Reconciling mass and number emissions through particle size: Implications for urban ultrafine particle modelling
Abstract
Ultrafine particles (UFPs) contribute only a small fraction of particulate mass but dominate atmospheric particle number, making size-resolved particle-number (PN) emissions essential for urban exposure modelling. This study evaluates how methodologies for estimating size-resolved UFP emissions affect simulated PN concentrations over Greater Paris, from regional background to street level. Simulations were performed for summer 2021 with the WRF-CHIMERE/MUNICH/SSH-aerosol modelling framework. A mass- and number-conserving algorithm was implemented to consistently combine PM mass emissions with PN emission factors in a sectional aerosol model. Sensitivity scenarios examined traffic exhaust emissions constrained by COPERT or on-board-measurement PN factors, traffic non-exhaust emissions, and the sector related to industrial processes without combustion, which includes construction activities. The reference simulation, based on PM mass emissions and prescribed representative diameters by activity sector, reproduced total PN concentrations well at background and traffic stations, showing that a simple mass-based methodology can estimate total PN concentrations across scales. However, uncertainties remained in the simulated size distribution, particularly for particles around 10 nm. Non-exhaust traffic emissions had a limited but non-negligible influence, contributing to about a third of total traffic PN. More detailed size-resolved PN emission factors, including particles below 10 nm, are needed to improve UFP exposure modelling.
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BibTeX
@article{park2026reconciling,
title = {{Reconciling mass and number emissions through particle size: Implications for urban ultrafine particle modelling}},
author = {Soo-Jin Park and Lya Lugon and Youngseob Kim and Alexia Baudic and Amandine Rosso and Jeroen Kuenen and Marya El Malki and Karine Sartelet},
journal = {Journal of Hazardous Materials},
year = {2026},
month = oct,
doi = {10.1016/j.jhazmat.2026.143879},
url = {https://hal.science/hal-05834535v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - Reconciling mass and number emissions through particle size: Implications for urban ultrafine particle modelling
AU - Soo-Jin Park
AU - Lya Lugon
AU - Youngseob Kim
AU - Alexia Baudic
AU - Amandine Rosso
AU - Jeroen Kuenen
AU - Marya El Malki
AU - Karine Sartelet
PY - 2026
DA - 2026/10/22
JO - Journal of Hazardous Materials
DO - 10.1016/j.jhazmat.2026.143879
UR - https://hal.science/hal-05834535v1
AB - Ultrafine particles (UFPs) contribute only a small fraction of particulate mass but dominate atmospheric particle number, making size-resolved particle-number (PN) emissions essential for urban exposure modelling. This study evaluates how methodologies for estimating size-resolved UFP emissions affect simulated PN concentrations over Greater Paris, from regional background to street level. Simulations were performed for summer 2021 with the WRF-CHIMERE/MUNICH/SSH-aerosol modelling framework. A mass- and number-conserving algorithm was implemented to consistently combine PM mass emissions with PN emission factors in a sectional aerosol model. Sensitivity scenarios examined traffic exhaust emissions constrained by COPERT or on-board-measurement PN factors, traffic non-exhaust emissions, and the sector related to industrial processes without combustion, which includes construction activities. The reference simulation, based on PM mass emissions and prescribed representative diameters by activity sector, reproduced total PN concentrations well at background and traffic stations, showing that a simple mass-based methodology can estimate total PN concentrations across scales. However, uncertainties remained in the simulated size distribution, particularly for particles around 10 nm. Non-exhaust traffic emissions had a limited but non-negligible influence, contributing to about a third of total traffic PN. More detailed size-resolved PN emission factors, including particles below 10 nm, are needed to improve UFP exposure modelling.
SN - 0304-3894
SN - 1873-3336
ER -