scholarly journals 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

2021 ◽  
Vol 14 (2) ◽  
pp. 923-943
Author(s):  
Francesco Canonaco ◽  
Anna Tobler ◽  
Gang Chen ◽  
Yulia Sosedova ◽  
Jay Gates Slowik ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Organic Aerosol ◽  
Uncertainty Assessment ◽  
Aerosol Mass ◽  
Five Factors ◽  
Concentration Peak ◽  
Rolling Window ◽  
Improved Performance ◽  
Term Data

Abstract. 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 (eBCtr) 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 non-continuous 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, SV-OOA and LV-OOA) was also conducted based on the criterion for SV-OOA. HOA and COA contribute between 0.4–0.7 µg m−3 (7.8 %–9.0 %) and 0.7–1.2 µg 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 µg m−3, 12.0 %), slightly higher mean concentrations during spring and fall (1.0 and 1.5 µg m−3, or 15.6 % and 18.6 %, respectively), and the highest mean concentrations during winter (1.9 µg m−3, 25.0 %). In summer, OOA is separated into SV-OOA and LV-OOA, with mean concentrations of 1.4 µg m−3 (26.5 %) and 2.2 µg 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 µg m−3 (3.4 %–15.9 %), from 0.6 to 2.2 µg m−3 (7.7 %–33.7 %) and from 0.9 to 3.1 µg 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.

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

2020 ◽  
Author(s):  
Francesco Canonaco ◽  
Anna Tobler ◽  
Gang Chen ◽  
Yulia Sosedova ◽  
Jay Gates Slowik ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Uncertainty Assessment ◽  
Aerosol Mass ◽  
Concentration Peak ◽  
Rolling Window ◽  
Improved Performance ◽  
One Year

Abstract. 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 one-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 days) and rolling PMF window to account for the temporal evolution of the sources. The rotational ambiguity is explored and the uncertainty 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 leads 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 biomass burning (BBOA) were the correlation with equivalent black carbon (eBCtr) 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 fraction of m/z 43 and m/z 44 in their respective factor profiles. Seasonal pre-tests revealed a non-continuous 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, SV-OOA and LV-OOA) was also conducted based on the criterion for SV-OOA. HOA and COA contribute between 0.4–0.7 μg m−3 (7.8–9.0 %) and 0.7–1.2 μg 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 μg m−3, 12.0 %), slightly higher mean concentrations during spring and fall (1.0 and 1.5 μg m−3, or 15.6 and 18.6 %, respectively), and highest mean concentrations during winter (1.9 μg m−3, 25.0 %). In summer, OOA is separated into SV-OOA and LV-OOA, with mean concentrations of 1.4 μg m−3 (26.5 %) and 2.2 μg m−3 (40.3 %), respectively. For the remaining seasons the seasonal concentrations of SV-OOA, LV-OOA and OOA range from 0.3–1.1 μg m−3 (3.4–15.9 %), 0.6–2.2 μg m−3 (7.7–33.7 %) and 0.9–3.1 μg m−3 (13.7–39.9 %), respectively. The relative PMF errors modelled for this study for HOA, COA, BBOA, LV-OOA, SV-OOA and OOA are on average ±34 %, ±27 %, ±30, ±11 %, ±25 % and ±12 %, respectively.

scholarly journals Organic aerosol source apportionment by offline-AMS over a full year in Marseille

2017 ◽  
Author(s):  
Carlo Bozzetti ◽  
Imad El Haddad ◽  
Dalia Salameh ◽  
Kaspar Rudolf Daellenbach ◽  
Paola Fermo ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Mediterranean Sea ◽  
Source Apportionment ◽  
Organic Aerosol ◽  
Aerodynamic Diameter ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass ◽  
Aerosol Source

Abstract. We investigated the seasonal trends of OA sources affecting the air quality of Marseille (France) which is the largest harbor of the Mediterranean Sea. This was achieved by measurements of nebulized filter extracts using an aerosol mass spectrometer (offline-AMS). PM2.5 (particulate matter with an aerodynamic diameter

scholarly journals Source Apportionment of Fine Organic and Inorganic Atmospheric Aerosol in an Urban Background Area in Greece

