6 research outputs found

    European aerosol phenomenology - 8 : Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets

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    Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013-2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30-240 min) and long-term data coverage (9-36 months), providing essential information to improve/validate air quality, health impact, and climate models.Peer reviewe

    Long-term real-time chemical characterization of submicron aerosols at Montsec (southern Pyrenees, 1570ma.s.l.)

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    Real-time measurements of inorganic (sulfate, nitrate, ammonium, chloride and black carbon (BC)) and organic submicron aerosols (particles with an aerodynamic diameter of less than 1 Î1/4m) from a continental background site (Montsec, MSC, 1570 m a.s.l.) in the western Mediterranean Basin (WMB) were conducted for 10 months (July 2011-April 2012). An aerosol chemical speciation monitor (ACSM) was co-located with other online and offline PM1 measurements. Analyses of the hourly, diurnal, and seasonal variations are presented here, for the first time, for this region. Seasonal trends in PM1 components are attributed to variations in evolution of the planetary boundary layer (PBL) height, air mass origin, and meteorological conditions. In summer, the higher temperature and solar radiation increases convection, enhancing the growth of the PBL and the transport of anthropogenic pollutants towards high altitude sites. Furthermore, the regional recirculation of air masses over the WMB creates a continuous increase in the background concentrations of PM1 components and causes the formation of reservoir layers at relatively high altitudes. The combination of all these atmospheric processes results in a high variability of PM1 components, with poorly defined daily patterns, except for the organic aerosols (OA). OA was mostly composed (up to 90%) of oxygenated organic aerosol (OOA), split in two types: semivolatile (SV-OOA) and low-volatility (LV-OOA), the rest being hydrocarbon-like OA (HOA). The marked diurnal cycles of OA components regardless of the air mass origin indicates that they are not only associated with anthropogenic and long-range-transported secondary OA (SOA) but also with recently produced biogenic SOA. Very different conditions drive the aerosol phenomenology in winter at MSC. The thermal inversions and the lower vertical development of the PBL leave MSC in the free troposphere most of the day, being affected by PBL air masses only after midday, when the mountain breezes transport emissions from the adjacent valleys and plains to the top of the mountain. This results in clear diurnal patterns of both organic and inorganic concentrations. OA was also mainly composed (71%) of OOA, with contributions from HOA (5%) and biomass burning OA (BBOA; 24%). Moreover, in winter sporadic long-range transport from mainland Europe is observed. The results obtained in the present study highlight the importance of SOA formation processes at a remote site such as MSC, especially in summer. Additional research is needed to characterize the sources and processes of SOA formation at remote sites.This study was supported by the Ministry of Economy and Competitiveness and FEDER funds under the PRISMA (CGL2012-39623-C02-1) and CARIATI (CGL2008- 06294/CLI) projects, and by the Generalitat de Catalunya (AGAUR 2009 SGR8 and the DGQA). The research received funding from the European Union Seventh Framework Programme (FP7/ 2007-2013) ACTRIS under grant agreement no. 262254. We would like to extend their gratitude to the personnel from the COU and the OAdM. We would also like to express our gratitude to the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model, and boundary layer height calculation, used in this publication. D. A. Day and J. L. Jimenez thank the DOE (BER/ASR) DE-SC0011105 and NOAA NA13OAR4310063.Peer reviewe

    A new method for long-term source apportionment with time-dependent factor profiles and uncertainty assessment using SoFi Pro: application to 1 year of organic aerosol data

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    A new methodology for performing long-term source apportionment (SA) using positive matrix factorization (PMF) is presented. The method is implemented within the SoFi Pro software package and uses the multilinear engine (ME-2) as a PMF solver. The technique is applied to a 1-year aerosol chemical speciation monitor (ACSM) dataset from downtown Zurich, Switzerland. The measured organic aerosol mass spectra were analyzed by PMF using a small (14 d) and rolling PMF window to account for the temporal evolution of the sources. The rotational ambiguity is explored and the uncertainties of the PMF solutions were estimated. Factor-tracer correlations for averaged seasonal results from the rolling window analysis are higher than those retrieved from conventional PMF analyses of individual seasons, highlighting the improved performance of the rolling window algorithm for long-term data. In this study four to five factors were tested for every PMF window. Factor profiles for primary organic aerosol from traffic (HOA), cooking (COA) and biomass burning (BBOA) were constrained. Secondary organic aerosol was represented by either the combination of semi-volatile and low-volatility organic aerosol (SV-OOA and LV-OOA, respectively) or by a single OOA when this separation was not robust. This scheme led to roughly 40 000 PMF runs. Full visual inspection of all these PMF runs is unrealistic and is replaced by predefined user-selected criteria, which allow factor sorting and PMF run acceptance/rejection. The selected criteria for traffic (HOA) and BBOA were the correlation with equivalent black carbon from traffic (eBC(tr)) and the explained variation of m/z 60, respectively. COA was assessed by the prominence of a lunchtime concentration peak within the diurnal cycle. SV-OOA and LV-OOA were evaluated based on the fractions of m/z 43 and 44 in their respective factor profiles. Seasonal pre-tests revealed a noncontinuous separation of OOA into SV-OOA and LV-OOA, in particular during the warm seasons. Therefore, a differentiation between four-factor solutions (HOA, COA, BBOA and OOA) and five-factor solutions (HOA, COA, BBOA, SVOOA and LV-OOA) was also conducted based on the criterion for SV-OOA. HOA and COA contribute between 0.4-0.7 mu g m(-3) (7.8 %-9.0 %) and 0.7-1.2 mu g m(-3) (12.2 %-15.7 %) on average throughout the year, respectively. BBOA shows a strong yearly cycle with the lowest mean concentrations in summer (0.6 mu g m(-3), 12.0 %), slightly higher mean concentrations during spring and fall (1.0 and 1.5 mu g m(-3), or 15.6% and 18.6 %, respectively), and the highest mean concentrations during winter (1.9 mu g m(-3), 25.0 %). In summer, OOA is separated into SV-OOA and LV-OOA, with mean concentrations of 1.4 mu g m(-3) (26.5 %) and 2.2 mu g m(-3) (40.3 %), respectively. For the remaining seasons the seasonal concentrations of SV-OOA, LV-OOA and OOA range from 0.3 to 1.1 mu g m(-3) (3.4 %-15.9 %), from 0.6 to 2.2 mu g m(-3) (7.7 %33.7 %) and from 0.9 to 3.1 mu g m(-3) (13.7 %-39.9 %), respectively. The relative PMF errors modeled for this study for HOA, COA, BBOA, LV-OOA, SV-OOA and OOA are on average +/- 34 %, +/- 27 %, +/- 30 %, +/- 11 %, +/- 25 % and +/- 12 %, respectively

    European aerosol phenomenology − 8: Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets

    No full text
    Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013–2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30–240 min) and long-term data coverage (9–36 months), providing essential information to improve/validate air quality, health impact, and climate models
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