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 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 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 Secondary organic aerosol formation from biomass burning emissions

2019 ◽  
Author(s):  
Christopher Y. Lim ◽  
David H. Hagan ◽  
Matthew M. Coggon ◽  
Abigail R. Koss ◽  
Kanako Sekimoto ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Secondary Organic Aerosol ◽  
Total Concentration ◽  
Organic Aerosol ◽  
Oh Radicals ◽  
Aerosol Formation ◽  
Atmospheric Aging ◽  
Aerosol Mass ◽  
Photochemical Aging ◽  
Organic Gases

Abstract. Biomass burning is an important source of aerosol and trace gases to the atmosphere, but how these emissions change chemically during their lifetimes is not fully understood. As part of the Fire Influence on Regional and Global Environments Experiment (FIREX 2016), we investigated the effect of photochemical aging on biomass burning organic aerosol (BBOA), with a focus on fuels from the western United States. Emissions were sampled into a small (150 L) environmental chamber and photochemically aged via the addition of ozone and irradiation by 254 nm light. While some fraction of species undergoes photolysis, the vast majority of aging occurs via reaction with OH radicals, with total OH exposures corresponding to the equivalent of up to 10 days of atmospheric oxidation. For all fuels burned, large and rapid changes are seen in the ensemble chemical composition of BBOA, as measured by an aerosol mass spectrometer (AMS). Secondary organic aerosol (SOA) formation is seen for all aging experiments and continues to grow with increasing OH exposure, but the magnitude of the SOA formation is highly variable between experiments. This variability can be explained well by a combination of experiment-to-experiment differences in OH exposure and the total concentration of non-methane organic gases (NMOGs) in the chamber before oxidation, measured by PTR-ToF-MS (r2 values from 0.64 to 0.83). From this relationship, we calculate the fraction of carbon from biomass burning NMOGs that is converted to SOA as a function of equivalent atmospheric aging time, with carbon yields ranging from 24 ± 4 % after 6 hours to 56 ± 9 % after 4 days.

scholarly journals Six-year source apportionment of submicron organic aerosols from near-continuous measurements at SIRTA (Paris area, France)

2019 ◽  
Author(s):  
Yunjiang Zhang ◽  
Olivier Favez ◽  
Jean-Eudes Petit ◽  
Francesco Canonaco ◽  
Francois Truong ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Ambient Air ◽  
Carbonaceous Aerosols ◽  
Time Resolved ◽  
Pronounced Increase ◽  
Paris Area ◽  
Multi Wavelength ◽  
High Concentrations

Abstract. Organic aerosol (OA) particles are recognized as key factors influencing air quality and climate change. However, highly-time resolved year-round characterizations of their composition and sources in ambient air are still very limited due to challenging continuous observations. Here, we present an analysis of long-term variability of submicron OA using the combination of Aerosol Chemical Speciation Monitor (ACSM) and multi-wavelength aethalometer from November 2011 to March 2018 at a background site of the Paris region (France). Source apportionment of OA was achieved via partially constrained positive matrix factorization (PMF) using the multilinear engine (ME-2). Two primary OA (POA) and two oxygenated OA (OOA) factors were identified and quantified over the entire studied period. POA factors were designated as hydrocarbon-like OA (HOA) and biomass burning OA (BBOA). The latter factor presented a significant seasonality with higher concentrations in winter with significant monthly contributions to OA (18–33 %) due to enhanced residential wood burning emissions. HOA mainly originated from traffic emissions but was also influenced by biomass burning in cold periods. OOA factors were distinguished between their less- and more-oxidized fractions (LO-OOA and MO-OOA, respectively). These factors presented distinct seasonal patterns, associated with different atmospheric formation pathways. A pronounced increase of LO-OOA concentrations and contributions (50–66 %) was observed in summer, which may be mainly explained by secondary OA (SOA) formation processes involving biogenic gaseous precursors. Conversely high concentrations and OA contributions (32–62 %) of MO-OOA during winter and spring seasons were partly associated with anthropogenic emissions and/or long-range transport from northeastern Europe. The contribution of the different OA factors as a function of OA mass loading highlighted the dominant roles of POA during pollution episodes in fall and winter, and of SOA for highest springtime and summertime OA concentrations. Finally, long-term trend analyses indicated a decreasing feature (of about 200 ng m−3 yr−1) for MO-OOA, very limited or insignificant decreasing trends for primary anthropogenic carbonaceous aerosols (BBOA and HOA, along with the fossil fuel and biomass burning black carbon components), and no trend for LO-OOA over the 6+-year investigated period.

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 Processing of biomass burning aerosol in the Eastern Mediterranean during summertime

2013 ◽  
Vol 13 (10) ◽  
pp. 25969-25999 ◽  
Author(s):  
A. Bougiatioti ◽  
I. Stavroulas ◽  
E. Kostenidou ◽  
P. Zarmpas ◽  
C. Theodosi ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Biomass Burning ◽  
Eastern Mediterranean ◽  
Late Summer ◽  
Organic Aerosol ◽  
High Temporal Resolution ◽  
Night Time ◽  
Air Masses ◽  
Aerosol Mass ◽  
Atmospheric Processing

Abstract. The aerosol chemical composition in air masses affected by wildfires from the Greek islands of Chios, Euboea and Andros, the Dalmatian Coast and Sicily, during late summer of 2012 was characterized at the remote background site of Finokalia, Crete. Air masses were transported several hundreds of kilometers, arriving at the measurement station after approximately half a day of transport, mostly during night-time. The chemical composition of the particulate matter was studied by different high temporal resolution instruments, including an Aerosol Chemical Speciation Monitor (ACSM) and a seven-wavelength aethalometer. Despite the large distance from emission and long atmospheric processing, a clear biomass burning organic aerosol (BBOA) profile containing characteristic markers is derived from BC measurements and Positive Matrix Factorization (PMF) analysis of the ACSM mass spectra. The ratio of fresh to aged BBOA decreases with increasing atmospheric processing time and BBOA components appear to be converted to oxygenated organic aerosol (OOA). Given that the smoke was mainly transported overnight, it appears that the processing can take place in the dark. These results show that a significant fraction of the BBOA loses its characteristic AMS signature and is transformed to OOA in less than a day. This implies that biomass burning can contribute almost half of the organic aerosol mass in the area during summertime.

scholarly journals Sources of organic aerosols in Europe: a modeling study using CAMx with modified volatility basis set scheme

2019 ◽  
Vol 19 (24) ◽  
pp. 15247-15270 ◽  
Author(s):  
Jianhui Jiang ◽  
Sebnem Aksoyoglu ◽  
Imad El-Haddad ◽  
Giancarlo Ciarelli ◽  
Hugo A. C. Denier van der Gon ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Agricultural Waste ◽  
Organic Aerosols ◽  
Basis Set ◽  
Anthropogenic Sources ◽  
Wood Burning ◽  
Gasoline Vehicles

Abstract. Source apportionment of organic aerosols (OAs) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models are used as potential tools to identify OA components and sources at high spatial and temporal resolution; however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modeled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in previous studies, which strengthens our confidence in our modeled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 to −0.4 µg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 % to 42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %), while biogenic emissions contributed ∼ 55 % to OA during summer in Europe on average. In both seasons, other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (∼ 5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modeling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.

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