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 330 ◽  
Author(s):  
Manousos Ioannis Manousakas ◽  
Kalliopi Florou ◽  
Spyros N. Pandis
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Fine Particulate Matter ◽  
Organic Aerosols ◽  
Mitigation Strategies ◽  
Traffic Emissions ◽  
Aerosol Mass ◽  
Aerosol Mass Spectrometry ◽  
Five Factors ◽  
Potential Risks

Fine particulate matter (PM) originates from various emission sources and physicochemical processes. Quantification of the sources of PM is an important step during the planning of efficient mitigation strategies and the investigation of the potential risks to human health. Usually, source apportionment studies focus either on the organic or on the inorganic fraction of PM. In this study that took place in Patras, Greece, we address both PM fractions by combining measurements from a range of on- and off-line techniques, including elemental composition, organic and elemental carbon (OC and EC) measurements, and high-resolution Aerosol Mass Spectrometry (AMS) from different techniques. Six fine PM2.5 sources were identified based on the off-line measurements: secondary sulfate (34%), biomass burning (15%), exhaust traffic emissions (13%), nonexhaust traffic emissions (12%), mineral dust (10%), and sea salt (5%). The analysis of the AMS spectra quantified five factors: two oxygenated organic aerosols (OOA) factors (an OOA and a marine-related OOA, 52% of the total organic aerosols (OA)), cooking OA (COA, 11%) and two biomass burning OA (BBOA-I and BBOA-II, 37% in total) factors. The results of the two methods were synthesized, showcasing the complementarity of the two methodologies for fine PM source identification. The synthesis suggests that the contribution of biomass burning is quite robust, but that the exhaust traffic emissions are not due to local sources and may also include secondary OA from other sources.

scholarly journals Simultaneous Aerosol Mass Spectrometry and Chemical Ionisation Mass Spectrometry measurements during a biomass burning event in the UK: Insights into nitrate chemistry

2017 ◽  
Author(s):  
Ernesto Reyes-Villegas ◽  
Michael Priestley ◽  
Yu-Chieh Ting ◽  
Sophie Haslett ◽  
Thomas Bannan ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Black Carbon ◽  
Source Apportionment ◽  
Organic Aerosol ◽  
Organic Nitrate ◽  
Ionization Mass ◽  
Night Time ◽  
Aerosol Mass ◽  
Pollutant Concentrations ◽  
The Uk

Abstract. Over the past decade, there has been an increasing interest in short-term events that negatively affect air quality such as bonfires and fireworks. High aerosol and gas concentrations generated from public bonfires/fireworks were measured in order to understand the night-time chemical processes and their atmospheric implications. Nitrate chemistry was observed during the bonfire night with nitrogen containing compounds in both gas and aerosol phase and further N2O5 and ClNO2 concentrations, which depleted early next morning due to photolysis of NO3 radicals, ceasing production. Particulate organic nitrate (PON) concentrations of 2.8 μg.m−3 were estimated using the m/z 46:30 ratios from AMS measurements, according to previously published methods. ME-2 source apportionment was performed to determine organic aerosol concentrations from different sources after modifying the fragmentation table and it was possible to identify two PON factors representing primary (pPON_ME2) and secondary (sPON_ME2) contributions. A slight improvement in the agreement between the source apportionment of the AMS and a collocated AE-31 Aethalometer was observed after modifying the prescribed fragmentation in the AMS organic spectrum (the fragmentation table) to determine PON sources, which resulted in an r2 = 0.865 between BBOA and babs_470wb compared to an r2 = 0.819 obtained without the modification. Correlations between OA sources and measurements made using Time of Flight Chemical Ionization Mass Spectrometry with an iodide adduct ion were performed in order to determine possible gas tracers to be used in future ME-2 analyses to constrain solutions. During bonfire night, high correlations (r2) were observed between BBOA and methacrylic acid (0.915), Acrylic acid (0.901), nitrous acid (0.864), propionic acid, (0.851) and Hydrogen cyanide (0.755). A series of oxygenated species, chlorine compounds as well as cresol showed good correlations with sPON_ME2 and the low volatility oxygenated organic aerosol (LVOOA) factor during an episode with low pollutant concentrations. Further analysis of pPON_ME2 and sPON_ME2 was performed in order to determine whether these PON sources absorb light near the UV region using an Aethalometer. This hypothesis was tested by doing multilinear regressions between babs_470wb and BBOA, sPON_ME2 and pPON_ME2. Our results suggest that sPON_ME2 does not absorb light at 470 nm while pPON_ME2 and LVOOA absorb light at 470 nm over that of black carbon. This may inform black carbon (BC) source apportionment studies from Aethalometer measurements, through investigation of the brown carbon contribution to babs_470wb.

