From real-time to long-term source apportionment of PM 10 using high-time-resolution measurements of aerosol physical properties: methodology and example application at an urban background site (Aosta, Italy)
5 affiliations
- 1Agenzia Regionale Protezione Ambiente Valle d'Aosta (Saint-Christophe, Italy)
- 2Regional Environmental Protection Agency (ARPA) of the Aosta Valley, Loc. La Maladière 48, Saint-Christophe, 11020, Italy
- 3National Research Council, Institute of Atmospheric Sciences and Climate, CNR-ISAC, Via Fosso del Cavaliere 100, Roma, 00133, Italy
- 4GEMMA Center, Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Piazza dell'Ateneo Nuovo 1, Milano, 20126, Italy
- 5National Research Council, Institute of Methodologies for Environmental Analysis, CNR-IMAA, Contrada S. Loja, Tito Scalo, 85050, Italy
Abstract
Identifying aerosol sources is essential for designing effective air quality policies. This study introduces a novel PM10 source apportionment approach – RASPBERRY (Real-time Aerosol Source apportionment using Physics-Based Experimental data and multivaRiate factoR analYsis) – based on the analysis of aerosol physical properties, namely particle size distributions and spectrally resolved light absorption. The availability of such measurements at high temporal resolution enables aerosol source apportionment from real time to long-term scales. To demonstrate the implementation of RASPBERRY, we apply the method to a five-year hourly dataset (2020–2024) from an urban background site in the north-western Italian Alps, combining observations from a cost-effective optical particle counter (Palas Fidas 200) and an aethalometer (Magee Scientific AE33). RASPBERRY identifies six source factors contributing to PM10: traffic (9 %), biomass burning (10 %), two secondary aerosol modes (condensation, 23 %, and droplet, 16 %), desert dust (21 %), and local dust resuspension (21 %). Hourly resolved RASPBERRY estimates, averaged to daily values, show strong agreement with traditional chemical source apportionment techniques. Further validation is provided through comparisons with ground-based remote sensing (lidar-ceilometers, sun photometers) and modelling tools (Validated ReAnalysis ensemble from the Copernicus Atmosphere Monitoring Service). Selected real-time applications are also presented, including emergency surveillance during accidental events and the rapid identification of long-range transport of secondary particles, desert dust, and smoke (Canadian wildfires, 2023–2024). Although demonstrated at a single site, RASPBERRY is readily transferable to international air quality networks, as it relies on optical instruments commonly employed by regulatory authorities and environmental protection agencies.
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BibTeX
@article{diemoz2026from,
title = {{From real-time to long-term source apportionment of PM 10 using high-time-resolution measurements of aerosol physical properties: methodology and example application at an urban background site (Aosta, Italy)}},
author = {Henri Diémoz and Francesca Barnaba and Luca Ferrero and Ivan K. F. Tombolato and Caterina Mapelli and Annachiara Bellini and Claudia Desandré and Tiziana Magri and Manuela Zublena},
journal = {Atmospheric measurement techniques},
year = {2026},
month = jun,
doi = {10.5194/amt-19-3625-2026},
url = {https://doi.org/10.5194/amt-19-3625-2026},
note = {CC BY},
}
RIS
TY - JOUR
TI - From real-time to long-term source apportionment of PM 10 using high-time-resolution measurements of aerosol physical properties: methodology and example application at an urban background site (Aosta, Italy)
AU - Henri Diémoz
AU - Francesca Barnaba
AU - Luca Ferrero
AU - Ivan K. F. Tombolato
AU - Caterina Mapelli
AU - Annachiara Bellini
AU - Claudia Desandré
AU - Tiziana Magri
AU - Manuela Zublena
PY - 2026
DA - 2026/06/03
JO - Atmospheric measurement techniques
DO - 10.5194/amt-19-3625-2026
UR - https://doi.org/10.5194/amt-19-3625-2026
AB - Identifying aerosol sources is essential for designing effective air quality policies. This study introduces a novel PM10 source apportionment approach – RASPBERRY (Real-time Aerosol Source apportionment using Physics-Based Experimental data and multivaRiate factoR analYsis) – based on the analysis of aerosol physical properties, namely particle size distributions and spectrally resolved light absorption. The availability of such measurements at high temporal resolution enables aerosol source apportionment from real time to long-term scales. To demonstrate the implementation of RASPBERRY, we apply the method to a five-year hourly dataset (2020–2024) from an urban background site in the north-western Italian Alps, combining observations from a cost-effective optical particle counter (Palas Fidas 200) and an aethalometer (Magee Scientific AE33). RASPBERRY identifies six source factors contributing to PM10: traffic (9 %), biomass burning (10 %), two secondary aerosol modes (condensation, 23 %, and droplet, 16 %), desert dust (21 %), and local dust resuspension (21 %). Hourly resolved RASPBERRY estimates, averaged to daily values, show strong agreement with traditional chemical source apportionment techniques. Further validation is provided through comparisons with ground-based remote sensing (lidar-ceilometers, sun photometers) and modelling tools (Validated ReAnalysis ensemble from the Copernicus Atmosphere Monitoring Service). Selected real-time applications are also presented, including emergency surveillance during accidental events and the rapid identification of long-range transport of secondary particles, desert dust, and smoke (Canadian wildfires, 2023–2024). Although demonstrated at a single site, RASPBERRY is readily transferable to international air quality networks, as it relies on optical instruments commonly employed by regulatory authorities and environmental protection agencies.
SN - 1867-1381
SN - 1867-8548
ER -