5 mu m in the urban compared to the rural sectors, which is indicative for road dust, brake and tyre abrasion as the main source. D-P distribution in rural hotspots is generally shifted toward larger particles >3 mu m, most likely related to natural dust from agricultural fields. These findings show that highresolution PM profiles can skillfully be recorded using bikes as mobile platform to identify spatial pollution patterns and attribute DP spectra to particular emission sources.
Permanent Link: https://hdl.handle.net/11104/0348824