scholarly journals Long-term chemical analysis and organic aerosol source apportionment at 9 sites in Central Europe: Source identification and uncertainty assessment

2017 ◽  
Author(s):  
Kaspar R. Daellenbach ◽  
Giulia Stefenelli ◽  
Carlo Bozzetti ◽  
Athanasia Vlachou ◽  
Paola Fermo ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Central Europe ◽  
Organic Aerosol ◽  
Epidemiological Studies ◽  
Alpine Valley ◽  
Enhanced Production ◽  
Inorganic Species ◽  
Yearly Average ◽  
Average Factor

Abstract. Long-term monitoring of the organic aerosol is important for epidemiological studies, validation of atmospheric models, and air quality management. In this study, we apply a recently developed filter-based offline methodology of the aerosol mass spectrometer to investigate the regional and seasonal differences of contributing organic aerosol sources. We present offline-AMS measurements for particulate matter smaller than 10 μm 9 stations in central Europe with different exposure characteristics for the entire year of 2013 (819 samples). The focus of this study is a detailed source apportionment analysis (using PMF) including in-depth assessment of the related uncertainties. Primary organic aerosol (POA) is separated in three components: hydrocarbon-like OA which is related to traffic emissions (HOA), cooking OA (COA), and biomass-burning OA (BBOA). We observe enhanced production of secondary organic aerosol (SOA) in summer, following the increase in biogenic emissions with temperature (summer oxygenated OA, SOOA). In addition, a SOA component was extracted that correlated with anthropogenic secondary inorganic species which is dominant in winter (winter oxygenated OA, WOOA). A factor (SC-OA) explaining sulfur-containing fragments (CH3SO2+), which has an event-driven temporal behavior, was also identified. The relative yearly average factor contributions range for HOA from 3 to 15 %, for COA from 3 to 31 %, for BBOA from 11 to 61 %, for SC-OA from 5 to 23 %, for WOOA from 14 to 28 %, and for SOOA from 14 to 40 %. The uncertainty of the relative average factor contribution lies between 5 and 9 % of OA. At the sites north of the alpine crest, the sum of HOA, COA, and BBOA (POA) contributes less to OA (POA/OA = 0.3) than at the southern alpine valley sites (0.6). BBOA is the main contributor to POA with 88 % in alpine valleys and 43 % north of the alpine crest. Furthermore, the influence of primary biological particles (PBOA), not resolved by PMF, is estimated and could contribute significantly to OA in PM10.

scholarly journals Simultaneous aerosol mass spectrometry and chemical ionisation mass spectrometry measurements during a biomass burning event in the UK: insights into nitrate chemistry

2018 ◽  
Vol 18 (6) ◽  
pp. 4093-4111 ◽  
Author(s):  
Ernesto Reyes-Villegas ◽  
Michael Priestley ◽  
Yu-Chieh Ting ◽  
Sophie Haslett ◽  
Thomas Bannan ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Oxides Of Nitrogen ◽  
Night Time ◽  
Aerosol Mass ◽  
Ionisation Mass Spectrometry ◽  
Chemical Ionisation ◽  
Ionisation Mass

Abstract. Over the past decade, there has been an increasing interest in short-term events that negatively affect air quality such as bonfires and fireworks. High aerosol and gas concentrations generated from public bonfires or fireworks were measured in order to understand the night-time chemical processes and their atmospheric implications. Nitrogen chemistry was observed during Bonfire Night with nitrogen containing compounds in both gas and aerosol phases and further N2O5 and ClNO2 concentrations, which depleted early next morning due to photolysis of NO3 radicals and ceasing production. Particulate organic oxides of nitrogen (PONs) concentrations of 2.8 µg m−3 were estimated using the m ∕ z 46 : 30 ratios from aerosol mass spectrometer (AMS) measurements, according to previously published methods. Multilinear engine 2 (ME-2) source apportionment was performed to determine organic aerosol (OA) concentrations from different sources after modifying the fragmentation table and it was possible to identify two PON factors representing primary (pPON_ME2) and secondary (sPON_ME2) contributions. A slight improvement in the agreement between the source apportionment of the AMS and a collocated AE-31 Aethalometer was observed after modifying the prescribed fragmentation in the AMS organic spectrum (the fragmentation table) to determine PON sources, which resulted in an r2 =  0.894 between biomass burning organic aerosol (BBOA) and babs_470wb compared to an r2 =  0.861 obtained without the modification. Correlations between OA sources and measurements made using time-of-flight chemical ionisation mass spectrometry with an iodide adduct ion were performed in order to determine possible gas tracers to be used in future ME-2 analyses to constrain solutions. During Bonfire Night, strong correlations (r2) were observed between BBOA and methacrylic acid (0.92), acrylic acid (0.90), nitrous acid (0.86), propionic acid, (0.85) and hydrogen cyanide (0.76). A series of oxygenated species and chlorine compounds showed good correlations with sPON_ME2 and the low volatility oxygenated organic aerosol (LVOOA) factor during Bonfire Night and an event with low pollutant concentrations. Further analysis of pPON_ME2 and sPON_ME2 was performed in order to determine whether these PON sources absorb light near the UV region using an Aethalometer. This hypothesis was tested by doing multilinear regressions between babs_470wb and BBOA, sPON_ME2 and pPON_ME2. Our results suggest that sPON_ME2 does not absorb light at 470 nm, while pPON_ME2 and LVOOA do absorb light at 470 nm. This may inform black carbon (BC) source apportionment studies from Aethalometer measurements, through investigation of the brown carbon contribution to babs_470wb.

scholarly journals SoFi, an Igor based interface for the efficient use of the generalized multilinear engine (ME-2) for source apportionment: application to aerosol mass spectrometer data

2013 ◽  
Vol 6 (4) ◽  
pp. 6409-6443 ◽  
Author(s):  
F. Canonaco ◽  
M. Crippa ◽  
J. G. Slowik ◽  
U. Baltensperger ◽  
A. S. H. Prévôt
Keyword(s):  
Source Apportionment ◽  
Mass Spectra ◽  
A Priori ◽  
Aerosol Mass Spectrometer ◽  
Pmf Model ◽  
Aerosol Mass ◽  
Five Factors ◽  
Multilinear Engine ◽  
Constrained Models ◽  
Spectrometer Data

Abstract. Source apportionment using the bilinear model through the multilinear engine (ME-2) was successfully applied to non-refractory organic aerosol (OA) mass spectra collected during winter 2011 and 2012 in Zurich, Switzerland using the aerosol chemical speciation monitor ACSM. Five factors were identified: low-volatility oxygenated OA (LV-OOA), semivolatile oxygenated OA (SV-OOA), hydrocarbon-like OA (HOA), cooking OA (COA) and biomass burning OA (BBOA). A graphical user interface SoFi (Source Finder) was developed at PSI in order to facilitate the testing of different rotational techniques available within the ME-2 engine by providing a priori factor profiles for some or all of the expected factors. ME-2 was used to test the positive matrix factorization (PMF) model, the fully constrained chemical mass balance (CMB) model, and partially constrained models utilizing a values and pulling equations. Within the set of model solutions determined to be environmentally reasonable, BBOA and SV-OOA factor mass spectra and time series showed the greatest variability. This variability represents uncertainty in the model solution and indicates that analysis of model rotations provides a useful approach for assessing the uncertainty of bilinear source apportionment models.

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